Essays on Power in Digital Platforms
by
Martín Harracá
Submitted for the Degree of Doctor of Philosophy
Department of Digital Economy, Entrepreneurship, and Innovation
Surrey Business School
Faculty of Arts and Social Sciences
University of Surrey
Supervisors:
Annabelle Gawer
Carla Bonina
Itziar Castelló
©Martín Harracá
2023
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Essays on Power in Digital Platforms
Declaration
This thesis and the work to which it refers are the results of my own efforts. Any ideas, data, images or text
resulting from the work of others (whether published or unpublished) are fully identified as such within the work
and attributed to their originator in the text, bibliography or in footnotes. This thesis has not been submitted in
whole or in part for any other academic degree or professional qualification. I agree that the University has the
right to submit my work to the plagiarism detection service TurnitinUK for originality checks. Whether or not
drafts have been so-assessed, the University reserves the right to require an electronic version of the final
document (as submitted) for assessment as above.
Signature:
Martín Harracá
Date:
August 25. 2023
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Essays on Power in Digital Platforms
Summary
This thesis investigates power in a new organisational form: the digital platform. Platforms have disrupted our
societies by creating and coordinating novel, flexible, and shifting forms of social interaction, changing how we
trade, work, and communicate. The profound and abrupt economic transformation brought by platform
companies like Amazon, Google, and Meta, while carrying initial expectations of increased freedom of choice,
higher social cohesion, and power distribution, was soon shadowed by the growing evidence of platform power
concentration and abuse. This research critically examines the characteristics and dynamics of power within digital
platforms, specifically focusing on platforms’ organising structures and influence.
This problem is approached from three different dimensions. The first dimension pertains to the structure of social
interactions, recognising the mechanisms through which platforms shape power relations and autonomy by
influencing agents’ interactions and modulating participatory practices. The subsequent dimension is centred on
the platform's governance, contrasting the principles guiding the governance and how it is enacted, and how this
shapes power dynamics within the platform. Lastly, the third dimension focuses on the interplay between firms,
assessing the extent of influence wielded by the platform's owner in directing shifts in the value creation and
capture strategies of other participant firms.
Each dimension of the research problem is addressed in one study in a dedicated chapter, after charting the
foundational concepts that characterise digital platforms and summarising extant research on platform power. The
first study is based exclusively on conceptual development, while the second and third are a qualitative case study
of the Amazon Marketplace, focused on Amazon’s and the sellers’ practices and how these affect each other.
Overall, this thesis contributes to advancing our knowledge of how we understand platforms and provides new
ways to characterise platform power, its dynamics, and its consequences.
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Essays on Power in Digital Platforms
Acknowledgements
This project started way back in time, and initially as an informal activity. In the last years of my licentiate degree, I
discovered my passion about research and knew I wanted it to become an important part of my life. At the time, I
rejected the idea of making it my main occupation: I thought about keeping it as a side activity, so I would be
relieved from any formal strings and focus on what I really wanted to say and explore. For several years, other than
some dispersed writing retreats and moments of inspiration, that strategy didn’t seem to be working very well. I
find now, however, that many fundamental ideas were sown during that period, and eventually came to
expression once I formally enrolled in the program - and probably there are still others, waiting. In a similar way,
this journey was not at all what I expected. With the hindsight of backward looking, I recognize in it the same
pattern of the things that deeply changed me: I started by rejecting and feeling alienated by it, but that
estrangement soon turned organically into enthusiasm and joy.
This work, like all, is the result of a collective effort and the net of affection and support beneath it. An intricated
net composed of people inhabiting different worlds whom, while mostly don’t know about each other, have here
a point of convergence. I divide these worlds into three, inspired by Julio Cortazar and his Rayuela [Hopscotch].
Del lado de allá [from the side beyond] acknowledges those who were involved in this journey in Europe. Del lado
de acá [from this side] acknowledges those who were involved in Argentina. This part is written in Spanish, as it is
the native language of all the people I thank and my own. Finally, De otros lados [from other sides] acknowledges
other brilliant people that has inspired this work in multiple unsuspected ways.
Del lado de allá [from the side beyond]
I need to start acknowledging my supervisory team, Annabelle, Itziar, and Carla, for the fundamental importance
they had in this experience. It was a dream team, each contributing in their own unique way, and constantly
pushing me into new and higher grounds. I am much obliged; it was truly a privilege to learn and work with you.
I want to thank all the colleagues from the Department of Digital Economy, Entrepreneurship, and Innovation, and
especially Glenn Parry, for the insightful conversations and their effort in creating a welcoming and integrative
space, particularly during the periods of lockdown. I also want to thank Prof. Alexander, Karen, Veena, Carolina,
and other members of the Surrey Business School staff for their continuous and warm support during these years.
A very special thank you to Lydia and Hannah, for being such great allies in navigating together parts of this PhD. I
also want to thank Yiwen, Adam, Parul, and Ivone, for those brief but meaningful connections in the worlds apart
that are academic conferences.
To my Argentinian friends in London, Matías, Jimena, Joel, and Cecilia, thank you for making so homely a new city
and its culture.
To Maria, Tejash, and Lea, for all the sharing and teaching, and for building a true home together.
To Thi, Fernando, and Julio, obrigado de coração. I can’t imagine having gone through this without you, thank you
for making it a bright experience.
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Essays on Power in Digital Platforms
Del lado de acá [from this side]
En primer lugar, quiero agradecer a quienes son los principales responsables de haber despertado mi curiosidad
intelectual, y por introducirme a nuevos mundos de pensamiento. Gracias Pablo, Axel, Juan, Mercedes, y Marcelo.
También agradezco por la profunda influencia que tuvieron en mí a Daniel Heymann, Enrique Kawamura, y Carlos
Mora.
Agradezco al grupo de investigaciones en plataformas, liderado por Pablo, y a Sonia, Facundo, Andrea, y Nicolás,
por las sesiones compartidas y las charlas inspiradoras.
A mis compañeros de discusión y militancia Itai, Pablo, Andrés, Igal, Facu, Caro, Ema, Fede, Dani, Bruno, Martín,
Flor, Seba, Guido, Luis, Lean y Vale, por enseñarme a hacer carne la reflexión.
A esa experiencia única de investigación colectiva que fue la topa y que me marcó profundamente. Gracias Pilar,
Cata, Pablo, y Lean.
A los miembros del Seminario de París, Bruno, Leandro y Beto, por ser una fuente permanente de estímulo
intelectual.
Gracias a Nay, por estar siempre que andamos sin buscarnos. A Eugx, por tirar abajo paredes. A Mariana, por
acompañarnos sin importar la distancia. A mis vecinos para siempre, Seba, Aye, Mariana, Andrés y Beto. A Ro y
Flor, por toda una vida de conexión y entendernos. A Ger y Gonza, por empujarme cuando lo necesitaba y
ayudarme a llegar, por estar allá y acá, y por Richard.
A Liliana, Jorge, y Lito, por lo que hicieron para que sea lo que soy. A Jose, Inti, Juan, Allen, Charly, Quillén, Nelson,
Lolo, Aye, Rodri y Alicia, por enseñarme a agrandar la familia. A Rosa, que está más cerca de lo que piensa.
Gracias Hui por compartir tus días conmigo, por tu alegría, y por enseñarme nuevos horizontes de lo que creía
posible. Gracias Doris.
De otros lados [from other sides]
To Elena, Paul, Alexandre, Paula, Bernard, Stephen, Gillian, Phil, Sacha, Marlon, Sam, Noé, Ian, Thomas, GuyManuel, Santiago, Pantro, Niño, Chatrán, Doctora, Laura, Mark, Donald, Dave, Mike, Stephan, Brian, Karl, Rick,
Robert, Robin, Will, Elizabeth, David, Milton, Mariana, Dan, David, Stephen, Ed, Ben, Giorgio, Gustavo, Javier, Josh,
Tom, Gaspard, Xavier, Ray, Leonard, Natalia, Lali, Sara, Jaime, Gernot, Klaus, Michael, Peter, Bjorn, John, Jeff, Tom,
Jonny, Colin, Ed, Philip, Karinn, Olof, Jason, Macu, Jean, Terry, Victoria, Lea, Henry, George, Sumner, Becki, Barzana,
Heredia, Delta, and Garay. Thank you for the inspiration and the peace you brought me.
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Table of Contents
Declaration ...................................................................................................................................................................... 2
Summary ......................................................................................................................................................................... 3
Acknowledgements ....................................................................................................................................................... 4
Table of Contents ........................................................................................................................................................... 6
List of Tables and Figures ............................................................................................................................................. 8
1.
Introduction ...................................................................................................................................................... 9
1.1.
Purpose and objectives of this study ....................................................................................................................................... 9
1.1.1.
1.1.2.
1.1.3.
1.2.
Central concepts and related research ................................................................................................................................. 13
1.2.1.
1.2.2.
1.3.
2.
Motivation and problem statement .................................................................................................................................... 9
Objectives and methodological approach .................................................................................................................... 10
This research in context: The impact of the COVID-19 pandemic ...................................................................... 12
Conceptualizing digital platforms..................................................................................................................................... 13
Extant research on power in digital platforms ............................................................................................................ 19
Thesis overview .............................................................................................................................................................................. 25
How digital platforms organize immaturity: A sociosymbolic framework of platform power ..........28
2.1.
Organized immaturity ................................................................................................................................................................. 29
2.2.
Platforms and the accumulation of power ......................................................................................................................... 30
2.2.1.
2.2.2.
2.3.
A socio-symbolic perspective on digital platforms ......................................................................................................... 33
2.3.1.
2.3.2.
2.3.3.
2.3.4.
2.4.
Fields, capitals, and habitus in digital platforms......................................................................................................... 33
A socio-symbolic perspective of power accumulation and its consequences for organized immaturity
37
Forms of Platform Power ...................................................................................................................................................... 38
Platform Power Dynamics .................................................................................................................................................... 44
Discussion ......................................................................................................................................................................................... 46
2.4.1.
2.4.2.
2.4.3.
2.5.
3.
Platforms as organizing agents ......................................................................................................................................... 30
Platforms’ accumulation of power and the consequences for individuals’ autonomy erosion .............. 31
Rethinking Organized Immaturity from a Sociosymbolic Perspective .............................................................. 47
Contribution to the Understanding of Platform Power Accumulation ............................................................. 48
Contributions to Practice and Avenues for Future Research ................................................................................ 49
Conclusion ........................................................................................................................................................................................ 50
Two-faced governance in platform ecosystems ........................................................................................51
3.1.
Introduction ..................................................................................................................................................................................... 51
3.2.
Literature - Related Research ................................................................................................................................................... 52
3.2.1.
3.2.2.
3.2.3.
3.2.4.
3.3.
3.3.1.
3.3.2.
3.3.3.
3.4.
3.4.1.
3.4.2.
3.4.3.
3.5.
3.5.1.
Governance in platform ecosystems ............................................................................................................................... 53
The consensus on platform governance: Four central claims ............................................................................... 54
Minority views on platform governance ........................................................................................................................ 55
Research Question .................................................................................................................................................................. 56
Research methods ......................................................................................................................................................................... 56
Empirical setting: Amazon and its Marketplace .......................................................................................................... 56
Data collection .......................................................................................................................................................................... 57
Data analysis .............................................................................................................................................................................. 59
Findings ............................................................................................................................................................................................. 59
Amazon governance practices ........................................................................................................................................... 59
Sellers’ adaptive ecosystem participation practices .................................................................................................. 71
Two-faced governance .......................................................................................................................................................... 76
Discussion ......................................................................................................................................................................................... 77
Contribution to the platform strategy literature ........................................................................................................ 78
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3.5.2.
3.5.3.
3.5.4.
3.5.5.
3.6.
4.
Enriching the construct of platform governance ....................................................................................................... 79
Contributions to the literature on platform power ................................................................................................... 80
Managerial and policy implications ................................................................................................................................. 81
Limitations and avenues for future research ................................................................................................................ 81
Conclusion ........................................................................................................................................................................................ 82
The evolutionary dynamics of platform orchestration .............................................................................84
4.1.
Introduction ..................................................................................................................................................................................... 84
4.2.
Literature - Related Research ................................................................................................................................................... 85
4.3.
Research methods ......................................................................................................................................................................... 90
4.3.1.
4.3.2.
4.3.3.
4.4.
Findings ............................................................................................................................................................................................. 95
4.4.1.
4.4.2.
4.4.3.
4.5.
Why do sellers adopt new business models? .............................................................................................................. 95
Amazon’s role: orchestrating change .............................................................................................................................. 96
Evolutionary interplay between Amazon and the Sellers ..................................................................................... 104
Discussion and conclusions..................................................................................................................................................... 106
4.5.1.
4.5.2.
5.
Empirical setting: The Amazon Marketplace and its sellers’ business models .............................................. 90
Data collection .......................................................................................................................................................................... 93
Data analysis .............................................................................................................................................................................. 94
Contributions to platform research................................................................................................................................ 106
Limitations and avenues for future research .............................................................................................................. 107
Discussion and general conclusions ......................................................................................................... 108
5.1.
On the nature of platforms as organising agents ......................................................................................................... 110
5.2.
On the characterisation of platform power ...................................................................................................................... 110
5.3.
On platform power dynamics................................................................................................................................................. 111
5.4.
On the consequences of platform power ......................................................................................................................... 112
5.5.
Policy Implications ...................................................................................................................................................................... 113
5.6.
Limitations and future research ............................................................................................................................................. 114
5.7.
Final remarks: repurposing platforms for social change............................................................................................. 116
References .................................................................................................................................................................. 117
Appendix .................................................................................................................................................................... 130
A.
Glossary of Amazon’s programs and policies ................................................................................................................. 130
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List of Tables and Figures
Table 1. Extant research on power in digital platforms ........................................................................................................................ 20
Table 2: Summary of publications’ chapters ............................................................................................................................................. 27
Table 3: Forms of Platform Power and the Organization of Immaturity ....................................................................................... 43
Table 4. Data Sources: Detail ........................................................................................................................................................................... 58
Table 5. Amazon’s declared governance: Examples, practices, and outcomes .......................................................................... 60
Table 6. Amazon’s undeclared governance: Examples, mechanisms, practices, and outcomes ......................................... 62
Table 7. Amazon’s undeclared governance practices (1): Create an unpredictable and precarious environment for
sellers. Evidentiary support .............................................................................................................................................................................. 64
Table 8. Amazon’s undeclared governance practices (2): Profit from an asymmetric position. Evidentiary support 65
Table 9. Comparison between Amazon’s claims, legal responsibilities, and actual practices.............................................. 70
Table 10. Sellers’ adaptive participation: Examples, mechanisms, practices, and outcomes ............................................... 71
Table 11. Sellers’ adaptive ecosystem participation practices: Evidentiary support ................................................................ 72
Table 12. Detail of Sellers’ adaptive practices for bending, eluding, or hacking the platform’s rules ............................. 75
Table 13. Challenging evidence to the literature’s central claims on platform ecosystem governance and
consequences for theory ................................................................................................................................................................................... 78
Table 14. Complementor orchestration: main findings and issues raised in the literature reviewed ............................... 89
Table 15. Types of sellers’ business models in the Amazon Marketplace .................................................................................... 92
Table 16. Detail of the data sources ............................................................................................................................................................. 93
Table 17. Amazon’s orchestration activities: Examples, practices, and outcomes .................................................................... 98
Table 18. Summary of Amazon’s orchestration activities over time: evolution of functionalities availability and key
changes in seller competition ....................................................................................................................................................................... 102
Table 19. Detail of functionalities available for sellers in the Marketplace over time ........................................................... 103
Table 20. Contributions of this thesis to research on platforms and platform power .......................................................... 109
Figure 1: Platforms as market facilitators ................................................................................................................................................... 15
Figure 2: Platforms as technological architectures ................................................................................................................................ 17
Figure 3: Platforms as organisational forms.............................................................................................................................................. 19
Figure 4: Platform Power Dynamics over Time ........................................................................................................................................ 44
Figure 5. Two-faced platform governance: A process model ............................................................................................................ 77
Figure 6. How new sellers’ business models appear on the Marketplace .................................................................................... 96
Figure 7. Amazon’s orchestrating role in the appearance of new business models ................................................................ 99
Figure 8. The appearance of the Private Label business model in the Marketplace.............................................................. 100
Figure 9. The appearance of the Aggregator business model in the Marketplace ................................................................ 101
Figure 10. Interplay between the sellers’ business models evolution and Amazon’s value proposition, orchestration,
and value capture strategies ......................................................................................................................................................................... 104
Figure 11. Changes in the sellers’ importance in the Marketplace and of Amazon’s sources for value capture ...... 105
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1. Introduction
1.1. Purpose and objectives of this study
1.1.1. Motivation and problem statement
The advent of digital platforms such as those operated by Amazon, Google, Meta, or Uber has brought a
profound economic transformation, challenging established forms of coordination and exchange (Cusumano et
al., 2019; Parker et al., 2016). They have created new markets and disrupted existing ones, as platforms excel at
business growth and value capture (Cusumano et al., 2019; Manyika et al., 2018) and play a major role in fostering
innovation (Ringel et al., 2019). Platforms have reshaped entire industries, like Google and Facebook with
advertising or Amazon with retail–, have expanded the horizons of product innovation efforts by articulating
networks of developers around operating systems such as iOS and Windows, have created global labour
marketplaces, such as Upwork, and networks with billions of interacting individuals, like Instagram, Twitter, or
YouTube. Overall, digital platforms have changed how society trades, works, and communicates.
The novelty of platforms and their impact has been accompanied by a growing scholarly interest, attaining a
stable position in the economics, information systems, and management research agendas.
To a large extent, this research has attributed the platforms’ importance to how they contribute to creating value
in new ways. Cusumano et al. (2019) differentiate between transaction platforms, which create value by facilitating
matchmaking and exchange between groups of agents subject to network effects, and innovation platforms,
which provide a technological foundation or infrastructure upon which third parties generate complementary
innovation in the form of new products, new services, or new technologies. Correspondingly, foundational
platform studies have focused on how they enable market creation and impact competition (Armstrong, 2006;
Eisenmann et al., 2009; Evans, 2003, 2010; Gawer & Henderson, 2007; Hagiu, 2013; Rochet & Tirole, 2003; Rysman,
2009) and which platforms’ configurations and features drive innovation and how (Adner & Kapoor, 2010; Baldwin
& Woodard, 2009; Chesbrough, 2006; M. Cusumano & Gawer, 2002; Gawer, 2009).
Underpinning these new ways to create value is a more fundamental fact: platforms act as new organisational
forms that, using a shared technological infrastructure, are capable of coordinating groups of heterogeneous and
formally independent actors – both individuals and organisations – towards system-level goals (Gawer, 2014;
Kretschmer et al., 2022; McIntyre et al., 2021). Conceptualising platforms as organisational forms stresses the
centrality of their constituents’ agency and the interplays among their roles, positions, and strategies (Gawer,
2014). Further, this approach highlights the flexible and continuously evolving nature of the relationships formed
between platform participants (Gulati et al., 2012; Kretschmer et al., 2022). Along with platform firms – companies
created based on a platform, such as Google or Uber – other longstanding companies are also adopting this type
of organisational strategy in sectors as diverse as real estate, transportation, health services, or finance (Evans &
Gawer, 2016). This process can be led by the transformation in some of its business units (like General Electric or
Siemens with their industrial “Internet of Things” platforms – Predix and MindSphere), but also by drastic and
structural organisational overhauls (as in Haier, a prominent Chinese appliances producer that “platformized” both
its internal divisions and supply chain network [Hamel and Zanini 2018]).
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Essays on Power in Digital Platforms
As platforms developed and spread globally, the predominantly optimistic views of the '00s and part of the 10's
decades regarding public opinion and the attitude of governments towards platforms gave place to a steep
"change of mood" (Cusumano et al., 2019). In an increasingly unequal world, platforms have delivered some of the
largest and fastest-earned fortunes in history, while their expansion into new and diverse areas of human
experience has turned widespread enthusiasm and support into a growing concern for the social implications of
this phenomenon (Eubanks, 2018; Lanier, 2018; Lehdonvirta, 2022; Srnicek, 2016; Zuboff, 2019). Involved in highprofile conflicts such as those related to Cambridge Analytica in the Brexit referendum or the United States Capitol
attack of January 6 2021, platforms have been pointed out for bringing issues of surveillance, manipulation of
choice, disinformation and censorship, market dominance leading to discriminatory clauses, restriction of access,
or limitation in content creation, and the worsening of labour conditions (Beer, 2017; Gawer & Srnicek, 2021;
Landini, 2016; Lyon, 2018; Stigler report, 2019; van Doorn & Chen, 2021).
Along with this “change of mood”, research related to the so-called platforms’ “dark side” and their power has
also become more prominent (Flyverbom et al., 2019; Kölbel et al., 2023; Trittin-Ulbrich et al., 2021; Verbeke &
Hutzschenreuter, 2020). In contrast with the initial characterisation of platforms as simply matchmakers (Caillaud
& Jullien, 2003; Evans, 2003; Rochet & Tirole, 2003), it is increasingly recognised that its owners are not neutral
intermediaries in the transactions they orchestrate but interested parts (Cutolo & Kenney, 2021; Furman, 2019;
Khan, 2018). Platforms shape the rights of access, use, and property of its participants and have a distinctive role
in the instrumentalisation of exchanges, as they supervise, drive, inhibit and even prohibit them (Alaimo &
Kallinikos, 2017; Curchod et al., 2019; Landini, 2016). This allows platforms to tightly organise and command
resources they do not own, redefining what has traditionally been considered an organisation’s scope and reach.
My1 inquiry is motivated by the transformations brought by platforms as an organising agent and its impact on
how power is structured and produced in this context. Platforms are both the vehicles and the embodiment of
society’s digitalisation: they bring novel ways of interaction by building over while transforming the relations
among its participants; they provide the space for these interactions to happen and establish the rules governing
them. As these changes conflict with pre-existing social and economic structures, platforms reconfigure power
relations. This thesis explores how power is produced and exerted in the context of platforms and how its agents’
practices are transformed as a consequence.
1.1.2. Objectives and methodological approach
This investigation aims to understand how power is reconfigured in platforms as new organisational forms. I will
approach this problem from three dimensions:
The first dimension is at the level of the social interactions’ structure. Platforms have become a space on which an
increasing number and variety of social interactions take place. The objective is understanding how platforms
shape power relations and autonomy by structuring agents' interactions and influencing their participation
practices. This problem is examined in Chapter 2.
1
In this thesis I use the first person in singular except in Chapters 2 and 3, which are co-authored.
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The second dimension concerns the platform’s rules for participation. One of the foundations on which platforms
operate is a set of governance rules that facilitate coordination and ensure participants’ good behaviour. The
second objective, discussed in Chapter 3, is to identify the premises under which this organisational form is
supposed to work, evaluate to what extent it does, and how this affects power dynamics in the platform.
The third dimension consists of changes in the relation between firms. Orchestration is a fundamental activity in
platforms by which the platform owner influences the participants to attain desired platform-level outcomes. The
third objective, considered in Chapter 4, is to assess the platform’s owner power to orchestrate changes in the
participant firms’ way of creating and capturing value.
As a thesis by publications, these objectives are addressed in separate chapters, each with its own research
question and specific methods. Nevertheless, the research activities that produced each publication are
intertwined and were guided by a shared research objective, design, and approach.
This research’s object, the transformation of power in new organisational forms, is a complex, multifaceted,
relational phenomenon and consequently demands an approach that can deal with this intricacy. Further, it has
multiple expressions, requiring a way to rigorously integrate different types of sources and data types
documenting the phenomenon. In addition, platforms evolve fast, so the approach needs to adapt and cope with
the object developing as the research takes place.
Grounded theory was identified as a suitable methodological stance to accommodate these requirements, as it
can be regarded as a systematic but still highly flexible strategy oriented to theory building (Charmaz & Bryant,
2008; Thornberg & Charmaz, 2014). The method is best suited for exploring new elements or connections in the
social reality and, hence, might adequately address power in new contexts. Among the three differentiated
branches that evolved from Glaser & Strauss’ original framework (1967) – namely Classical/Glaserian (Glaser,
1987), Straussian (Corbin & Strauss, 2008), and Constructivist (Charmaz, 2000; Charmaz & Bryant, 2008) – this
research is inspired by the Constructivist approach, as its higher flexibility and its gnoseological point of view
better suit the research problem and context.
Grounded research follows an iterative process, where decisions on data collection and analysis are taken vis a vis
the progress in the theoretical development. From the point of view of logic, this approach implies a movement
between induction and abduction, where data first inspires theory development, followed by interrogation of that
theory and further data exploration, subsequently producing new provisional hypotheses (Thornberg & Charmaz,
2014). This iterative process facilitates data triangulation, enhancing the project's trustworthiness and increasing
the potential for contribution. The cornerstone of data analysis and theory development in grounded approaches
is the process of coding, starting with open coding (initial familiarisation and exploration of the data), followed by
focused or selective coding (selection from the initial codes based on analytical relevance or interest), that is
combined with theoretical coding (categories brought the researcher based on existing theories) (Charmaz &
Bryant, 2008; Kenny & Fourie, 2015; Thornberg & Charmaz, 2014). Theoretical saturation is the methodological
tool used to give closure to this iterative analysis process, meaning that data fills the properties of a theoretical
category (Charmaz & Bryant, 2008).
While Chapter 2 is based exclusively on conceptual development, Chapters 3 and 4 are based on an in-depth case
study of the Amazon Marketplace. The case study is informed by semi-structured interviews, participatory
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observation, and various types of archival sources and was conducted between November 2019 and December
2022. These sources were used for both chapters, except for Amazon’s financial statements, that were used only in
Chapter 4. The Amazon Marketplace is the platform Amazon uses to run its retail business, where consumers can
purchase products sold by Amazon and third-party sellers (“sellers” from now on). The Marketplace is a wellsuited empirical setting to conduct this research, being simultaneously one of the longest-standing and largest
platforms worldwide. The study focused on Amazon’s and the sellers’ practices, and how these affected each
other. This focus yielded rich information about the organisational and power dynamics emerging from the
relationship between the platform owner and a group of highly heterogeneous organisations – the sellers –.
1.1.3. This research in context: The impact of the COVID-19 pandemic
The COVID-19 pandemic had various effects on this research, including on me personally as a researcher, in the
research activities, and in the object of study. I provide next a brief account of them to build additional context for
this research.
I moved from Buenos Aires (Argentina) to Guildford (UK) in September 2019 to start the research that produced
this thesis. Only six months later, in March 2020, the outbreak of COVID-19 was declared a pandemic, and all
levels of social life were heavily disrupted. Along with the rising uncertainty and generalised social anxiety, all the
activity in the University went soon online, and the people I knew (mostly national and international students) left
the area to stay with their families. Previous to the outbreak, I had a flight booked to Buenos Aires to meet my
(then) soon-to-be newborn nephew, in late March. After discussing it with my supervisors, we agreed I’d travel
and continue the research activities online for the moment. Argentina’s air space closed just a few days before the
flight. I managed to change my flight to Rio de Janeiro (Brazil) - where travelling was still possible -and after 24
hrs hoping through airports and taxis, I entered Argentina via Puerto Iguazu’s triple border by land. I made it to
Buenos Aires using an emergency government charter flight, transporting groups of strained citizens, on the same
day that a total lockdown was imposed in the country. The following months were marked by constant tension
between the evolution of the sanitary situation, the assessment of the possibilities of physically returning to the
University - driven by changes in local and international regulations -and the varying social unrest. Due to this
changing situation, my experience in that period was very different from that of most people, who felt stuck and
that could not move, as I moved fifteen times in twelve months. These conditions, while demanding significant
efforts, also imbued me with energy and inspiration for the research. During these challenging times, I received
full support from my supervisors and the University for better adapting to these conditions.
The pandemic also impacted the research as it altered the possibilities of conducting the planned activities. On the
one hand, the data collection plan was fundamentally based on interviews. The pandemic significantly delayed the
recruitment of informants (described below in sections 3.3.2 and 4.3.2). In addition, limitations for in-person
meetings and travelling reduced the possibility of conference participation and other formal and informal spaces
for discussing the progress of the research.
Finally, the pandemic also impacted the object of this study — first, limitations to move and meet dramatically
increased society’s reliance on digital technologies. Most large digital platforms played essential roles during the
pandemic, facilitating connectivity, and supporting governments with activities such as data analysis and logistics.
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This position naturally meant an increasing importance and power of these companies. Second, the generalised
restrictions for people to leave their houses led to a sharp and fast increase in e-commerce, abruptly increasing
the volume of Amazon’s and its marketplace’s operations. This, in turn, stressed the system and created new
tensions to be addressed between the company, the sellers, and the logistics providers.
1.2. Central concepts and related research
This section provides a contextualisation for the general problem and objectives discussed in this thesis and the
specific objectives addressed in chapters 2, 3, and 4. As each chapter counts with a review of the literature relevant
to the particular problem addressed, I here offer a broader and deeper discussion of the fundamental concepts
structuring this research. First, I review the concept of platform. By revisiting the foundational work of three
complementary perspectives on platforms, I contrast the different ways platforms are characterised and deemed
novel research objects. Second, I summarise extant research on platform power. I identify three approaches from
which platform power has been studied, each with its focus and conceptual background.
1.2.1. Conceptualizing digital platforms
Previous efforts to systematise platform research concur that two complementary approaches have laid the
foundations for the conceptualisation of platforms (Gawer, 2014; McIntyre & Srinivasan, 2017; Reuver et al., 2018;
Rietveld & Schilling, 2020; Saadatmand et al., 2019): One is based on the industrial organisation economics
literature, portraying platforms as market facilitators, and the other is based on the product development and
information systems literature, characterising platforms through their technological architecture. The bridging of
these research streams (Gawer, 2014) gave birth to the organisational view of platforms that conceptualise them
both as agents and as organising actors endowed with a unique structure. In this section, I highlight the
theoretical underpinnings of these approaches and their primary contribution to the understanding of platforms.
1.2.1.1. Platforms as market facilitators
In the economics literature, platforms are conceptualised as “multi-sided markets”: intermediaries that bring
together, coordinate (match), and facilitate exchanges between heterogenous groups of actors by aligning market
incentives (Caillaud & Jullien, 2003; Rochet & Tirole, 2003). A typical example of a platform acting as a market
facilitator is Uber: the platform provides a space where different types of agents looking to exchange (drivers and
passengers) are matched based on parameters such as time and proximity.
The economics literature on platforms is rooted in two streams of research, both closely connected to the
diffusion of information technologies in business activities. The first one consists of the foundational economic
studies on networks’ properties (Katz & Shapiro, 1985, 1986), which introduced the central concept of network
externalities, a situation where “the utility that a user derives from consumption of the good increases with the
number of other agents consuming the good” (Katz & Shapiro 1985; 424). This characteristic makes networked
markets prone to converge to a single product or technology, as each consumer will be better off in the network
with more consumers. This stream argues that a sponsor of a specific networking technology can strategically
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Essays on Power in Digital Platforms
promote specific asset investments and take advantage of network effects to tip the market (Katz & Shapiro,
1986). The second stream focuses on the problem of matchmaking and the coordination of heterogeneous
groups of users. Through studies on Internet information brokers and card payment networks they introduce the
concept of two-sided markets (Baye & Morgan, 2001; Rochet & Tirole, 2002; Schmalensee, 2002). Here, the
network coordinator can both maximise its profits and consumer participation by adequately balancing the fee
structure, charging different prices to different groups of consumers and cross-subsidizing them.
From the economics perspective, a platform acts as a matchmaker between groups of actors previously impeded
to exchange because of the existence of transaction costs. The “chicken-and-egg” problem of attracting and
keeping the different sides of the market is solved by defining a split price structure to cross-subsidize between
them, hence forming a two-sided market (Caillaud & Jullien, 2003; Rochet & Tirole, 2003). By enabling the
transactions, platforms internalise the network externalities and consequently increase social welfare (Evans, 2003).
Since the size of network effects typically grows more than proportionally to the cost of expanding the network, it
is argued that concentration is likely to be the most efficient market configuration in this context (Caillaud &
Jullien, 2003; Evans, 2003).
Subsequent foundational studies enriched this framework by distinguishing direct network effects (among the
same type of actors) from indirect network effects (across different types) (Parker & Van Alstyne, 2005) and
demonstrating their importance for determining the price structure and consumer multihoming decisions
(Armstrong, 2006). Other contributions explored additional critical decisions in platform markets, such as how to
adequately identify the platform’s sides and scope (Hagiu, 2006), how to define the governance and ownership
structure (Nocke et al., 2007), and how to build strategic competitive advantages in platform competition
(Eisenmann et al., 2006).
Figure 1 shows digital platforms as conceptualised by the economics literature, that is, as multi-sided markets. The
focal point is “the space for interaction”, created by the platform owner. Its role is to provide the vision and
manage the balance within the space, a service for which it profits from interactions. The “sides” are each
composed of relatively homogenous agents that need to connect to the other sides, but this is hindered by the
existence of transaction costs. As the common space makes interactions possible, value is created by internalising
the latent network externalities.
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Essays on Power in Digital Platforms
Figure 1: Platforms as market facilitators
Transaction costs
Transactions
Agent
group A
Agent
group B
Value creation
Value
capture
Matchmaking
Incentives design
Safeguard transactions
Platform
Owner
Platform
owner’s roles
Value creation
activities
Platform’s value
capture
1.2.1.2. Platforms as technological architectures
The product development and information systems literature has characterised platforms based on their particular
hierarchically layered technological architecture (Baldwin & Woodard, 2009; Tiwana et al., 2010). This stream’s
primary motivation has been to explore how the configuration of this architecture and the relationships of
cooperation and competition among its participants have greatly facilitated innovation efforts (Adner & Kapoor,
2010; Gawer & Henderson, 2007).
In the field of product innovation, a platform is defined in relation to the idea of modularity (Baldwin & Clark,
2000; Baldwin & Woodard, 2009). A modular design is characterised by a group of fundamental and stable
functionalities that are redeployed in combination with other complementary functionalities to conform a family
of products (Ulrich, 1995). Interfaces are the rules governing the interactions among parts (Baldwin & Clark, 2000)
and contribute to reducing systems’ complexity by reducing the amount of information required to develop each
functionality (Gawer, 2014). Considered together, these elements define a platform’s architecture: the stable
functionalities are named the platform’s core, the variable elements are the platform’s periphery, and their
interaction is facilitated by the interfaces (Baldwin & Woodard, 2009; Tiwana et al., 2010). A classic example in this
approach are smartphone’s operating systems, such as Android and iOS: the operating system contains the
phone’s core functionalities, while the apps, developed by third-party developers through standardized interfaces,
provide additional functionalities and constitute the periphery.
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Modular architectures lead to economies of scale and scope, which are strong incentives to use modular design
strategies (Baldwin & Woodard, 2009; Gawer, 2014). Economies of scale can be achieved through the reutilization
of core functionalities, the amortisation of fixed costs, and the recombinant innovation of modules, while
economies of scope can be gained mainly through the reduction in the cost of new product development.
Critically, the extent of the economies achieved, and the system's potential to foster innovation will depend on
adequately designing the architecture and defining which element plays each role and how they interact. Since
this research deals with platforms that provide the basis for interaction among formally independent
organisations (“industry platforms” [Gawer & Cusumano, 2014a]), solving the architecture design problem involves
a complex strategic interplay. The organisation that solves some essential problem in the industry and provides
the vision of how a product, technology, or service can be at the centre of the network becomes the platform
“hub”, “owner”, “leader”, or “orchestrator”, with design rights over the core functionalities and the interfaces
(Cusumano & Gawer, 2002). In turn, the agents contributing by creating, expanding, and delivering additional
value building on top of the platform’s core are called “complementors” (Gawer & Henderson, 2007). It is not
unusual for the hub to hide the core’s design parameters to protect its resources and make its functionality
reachable only through visible interfaces (Baldwin & Woodard, 2009). Nevertheless, this setting creates the space
for cooperation with minimum coordination requirements: by complying with the design parameters established
by the hub, each module can be developed, operated, and even priced independently (Jacobides et al., 2018).
The existence of the centre-periphery structure and the division of roles motivated scholars to explore how the
hubs’ behaviour influences the overall system’s innovation dynamics, particularly concerning two decisions:
platform openness and governance rules.
Since interfaces are how the platform enables its connection with other actors, its degree of openness –
accessibility to build interoperability by third parties – defines its potential to attract complementors. However,
achieving a virtuous innovation cycle requires a delicate balance (Boudreau, 2010; Gawer & Henderson, 2007):
ease of integration maximises participation and, therefore, the potential to add on and tap into external resources.
On the other hand, it also provides opportunities for competitors to thrive using the hub’s unique developments
and resources (Benlian et al., 2015; Boudreau, 2017).
The definition of the platform’s governance is also critical to achieving harmonious growth in complementors’
engagement: while stringent rules can repress innovation potential, being too lax will turn the platform into a “no
man’s land”, deteriorating commonalities and eroding its value (Boudreau, 2012; Tiwana et al., 2010). In this
context, scholars have focused on how to design rules that align incentives to enable both competition and
cooperation, as well as to prevent abuses of “star” complementors that might create bottlenecks (Daymond et al.,
2022; Wareham et al., 2014).
Figure 2 represents a platform based on its technological architecture. Within this framework, interactions occur
under specific premises: actors do not interact directly but through devices that communicate with interfaces
specified for each type of user. Interfaces grant and regulate access to the core functionalities of the platform.
They further enable innovation by complementors, who develop products or services in the periphery and expand
the platform’s functionalities, increasing overall value creation. The platform owner is responsible for designing
the architecture and defining the governance layers that regulate the users’ and complementors’ participation.
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Figure 2: Platforms as technological architectures
Complementors
Innovation
Periphery
Core
Users
Users
Design architecture
Define governance
Platform
Owner
Platform
owner’s roles
Value creation
activities
Platform owner’s
value capture
Governance
layers
Technological
architecture
Interfaces
Devices
1.2.1.3. Platforms as organisational forms
While both the economics and the information systems frameworks offer valuable answers to the specific
problems each addressed (how platforms create and reshape markets and foster innovation), these frameworks
were essentially unconnected. The lack of cross-pollination between these streams offered an opportunity to
develop integrative frameworks and unify the platform theory. The organisational view of platforms was an answer
to that vacancy, first introduced by Gawer (2014) and later developed and expanded through subsequent studies
(Gawer, 2021; Jacobides et al., 2022; Kretschmer et al., 2022; McIntyre et al., 2021; Rachlitz, 2023)
The organisational approach expands the previous characterisations because, while considering both the
platforms’ role as interaction coordinators and the implications of their specific technological structure, it focuses
on the platforms’ particular way of organising the multiple sets of relationships among its constituents (Gawer,
2014; Kretschmer et al., 2022; Rachlitz, 2023). They can therefore be considered “evolving organisations or
metaorganisations”2 (Gawer, 2014; 1240), structures “between organisations and markets, providing a mixture of
Gawer (2014)’s original characterisation includes three key features in her definition: “technological platforms can
be usefully conceptualized as evolving organisations or metaorganisations that: (1) federate and coordinate
constitutive agents who can innovate and compete; (2) create value by generating and harnessing economies of
scope in supply or/and in demand; and (3) entail a modular technological architecture composed of a core and a
periphery.” (p. 1240)
2
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market-based and hierarchical power, and a mixture of market-based and hierarchical incentives” (Kretschmer
et al., 2022; 407).
Under this approach, platforms can be considered a “new kind of social ordering” (Rachlitz, 2023) or a “particular
kind of technology of organising” that solves the problem of coordinating autonomous entities toward a systemlevel goal without hierarchical formal authority (Gulati, Puranam, and Tushman 2012). This form of organising can
be found in very different organisational contexts (such as firms or industry ecosystems), in each of which its
constitutive agents will likely vary as well (Gawer, 2014).
This approach does not fix, based on pre-existing characteristics, the role that participants (which can be both
individuals and organisations) adopt nor the nature of their interactions. Instead, their roles and interactions, and
how they change, are explained by participants’ strategic behaviour, recovering the centrality of agency (Gawer,
2014). This conceptualisation implies that relationships between members can vary from cooperation to
competition and back to collaboration, or even coexist simultaneously on different sides or features of the
platform.
As stated above, this approach recognises the platform’s structure as a defining aspect, but its importance is also
framed in the context of agency: the primary source of authority in platforms regulating constituents’ actions
emanates from the control of the technological core and the interfaces (Kretschmer et al., 2022). In this context,
the platform owner has a decisive role. The centre-periphery structure defines a framework, the playing field
within which the participants collaborate and compete with uneven success (Adner & Kapoor, 2010; Dhanaraj &
Parkhe, 2006). The asymmetry crystallised in this relationship is the ability to set the rules and manage
participation in the platform.
Another dimension that distinguishes the organising in platforms is the nature of incentives and their role in
coordination and governance. Since constituents are formally autonomous in most cases, their contribution in the
platform is subject both to their individual success and to how they perceive the platform’s overall success
influences it (Kretschmer et al., 2022). Consequently, motivation in the platform is shaped simultaneously by
market mechanisms, by the governance rules set to oversee participation, and by boundary setting, “nudges”, and
other tools guiding participants towards desirable contributions (Claussen et al., 2013; Ghazawneh & Henfridsson,
2013; Kretschmer et al., 2022)
Adequately designing the rules of interaction while balancing the incentives constitutes a coordination problem
specific to the platform. For example, Gawer & Cusumano (2014) compare it with how coordination works in two
other industrial configurations: dominant design and supply-chain. The first refers to “the standard for what form
and features users expect a particular product to take in the future” (Gawer & Cusumano, 2014; 420), and its
defining characteristic is that it emerges within an industry without the need for central coordination to guide it.
At the other end, a supply chain requires tight coordination and has a “master builder” who plans it in detail and
controls its evolution. Platforms differ from both because while there is hierarchical coordination, it relies on how
modularity is designed, and while the outcome can be induced, it cannot be tightly planned in advance.
Figure 3 depicts platforms as organisational forms. From this perspective, the defining aspect of the platform is
how it organises autonomous participants towards system-level goals of value creation, either by facilitating
innovation or enabling transactions. Participants’ roles are not pre-defined, as they result from their strategies
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within the conditions set by the platform owner: how it designs the platform and sets the governance and
incentives. The differences in roles create a hierarchical structure within the platform that is presided over by the
owner.
Figure 3: Platforms as organisational forms
Periphery
Transactions
Participants
Innovation
Participants
Core
Organizing participants through:
- Platform design
- Governance and incentives setting
Platform
Owner
Platform
owner’s roles
Value creation
activities
Platform owner’s
value capture
Governance
layers
Technological
architecture
1.2.2. Extant research on power in digital platforms
As the platforms’ social and economic importance increased, accounts associating platforms with power abuses
also became more prominent. Both academic researchers and journalists began documenting a new set of
platform-related issues, such as consumer and business harm based on market dominance, widespread
surveillance, social opinion manipulation, harmful psychological effects on users – such as addiction – and the
worsening of labour conditions. In addition to documenting the abuses, researchers began to explore the sources
of platform power and the specific mechanisms that lead to abuse. I distinguish three streams of research in
platform power – market-based, sociomaterial, and techno-economic –, summarised in Table 1. Each stream has a
different focus and conceptual approach, although we can trace some shared arguments in their explanations: one
stream focuses on how platforms’ features create market power and affect market competition, the second on
how the technical objects involved in society’s digitalisation reshape agents’ actions and the forms of control, and
the third stream focuses on how the platforms’ specific means of resource extraction and production control
creates new forms of power and dependence.
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Table 1. Extant research on power in digital platforms
Approaches to
platform power
Market-based
Focus
Identifying the
mechanisms by which
platforms can shape
market structures and
exchanges and influence
competitive outcomes
Characterisation of power
Three primary sources driving platform power:
- Gatekeeping, resulting from the specific intermediary role
that platforms play, allowing its owner in concentrated
markets to define the market’s rules
- Data capture and control, used to both improve and develop
services and create entry barriers to fend off competitors
- Leveraging, consisting of the platform’s owner's
effortlessness to achieve a dominant position in an adjacent
market, based on access to large strategic assets (e.g.,
informational, financial, etc.)
Sociomaterial
Analysing norm
production and control
mechanisms by exploring
how actors mobilise
digital artefacts to
reshape actions and
choices.
Power asymmetries are created by how technological objects
are deployed in platforms
- Algorithms automatically manage the digital interactions and
objects that constitute platforms, concealing the rationalities
and decisions behind their design
- Encoding defines how offline objects and actions are
translated into a digital language
Consequences of power
Harms to consumers: imposition of supra-monopoly
prices, discriminatory clauses, or restricted access to
the platform. Limitation of choice by the creation of
lock-ins and behaviour manipulation
Harm to businesses: preventing competitors from
entering the platform’s market (competition “for” the
market, e.g., use of data holdings as barriers to entry,
creation of interoperability lock-ins) and preventing
competition within the markets created by the
platforms (competition “in” the market, e.g., effects of
the platform owner entering its complementors’
market space)
Notable examples in
the literature
Crémer et al. (2019);
Furman (2019); Hagiu
et al. (2020); Jacobides
(2021); Khan (2016, 2018);
Stigler report (2019); Zhu
(2019)
Digitalisation exerts a structuring effect on
interactions, reshaping them. Choice is constrained
and directed by the continuously restructured
platform interfaces. Algorithms are socially embedded:
shaped by visions and expected outcomes; they
express and reinforce some realities at the expense of
others. This creates “black boxes” that eschew
questioning and abrogate responsibility.
Alaimo & Kallinikos
(2017); Beer (2017); Calo
& Rosenblat (2017);
Curchod et al. (2019);
Eaton et al. (2015);
Flyverbom et al. (2016);
Kelkar (2018); Orlikowski
& Scott (2015); Stark &
Pais (2020)
Control of crucial digital resources creates
dependence as platforms can restrict consumer access,
impose participation rules, expand dominance into
new markets, and further deploy additional forms of
control.
Andreoni & Roberts
(2022); Coveri et al.
(2022); Cutolo & Kenney
(2021); Rikap (2022b);
Srnicek (2016, 2021);
Vasudevan (2022); Zuboff
(2019)
- Interfaces and other boundary resources manage users’
visibility and access to the platform’s functionalities
Techno-economic
Exploring how the
interrelation between the
platform firm’s
technological features
and its capital
accumulation logic
creates new forms of
power and dependence
The platform firms’ infrastructural position grants them control
over resources that became critical for trading, working, and
communicating in the digital phase of capitalism.
New accumulation logics are based on surveillance and data
capturing, for which platforms have been optimised.
Platform firms act as capitalist rentiers since their
infrastructural position creates barriers to capital
mobility, originating rents that the platform firm
captures.
Source: Based on the literature reviewed
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1.2.2.1. Market-based platform power
One approach to platform power, developed by industrial organisation and competition law scholars, focuses on
the specific mechanisms by which platforms can shape market structures and exchanges and influence
competitive outcomes (Busch et al., 2021; Jacobides, 2021; Khan, 2016, 2018; Lianos & Carballa-Smichowski, 2022).
As a topical issue, there is an ongoing and vigorous debate between regulatory agencies and scholars about what
market power and its abuse means within digital platforms (Crémer et al., 2019; Cusumano et al., 2021; Furman,
2019; Hagiu et al., 2020; Peitz, 2023; Petit & Teece, 2021; Stigler report, 2019). In the heat of this debate, three
primary sources that drive platform market power have been distinguished: gatekeeping, data capture and
control, and asset leveraging.
Gatekeeping results from platforms' specific intermediary role in concentrated markets (Khan, 2018). Driven by
network effects, digital markets tend to create winner-takes-all-or-most outcomes (Cusumano et al., 2019), with
one or a few companies controlling the market. In this context, a platform has a favourable position from where to
define the market’s rules, including who can access it and how the transactions occur, as well as to charge supramonopoly prices (Busch et al., 2021; Crémer et al., 2019; Furman, 2019; Khan, 2018; Stigler report, 2019).
Data capture and control is a fundamental part of platform business models (Crémer et al., 2019; Furman, 2019;
Khan, 2018). User and data bases are some of the more valuable assets platform companies have, providing the
source to improve existing services and develop new ones and create entry barriers to fend off competitors. By
collecting unprecedented amounts of user data, platform owners can thoroughly understand their users’ needs
and preferences. This knowledge can be used to improve targeted marketing and product development but can
also be monetised through business intelligence services to third parties (Busch et al., 2021; Crémer et al., 2019;
Furman, 2019).
Leveraging consists of the platform’s owner's effortlessness to achieve a dominant position in a market that is
both different but adjacent to the one in which it is currently positioned (Khan, 2018). This conduct is possible due
to the platform’s owner's access to large informational, logistical, and financial assets and because digitalisation
eases the creation of large economies of scale (such as the ability to manage additional operations and users with
a negligible marginal cost) and scope (like the use of large databases from one market to understand and tip
another one). This has led large platform firms to enter apparently unrelated markets and quickly achieve a
dominant position in them (Crémer et al., 2019; Furman, 2019; Stigler report, 2019).
The market-based approach to platform power contributes by identifying anti-competitive platform practices and
how they can cause harm to individuals and businesses.
First, effects on individuals are assessed considering their role as consumers. Consumer harms derived from
gatekeeping power include, for example, facing supra-monopoly prices, imposing discriminatory clauses, or
restricting access to the platform (Furman, 2019; Gawer & Srnicek, 2021; Stigler report, 2019). The capture and
manipulation of data have also been identified as a potential source of consumer harm, such as the limitation of
choice by the creation of lock-ins and behaviour manipulation due to the use of nudges and “dark patterns” in
user interface design (Busch et al., 2021; Crémer et al., 2019; Furman, 2019; Gawer & Srnicek, 2021; Khan, 2018).
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Next, anti-competitive practices affecting businesses can be divided between those done to prevent competitors
from entering the platform’s market (competition “for” the market) and those done to avoid competition within
the markets created by the platforms (competition “in” the market) (Furman, 2019). Examples of practices limiting
competition for the market are the use of data holdings as barriers to entry, the creation of interoperability lock-in
to prevent user multi-home to other platforms, or the use of predatory pricing to capture and tip the market
(Crémer et al., 2019; Furman, 2019). Competition in the market has been approached by the literature of
competition with complementors and dual marketplaces (Hagiu et al., 2020; Zhu, 2019), exploring the effects of
the platform owner entering its complementors’ market and the strategies used by both them in preparation and
response to that action. These contributions identified product spaces more likely to be entered (Zhu & Liu, 2018),
how complementors’ entry decisions (Lan et al., 2019) and profitability (Hagiu et al., 2020) are impacted by the
platform’s business model, and responses in complementors’ innovation and value-capture strategies when facing
platform’s entry threats (Wen & Zhu, 2019).
1.2.2.2. Sociomaterial approaches to platform power
Another stream of researchers has approached platform power by focusing on society’s digitalisation and how the
specific technological objects and processes deployed in platforms create different power asymmetries. These
scholars discuss how digital artefacts are mobilised by actors to reshape actions and choices, analysing the
mechanisms of norm production and control in the digital realm (Alaimo & Kallinikos, 2017; Beer, 2017; Flyverbom
et al., 2016; Orlikowski & Scott, 2015).
Algorithms are one of the central objects in this stream of research since, as a sequence of self-contained actions,
algorithms automatically manage the digital interactions and objects that constitute platforms. The basic
algorithmic function of search and match creates a multi-layered problem of power asymmetry since the
inspection and control of its computing processes pose technical challenges for users and regulators (Beer, 2017;
Just & Latzer, 2017). The criteria for how results are displayed and sorted, the fairness in the treatment of data
entities, and the limitation of results (filtered selections) are of social interest while also being carried out in
camera (Faraj et al., 2018). Maintaining the inscrutability of algorithms is argued to be necessary for competitive
reasons, as their secrecy is usually critical to retaining competitive advantage (Agrawal et al., 2019). However,
studies identifying algorithmic bias and discrimination have raised concerns about this issue and call for
mechanisms of social algorithmic audition (Danaher et al., 2017; Larsson & Heintz, 2020). Furthermore, bias might
be found not only in the algorithm's rules but also as an emergent property of the data used as input (as was
observed for racial biases), creating additional complexity for regulation (Noble, 2018).
The challenge to unpacking the consequences of algorithms for power lies in the need to grasp their technical
features in conjunction with a socially structured analysis of the device (Beer, 2017; Introna, 2016; Orlikowski &
Scott, 2015). This issue highlights the social embeddedness of algorithms, as they are shaped by visions and
expected outcomes. Beer (2017) argues the need to move beyond the “immediate consequences of code” and
understand algorithms' different roles in social processes. In particular, he draws attention to how the notion of
algorithm circulates in the social fabric and notes its symbolic power to determine how things are or should be
done. In a similar vein, Orlikowski and Scott (2015) delve into the algorithms’ performative character, as the
constituted-in-practice materialisation of a service. Furthermore, they highlight that algorithms express and
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reinforce some realities at the expense of others. As “algorithms act; they do things” (Orlikowski & Scott, 2015), we
are brought back to the problem of how they make decisions and also how they constitute the world in which we
make our choices (Beer 2017). The “black box of algorithmic culture” (Orlikowski & Scott, 2015; Pasquale, 2015;
Striphas, 2010) creates a world of secrecy that eschews questioning and abrogates responsibility (Introna, 2016).
In digital platforms, algorithms create specific power asymmetries as they are used for “algorithmic management”
of social interactions (Calo & Rosenblat, 2017; Curchod et al., 2019; Lee et al., 2015; Stark & Pais, 2020). Typically
deployed for this purpose in digital marketplaces for service provision, such as Uber, TaskRabbit, eBay, or Upwork,
algorithms offer an unprecedented capacity to monitor and correct specific tasks and reshape labour conditions
(Calo & Rosenblat, 2017; Neyland & Möllers, 2017; van Doorn & Chen, 2021). Algorithms transform the typical
managerial function of evaluation, dislocating both hierarchical power and the subordinates’ exercise of agency
(Curchod et al., 2019): as managers, algorithms might prove to be inaccessible, unappealable, and tireless,
constraining human agency and negating the possibility to adapt, respond, or deviate from control mechanisms
(Curchod et al., 2019; Introna, 2016).
Encoding is a crucial process when assessing digitalisation’s power dynamics, as it is the activity that defines how
offline objects and actions are translated into a digital language (Alaimo & Kallinikos, 2017). Once codified, actions
must be performed in accordance with the rules established by the programmer. Thus, the codification and the
rules exert a structuring effect over the initial interactions, shaping them (Alaimo & Kallinikos, 2017; Curchod et al.,
2019). It has even been claimed that encoding makes cyberspace an arena of potentially perfect control (Landini,
2016) since it creates the actions that users are invited to perform in a way that can be stored and processed.
Finally, another set of studies has explored how the design and manipulation of platform architectural elements,
such as interfaces and other boundary resources (Ghazawneh & Henfridsson, 2013), shape power dynamics in the
platform. As stated above (section 1.2.1.2), interfaces manage access to the platform’s core functionalities, and
consequently, their design plays a fundamental role in defining the relationship with the platforms’ constituents.
Indeed, a defining feature of the changing scope of the category of user is the fact that they are limited and
controlled by various kinds of interfaces (Kelkar, 2018). This means that the type of tools available to users, what is
visible to them and what is not, and the amount of freedom they enjoy in the digital platform are decisions taken
at the architecture design level. In this train of thought, Bradshaw and Howard (2018) highlight how choice is
constrained and directed by the continuously restructured platform interfaces designed to satisfy people’s various
desires for identification and social connection. In addition to the impact on individuals, scholars have explored
how the evolution of the deployment and use of boundary resources has consequences regarding power
relationships among businesses. For example, Eaton et al. (2015) describe the “paradoxical tensions of generativity
and control” arising from the cycles of resistance and accommodation between software developers and Apple in
the iOS ecosystem. These cycles, whose outcome is innovation in the form of new software applications, result
from how the differences in actors’ resources affect their easiness of overcoming the limitations imposed by the
boundary resources.
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1.2.2.3. Techno-economic platform power
A third stream of research has focused on how the interrelation between the platform firm’s technological features
and its capital accumulation logic creates new forms of power and dependence. This approach is developed
mainly by political economy scholars that argue limitations in the explanations of platform power based
exclusively on market relations, bringing forward the importance of resource extraction and production control for
value appropriation (Cutolo & Kenney, 2021; Langley & Leyshon, 2017; Rikap, 2022b; Srnicek, 2016; Vasudevan,
2022; Zuboff, 2019).
This stream associates the advent of platforms with a profound change in social and economic relations and how
capitalism works. One of the most influential contributions from this perspective is Zuboff’s thesis of “surveillance
capitalism” (2019). This theory argues that with the advancement of large technological companies into most
aspects of social life, capitalism has entered a new phase of accumulation based on surveillance that claims human
experience as free raw material for translation into behavioural data. While some of this data is applied to product
development, most is appropriated as “behavioural surplus”: data is fed into machine intelligence to create
prediction products - anticipating what a user will do – sold in specific advertising markets. Furthermore, tech
companies can produce statistically relevant user behaviour modifications by nudging, tuning, herding and
conditioning users through the computational infrastructure. Zuboff summarises these dynamics by arguing the
appearance of a new “instrumentarian power”, consisting of capabilities for computational-based behaviour
shaping toward specific ends to achieve “guaranteed outcomes”.
In a similar vein, other scholars have proposed the hypothesis of “platform capitalism“ (Langley & Leyshon, 2017;
Srnicek, 2016). Rather than being solely a manifestation of wider social transformations, these authors depict
platforms as “a discrete mode of socio-technical intermediary and capitalist business arrangement”, driving a
profound change in economic circulation (Langley & Leyshon, 2017; 15). By providing a digital space for others to
interact, platforms are considered the vehicle optimised to extract and exploit a crucial and now abundant raw
material: data (Srnicek, 2016). Data can now be captured from an ample variety of sources such as natural
processes (e.g., weather conditions, crop cycles, etc.), industrial activities (e.g., assembly lines, continuous flow
manufacturing, etc.), and other businesses and users’ behaviours (e.g., web tracking, usage data, etc.). Finally, data
serves vital functions that explain the platform’s dominance: they create competitive advantages by educating
algorithms; they enable the coordination and outsourcing of workers; they allow for the optimisation and
flexibility of productive processes; they make possible the transformation of low-margin goods into high-margin
services; and data analysis is itself generative of new data, in a virtuous cycle (Srnicek, 2016).
A common theme in explaining platform power from this approach is how the platform firms’ infrastructural
position creates dependence for consumers and for other businesses (Andreoni & Roberts, 2022; Coveri et al.,
2022; Cutolo & Kenney, 2021; Li & Qi, 2022). Unlike previous forms of monopolisation, limited to specific markets
or sectors, platform firms control resources critical to all digital economy participants (Coveri et al., 2022; Li & Qi,
2022). Control of these resources creates dependence because platforms can restrict consumer access, impose
participation rules, and further deploy additional forms of control. Cutolo & Kenney (2021) explain the dynamics
of dependence over time, describing how power asymmetries evolve with the participants’ involvement in the
platform. Using the example of entrepreneurs, they show how while new entrants typically benefit from the
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resources provided by the platform that enable a fast and cost-effective way to enter a market, more mature
businesses become locked in and highly dependent on the platform’s decisions. Further, the creation of
dependence relations can also be identified between platforms: Li & Qi (2022) highlight platforms’ heterogeneity
regarding control over digital infrastructures, leading to the existence of a hierarchical power structure where
while small platforms have some power over users, large platforms dominate both of them.
Finally, one of the expressions of platform power emerging in this approach is the characterisation of platform
firms as capitalist rentiers (Andreoni & Roberts, 2022; Rikap, 2022b; Srnicek, 2021; Vasudevan, 2022). As argued
above, the platform’s infrastructural position produces dependence and further creates barriers to capital mobility,
originating rents captured by the platform firm (Vasudevan, 2022). This stream has identified several different
forms of rent derived from infrastructural asset control, such as advertising, monopoly, innovation, or political
rents (Andreoni & Roberts, 2022; Srnicek, 2021). Other factors besides the platform’s infrastructural position are
also associated with rent capturing. For example, Rikap (2022) describes how platforms appropriate knowledge
and data and transform it into rent-bearing intangible assets such as the platform’s core algorithms.
1.3. Thesis overview
This section describes this thesis’ structure and summarises each chapter’s central argument. The body of this
thesis by publications consists of five chapters plus the references and appendices. The current chapter (Chapter
1) provides a general introduction to this research, chapters 2, 3, and 4 contain the publications, and chapter 5
discusses the thesis’ findings and contributions and offers some general conclusions. Table 2 summarises the
publication chapters' authorship, research questions, methods, findings, and specific contributions.
The current chapter is a general introduction to this study, presenting the problem statement and motivation, the
general and specific objectives, the methodological approach, and the research context. The leading research
problem is understanding how power is reconfigured in platforms as new organisational forms. To contextualise
this problem, this chapter reviews the concept of platform by revisiting the foundational work that built three
different perspectives on platforms: as market facilitators, as technological architectures, and as organisational
forms. Next, it summarises extant research on platform power and identifies three main approaches: marketbased, sociotechnical, and techno-economic. To conclude, it provides an overview of the thesis.
Chapter 2, “How digital platforms organise immaturity: a sociosymbolic framework of platform power”,
conceptualises how the way platforms structure social interactions and practices shapes power relations and
agents’ autonomy. A guiding construct in this chapter is that of organised immaturity, defined as the erosion of
the individual’s capacity for public use of reason (Scherer & Neesham, 2020). Drawing on Bourdieu’s concepts of
field, capitals, and habitus, this chapter provides a sociosymbolic perspective on platforms’ power dynamics.
Digital platforms are characterised as organisations mediated by a digital infrastructure and a digital habitus in
which agents accumulate capitals by operating in a field. Power dynamics in the platform are explained by the
agents’ practices, positions, and strategies and how the digital infrastructure and the digital habitus shape these.
This chapter builds a framework identifying five forms of platform owner power accumulation (constitutional,
juridical, discursive, distinction, and crowd) and two forms of counterpower (crowd and hacking). It also explains
the evolution of the power dynamics over time and proposes a three-phase model in which the forms of power
operate. These phases are platform formation and field enclosure, platform domination within the original field,
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and platform cross-field expansion. Overall, this chapter offers a holistic and dynamic understanding of platform
power, where multiple coexisting forms of power are exerted and confronted by different types of agents. It also
explains the organising dynamics of immaturity and how immaturity is constituted in practice.
Chapter 3, “Two-faced governance in platform ecosystems”, explores the problem of the platform’s rules for
participation and its compliance through an inductive grounded study of the Amazon Marketplace. Discussing
established claims in the economics and management literature on platform governance, this chapter explores the
existence of discrepancies between a platform owner’s declared ecosystem governance and its actual practices
and their consequences. The chapter shows the existence of two sets of governance practices: on the one hand,
Amazon’s officially declared set of rules, roles, and activities and, on the other hand, a set of practices and
“unwritten rules” of participation that depart from the official governance. It documents these discrepancies and
their impact on the Marketplace’s sellers. Further, the study also identifies a set of adaptive practices that sellers
adopt, finding that they, too, resort to sets of declared and undeclared practices. The chapter consequently argues
the existence of a “two-faced governance” strategy in the Marketplace, defined as the platform owner’s practice of
pursuing simultaneously seemingly contradictory governance practices. This two-faced platform governance
creates unpredictability for sellers and enhances, at least in the short term, Amazon’s bargaining power over them.
Overall, this chapter enriches the construct of platform governance by identifying that there are two types of
governance practices (declared and undeclared), showing how the two interact and their consequences for power
dynamics.
Chapter 4, “The evolutionary dynamics of platform orchestration”, examines the reach of the platform’s owner
orchestration capabilities by assessing its influence on its complementors’ business models through an inductive
long-term study of the Amazon Marketplace. Observing the existence of multiple and heterogeneous business
models for sellers in the Marketplace, this chapter first identifies the process through which new sellers’ business
models appear and are adopted in the Marketplace. It then shows how Amazon influences this process,
identifying the specific orchestration activities used and how they operate. The chapter then illustrates this by
describing Amazon’s influence on the appearance of new sellers’ business models in two different periods. Next, it
describes how the appearance of new business models benefits Amazon by improving its value proposition and
increasing its value capture. Finally, the chapter discovers a pattern of dynamic adjustments between Amazon and
the sellers’ business models, resulting in an evolutionary interplay where both are transformed. Overall, the
chapter illuminates new platform owner orchestration capabilities and identifies ways in which it can create forms
of complementor dependence.
Chapter 5 discusses the contributions of the previous chapters, showing how this thesis enriches our
understanding of platforms and how we characterise platform power, its dynamics, and its consequences. Overall,
it argues that this research illuminates new aspects of platforms as organising agents and provides a multifaced,
multidirectional, and dynamic characterisation of platform power. The chapter highlights the identification of new
strategies of platform power, how these strategies change vis a vis the platform, and further the recognition of the
consequences of platform power over autonomy and decision-making, both on individuals and organisations. This
chapter also discusses implications for policy, the research’s limitations, and avenues for future research. It
concludes with some final remarks about the potential social implications of this research for platforms.
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Table 2: Summary of publications’ chapters
Chapter 2: How digital platforms organise
immaturity
Chapter 3: Two-faced governance in platform
ecosystems
Chapter 4: The evolutionary dynamics of
platform orchestration
Authorship
Martín Harracá, Itziar Castelló, Annabelle Gawer
Martín Harracá, Annabelle Gawer
Martín Harracá
Publication /
presentation
Published in Business Ethics Quarterly (March 2023),
doi:10.1017/beq.2022.40. Presented as a conference
paper at the 2021 EGOS and the 2022 AoM conferences.
Presented at the 2022 Platform Strategy Symposium,
the 2022 RaDMA, 2023 EGOS, and the 2023 SASE
conferences. It is currently under review for publication.
Presented in the PhD workshop of the 2023 EU-DPRN
conference and accepted to be presented at the 2023
ICIS Conference (acceptance rate ~25%).
How do digital platforms organise immaturity?
Are there sustained discrepancies between a platform
owner’s declared ecosystem governance and its actual
practices? What are the consequences of these
discrepancies on the platform owner and its ecosystem
members?
How do platform owners orchestrate the appearance of
new complementors’ business models? How does the
platform owner benefit from this?
Conceptual development
Inductive grounded study of the Amazon Marketplace, based on interviews, participatory observation, and archival
sources
Discusses the platform’s role in organising immaturity,
defined as the erosion of the individual’s capacity for
public use of reason. Adopts a sociosymbolic
perspective, based on Bourdieu’s concepts of fields,
capitals, and habitus, to characterise digital platforms as
organisations mediated by a digital infrastructure and a
digital habitus in which agents accumulate
capitals/power by operating in a field.
Evidence of a “two-faced” platform governance, defined
as the platform owner’s practice of pursuing
simultaneously seemingly contradictory governance
practices. It comprises the platform firm’s officially
declared set of rules, roles, and activities and, on the
other hand, a set of practices and “unwritten rules” of
participation that depart from the official governance.
Research
question
Methods
Central
argument
and findings
Specific
contributions
Develops an integrative and dynamic conceptualisation
of platform power through a framework with five forms
of power (constitutional, juridical, discursive, distinction,
and crowd) and two forms of counterpower (crowd and
hacking) accumulation along three-phases of field
transformation (field enclosure, field domination, and
cross-field expansion).
Evidence of a set of adaptive practices that ecosystem
participants adopt, also resorting to sets of declared and
undeclared practices.
This two-faced platform governance creates
unpredictability for complementors and enhances, at
least in the short term, the platform firm’s bargaining
power over them.
Explains the organising dynamics of immaturity based
on the relations between the platform structure, the
digital objects, and the agents’ strategies. Analyses how
immaturity is constituted in practice and explains and
nuances the possibility of emergence and the selfinfliction dimensions of immaturity.
Contributes to the platform strategy literature by
providing new evidence that runs contrary to the central
claims of the platform governance literature.
Builds a three-phase model of platform power dynamics
over time. This model expands current views on
platform power, providing a more holistic scheme in
which power is accumulated and contested and
highlighting how agents other than the platform owner
play a role in producing and exercising forms of power.
Enriches our understanding of how platform power can
be identified and exploited. It provides evidence that
platform power can be exerted in ways not previously
specified by focusing on the strategic mismanagement
of the rules and the creation of uncertainty.
Enriches the construct of platform governance by
identifying that there are two types of governance
practices, declared and undeclared, and their interaction
Identifies the process through which new sellers’
business models appear in the Marketplace.
Evidence showing that Amazon successfully
orchestrated the appearance of new sellers’ business
models in its Marketplace.
Identifies a pattern of dynamic adjustments between
Amazon and the sellers’ business models, resulting in an
evolutionary interplay where both are transformed.
This interplay is triggered by Amazon’s orchestration
activities, which, by providing functionalities, structuring
seller competition, and increasing the competitive
intensity sellers face, influence the sellers’ business
model transformation. This transformation is
instrumental in improving Amazon’s value proposition
and increasing its value capture in the platform.
Expands our understanding of the platform owner’s set
of capabilities and responsibilities by showing that they
can orchestrate changes in its complementors’ business
models. Recognising these capabilities is relevant for
research on platform power as it identifies ways in which
the platform owner can create forms of complementor
dependence.
Contributes to the platform orchestration stream of
literature by identifying new sets of the platform
owner’s orchestration activities and explaining the
mechanisms by which these activities transform the
complementors’ business models.
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Essays on Power in Digital Platforms
2. How digital platforms organize immaturity: A sociosymbolic
framework of platform power3
Organized immaturity, defined as the erosion of the individual’s capacity for the public use of reason (Scherer
et al., 2020), differs from other forms of control in that it is a self-inflicted and emergent (as opposed to
orchestrated) collective phenomenon in which autonomy-eroding mechanisms mutually reinforce each other
(Scherer et al., 2020; 9).
The phenomenon of autonomy erosion and increasing user control has been discussed in the context of the dark
side of digitalization (Flyverbom et al., 2019; Trittin-Ulbrich et al., 2021). Scholars have looked at how the
automation of interactions through algorithms can lead to an emergent manipulation of choice and autonomy
erosion (Alaimo & Kallinikos, 2017; Beer, 2017; Just & Latzer, 2017; Orlikowski & Scott, 2015), but there is still little
exploration of the organizing role of platforms in this process.
Digital platforms have been described as organizational forms that orchestrate activities between independent
users through the use of digital interfaces (Constantinides et al., 2018; M. Cusumano et al., 2019; Gawer, 2014,
2021; McIntyre et al., 2021). Increasingly, scholars denounce the negative effects of power accumulation by digital
platforms and platform owners. For example, studies of the structural constitution of markets criticize gatekeeping
positions that impose discriminatory clauses or limit content access and creation, with consequences for users’
choices (Crémer et al., 2019; Jacobides, 2021; Khan, 2018). Other researchers, such as Kelkar (2018), Stark and Pais
(2020), and Flyverbom et al. (2019), discuss sociomaterial perspectives on platforms and show how platform
owners design the interfaces, prescribing what is accessible to users and what choices they may enjoy in the
digital platform; this, again, restricts choice and creates negative psychological effects on users (Seymour, 2019;
Wu et al., 2019). Lanier (2018) and Zuboff (2019) present systems of surveillance promoted by the power of digital
platforms that explain how the datafication of human experience leads to increasing forms of domination.
These studies provide valuable explanations of how the increasing power of platforms hinders freedom of choice
and individual autonomy. However, their explanations are partial, focusing either on the market mechanisms that
limit consumer choice or on the specific role of digital objects, such as algorithms, that constrain the platform
users’ autonomy. The fundamental aspects of the organizing of immaturity, such as the tension between
organizing and emergence, and the relationship between self-infliction and the power accumulation strategies of
key agents, such as platform owners, remain unexplored though. These tensions are essential to explaining how
organized immaturity is created and reproduced. We claim that there is a need to explain the power accumulation
of the different agents of the platforms and its relation to the mechanisms that lead to the delegation of
autonomous decision-making. Therefore, in this article, we ask, How do digital platforms organize immaturity?
This chapter was published as a co-authored article with Itziar Castelló and Annabelle Gawer in Business Ethics
Quarterly (2023), in the special issue “Socio-Technological Conditions of Organized Immaturity in the Twenty-First
3
Century”, doi:10.1017/beq.2022.40. It was also presented as a conference paper at the 2021 EGOS and the 2022
AoM conferences.
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Essays on Power in Digital Platforms
To tackle this issue, we build a sociosymbolic perspective of power accumulation in digital platforms inspired by
Bourdieu’s writings (Bourdieu, 1977, 1979, 1984, 1987, 1989, 1990, 1991, 2005, 2011, 2014; Bourdieu & Wacquant,
2007). A sociosymbolic perspective supports building a dynamic conceptualization of power accumulation based
on agents’ practices, positions, and strategies. The concepts of field evolution and habitus allow further
explanation of the emergence of immaturity and the mechanisms of self-infliction. By situating the concepts of
fields, capitals, and habitus in the context of digital platforms, we describe digital platforms as organizations
mediated by a digital infrastructure and a digital habitus in which agents accumulate capitals by operating in a
field. We explain the role of the digital habitus in organizing immaturity, complementing prior literature on
materiality and affordances. We propose a framework of power accumulation in which the dynamics of platform
owner power accumulation and counterpower accumulation coexist. The platform owner accumulates power in
five forms: constitutional, juridical, discursive, distinction, and crowd. There are two forms of counterpower: crowd
and hacking. We also explain the evolution over time of the power dynamics and propose a three-phase model in
which the forms of power operate. These phases are platform formation, platform domination within the original
field, and platform cross-field expansion.
This framework makes two significant contributions. First, we build a theoretical apparatus that explains the
organizing dynamics of immaturity by explaining the relations between the structure, the digital objects, and the
platform owner’s power accumulation strategies. From these, we can explain the tension of emergence and selfinfliction. With this framework, we draw on sociological perspectives to expand the understanding of organized
immaturity in digital spaces by focusing on describing the practices that constitute the webs of relations that
configure the digital habitus and the processes of power accumulation. Second, we contribute to the platform
literature by developing a three-phase model of platform power dynamics over time. This model expands current
views on platform power, providing a more holistic scheme in which power is both accumulated and contested
and highlighting how agents other than the platform owner play a role in producing and exercising forms of
power. This article concludes by providing policy recommendations on how to understand and tackle organized
immaturity and highlighting potential avenues for further research.
2.1. Organized immaturity
Organized immaturity has been defined as a collective, albeit not necessarily orchestrated, phenomenon where
independent reasoning is delegated to another’s guidance (Scherer & Neesham, 2020). It is inspired by the
Kantian principle that humans should have intellectual maturity involving autonomy of judgment, choice, and
decision-making without the guidance of an external authority. It also relates to the ability to use experience to
reason and reflect critically and ethically on complex or problematic situations and to challenge norms and
institutions (Scherer & Neesham, 2020). The concept of organized immaturity differs from other forms of control
in two ways. First, it is a “self-inflicted” (Kant, as cited in Scherer & Neesham, 2020; 8) process, referring to harm
done by humans to themselves, often in a nonconscious manner. From this perspective, “immaturity” is therefore
a condition of the human being that arises when an individual defers or delegates their own autonomous
reasoning to external authorities (Dewey, 1939). The second way in which organized immaturity differs from other
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Essays on Power in Digital Platforms
forms of control is that it is an emergent (as opposed to orchestrated) collective phenomenon in which
autonomy-eroding mechanisms mutually reinforce each other (Scherer & Neesham, 2020; 9).
According to Scherer and Neesham (2020), the study of immaturity relates also to its organizing elements. The
perpetuation of modern forms of immaturity has been associated to organizations and institutions that create the
conditions for the self-inflicted immaturity. Organized forms of immaturity have been addressed in the critical
analysis of bureaucratic organizations, where the individual is subject to various forms of domination and control
(Clegg, 1989; Hilferding, 2005).
The Fourth Industrial Revolution (Philbeck & Davis, 2018; Schwab, 2017) has ushered in a consolidation of the
globalized information and communication technologies that are driving the organization of economic life.
However, the infrastructures and mechanisms behind these sociotechnological systems curb individual liberties
and impact people’s autonomy (McCoy et al., 2018; O’Connor & Weatherall, 2019).
The term organized immaturity is not explicitly used in most of the literature studying forms of control related to
digitalization (with the exception of Scherer and Neesham [2020] and Scherer et al. [2020]), but scholars are
increasingly analysing the “dark side of digitalization” (Flyverbom et al., 2019; Trittin-Ulbrich et al., 2021). In
particular, attention has been directed to the use of big data and systems based on artificial intelligence and to
how the automation of interactions through algorithms can lead to an emergent manipulation of choice. Even the
basic algorithmic function of search and match creates power asymmetries, since the inspection or control of its
guiding principles presents technical challenges for both users and regulators (Beer, 2017; Just & Latzer, 2017).
Biases might be found in the criteria for how results are limited, displayed, and sorted (Faraj et al., 2018) and may
even amplify properties of the data used as input, as has been observed in the context of racial biases (Noble,
2018). Researchers are increasingly pointing at the importance of unpacking the consequences of algorithms in
conjunction with a socially structured analysis of the device (e.g., Beer, 2017; Introna, 2016; Orlikowski & Scott,
2015). Through this, they show how the “black box of algorithmic culture” (Orlikowski & Scott, 2015; Pasquale,
2015; Striphas, 2010) creates a world of secrecy that eschews questioning and abrogates responsibility (Introna,
2016), eroding autonomous decision-making.
However, this emphasis on the artificial intelligence tools, algorithms, and coding processes that hinder autonomy
in decision-making must be complemented by research into the organizing structures of immaturity, that is, the
key organizing agents. Studying digital platforms can improve understanding about how organized immaturity
happens, as these platforms organize social interactions and transform the power relations of the different agents
who participate in the digital exchanges.
2.2. Platforms and the accumulation of power
2.2.1. Platforms as organizing agents
In the platform literature, digital platforms have been described as new organizational forms that orchestrate
activities between independent users through the use of digital interfaces (Gawer, 2014; Kretschmer et al., 2022;
McIntyre et al., 2021). Platforms can be considered a “particular kind of technology of organizing” (Gulati et al.,
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Essays on Power in Digital Platforms
2012; 573) or “hybrid structures between organizations and markets” (Kretschmer et al., 2022; 4), as they use a
mixture of market and hierarchical incentives to coordinate autonomous agents. Platform organizations are
distinct from hierarchies, markets, and networks (Gawer, 2014) because, as Kornberger et al. (2017; 81) argued,
“platform organizations question not only extant organization designs but also, quite fundamentally, the [Coasian]
idea of the firm . . . and . . . of value creation processes.”
Two fundamental characteristics define the digital platform as an organizing agent: how its digital architecture is
structured and how it coordinates interactions. From an organizational perspective, platforms can be described by
the common set of design rules that define their technological architecture. This system is characterized by a
“core” functionality with low variety and a complementary set of “peripheral” functionalities with high variety
(Tiwana et al., 2010). The rules governing interactions among the parts are the interfaces (Baldwin & Woodard,
2009). Interfaces contribute to reduce a system’s complexity by greatly simplifying the scope of information
required to develop each functionality (Gawer, 2014). Together, the centre, the periphery, and the interfaces define
a platform’s architecture (Baldwin & Woodard, 2009). The centre–periphery structure therefore defines an
asymmetric framework in which the participants collaborate and compete (Adner & Kapoor, 2010), under
conditions set by the platform owners on two elements: openness and governance rules (Boudreau, 2010; Gawer
& Henderson, 2007).
Platforms coordinate transactions by creating “multisided markets,” in which their owners act as intermediaries to
bring together (match) and facilitate exchanges between different groups of users by aligning market incentives
(Rochet & Tirole, 2003). Interactions occur in a networked structure, implying that the value derived from platform
usage increases exponentially with each additional user (Katz & Shapiro, 1985). As the value for participants grows
with the size of the platform, it is optimal for them to converge on the same platform, leading to the prediction
that platforms will tend to create concentrated markets organized by increasingly powerful owners (Caillaud &
Jullien, 2003; Evans, 2003).
2.2.2. Platforms’ accumulation of power and the consequences for individuals’ autonomy
erosion
The characteristics of platforms described in the preceding section have facilitated the accumulation of power by
platform owners, leading to “new forms of domination and competition” (Fuchs, 2007; 7) that are increasingly
eroding people’s capacity to make independent decisions. The consequences of the platforms’ power
accumulation for manipulation of choice and autonomy delegation have been analysed from two perspectives:
first, in relation to the structural constitution of markets and how this structure can lead to manipulation of users’
choices, and second, from a sociomaterial perspective that looks at the interaction of digital objects (e.g.,
algorithms) and the platform users.
From the perspective of the structural constitution of markets, the accumulation of power and manipulation of
choice is associated to the growing centrality of large platforms in the economy. Consumers and business partners
can have their choices manipulated because of the specific intermediary role that platforms play. Once the market
has been tipped, this role provides the platform owner with a position from which they can charge
supramonopoly prices and define the rules of the market, including who can access it and how the transactions
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occur (Busch et al., 2021; Jacobides, 2021; Khan, 2018). In this way, platforms are increasingly operating as
gatekeepers, imposing discriminatory clauses or limiting content access and creation (Furman, 2019; Stigler report,
2019). Choice making can also be limited due to market concentration driven by platforms, in that a platform
enhances its owner’s opportunities to leverage its assets (Khan, 2018). Thus the owner can entrench their
(platform’s) position in a market and enter an adjacent one by creating economies of scale and scope occur
(Jacobides, 2021; Khan, 2018). This brings the possibility of creating a dominant position in apparently unrelated
markets through practices like vertical integrations, killer buys, predatory pricing, and self-preferencing (Crémer
et al., 2019; Furman, 2019). In addition, the capture and control of transactional data may be used to improve
platform services, while also enabling the creation of entry barriers that fend off competition (Khan, 2018).
Market-based analyses provide a view of power accumulation based on asset control and market position.
However, they have been criticized for overlooking the impact of other noneconomic dimensions and for
portraying power as relatively unidirectional (Lynskey, 2017, 2019; Margetts et al., 2021). Such critiques recognize
that the deep social impact of platform power cannot be tackled from a market perspective alone (Lianos &
Carballa-Smichowski, 2022; Margetts et al., 2021).
Sociomaterial perspectives place affordances and materiality of the digital objects at the centre of the platform
interactions (Curchod et al., 2019; Fayard & Weeks, 2014; Kornberger et al., 2017). In this perspective, digital
objects, such as code, interfaces, and algorithms, are described as central objects that can hinder autonomy. For
example, when platform owners design the interfaces, they define the category of user, prescribing what is
accessible to users and what choices they enjoy in the digital platform (Kelkar, 2018). Encoding, which comprises
the rules for how offline objects and actions are translated into a digital language (Alaimo & Kallinikos, 2017), is
also defined by platform owners. Once codified, actions must be performed in accordance with the rules
established by the platform. Thus the affordances of technology shape and mold the interactions of the users with
the platforms (Alaimo & Kallinikos, 2017). Furthermore, algorithms and codes have been denounced for their
opacity (Etter & Albu, 2021). The inspection and control of a platform’s guiding principles present technical
challenges for both users and regulators (Beer, 2017), which enables manipulation. For example, Seymour (2019)
and Wu et al. (2019) describe how the manipulation design techniques employed by platform firms like Facebook
and Twitter are worrying not only because they affect an individual’s freedom of choice but also because they can
cause users to experience harmful psychological effects, such as addiction.
Yet the aforementioned studies of affordances and materiality offer a limited understanding of how emergence
and self-infliction of organized maturity are patterned by the strategic choices of platform owners and other
agents. To further understand the organized immaturity of digital platforms, it is important to look at how
practices are shaped and organized by the relations between the technological objects, the different users’
strategies, and structural elements that conform the power accumulation of the platform.
Some scholars have begun to offer holistic models that explain the accumulation of power by platform firms and
its consequences for the authority erosion of different agents. Lanier (2018) and Zuboff (2019) describe digital
platforms’ datafication of human experience, which leads to increasing forms of domination in what they term
“surveillance capitalism.” Surveillance is enabled by the asymmetric positions of platform owners and users,
defined by technological architecture, and executed through monetization strategies based on user data. Zuboff
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(2019) argues that despite the explicit narrative of platforms as both positive and objectively inevitable, their
strategies and business models—based on voluntary data sharing—are fundamentally connected to the extraction
of economic rents. Surveillance reduces human experience to free raw material for translation into behavioural
data and prediction products (Zuboff, 2019), eroding individual autonomy and disrupting intellectual privacy
(Richards, 2012). Surveillance has become a naturalized practice that we all—willingly or not—perform (Lyon,
2018). Surveillance theories therefore contribute to this debate by offering an understanding of the instrumental
connection between the business model and technological objects that constitute the platform and the selfinfliction aspects of immaturity processes.
Yet, we argue that further work is needed to understand not only the expansion of immaturity through a system
of economic surveillance but also how the everyday practices of leading and participating in the platform relate to
immaturity emergence. Moreover, we argue that these views should be enriched with a theory of how agency is
constituted and transformed by platform power dynamics, how these dynamics have an organizing role in
producing and reproducing the delegation of autonomous decision-making, and how the emergence of
immaturity and the strategic power accumulation by platform owners are connected.
2.3. A socio-symbolic perspective on digital platforms
To further explain how platforms organize immaturity, we draw on Bourdieu’s sociosymbolic theory and the
concepts of field, capitals, and habitus. A sociosymbolic perspective situates the agents in a field and explores the
power accumulation dynamics of each agent. It takes materiality into consideration, but, through the concept of
habitus, it is able to explain how interactions are also mediated by previous history and the networks of relations
in a way that complements the notion of affordances and its connotations for the perception of physical artifacts
and technology (Fayard & Weeks, 2014). Furthermore, a sociosymbolic approach allows us to build an integrative
conceptualization of power accumulation and its dynamics based on agents’ practices, positions, and strategies. It
shows how multiple types of powers can coexist and accounts for how the relative positions of agents shape their
motivations and actions, explaining the practices of immaturity and its relation to self-infliction. We explain this
further, first by providing an overview of how a sociosymbolic perspective generally explains power and its
dynamics through the concepts of field, capital, and habitus; we thus show how digital platforms can be
understood through these lenses. Second, we describe the dynamics that lead to specific forms of power
accumulation and explain how they can evolve over time.
2.3.1. Fields, capitals, and habitus in digital platforms
Bourdieu’s sociosymbolic theory was developed to explain social stratification and dynamics in (offline) societies
by focusing on how agents (people, groups, or institutions) produce, reproduce, and transform social structures
through practice (i.e., what they do in everyday life). Through practice, agents produce particular social spaces
with specific boundaries demarcated by shared interests and power relations; these social spaces are termed fields
of practice (Bourdieu & Wacquant, 2007).
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2.3.1.1. Fields
A field (champ) is a key spatial metaphor in Bourdieu’s work. It represents “a network, or a configuration, of
objective relations between positions” (Bourdieu & Wacquant, 2007; 97). These positions are objectively defined
“to field occupants, agents or institutions . . . by their present and potential position (situs) in the structure of the
distribution of species of power (or capital)” (Bourdieu & Wacquant, 2007; 97). Individuals, groups, or
organizations can be agents in a given field, and one individual may have different agencies (or “roles”),
depending on their situation in the field.
The concept of “field” can be related to digital platforms in the sense that the organization and production of
practices situates the platform in relation to an existing field. This may be the field of cultural production (e.g.,
Facebook) or the field of goods exchange (e.g., Amazon). The fields have specific logics and structures that define
them. Different agents can have multiple roles; for example, an Instagram user may be both a contributor and a
consumer of content. The relational aspects of the fields are also very compatible with network-based
perspectives (Portes, 1998) because the field in which the platform is embedded functions on the basis of relations
created during the practice of exchanges that constitute the field. The technological infrastructure creates a
centre–periphery structure, which provides the foundation on which the practices occur, both enabling and
regulating them. This approach to platforms highlights the practice of the agent and its position but also
simultaneously shows how the platform’s constitutive elements are deeply interconnected. Taking Twitter as an
example, the extent to which a specific content generated by a user is reproduced depends on the user’s social
position in the network but also on the priorities defined by the platform’s algorithms, which create the structure
in which the content is shared.
Multiple nested and overlapping fields can be found on any platform, just as they are in any (offline) social
context. For example, YouTube constitutes a huge field of people broadly interested in sharing and viewing online
video content. However, YouTube also hosts a variety of other, more focused subfields, for instance, a field
cantered on cryptocurrency videos. At the same time, platforms do not necessarily constitute a field in its entirety,
for while some online fields exist mostly in a single platform, like the field of video content sharing on YouTube,
competing platforms have entered some subfields, such as gaming videos in Twitch. At the same time, other
online fields are embedded in larger fields of practice. For example, job seekers would look at job opportunities in
LinkedIn while engaging offline with the job-offering companies.
Yet the creation of a digital platform can also be conceptualized as an attempt to “enclose” part of a field: an
agent (the platform creator) designs a value creation model for users (the specific practices to be performed by
them within the field) and develops the digital infrastructure that makes interactions possible. Digital platforms
enclose the field because they attempt to create “exclusive control rights” (Boyle, 2003) over dimensions of
practices that were previously in the public domain. Consider Google’s Street View, launched in 2007, which
permits users to view the fronts of buildings from a pedestrian’s viewpoint. The service utilizes photographs taken
by Google of objects that are not covered by intellectual property rights, albeit that the photographs were taken
without the authorization or agreement of the communities, and their use is monetized (Zuboff, 2019). In this
case, Google Street View becomes not only a new service for users but also a new way of exploiting value through
dispossession of public goods and private data (Zuboff, 2019).
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A field enclosure by a platform also includes encoding social interactions defined by more or less variable
practices (e.g., hailing a taxi on the street) into a precisely defined process in a controlled space (using a ridehailing app). This appropriation is produced through the codification of social interactions, control over the digital
space, and the data generated by these interactions. Moreover, by enclosing a field, digital platforms modify both
the practices and the agents’ relative positions. For example, drivers and passengers are inscribed into a database
owned by the platform owner and are organized into groups from which they are picked and matched.
Furthermore, the creation of the platform can transform the scope of the field. Digitalized practices often involve
connecting with deeply intimate aspects of users’ lives (Lupton, 2016), such as private data exemplified in photos,
comments, or information about consumption habits. While typically regarded as private, the encoding of these
portions of experience puts them into the potential reach of a field and exposes them to its specific field logic.
Furthermore, because of the new ways of performing certain practices, platforms collide with the established
scopes of the field, changing the agents and institutions involved in it. This is the so-called disruptive nature
(Stigler report, 2019) of the platform. Examples can be found in conflicts around regulatory frameworks triggered
by the introduction of platforms to some industries, such as Uber’s entry into the field of transportation and
Airbnb’s into hospitality.
2.3.1.2. Capitals
Fields are dynamic spaces defined by the relations of power between players that constitute the structure of the
field (Bourdieu & Wacquant, 2007). These relations result from “the possession and activation of resources that
are both materially and symbolically produced and perceived” (Bourdieu, 1989; 16). These resources are the
capitals.
The accumulation of capitals give access to “the specific profits that are at stake in the field, as well as by their
objective relation to other positions (domination, subordination, homology, etc.)” (Bourdieu & Wacquant, 2007;
97). In each of the specific fields, the spaces of objective relations are the sites of a logic specific to those who
regulate the fields. This logic does not need to follow purely economic rationalities to be described (Sandberg &
Alvesson, 2011). For example, TikTok users who copy their nearest higher-status digital neighbours in a particular
contest or “dance” might not be guided by economic rationality, but they do follow the logic of the platform.
Capitals are therefore the resources—scarce and socially valued stocks of internalized abilities and externalized
resources—that each agent has. Bourdieu defines three fundamental forms of capital through which power is
accumulated: economic capital (money and other assets), cultural capital (knowledge and familiarity with accepted
norms), and social capital (reflected in the actor’s creation of connections and social networks) (Bourdieu, 2011).
To these, Bourdieu adds symbolic capital, “which is the form that one or another of these species takes when it is
grasped through categories of perception that recognize its specific logic, . . . [that] misrecognize the arbitrariness
of its possession and accumulation” (Bourdieu & Wacquant, 2007; 118)., that is, the reflection in the relations of
the field of accumulated prestige, consecration, or honour (Bourdieu, 1993). For Bourdieu, power struggles are
mainly symbolic, and agents who are willing to increase their power will ultimately exercise the symbolic capital
that will help them to be “perceived and recognized as legitimate” (Bourdieu, 1989; 17) in what Bourdieu (1984)
also calls “distinction.”
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Social dynamics in fields are cantered on the generation of distinction(s) by agents, who “constantly work to
differentiate themselves from their closest rivals” (Bourdieu & Wacquant, 2007; 100)., although the actors’
participations in these games are typically no more than “unconscious or semi-conscious strategies” (Bourdieu,
1969; 118). Distinction operates through the accumulation of capital that matters to the field. Thus, fields are
spaces of conflict and competition in which the hierarchy is continually contested. However, agents can attempt to
convert one form of capital into another or transfer it to a different space, depending on the specific logic of the
field (Levina & Arriaga, 2014).
The concept of distinction can be assimilated to the concept of “status” as it is used to explain the means of
interaction on digital platforms (Levina & Arriaga, 2014). For example, on digital platforms like YouTube, a user’s
social network position and cultural skills (e.g., their offline knowledge about a particular topic) combine with their
taste and the time and money they invest into the field. Together, these shape which content gets noticed and
which is ignored (Levina & Arriaga, 2014) and therefore which agents become “influencers” or agents with high
status in the network.
2.3.1.3. Habitus
Besides the description of how agents, through their collective actions, shape emergent field structures and the
understanding of which capital matters and how, Bourdieu also looks at how structure shapes agency. Bourdieu
uses the notion of habitus to describe the socially learned schemata of perception and inclinations to action
(Bourdieu & Wacquant, 2007). Habitus is the internalization of the logic of the field. It is a set of historical relations
incorporated within individual bodies in the form of mental and corporeal schemata (Ignatow & Robinson, 2017).
These relations, or the “system of schemes of perception and appreciation of practices, cognitive and evaluative
structures,” are “acquired through the lasting experience of a social position” (Bourdieu, 1989; 19); that is, they are
acquired through interaction with other social agents. The habitus includes related comportment (posture and
gait), aesthetic likes and dislikes, habitual linguistic practices, and ways of evaluating oneself and others via
categories. It forges not only actions but also desires and aspirations (Ignatow & Robinson, 2017). While
cognitively embedded, it is also embodied in gestures, postures, movements, and accents (Ignatow & Robinson,
2017). Its reproduction depends mainly on institutions like family and school. Mastery of the habitus tends to
guarantee distinction and constancy of practice over time (Bourdieu, 1990).
Crucially, the constitution of the habitus is recursive: while agents can reshape social distance and the ways it may
be perceived, their own perception is likewise framed by their own position in the social structure. This recursive
cycle is the process of constitution of the sociosymbolic space, where changes in position can be understood as
the outcome of symbolic struggle. Habitus is therefore a way of conceptualizing how social structures influence
practice without reifying those structures (Costa, 2006).
In his studies of class, taste, and lifestyles, Bourdieu (1984) illustrates how habitus shapes taste in ways that make a
virtue out of necessity. For example, working-class people develop a taste for sensible, plain food, furnishings, and
clothes, and they shun fancy extravagances (Bourdieu, 1984). Hence habitus leads to the “choice of the necessary,”
and in so doing, it tends to generate practices that ultimately reproduce the original objective conditions, through
which it functions as structure (Costa, 2006). Thus, given a set of conditions, “habitus affords an actor some
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thoughts and behaviours and not others, making those thoughts and behaviours seem more appropriate,
attractive, and authentic than others” (Fayard & Weeks, 2014; 245). Ultimately, however, it is the actor who decides
what to do. Often the decision occupies no conscious thought, but, as Bourdieu (1990; 53) argues, it is “never
ruled out that the responses of the habitus may be accompanied by strategic calculation tending to perform in a
conscious mode.”
The concept of digital habitus has been used in the analysis of digital spaces (e.g., Ignatow & Robinson, 2017;
Levina & Arriaga, 2014; Romele & Rodighiero, 2020) to explain the ways of acting, namely, the social and
technologically ingrained habits, skills, and dispositions that define the practices in the digital field. Ignatow and
Robinson (2017) argue that digital machines are not only the crystallized parts of habitus but also habitus
producers and reproducers. This is because practices performed in digital platforms have technological and
symbolic mediations: they are digitized—coded—and they are performed through a constant interaction with
algorithms and the data that feed the learning of the algorithms. For algorithms to constitute the habitus, they
need the platform to be able to extract increasingly large amounts of data and transform them into capital. In this
context, the data work as the culture that informs the knowledge about the social space. The norms of the
platform are constantly shaped by the interaction between the data, the algorithm, and the agents. The capital
created by this interaction can be appropriated by certain agents who know how to use these results to their
advantage.
The mechanism of the digital habitus has two consequences. As socialization is increasingly done through digital
platforms, the algorithmic logic becomes a norm that everyone needs to learn to play by or with (Beer, 2017), and
thus it becomes part of the habitus. It becomes the representation of the current taste of a social class or group so
that their decisions resemble each other. However, unlike the offline habitus, it derives from code as well as from
action; thus it is somehow defined behind closed doors by the platform owners. Second, as Ignatow and Robinson
(2017) argued, the digital habitus becomes a (re)generator of the social group because it is mediated by the
property of the algorithmic practice that relates to aggregation for prediction. The singularities of social agents
are reduced to aggregates of decisions, actions, desires, and tastes. This phenomenon has been called
“personalization without personality” (Ignatow & Robinson, 2017; 100), personality being the principle that gives
unique style to each human process of individualization.
Having set the theoretical apparatus to explain how digital platforms can be understood from a sociosymbolic
perspective, we turn now to defining how digital platforms accumulate power and how power accumulation
increases the problem of organized immaturity.
2.3.2. A socio-symbolic perspective of power accumulation and its consequences for organized
immaturity
Building on Bourdieu’s later writings on the State and its forms of power (Bourdieu, 1989, 2014) and in light of the
latest developments of digital platforms and their accumulation of power, we direct our analytic attention to the
platform owner and its relations with the other platform agents and sociodigital objects. Thus, we go beyond the
extant analysis of distinction in digital platforms done by scholars of digital sociology (e.g., Ignatow & Robinson,
2017; Julien, 2015) which focuses on users, to capture the mechanisms of field transformation led by platform
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owners in their relationship with the other platform agents. We follow Bourdieu (2014) in terming these
mechanisms “forms of power” and showing how these contribute to explaining organized immaturity.
Drawing on Bourdieu’s writings (Bourdieu, 1984, 1989, 1991), we define the forms of power, distinguishing
between two general dynamics. We first define five forms of power (constitutional, juridical, discursive, distinction,
and crowd) that drive the accumulation of power within the platform. Second, inspired by recent literature on
platforms (Bucher et al., 2021; Eaton et al., 2015; Krona, 2015; Ziccardi, 2013), we show how counterpower can also
be performed by end users and other peripheral agents through crowd and hacking power. Crowd and hacking
power are not concepts derived directly by Bourdieu’s theory but provide a more comprehensive view of power
accumulation dynamics.
We then articulate the platform power dynamics through three phases of platform evolution, which are derived
from an interpretation of platform innovation research (Cutolo & Kenney, 2021; Kolagar et al., 2022; Rodon Modol
& Eaton, 2021; Teece, 2017): formation, where the platform is launched and starts to be used by agents;
domination, where the platform has been widely adopted and operates under a relatively stable design within the
original field; and cross-field expansion, where the platform expands to other fields, leveraging their accumulation
of power. Although we describe for each stage the dominant forms of power and counterpower accumulation that
enable the transformation of the field, we acknowledge that several forms of power coexist in these phases, that
the evolution of platforms is often nonlinear, and that not all platforms will become dominant.
2.3.3. Forms of Platform Power
2.3.3.1. Constitutional Power
Constitutional power is the ability to “transform the objective principles of union and separation, . . . the power to
conserve or to transform current classifications” (Bourdieu, 1989; 23). Within the platform, this power comprises
both the architectural design (platform layers and modularity, design of user interfaces and experiences) and the
capacity to define the rules, norms, categories, and languages that make up the digital interactions. Constitutional
power shapes the digital medium for interactions and defines what may and may not be accessed by each type of
agent within the platform.
Constitutional power is exercised mainly by the platform owner. As the provider of the digital infrastructure upon
which other agents collaborate, the owner defines the symbolic space through code. Code symbolically creates
the objects that constitute the relations, being a neat, unified, and unambiguous language with no openings for
interpretation (Lessig, 2009). In the digital realm, the actor who manages the code can increase its symbolic
imposition and therefore its legitimization. As the legitimation process is unified, creation and transformation are
delegated. This legitimation is “world-making” (Bourdieu, 1989), as it explicitly prescribes the possible realities and
actions. The platform owner is therefore able to hold a monopoly over legitimate symbolic violence (Bourdieu,
1989), having a differential capacity to influence and settle symbolic struggle. The possibility of obtaining and
activating this symbolic capital is associated with complex technological competences, which are scarce and highly
concentrated (Srnicek, 2016; Zuboff, 2019).
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The coherent body of code adopted by the symbolic space through constitutional power is not a neutral technical
medium (Beer, 2017; Gillespie, 2010), and it can trigger autonomy eroding. Code is created and transformed in
accordance with the objectives of the platform owner and correspondingly managed toward these goals. For
example, Kitchens et al. (2020) show how the differences in platform design for Facebook, Twitter, and Reddit
create a differentiated impact on the diversity of news and the type of content their users consume. Calo and
Rosenblat (2017) and Walker et al. (2021) find that the algorithmic design in Uber reduces drivers’ insights about
their working conditions and the competition they face, hindering their autonomy. Even without assuming
strategic manipulation, the limited symbolic and repetitive action of users implies a delegation of users’ own
independent reasoning and the emergent coordination of their actions by the platform.
2.3.3.2. Juridical Power
Along with the architecture definition, a second feature that is critical to the thriving of the platform is its
governance. While constitutional power has to do with the design of governance, juridical power is the capacity to
sanction via the created rules and the authority to arbitrate in disputes (Bourdieu, 1987, 2005). Typically, it can
take a variety of forms, such as sanctioning rule infringement, reporting abuses, or managing access to the
platform (Adner & Kapoor, 2010).
Digital technologies can enable increased participation and distribution of roles among agents, which is why
studies of governance in these contexts have favoured the idea that digitalization processes are highly
democratizing (von Hippel, 2006; Zittrain, 2009). However, the hierarchical structure of digital platforms facilitates
the creation of governance layers, meaning that the importance of those decisions can be easily packaged,
resulting in a limited distribution of power in the field. For example, transaction-oriented platforms like Amazon,
eBay, and Uber rely on user-based rating systems to ensure good quality and sanction inadequate behaviour;
however, the platform owner designs the rankings and retains control of other actions, such as account activation
and suspension (Gawer & Srnicek, 2021).
This role division effectively creates and redistributes power and therefore restricts the capacity of some agents to
interact without the intervention of the digital platform owner. Hence the definition and distribution of roles will
interact with (and eventually transform) the authority structure and the conflict management mechanisms that
pre-exist in the field, including regulation. For example, Valdez (2022) explores how Uber uses what she calls
“infrastructural” power to deploy a strategy of “contentious compliance,” both adapting to and challenging
existing regulation. This strategy allows the company to exploit differences in regulation and regulatory scrutiny to
reduce users’ access to information and acquired rights.
2.3.3.3. Discursive Power
A third distinctive form of power that characterizes agents’ strategic interplay is discursive power. Discursive
power is the power exercised in linguistic exchanges, which are embodied and learned but also generative of the
habitus (Bourdieu, 1991). The way agents talk about platforms and the words they use to explain them—these
discourses configure the collective narrative of what is possible on and valuable in a platform.
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Platforms are narrated as part of a broader, already-institutionalized rational-technological narrative in which
customer-centrism, effectiveness, and rationality of the exchanges are dominant values (Garud et al., 2022;
Gillespie, 2010). Technological determinism discourses promoted by platform owners reinforce the idea that
platforms’ algorithms are inscrutable and of a complexity unfathomable to the public or the regulator (Martin,
2021; Pasquale, 2015). These discourses have led to a broader narrative of a “Manifest Destiny” (Maddox &
Malson, 2020) of digital platforms, where the user is explicitly asked to delegate their own reasoning to the
platform. This, alongside user dispersion, is a fundamental element that enables prescribing actions. Critical to
maintaining user dispersion is the narrative that users are directly connected through the platform, which is
presented as an agora of exchanges. In actuality, platforms mediate that interaction, formatting it, regulating it, or
even suspending it.
2.3.3.4. Distinction Power
Distinction power is the creation of categories and the mechanisms of categorization that drive choice in the
platform. It builds on the concept of distinction proposed by Bourdieu (1984). It defines the rules and practices
that inhabit the habitus and designates which of them are legitimated and considered by society to be natural.
The purpose of this type of power is to produce a behavioural response that serves some agents’ specific
accumulation of capital. The platform owner can influence user behaviour by modifying the interfaces, the
encoding, and the algorithms, thereby manipulating the user’s decision-making. At the same time, users can
access and activate this power through their digital habitus, allowing them to influence and drive other users’
choices.
On platforms, distinction power is often exercised through what Kornberger, Pflueger, and Mouritsen (2017) call
evaluative infrastructures. Evaluative infrastructures are the different interactive devices, such as rankings, ratings,
or reviews, that establish an order of worth among the users of the platform, driving the “attention” (Goldhaber,
1997) of other users. They relate agents and their contributions with each other, but they are also instruments of
power. They define not only how agents are perceived and ranked in the community but also how the hierarchy is
monetized by the platform’s owners (Kornberger et al., 2017). Status markers are examples of how distinction
power is exercised. As they define how user activity and loyalty to the platform are rewarded, they become a
fundamental element in guiding agents’ accumulation strategies. For example, YouTube and Wikipedia changed
their strategy for recognizing content to stimulate newcomers (Kornberger et al., 2017). Ignatow and Robinson
(2017) refer to this process as the “übercapital.” Übercapital emphasizes the position and trajectory of users
according to the scoring, gradings, and rankings and is mobilized as an index of superiority that can have strong
reactive or performative effects on behaviour (Ignatow & Robinson, 2017).
A key feature of distinction power is that it is exercised heterogeneously over different users through differences
created by constitutional and juridical power. Different types of users are granted different forms of agency, not
only by the platform designers but also by their own intervention on the platform (Levina & Arriaga, 2014). For
instance, passive users may be granted agency through technological features. For example, YouTube gives
agency to passive users by displaying the number of views. Merely by viewing a piece of content, individuals cast
a vote on its value, which has significant consequences for the content producers. Other users become judges or
“raters” and producers of information at the same time. For example, retweeting on Twitter is both a contribution
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to the platform and an act of evaluation. As well as users who are raters, there are often users who act also as
“expert evaluators” (users who have accumulated significant cultural capital). One such example is the
“superdonor” on crowdfunding platforms like Kickstarter, whose expert evaluations influence which projects are
funded. Expert evaluators tend to form a tight-knit group within a field (Aral & Walker, 2012; Vaast et al., 2013).
Other users might have what Bourdieu called “institutionalized consecration” (Levina & Arriaga, 2014), which is the
formal authority to evaluate content given by the platform designers. These are typically site moderators and
community managers, who have more power than others to judge contributions (Levina & Arriaga, 2014). In sum,
these different types of agencies are designed by the platform owners to orient users’ actions and to promote and
demote content (Ghosh & Hummel, 2014). They are typically linked to how the platform owner designs revenue
models (Zuboff, 2019).
The forms of power presented so far tend to reinforce the power position of the platform owner, but there are
other forms of power that create the opposite tensions, that is counterpower accumulation. These are crowd and
hacking power.
2.3.3.5. Crowd Power
In the accumulation process, users are in a unique position in that they are the agents who produce the platform’s
activity. Crowd power results from the influence that users can exert on the platform by the sheer mass of their
actions, which may or may not be coordinated (Bennett et al., 2014; Culpepper & Thelen, 2020). These practices
are, in essence, the exercise of the digital habitus. The exercise of the habitus can have a long-lasting effect on the
platform’s structure. Practices can both inspire new functionalities and generate unexpected transformations to
the value proposition, which the platform owner can recapture through redesigning the code. For example, this
has been observed in the sharing and creator economies, in which, because the provider side of the platform is
the main value creator—for example, graphic designers, programmers—the platform owner periodically changes
the design to facilitate delivery of that value (Bhargava, 2021; Bucher et al., 2018).
As Bourdieu (1990) argued, the agents ultimately decide what they do, and the digital habitus may be
accompanied by strategic calculation, even if most of the practices are bound by parameters defined by the
platform owners and managed automatically by algorithms. This creates the opportunity for practices not aligned
with the value proposition to go viral, eventually posing challenges to the balance envisioned in the platform
design. For example, Krona (2015) uses the notion of “sousveillance”— an inverted surveillance “from the bottom”
or “from many to a few”—to describe the novel use of an audiovisual sharing platform by social movements
during the Arab Spring uprising. This emergent use emphasizes the emancipatory potential of users to create
collective capabilities and decision-making (Ziccardi, 2013), which we designate as crowd platform power–
challenging forms of power.
Yet, platform owners can attempt to use crowd power in their favour, in what we call the crowd platform power–
enhancing forms of power, through constitutional power (architecture design, limiting the possibility of contact
between users), juridical power (policing and sanctioning users), and distinction power (by shaping the evaluative
infrastructure). For example, Thelen (2018) shows how Uber “weaponized” the volume of its users in a regulatory
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dispute by introducing a button on its interface that would send a templated complaint email to local government
on the user’s behalf.
2.3.3.6. Hacking Power
Hacking power is the ability to identify the features and categories of digital spaces, such as overlooked
programming errors and ungoverned areas, that may be used for a different purpose than the one originally
intended (Hunsinger & Schrock, 2016; Jordan, 2009). There are numerous examples in the literature of expressions
of this type of power in digital platforms. Eaton et al. (2015) have described the continuous cycles of resistance
and accommodation performed by groups of hackers and Apple that surround the jailbreaking of each new
release of the iOS. Bucher et al. (2021) and Calo and Rosenblat (2017) have shown how workers learn to anticipate
patterns in algorithms that control their work processes and use this knowledge to defend themselves from
abuses.
Hacking power is the antithesis of individual immaturity, as it requires not only the exercise of independent
reasoning but also a degree of understanding of the specific system in which the power is exercised. It is
deliberate and purposeful, unlike crowd power, which is independent of users’ understanding because it stems
from the combined volume of their actions. At the same time, hacking power necessarily operates in the margins
or interstices of the platform. Furthermore, hacking power can be thought of as opposed to the constitutional and
juridical powers; as such, it will be dispersed, under the radar, and is often considered illegal (Castells, 2011). This
creates difficulties for creating and accumulating this power in the field and consequently for using it to challenge
other forms of power. Table 3 summarizes the different forms of power and provides further examples.
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Table 3: Forms of Platform Power and the Organization of Immaturity
Form of power
Definition
Organization of immaturity
Examples of the use of platform power
Constitutional
Design and control of the platform’s
architecture (modules, interfaces,
layers, and algorithms) and the capacity
to define the rules, norms, categories,
and languages that make up the digital
interactions
Explicitly prescribes realities and actions,
granting the platform owner a monopoly
over legitimate symbolic violence, leading
to the delegation of users’ own
independent reasoning and the emergent
coordination of their actions by the
platform.
- Definition of user requirements to join (e.g., require proof of identity to join
Airbnb)
- Definition of possible interactions (e.g., the introduction of the “Like” button on
Facebook)
- Definition of allowed and forbidden user actions (e.g., the impossibility of editing
a tweet on Twitter)
Juridical
Capacity to sanction via the created
rules and the authority to arbitrate in
disputes
Disciplines users’ voice and participation
and align them to the platform’s interests
and values
- Sanction rule infringement (e.g., suspension of a Lyft driver’s account for using an
alternative route)
- Report abuses (e.g., users flagging inappropriate content on Instagram)
- Management of access to the platform (e.g., restrict blacklisted users from using
Tinder)
Discursive
Power exercised in linguistic exchanges,
which are embodied and learned but
are also generative of the habitus
Shapes collective discourse; asks users to
delegate their own reasoning to the
platform
- Discourses of efficiency, technological determinism, or complexity promoted by
the platform owners (e.g., accuracy and neutrality of Google Search results)
- Narratives created within users’ communities (e.g., the superiority of PC/Windows
gamers over Mac users)
Distinction
Creation of categories and the
mechanisms of categorization that
drive a user’s choice in the platform
Enacts the platform owner’s capability to
shape behaviour and the digital habitus
- Definition of users’ performance, status, or visibility metrics (e.g., definition of a
property’s valuation metrics in Booking)
- Creation of differentiated tools to define hierarchies among users (e.g., ability to
view profiles while remaining anonymous for LinkedIn premium users)
Crowd
Users’ influence on platforms by the
shared mass of their actions,
coordinated or not; can become
manipulated by the platform owner
Implicitly contests immaturity when used
against platform power accumulation
- User viralization of a message or practice (e.g., coordination of a protest through
a Telegram channel)
- Force a change in the platform’s functionalities (e.g., introduction of feedback
options for service providers in UpWork)
- Manipulation of users by covertly coordinating their actions (e.g., mobilization of
Uber’s users to settle a regulatory dispute)
Hacking
Exploitation of a platform’s features
and categories for a different purpose
than the one originally intended
Explicitly contests individual immaturity, as
it requires the exercise of independent
reasoning and the understanding of the
platform’s rules
- Evade the platform’s restrictions on functionality (e.g., jailbreaking of Apple’s iOS)
- Performance of forbidden practices (e.g., get away with selling counterfeit
products on Amazon)
- Abuse the logic of the algorithm in users’ favour (e.g., disguise a user’s IP address
to access additional content on Netflix)
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2.3.4. Platform Power Dynamics
By discussing platforms in the context of fields, we have shown how the relations between the different key agents
can be understood through dynamics of power accumulation. On one hand, users activate their capitals through
the production of the practices that configure the digital habitus, which enhances their understanding of the ways
of participating on the platform. However, it is mainly the platform owner who captures most of the value creation
process through constitutional, juridical, discursive, and distinction power. This uneven distribution facilitates the
creation of a leveled field upon which the relative positions can be consolidated while, at the same time, enlarging
the distance between agents and therefore their capacity to decide in an autonomous way.
We articulate these power dynamics through the phases of platform evolution to explain how platforms transform
the agents’ relative positions over time and its impact on organizing immaturity. Figure 4 depicts the evolution in
three phases.
Figure 4: Platform Power Dynamics over Time
Platform Evolution over
Time
Forms of
Platform-related Power
Platform Formation
and Field Enclosure
(Phase 1)
Platform Domination
within Original Field
(Phase 2)
Platform
Cross-Field Expansion
(Phase 3)
Constitutional Power
Juridical Power
Forms of
Platform Power
Accumulation
Discursive Power
Distinction Power
Crowd Power (Platform-Power-Enhancing)
Forms of Platform
Counter-Power
Accumulation
Crowd Power (Platform-Power-Challenging)
Hacking Power
2.3.4.1. Phase 1: Platform Formation and Field Enclosure
In platform formation, the primary objective for the platform owner is to get users to adopt the platform and
regularly perform their practices on it. Constitutional, juridical, and discursive power are three of the forms of
power through which platform owners attempt to enclose the field organizing the emergence of immaturity, for
example, by designing a value creation model to create “exclusive control rights” (Boyle, 2003) over dimensions of
practices that were previously in the public domain. At the same time, these forms of power organize immaturity.
First, constitutional power (in the form of rules, norms, categories, and languages) defines how and under what
conditions interactions are performed and how the different agents can express their preferences. Through
juridical power, platform owners have the capacity to define the sanctions that will promote or restrict an agent’s
capacity to operate on the platform, for example, who can exercise their voice on the platform and who cannot
and what sanctions are going to be applied to misbehaviour. Finally, discursive power creates a common narrative
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about the value of the platform, restricting the capacity of agents to think beyond discourses that are presented
as truths.
2.3.4.2. Phase 2: Platform Domination within Original Field
Platform adoption and sustained use create the conditions for it to increasingly occupy the field. The increasing
participation of agents on the platform can change the predominant accumulation logics of the different agents in
the field, shaping the digital habitus. The process of capital accumulation of different agents leveraged by
distinction power defines further how immaturity is organized by promoting the processes of self-infliction of
immaturity. Capital accumulation on platforms is expressed as more data and the levying of fees, and the influx of
users is repurposed as capital to develop the platform. In turn, users invest different combinations of capitals (data
about their practices, social networks, money, and other assets) with logics of both consumption (purchasing,
sharing digital content) and profit and accumulation (influencer, merchant, driver). To thrive in the accumulation
dynamics, agents must increasingly invest themselves in the platform, adapting their strategies so they align with
those that are relevant to the platform and embedded in the digital habitus. Users adapt their practices to learn
the specific logics. This brings user practices closer to their archetypical category, and because they are better
rewarded, it further legitimizes the practices of the digital habitus. When users grasp the critical elements of the
digital habitus that correspond to their type, their practices experience and enjoy a viral thrust that characterizes
the platform logic (e.g., they may become social media superusers or influencers). This success in increasing the
capital leveraged by the mechanism of distinction power, such as rating in the platform, calls for higher
investment, increasing the users’ dependence on the platform and thus contributing to the self-inflictive process
of immaturity.
At the same time, the processes that reinforce platform power accumulation coexist with other processes that
create tensions that call for change and adjustment. Misalignments between users’ practices and their expected
behaviour can quickly accumulate, destabilizing the platform’s operation or posing challenges for its governance.
In addition, platforms with massive user bases and innumerable interactions can become problematic for the
platform owner to police, creating the space for agents to exercise their hacking power. These counterpower
accumulation forces can therefore create an emergent enlightenment—as opposed to immaturity—for the agents.
2.3.4.3. Phase 3: Platform Cross-Field Expansion
In a third phase, the platform’s domination over the field leads to the possibility of integrating new fields, further
contributing to the accumulation of power and the organizing of immaturity. Once a platform has become the
dominant agent, a position in which the structure itself acts on the owner’s behalf, it can expand the scope of the
field to new geographies and users and even enter and integrate previously separated fields. For example, Uber’s
launch of Uber Eats was deployed using the platform’s extant base of users (drivers and passengers, viewed now
as commensals).
From the domination position, the owner can operate in the various fields with great freedom, changing the
exchange rate of the capitals at play and accumulating power. Highly dominant expressions of constitutional
power include interoperability lock-ins, the use of dark patterns and biased information that impede sovereignty
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of choice, and digital workplace design and control. Juridical power can be commanded from a position of
gatekeeping, permitting arbitrary suspension of users’ accounts, biased arbitration in a dispute, the imposition of
discriminatory clauses, restriction of access to the platform, or limits on freedom of speech. Abuses of power are
typically supported by the discursive power that enacts the discourse of Manifest Destiny and uses opaque
arguments to justify the increased accumulation of power and the need to enforce the juridical power measures of
the platform owner. Also in this phase, a full deployment of distinction power relates to the platform owner’s
ability to monopolize the capture and processing of data through control of the technological architecture. This
can be used to drive user choice in multiple ways, such as information asymmetries about the activities of a
market or participant and political influences on social media platforms.
The activation of powers in the cross-field expansion phase depicts the dynamics within a field in a given moment,
but it does not mean that the dominion of the platform owner is absolute or that the platform becomes a “total
institution” (Bourdieu & Wacquant, 2007). What we highlight is how the field’s structural homology with the
platform eases a fast concentration of powers and creates remarkable obstacles to modifying this situation,
whether from within (due to users’ habituation) or outside of the platform (because of network and lock-in effects,
barriers to entry, and technical complexity). In addition to this, the form of dominion that the platform’s specific
logic enables is very effective because by creating multisided businesses, it invisibilizes the specific accumulation
and struggle dynamics with respect to the core practices users perform. For example, Amazon is “a place to buy
and sell online,” and the fact that the company accumulates capital from the capture of user data and the use of
its sellers’ capitals is not evident to the platform’s users. Thus the platform’s “rules of the game” may appear to be
somewhat objective and relatively neutral, but they are in fact part of the organization of immaturity.
2.4. Discussion
In this article, we present a sociosymbolic approach to power dynamics in digital platforms and how they relate to
organizing immaturity. A sociosymbolic approach explains the structural and agentic dynamics of power
accumulation leading to organized immaturity. We contrast the power asymmetries between the platform owner,
as the central coordinating agent, and the rest of the agents directly participating in the platform to present five
main forms of power enacted by the platform owner: constitutional, juridical, discursive, distinction, and crowd.
We also present two forms of power that explain how users counteract the platform owner’s power accumulation:
crowd and hacking. We explain how these forms of power are fundamental for understanding the different ways
in which immaturity is organized. We show that constitutional power limits the symbolic world of the users and
therefore their capacity to influence new rules and vocabularies that orchestrate participation. We explain how
through juridical power, the platform owners have the capacity to define the sanctions that restrict the voice and
participation of users. We show how through the digital habitus, the logic of the field is constituted, explaining the
emergence of immaturity and its self-infliction. However, we also argue that distinction power enacts the platform
owner’s capability to shape behaviour through creating evaluative infrastructures that mediate the emergence of
immaturity. Furthermore, we argue that the construction of a narrative of omniscience, through discursive power,
explicitly asks users to delegate their own reasoning to the platform. We also highlight the existence of forms of
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power (hacking and crowd) that help users to accumulate power and resist the central authority of the platform
owners.
Finally, we describe power dynamics and their relation to organized immaturity through three phases: first,
platform formation, where forms of power—mainly constitutional, juridical, and discursive—operate to promote
the field enclosure and set the basis for immaturity to occur; second, platform domination in the field, where
distinction power promotes the field reproduction and processes of self-infliction of immaturity, while hacking
and crowd power create resistance to the central authority; and third, platform cross-field expansion, in which
power accumulation dynamics lead to the integration of new fields and increasing dynamics of immaturity. In
defining the power accumulation dynamics, we explain the emergent character of immaturity and its relation to
agents’ strategies.
By focusing on the digital platform and its power dynamics, we contribute in two ways to the current literature.
First, we build a framework that explains the organizing dynamics of immaturity, based on the relations between
the platform structure, the digital objects, and the agents’ strategies. Through this, we expand the understanding
of organized immaturity in the light of sociological perspectives. Our framework analyses how immaturity is
constituted in practice and explains and nuances the possibility of emergence and the self-infliction dimensions of
immaturity. Second, we provide a dynamic framework of platform power accumulation contributing to the
platform literature. Finally, we also provide policy recommendations on how to tackle immaturity, and we
highlight potential avenues for further research.
2.4.1. Rethinking Organized Immaturity from a Sociosymbolic Perspective
A sociosymbolic perspective on digital platforms and its power dynamics can push the boundaries of current
concepts of organized immaturity toward a post-Kantian and more sociologically grounded view (Scherer &
Neesham, 2020). This contributes to the understanding of organized immaturity in three ways. First is by
explaining the different components of the emergence of immaturity through power struggles. We show how
struggles are the result of agents’ different strategies, heterogeneously shaped by their positions on the platform
and their practices, but also by their discourses and the history of experiences of each individual that shape the
digital habitus. By showing the dynamics in these struggles, we contribute to explaining the process through
which immaturity emerges as a non-orchestrated phenomenon.
Second, we explain self-infliction by moving away from the more political understandings of autonomy erosion.
Political perspectives of immaturity look at the individual and its “(in)capacity for public use of reason” (Scherer &
Neesham, 2020; 1) and consider the “delegation of decision making to impersonal authorities they cannot
comprehend or control” (Scherer & Neesham, 2020; 4) as a condition of the individual. We, however, adopt a
sociological view that focuses on the generation of practices and places the individual in a space of sociosymbolic
power struggles. We complement previous literature exploring the symbolic aspects of technology and its impacts
on society and, more concretely, on autonomy erosion (Fayard & Weeks, 2014; Stark & Pais, 2020; Zuboff, 2019)
by providing a set of forms of power that articulate how self-infliction is embedded in the digital habitus and thus
how immaturity is organized. Our sociosymbolic perspective explains how the conditions of agency are shaped by
the specific structure of the platform and its power dynamics.
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Last, looking at fields through the power dynamics between the different agents can shed explanatory light on the
formation process of organized immaturity. The relationship between habitus and field operates in two ways:
while the field structures the habitus as the embodiment of the immanent necessity of a field, the habitus makes
the field a meaningful space in which the agents may invest their capitals and themselves (Bourdieu & Wacquant,
2007). By defining the stages through which this relationship unfolds, we contribute to showing the emergent,
dynamic, and accumulative nature of organized immaturity.
2.4.2. Contribution to the Understanding of Platform Power Accumulation
We have approached organized immaturity by analysing platforms as spaces of coordination and production of
practices, shaped by relations engrained into a digital habitus and the logic of the field. By better understanding
the forms of power and the role they play in field transformation, we have identified more clearly the different
forms of power accumulation through which digital platforms can become vehicles for organized immaturity and
its dynamics. This contributes to the literature of platforms in the following ways. First, our description of the
structural process of power accumulation on the platform expands market and network approaches (Eaton et al.,
2015; Jacobides, 2021; Khan, 2018) by showing the importance of the social, cultural, and symbolic dimensions of
capital. This lays the foundations for fundamentally reconceptualizing platform power and further explaining how
power is exercised by the platform owner (Cutolo & Kenney, 2021; Kenney et al., 2021).
Second, we enrich structural approaches to platforms by presenting how fields can be transformed through
dynamics of power accumulation that extend beyond the consequences of an asymmetric structure (Curchod
et al., 2019; Hurni et al., 2021). Furthermore, our framework shows how platforms can be reshaped by the
interaction of agents’ strategies and the reconfiguration of the fields. By introducing a field view, we provide a
more holistic scheme in which power is both accumulated and contested. We also highlight how agents other
than the platform owner play a role in producing and exercising forms of power. This nuances our understanding
of field dynamics and agent interaction in the context of platform power dynamics.
Third, our model complements sociomaterial studies on platform power (e.g., Beer, 2017; Kornberger et al., 2017;
Stark & Pais, 2020) with the notion of the digital habitus and its relation to organized immaturity. Other authors
have analysed technological affordances as social designations of a space and the social and cultural factors that
signify a space and set a generative principle of governance (Jung & Lyytinen, 2014). Although these authors do
not talk explicitly about habitus or social capital, they reflect on the generative reproduction of norms by
individuals in contact with their social spaces; this is very similar to the Bourdieu definition of habitus in social
spaces. We complement the sociomaterial view of platforms by showing how the digital habitus works and by
emphasizing the role of the platform as an organizing agent with a privileged capacity of capital accumulation.
We present the platform as a space of symbolically mediated power relationships in which the digital objects and
structural elements interplay to conform the logic of the field. We provide an understanding of the multifaceted
nature of power as a process resulting from agents’ practices and strategies, the habitus, and capital accumulation
in a field. We argue that this conceptualization defines power in platforms not only as an “instrument” (Zuboff,
2019) at the service of the platform owners but as a web of relations utilized by agents who can better exploit the
different forms of capital. We also contribute to the debate about the coordinating role of platforms and how they
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create generative forms of distributed control while power remains centralized, in an interplay between
hierarchical and heterarchical power relations (Kornberger et al., 2017).
Bourdieu’s (1977, 1990) concepts of capitals, habitus, and distinction have been used before in the study of the
social consequences of digitalization and platforms’ increase of power (e.g., Fayard & Weeks, 2014; Levina &
Arriaga, 2014; Romele & Rodighiero, 2020). We complement that research with a view of platforms’ accumulation
of power and its role in the organizing of immaturity. We go beyond the explanation of distinction power to
define constitutional, juridical, discourse, crowd, and hacking forms of power, thereby offering a more complete
view of how platforms accumulate power and organize immaturity.
2.4.3. Contributions to Practice and Avenues for Future Research
Our article provides a conceptual framework to practitioners that can enable platform owners, users, and policy
makers to fundamentally rethink how they might address the platforms’ negative consequences for society. First, it
highlights immaturity as a relevant concept to address social issues in platforms. Our detailed understanding of
the mechanisms leading to immaturity and the manipulation of individuals’ decisions can help policy makers to
identify and set limits on these types of powers, especially in the light of platform domination. By explaining the
organizing dynamics of immaturity, we direct attention to the more holistic assessments of the social
consequences of platforms. Concretely, we emphasize how these are not just concerned with the concentration in
specific industries (such as retailing or advertising) but also involve constraints on human rights (such as freedom
of speech). Furthermore, we show how the consequences of organizing our practices through platforms are
embedded in social structures and expressed in the transformation of fields. We believe that this line of thought is
fundamental if we are to collectively rethink the social role of platforms.
Our article has also limitations that open up avenues for further research. We have identified not only forms of
platform power accumulation but also forms of platform counterpower accumulation. As our focus in this article
has been on how platforms organize immaturity, we have devoted more attention to the forms of power
accumulation. However, future work is needed to deepen our understanding of how platforms lose power. For
example, in recent years, we have witnessed an increasing backlash against big tech platforms, fuelled by
reputational scandals and vigorous societal complaints (Gawer & Srnicek, 2021; Joyce & Stuart, 2021). We have
also observed a new wave of regulatory initiatives that intend to curb platforms’ power by forcing interoperability
and limiting self-preferencing and acquisitions (Cusumano et al., 2021; Jacobides et al., 2020), even when the
effectiveness of these policies is being debated (Rikap & Lundvall, 2021). For example, in Europe, the new
legislation of the Digital Markets Act (European Commission, 2022b) and the Digital Services Act (European
Commission, 2022a) are respectively intended to create more contestability in digital platform markets. In the
United States, there has been intense debate around the possible revocation of Section 230, which has so far
provided a shield for platforms’ activities in social networks (Stigler report, 2019), leading to abuses of power and
increasing immaturity. In parallel to regulatory or external counterpower mechanisms, research into power
dynamics could also analyse the flows of affects and affective intensification (Just, 2019) that happen with the
abuse of the digital habitus. Incipient research (e.g., Castelló & Lopez-Berzosa, 2021; Just, 2019) has shown how
these flows of affects not only shape collective meanings but can also lead to increasing forms of hate speech and
the renaissance of populist politics. More should be researched about what forms of counterpower may emerge in
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society to reduce populism and hate speech. We believe that our framework sets grounds for studying the more
concrete practices of immaturity in platforms but also new forms of resistance.
2.5. Conclusion
Building on the concepts of fields, capitals, and habitus, we propose a sociosymbolic framework to explain
organized immaturity in digital platforms. We articulate six forms of power that characterize the different ways in
which platforms organize immaturity. It is our suggestion that a more precise understanding of the digital
platforms’ role in driving organized immaturity can become the basis for fundamentally rethinking the role of the
digital platform in society. Can the processes that lead to organized immaturity be reoriented toward organized
enlightenment? We argue that a first step in this direction is to better understand how power is performed in
digital platforms, which is what our framework contributes to explaining.
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3. Two-faced governance in platform ecosystems4
3.1. Introduction
Platform ecosystems have acquired enormous economic importance, disrupting and creating markets and
challenging established forms of economic and social coordination (Cusumano et al., 2019; Rochet & Tirole, 2006;
Parker et al., 2016). Platform firms orchestrate autonomous actors towards system-level goals without formal
authority in platform-based ecosystems (Adner & Kapoor, 2010; Gawer, 2014; Jacobides et al., 2018). Thus,
platforms must set governance mechanisms to govern their ecosystem members' participation (Gawer, 2014;
Kretschmer et al., 2022). Platform governance, or platform ecosystem governance, refers to the policies and
mechanisms the platform firm adopts to govern its operations on the different sides and maintain its ecosystem
(Tiwana et al., 2010). It regulates access to the platform and the interactions among its different sides (Boudreau &
Hagiu, 2008; Hagiu, 2014). In most of the largest platform ecosystems, the owner typically centralises governance
design and enforcement (Gawer, 2021). A platform owner governs its ecosystem by defining the rules for
ecosystem participation and encouraging its participants to engage in desirable behaviours (Cusumano et al.,
2019). As such, platform ecosystem governance relies on designing, deploying, and enforcing incentives and
control mechanisms to ensure collaboration and value-creating activities by the ecosystem participants. While this
creates an asymmetric position between the participants and the owner, the literature tends to assume that
participants have agency and decide whether to follow the rules or leave the platform (Kretschmer et al., 2022).
A consensus in the economics and management literature has emerged on how platform governance should be
designed and enforced. It claims that: (1) it is in the platform owners’ interest to define and enforce governance
rules that aim to keep their ecosystem participants satisfied (Hagiu, 2013; Parker et al., 2016); (2) governance rules
should be clear and precise enough to be followed by ecosystem members (Saadatmand et al., 2019; Wareham
et al., 2014); (3) the platform owner should enforce these rules (Jacobides et al., 2018; Constantinides et al., 2018);
and (4) sustained governance infringement would lead to platform failure (Boudreau, 2012; Huber et al., 2017).
However, anecdotal evidence and investigative journalism have highlighted cases when some platforms do not
seem to govern their ecosystem effectively. Examples include how Amazon includes thousands of banned, unsafe
and illegal products in its Marketplace (Berzon et al., 2019) and how it experiences persistent problems with fake
reviews (Nguyen, 2021). Other examples include Facebook’s failure to control what is generally framed as hate
speech (The Guardian, 2022). These accounts are usually interpreted as operational failures from the platform in
policing its ecosystem effectively. However, despite anecdotal evidence to the contrary, there has yet been a scant
systematic empirical exploration of the extent to which platform owners may be deliberately engaging in practices
inconsistent with their own declared governance rules. Furthermore, there has been limited empirical research on
whether the platform owner may actually benefit from these discrepancies.
This chapter was presented as a conference paper co-authored with Annabelle Gawer at the 2022 Platform
Strategy Symposium (Boston University), and the 2022 RaDMA, 2023 EGOS, and the 2023 SASE conferences. It is
currently under review for publication.
4
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This article asks: Are there sustained discrepancies between a platform firm’s declared ecosystem governance and
its actual practices? And if so, what are their consequences on the platform owner and its ecosystem members? To
address these questions, we studied Amazon between 2019 and 2022. We analyse how Amazon has governed its
Marketplace and examine the effect of its actual governance. We adopted an inductive, grounded approach based
on semi-structured interviews, participatory observation, and secondary data sources.
We find evidence of a sustained mismatch between the governance the platform declares to abide by and its
actual practices. We identify what we call the platform’s “two-faced” governance, which we define as the platform
owner’s practice of pursuing simultaneously seemingly contradictory governance practices. On the one hand, they
consist of practices consistent with the declared governance rules, roles, and activities. On the other hand, we
observe undeclared practices and “unwritten rules” of participation that depart from the declared governance.
These undeclared practices include the lack of platform owners’ support for complementors and the strategic
mismanagement of the declared governance rules, creating contradictory conditions for platform participation.
We also identify a set of adaptive practices that ecosystem participants adopt and find that they, too, resort to
sets of declared and undeclared practices. We present a process of two-faced platform governance that clarifies
how these declared and undeclared practices interact.
Our observations of the platform’s own contradictory rules, the discrepancies between official rules and actual
implementation, the frequent and unpredictable changing of rules, and its discretionary enforcement are
consistent with what might be a strategy used by the platform owner to further increase, at least in the short term,
its bargaining power over complementors. Whether it is an emergent or a deliberate strategy is outside the scope
of this paper.
Our findings principally contribute to the platform strategy literature. First, we provide evidence that runs contrary
to the four central claims of the platform strategy literature. Second, we enrich the construct of platform
governance by claiming it needs to be expanded to include the declared and undeclared governance practices we
identify and characterise. Third, we contribute to the growing literature on platform power (Crémer et al., 2019;
Gawer & Srnicek, 2021). Fourth, we derive implications for managers and policymakers.
In the next section, we review extant research on platform governance and summarise the key claims by which this
literature describes how platform governance should be designed and implemented. We then outline the
characteristics of the Amazon Marketplace and detail our data collection and analysis methods. Next, we present
our findings, describing Amazon’s declared and undeclared governance practices and how sellers adapt and
respond to them, and we present our process model of two-faced platform governance. Finally, we discuss the
consequences of our results for platform theory and practice, present our study’s limitations, and offer some
concluding remarks.
3.2. Literature - Related Research
Platforms are novel organisational forms (Gawer, 2022; Kretschmer et al., 2022; McIntyre et al., 2021) that operate
centrally within platform-based ecosystems (Adner & Kapoor, 2010; Gulati et al., 2012; Jacobides et al., 2018) and
solve the problem of coordinating autonomous entities toward a system-level goal without formal hierarchical
authority. They coordinate transactions by acting as intermediaries that bring together (match) and facilitate
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exchanges between different groups of actors by creating market incentives (Caillaud & Jullien, 2003; Rochet &
Tirole, 2003). The platform’s digital architecture is structured around a core of stable functionalities that are
redeployed in combination with complementary functionalities through interfaces to generate a family of
products (Tiwana et al., 2010; Gawer, 2014). This modular structure, designed by the platform owner, defines an
asymmetric framework in which complementors collaborate and compete (Adner & Kapoor, 2010; Dhanaraj &
Parkhe, 2006). The platform-based ecosystem consists of a constellation of agents connected via the platform. The
ecosystem participants include individuals and organisations that can play various roles, including buyers, sellers,
developers of complementary innovation, and end-users.
3.2.1. Governance in platform ecosystems
The construct of governance has been deployed in the strategy, information systems, and organisation literatures
with slightly different meanings and emphases in contexts as diverse as territories, corporations, or IT systems. A
common trait is that governance entails “creating the conditions for ordered rule and collective action” (Stoker,
2018; 15) and that it consists of “the orchestrated use of mechanisms to encourage consistent behaviour” (Staub
et al., 2023; 909, citing De Haes & Van Grembergen [2009] and Weill & Ross [2004]). In all streams of literature, in
the context of platforms and ecosystems, platform governance is understood as aiming to encourage formally
autonomous actors within the ecosystem to achieve the platform’s goals productively. Some of the literature in
information systems has taken the construct of platform governance to mean the design and deployment of
governance decisions (Tiwana, 2014) and has focused on how these decisions are distributed (Baldwin &
Woodard, 2009; Tiwana et al., 2010). This literature has focused on how rules and values are used to design and
implement governance decisions (Ghazawneh & Henfridsson, 2013; Huber et al., 2017; Kretschmer et al., 2022;
Tiwana et al., 2010). Strategy scholars tend to focus on how platform governance reflects the platform owner’s
strategies for creating and appropriating value (Chen et al., 2021a; Kretschmer et al., 2022). In this line of research,
Cusumano, Gawer, and Yoffie (2019; 67) characterise platform governance as “decid[ing] what behaviours to
encourage or discourage on the platform, and how to enforce the rules”. This definition summarises both platform
governance’s practices (deciding and enforcing), tools (rules and incentives), and target outcomes (desirable
behaviours). Consistent with this approach, Huber et al. (2017) define governance practices as the specific
activities through which the decisions about behaviours and rules are implemented.
In this study, we adopt Cusumano et al. (2019) characterisation of platform governance complemented by Huber
et al. (2017) characterisation of governance practices because they summarise two critical aspects of platform
governance. First, they are consistent with an approach that recognises the existence of different roles in the
platform ecosystem (Adner, 2017; Cusumano & Gawer, 2002). Platform owners are uniquely responsible for
defining and enforcing the rules. They are structurally central in controlling the technological architecture within
which platform ecosystem participants interact (Gawer, 2014; Kretschmer et al., 2022; Tiwana et al., 2010).
Complementors, in turn, have the role of expanding the core value proposition offered by the platform owner
(Gawer & Henderson, 2007; Parker & Van Alstyne, 2017). Second, as the participants are formally independent,
platforms must set mechanisms to encourage and discourage behaviours and enforce the rules (Gawer, 2014).
These mechanisms can be designed and deployed as combinations of legally binding contracts and informal
arrangements between a platform owner and its ecosystem participants (Tiwana et al., 2010; Uzunca et al., 2022).
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3.2.2. The consensus on platform governance: Four central claims
A consensus has emerged in the economics and management literature around how platform governance should
be designed and implemented. We identify and detail four central claims.
First, it is in the platform owner’s best interest to design the governance to satisfy all the platform sides . The
literature has emphasised the convenience for the platform of this confluence of interests, stating that “a
successful ecosystem is one in which all actors are satisfied with their positions” (Adner, 2017; 42) or that “the
platform owners’ priorities, then, are to protect their own interests and secure their competitive positions while
also securing the interests of producers and consumers who contribute to value-creation on the platform.”
(Constantinides et al., 2018; 384). This view of governance has been considered as not only essential to value
creation but also to winning in platform competition (Teece, 2018). The underlying logic is that since participation
is voluntary and all sides are needed to deliver the value proposition, strong enough incentives must be set in
place (Hagiu, 2013; Parker et al., 2016). In addition, the literature claims that there are virtuous cycles, based on
“network effects”, in attracting participants and creating additional value for them that has positive consequences
for the platform owner. (Katz & Shapiro, 1985). However, satisfying all sides requires the platform owner to
manage the conflicts between participants' divergent interests (Adner, 2017) and find the right balance between
them. Platform governance research aims to illuminate these trade-offs and suggest ways to navigate them (Eaton
et al., 2015; Ghazawneh & Henfridsson, 2013; Islam et al., 2023; Staub et al., 2023; Wareham et al., 2014).
A second claim in the platform literature is that platform governance rules and roles should be clearly articulated
and precisely defined. If, as Tiwana et al. (2010) suggest, platform governance should aim to improve
coordination, then it needs to be clear and precise enough to be easily followed and enforced (Huber et al., 2017;
Islam et al., 2023; Uzunca et al., 2022). This claim has been associated with the rules governing access to the
platform’s core functionalities (Wareham et al., 2014) and the participants’ expected behaviours (Saadatmand et
al., 2019). Overall, formulating clearly “who is allowed to do what” is a priority in platform governance (Cusumano
et al., 2019; Jacobides et al., 2022) and has implications for both the platform owner and its ecosystem participants
(Parker et al., 2016).
A third claim in the platform literature is that platform owners should enforce the governance rules that they set.
The platform owner’s role goes beyond simply formulating the rules of ecosystem members’ participation; it also
requires it to enforce them to sustain the alignment of ecosystem members (Jacobides et al., 2018; Teece, 2018).
As Jacobides et al. (2018) argue, “platform governance appears to require a firm hand” (Jacobides et al., 2022:20)
to adequately coordinate operations and safeguard value creation. The behaviours included in enforcement
include platform owners rewarding and punishing ecosystem members’ behaviours, resolving conflicts, and
coordinating task execution (Constantinides et al., 2018; Uzunca et al., 2022). While a platform owner typically
centralises governance-enforcing efforts (Gawer, 2021), some features of platform governance can be delegated
to other actors through specific control mechanisms, often related to output or behavioural control (Levina &
Arriaga, 2014).
The fourth and last claim in the platform literature is that sustained violations of platform governance are bound
to lead to platform failure. The violations mentioned refer to both the platform’s and its ecosystem members’
violations. If governance is set in place to align participation and overcome conflicts, infringements by the
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ecosystem members will harm value creation (Boudreau, 2012; Huber et al., 2017). Consequently, “securing (…)
complementors’ contribution of value-adding complementarities and their compliance with the platform’s rules
and processes (…), is thus the most critical success factor of such organisations” (Saadatmand et al., 2019:1). For
platforms operating within vast ecosystems, it can be challenging to prevent all rule violations, sanction all
infringements adequately, or solve conflicts fairly and efficiently (Parker et al., 2016). Nevertheless, a platform
owner’s systematic failure to address breaches will likely create a toxic user environment and hinder their
participation (Boudreau, 2012; Huber et al., 2017). Parker et al. (2016) illustrate this effect in their account of how
Myspace’s demise can be attributed to a failure in policing advertised content. Similarly, Zhang et al. (2022) argue
that Apple’s governance failure after the iOS 7 jailbreak negatively impacted the developer community and led to
a significant decline in knowledge sharing.
Overall, extant research depicts a relatively unified view of platform governance and how it should be designed
and enforced for a successful platform strategy. In that consensus view, platform governance is essential to a
platform business design. It aims to create value for interconnected yet autonomous actors (the ecosystem
participants), coordinate their interactions, and align their behaviours. Platform owners are responsible for setting
and enforcing platform governance.
3.2.3. Minority views on platform governance
Departing from the consensus described above, a few scholars have explored situations when the platform owner
is not acting consistently with the governance they proclaim abiding by. These studies have tended to follow two
approaches.
In the first approach, the platform firm inconsistently applies its own rules in different situations, for example,
across different complementors. For example, Huber et al. (2017) have explored how platform firms, in the context
of the highly heterogeneous population of the enterprise software industry, do not consistently apply ecosystemwide governance rules and instead resort to specific dyadic arrangements. The authors observe and suggest that
platform firms situationally departing from ecosystem-wide governance can be a viable alternative to
orchestrating all complementors in an arm’s length way. Another example is Hurni et al. (2017)’s study, which
examines heterogeneity in complementors’ “dedication” to the platform. They suggest that platform owners
should either refrain entirely from practising rules with situational flexibility and benevolence, thereby achieving
moderate complementor dedication, or, alternatively, practice rules with both flexibility and benevolence
simultaneously, thereby maximising complementor dedication. In these studies, implementing specific rules for
specific types of complementors in specific situations, departing from unified ecosystem-wide governance, is
interpreted as benefitting both the platform owner and the complementors. While this line of research illuminates
valuable strategies for platform governance, it does not depart significantly from the views of the platform
owner’s roles and practices presented above.
In the second approach, a small but growing stream of academic articles, books, and policy reports has begun to
study platform owners’ abuses (Gawer & Srnicek, 2021; Stigler report, 2019; Cusumano et al., 2019). These studies
have focused mainly on how platform owners treat their complementors (Cutolo & Kenney, 2021; Khan, 2018;
Rietveld et al., 2020). This line of research describes the power asymmetries that enable abuse and has aimed to
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identify its sources (Jacobides, 2021). It has begun to explore the impact of platforms’ abuses on complementors
and has sought to assess the extent to which regulation and public agencies are equipped to deal with these
harms (Busch et al., 2021). However, this literature tends to address existing regulation's limitations and suggest
regulation changes rather than focusing on platform governance. An exception is Cusumano et al. (2021), who
explicitly examine the relationship between platform governance and government regulation, asking whether selfregulation, essentially an act of platform governance, can save digital platforms from overly intrusive top-down
government regulation.
Furthermore, anecdotal evidence and investigative journalism have highlighted cases when some platforms do not
seem to govern their ecosystem effectively. Examples include how Amazon includes thousands of banned, unsafe
and illegal products in its Marketplace (Berzon et al., 2019) and how it experiences persistent problems with fake
reviews (Nguyen, 2021). Other examples include Facebook’s failure to control what is generally framed as hate
speech (The Guardian, 2022). These accounts are usually interpreted as operational failures from the platform in
policing its ecosystem effectively.
3.2.4. Research Question
Based on our literature review, and despite the importance of the topic, we argue that there has not been any
systematic empirical exploration of the extent to which platform owners may be deliberately engaging in practices
inconsistent with their own declared governance rules. Furthermore, there has been limited empirical research on
whether the platform may actually benefit from these discrepancies.
This article, therefore, asks: Are there sustained discrepancies between a platform owner’s declared ecosystem
governance and its actual practices? And what are the consequences of these discrepancies on the platform
owner and its ecosystem members?
3.3. Research methods
To address the above questions, we studied how Amazon governed its Marketplace between 2019 and 2022.
Amazon is a well-suited empirical setting to conduct this investigation, as Amazon’s ecosystem is one of the
largest in the world, with 2 million sellers. We focus on the governance rules and practices of the platform owner –
Amazon – and how sellers adapt and respond to them. We adopted an inductive grounded approach, best suited
for problematising a field’s assumptions (Alvesson, 2011; Sandberg & Alvesson, 2011) and analysing a
phenomenon in an exploratory manner (Charmaz & Bryant, 2008; Eisenhardt, 1989). It is oriented towards theory
development rather than proving existing hypotheses (Thornberg & Charmaz, 2014).
3.3.1. Empirical setting: Amazon and its Marketplace
Amazon is a global, US-headquartered technological company and one of the most successful platform firms
worldwide. It is one of the top companies in the world by market capitalisation and revenue. As of February 2023,
it had 310 million active users in twenty-eight countries and employed 1.6 million people.
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While Amazon began in 1994 as an online bookstore retailer, it gradually diversified into selling many other
categories of products and services, including toys, electronics, furniture, fresh food, and media entertainment. As
of 2023, along with Alibaba.com, Amazon was the largest Internet-based retailer in the world. Amazon has
separate retail websites (called stores) in the United States, the United Kingdom, and twenty-six other countries. It
also offers international shipping globally for many of its products. Besides online retailing, the company
produced consumer electronics and media content. As of February 2023, it operated the world's most extensive
cloud infrastructure as a service provider, one of its largest online marketplaces, and a major global advertising
service5.
On Amazon's websites and apps, customers can purchase products sold by Amazon or sellers. The Amazon
Marketplace is the digital platform through which sellers reach customers and manage operations. For having an
account and listing products, Amazon charges a combination of five different fees: subscription, referral, closing,
high-volume listing, and refund administration. The subscription includes analytics and automation services
through the Amazon Marketplace Web Service. After receiving an order from a customer, the seller has three
options to fulfil it: doing it by themselves, using a third-party logistics provider, or using the Fulfilled-by-Amazon
(FBA) program for an additional fee. To gain visibility on the platform, sellers can use Amazon’s advertising
services to bid for better placements in search results. Finally, Amazon offers other services to sellers (see
Appendix A for a complete list of Amazon’s programs and policies): the seller online forum, the seller university
(with educational materials), and the service provider network (a directory of partnered third-party service
providers to sellers, such as accounting, taxes, marketing, etc.).
As stated in the 2018 letter to Amazon’s shareholders, the Marketplace’s importance for Amazon has steadily
grown. The sales volume provided by sellers surpassed that of Amazon in 2015 and kept growing. As of 2022, it
represented 65% of the total sales volume. Furthermore, in 2022, the revenue from the Marketplace (combining
seller and advertising services) amounted to 30% of Amazon’s total revenue, allegedly being its most profitable
business unit (Amazon, 2019, 2020, 2021, 2022a).
3.3.2. Data collection
We conducted this study between 2019 and 2022 and collected multiple data sources during that period (see
Table 4).
For a description of Amazon’s growth path and the interaction among its business units see Kenney et al. (2021),
Coveri et al. (2022), and Rikap (2022).
5
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Table 4. Data Sources: Detail
Data Source
Cases
Hours
37
23
Sellers
20
12
Amazon
2
2
Service providers*
9
5
Industry experts & media**
6
4
17
109
Events
9
93
Forums & social media
8
16
- Understanding of sellers’
characteristics and general
challenges
- Triangulation to identify
inconsistencies
Documents
Pages
-
602
3395
Legal agreements
424
1734
Reports and studies
Guides and educational materials
27
4
1060
95
Media articles
139
422
Legislation
Other documents (campaigns against
Amazon)
5
75
3
9
Interviews
Participatory observation
Archival
Use in the analysis
- Detailed understanding of the
Marketplace’s characteristics
and dynamics
- Identification of Amazon’s and
sellers’ practices
- Understanding of the
Marketplace’s operation
- Understanding of sellers’
characteristics and general
challenges
- Triangulation to identify
inconsistencies
* Four of our service provider informants were formerly sellers
** Three of our industry experts & media informants were formerly sellers
In a preliminary phase, between October 2019 and April 2020, we learned about how the Amazon Marketplace
operates. We sought to understand its key functionalities and services, fee structure, main communication
channels, and who the main actors are in its ecosystem. To achieve this, we gathered information from industry
reports, media articles, and Amazon’s official outlets and through participatory observation in online forums and
events. In this phase, we identified the sellers as the key informants for our research.
In the next phase, between May 2020 and November 2020, we focused on understanding the sellers’
characteristics. We consulted specialised reports, surveys, guides, and educational materials designed for them.
We outlined sellers’ demographics and composition and identified the most popular product categories and
markets. Based on survey data (Jungle Scout, 2020, 2021), we also built a first outline of what sellers identify as
their main challenges and goals regarding the platform. We then created lists of potential sellers to interview in
the United Kingdom for reasons of proximity. Additional informants, including sellers in other European countries,
the United States, and China, were later reached through snowballing (Parker et al., 2019).
We conducted the first round of interviews between December 2020 and November 2021. We conducted and
recorded 23 online interviews, averaging 40 minutes each. The COVID-19 pandemic caused specific problems,
making it impossible to meet informants in person and causing industry-specific events to be cancelled.
Consequently, we found recruiting participants for this first round of interviews very challenging. Nevertheless,
once the interviews began, we were able to create rapport easily. The interviews followed a common
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questionnaire but had an open-ended format. Our questions to our informants focused on sellers’ participation in
Amazon Marketplace, their views on Amazon, and their relationship with the company.
After the first round of interviews and thanks to the suspension of some pandemic-related restrictions, we
collected more data by attending several large, in-person sellers’ conventions and meetups. This participation
helped us to understand the Marketplace’s communities better. It also helped us validate preliminary findings via
triangulation of the information obtained in the interviews.
We conducted a second round of interviews between March 2022 and May 2022, which consisted of 14 interviews
and averaged 40 minutes each. This second round maintained the semi-structured format, with questions now
centred on specific practices, dynamics, and characteristics of the Marketplace. We stopped recruiting participants
as we reached saturation (Rheinhardt et al., 2018) in the themes discussed.
Finally, we did a closing round of data collection consisting of revising additional archive material (financial
statements, surveys, market reports, and legislation) for triangulation (Rheinhardt et al., 2018) of our previous
findings. Using this material proved fundamental to validate insights or nuance insights from the data provided by
our informants when we noticed contradictions or discrepancies.
3.3.3. Data analysis
The data analysis followed an inductive grounded approach (Charmaz & Bryant, 2008; Gioia et al., 2013;
Rheinhardt et al., 2018; Thornberg & Charmaz, 2014).
After the initial revision of archival resources for immersion in the field, we transcribed and analysed the
interviews. At first, the interviews were open-coded (Corbin & Strauss, 2008) to identify key themes and conflicts.
Based on these initial codes, we built data structures (Gioia et al., 2013), which allowed us to identify the relevant
set of practices and start conceptualising the actors’ interactions and strategies towards the marketplace. We
resorted to the literature on platform strategy and governance to enhance our code structure and gain precision.
We did not follow a predefined sequence when analysing the practices. Instead, the iterations helped us identify
relevant practices and clarify their connections. In this way, some of Amazon’s practices became clear as we coded
sellers’ practices, and vice-versa. As we iterated in this analysis, both authors met periodically to discuss the
emerging categories and our interpretations of the data. In the later stages of the study, we started
conceptualising the interactions between the participants’ practices and building the process model. Once we
agreed on it, we made minor revisions to the code structure and the categories used. Finally, we prepared the final
version of the data structures connecting the practices with the supporting evidence (see Tables 7, 8, and 9).
3.4. Findings
We organise our findings in two parts. In the first one, we document (1) Amazon’s governance practices and (2)
sellers’ adaptive participation practices. In the second part, we identify and describe what we call the two-faced
governance of Amazon’s platform ecosystem, and we present a process model of how it operates.
3.4.1. Amazon governance practices
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We find that Amazon engages in two distinct sets of practices that seem, at first sight, to be inconsistent with each
other. Amazon’s first set of practices consists of what we call Amazon’s declared governance: this includes the
rules and roles that Amazon officially formulates and communicates externally and the activities through which it
implements them. The second set of practices consists of Amazon’s undeclared practices that depart from its
declared governance.
3.4.1.1. Amazon’s declared governance
Amazon presents itself as striving to be “Earth’s most customer-centric company, where customers can find and
discover anything they might want to buy online” (Amazon, 2022b). The company has declared that its
commitment to delivering this vision led them to open its digital platform for other retailers (sellers) to compete
with them through the Amazon Marketplace. In this way, Amazon offers sellers a space to reach a large audience
of potential clients and a suite of services that facilitate showcasing and fulfilling the products. At the same time, it
provides customers with an extensive range of products to choose from, secure means of exchange, and short
delivery times. As the platform owner, Amazon provides this space for interaction and claims to safeguard its
integrity, handling the communication with the customer and the payment and supporting sellers to complete the
transactions. In official documents and brochures, Amazon highlights how it “depends on sellers’ success” and
supports it by creating a trustworthy environment, preventing fraud and abuse, and offering the best services for
sellers to choose from. Sellers, in turn, must act fairly, honestly, and following the established rules and policies. As
specified in the Amazon Seller Code of Conduct, their primary responsibilities include providing accurate
information to Amazon and customers, not attempting to damage or abuse other sellers, influencing ratings and
reviews, and not circumventing the sales process.
We identify three main outcomes of the governance Amazon claims to pursue (see Table 5):
Table 5. Amazon’s declared governance: Examples, practices, and outcomes
Declared Governance Practices:
Examples
(1st-Order Concepts)
Declared Governance Practices
(2nd-Order Themes)
- Sales Rank and Advertising tools (better
positioning in search results); Featured
Merchant Status; Buy Box offer
-
- Fulfilment by Amazon; Worldwide Selling
-
Lower entry barriers to sellers
- Amazon Accelerator; Brand Registry and
Dashboard; A/B Experiments
- Product Reviews; Seller and Product Ratings; Ato-Z Guarantee; Amazon Brand Registry
- Addition of new segments and categories;
Increasing product selection
- Amazon Prime; Amazon Vine; Personalized
Recommendations
-
Provide tools for seller
development
Increase consumer trust
-
Improve offering to consumers
-
Increase consumer loyalty and
spending
-
Foment good behaviour
-
Ensure quality of interactions
- Community Rules; Amazon Seller Code of
Conduct
- Communication Guidelines; Seller Performance
Measurement
Provide visibility and access to
customers
Declared Governance
Outcome
(Aggregate Dimensions)
- Platform to attract and keep
sellers by creating
opportunities for profit
- Platform to attract and keep
consumers by assuring and
improving its buying
experience
- Platform to ensure favourable
conditions for transactions
Source: Based on interviews, participatory observation, and multiple archival sources
Attract and keep sellers on the platform by creating profit opportunities.
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The main incentive of the Marketplace for sellers is how it provides visibility and access to a large customer base.
As of 2021, 60% of US consumers declared to start their shopping searches on Amazon (Jungle Scout, 2022a).
Amazon also lowers sellers’ barriers to reaching customers by providing additional services, such as fulfilment. In
addition, the Marketplace includes various tools that facilitate the sellers’ business development, including data
analytics, brand development and protection, and market research and experimentation tools.
Attract and keep consumers on the platform by assuring and improving its buying experience.
Amazon declares to keep a loyal customer base by building trust in the buying experience through initiatives such
as encouraging customer product reviews, showcasing seller and product ratings, and offering a return guarantee.
Amazon keeps consumers attracted by its ongoing improvement of the platform’s offering, for example by adding
new product segments and reducing delivery times. Finally, Amazon aims to keep consumers on the platform and
increase spending through loyalty memberships (Prime) and personalised recommendations.
Ensure favourable conditions for transactions.
Since Amazon does not supervise individual transactions between sellers and customers, the company must set
mechanisms to ensure favourable transaction conditions. This involves specifying what types of behaviours are
allowed and establishing the punishments for infringement. The Community Rules, the Amazon Seller Code of
Conduct, and the typification of Offenses are some of the mechanisms used to ensure good behaviour. These
rules establish that users’ infringements can lead to account suspension and financial penalties. Similarly, the
quality of the interactions is safeguarded by overwatching seller performance and establishing communication
guidelines.
Typically, each outcome encompasses more than one practice and affects different types of participants
differently. For example, the product review functionality contributes to all three outcomes. It provides customers
with additional information about the product before the purchase, it can benefit the seller by showcasing the
account of a satisfied customer, and it works as a quality control device through the ratio of positive and negative
reviews. At the same time, while it is an incentive for customers, it works mainly as a control mechanism over
sellers.
We find that these governance practices are both contractually and materially embodied: on the one hand,
responsibilities and rules are defined in formal documents, such as the terms and conditions for users and the
legal agreement with sellers. But we also find that identifying how these practices are materially deployed is
crucial for understanding how they work. Governance practices can be deployed through the technological
infrastructure, for example, by the specific design of interfaces (e.g., how visible is the seller's performance in the
product page) or functionalities (e.g., how the seller's performance affects the position in search results). Further,
these practices are also visible in how digital and non-digital processes interact (e.g., how a delay in delivery is
reflected in seller performance).
We found that observing how the practices worked alongside platform
participants illuminated aspects of governance that were not observable through the legal documents.
3.4.1.2. Amazon’s undeclared governance
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We also find evidence of a wide range of Amazon’s practices inconsistent with its declared governance objectives,
official rules, and declared practices. These practices are undeclared: although we observe their presence in the
Marketplace’s operations, they are not part of any rules and roles explicitly set out. Furthermore, as these practices
can constitute law violations, Amazon denies engaging in them. However, our ecosystem member informants
openly and repeatedly mentioned them in events, forums, and social media, and they have been described in
industry reports and media articles. Next, rather than being isolated cases, we recognise patterns in these
governance practices, which systematically shape participants’ behaviours and change the value creation and
appropriation dynamics. We find that the undeclared governance practices undermine the conditions for sellers’
activities on the platform. At least in the short term, they appear to benefit Amazon by increasing its bargaining
power over its sellers.
We first describe the undeclared governance practices (see Table 6) and identify their outcomes: (1) Create an
unpredictable and precarious environment for sellers (see Table 7 for evidentiary support), and (2) Profit from an
asymmetric position (see Table 8 for evidentiary support).
Table 6. Amazon’s undeclared governance: Examples, mechanisms, practices, and outcomes
Undeclared Governance Examples:
Activities and Processes
(1st-Order Concepts)
- Automated service support;
Representatives lacking authority
or competence
- Lack of internal communication
and data sharing among
Amazon’s teams
Undeclared
Governance
Mechanisms
(2nd-Order Themes)
Undeclared Governance
Outcomes
(Aggregate Dimensions)
- Limited seller service
support
- Siloed and highly
competitive organisation
- Sellers internalise costs for
Amazon’s pitfalls due to the
difficulty of claim procedures
- Pass the error cost to
the seller
- Lack of details of how a policy
would be implemented or how a
critical parameter is measured
- Policy ambiguity
- Changes of forbidden and allowed
practices or to terms of use of
services and functionalities
- Constant update of
functionalities and rules
- Changes to inventory allowance in
warehouses; changes to seller
performance measurement
- Change of platform’s
parameters
- Unexpected and unexplained
account or product suspensions;
Warnings or suspensions based
on allegations unrelated to the
seller’s business
- Unreliable enforcement
of rules
- Lack of policing of fraudulent
sellers
- Inconsistent policing of
seller’s misbehaviour
and legal obligations
- Force sellers to use
optional services
- Penalize sellers for using nonAmazon shipping services; Force
sellers to pay to receive a better
support service
Undeclared
Governance Practices
(3rd-Order Themes)
- Lack of platform
owner’s support for
complementors
- Platform to create an
- Rules uncertainty
unpredictable and
precarious environment
for sellers
- Discretionary policing
- Impose the use of
services to sellers
- Limit competitive alternatives to
Amazon’s additional services
- Lock-in sellers through
the use of services
- Identify successful sellers’
products and launch a similar
- Copy sellers’ products
- Platform to profit from
asymmetric bargaining
position with sellers
- Unfair competition
with sellers
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Amazon version
- Favouring Amazon’s products in
search results and fulfilment times
- Elude rules for Amazon's
products
- Obtain market insights; Get
advantages by understanding
sellers’ competitive position
- Exploit sellers’ data
Source: Based on interviews, participatory observation, and multiple archival sources
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Table 7. Amazon’s undeclared governance practices (1): Create an unpredictable and precarious environment for sellers. Evidentiary support
Practice
Governance Mechanism
Exemplary excerpts from interviews
“Every time you have a problem is "that's not my department" or “can I
speak to the relevant department?”, “No, they’re firewalled off”
- Limited seller service
support
- Lack of
platform
support for
sellers
- Pass the error cost to the
seller
- Siloed and highly
competitive organisation
- Policy ambiguity
- Rules
uncertainty
- Discretionar
y policing
- Constant update of
functionalities and rules
“But nonetheless, trying to get anyone to actually help you sorted out is
another matter entirely.”
“They are going so big that it's very, very difficult to get even the simplest
things resolved with them.”
"It's funny how many workarounds and systems you have to build just to be
able to prove you overcharge me $1,000 on this item."
"You get a black mark for dispatching it late. But it's not late. It's actually
Amazon's delivery drivers collected it late."
Other supporting evidence
"Amazon’s Seller Support Central generally prompt automated, unhelpful responses,
which may be entirely unrelated to the specific case, question, or concern raised by
the seller.” (Nadler & Cicilline, 2022)
Three surveys conducted between 2020 and 2022 show that between 58% and 66%
of respondents have experienced poor seller support from Amazon" (ILSR, 2022;
Jungle Scout, 2020, 2021)
“A third-party bookseller told Subcommittee staff that Amazon delisted 99% of his
business’s inventory in September 2019. The bookseller requested that Amazon
return its products, which were stored in Amazon’s warehouses.1675 As of July
2020, Amazon had only returned a small fraction of the bookseller’s inventory and
continued to charge him storage fees.” (Nadler & Cicilline, 2022)
“The teams are very siloed… there's a lack of communication in a lot of
cases… they're obviously very protective of the data, so there's a lot of
things that certain teams can't see.”
“Amazon is deliberately siloed, so you have these kinds of competing
factions.”
“Whenever Amazon put a new policy or procedure in place… they're not
direct in their wording. So, they leave things kind of open ended” “That's
one thing that's really frustrating: nothing's ever clear.” " I feel like that kind
of makes it very difficult to excel in anything, because they're always
keeping something just out of reach of you."
"It's really, really difficult for sellers to keep up with all these constantly
changing demands."
"I do think that it's incredibly difficult, operating in Amazon… the rules are
always changing."
The constant change of the Amazon's policies and terms of service was identified as
a concern for sellers in three surveys from 2021 and 2022, with answers ranging
from 47% to 61% (ILSR, 2022; Jungle Scout, 2021, 2022b)
- Change of platform’s
parameters
"Even if we're perfect in almost every single metric, we have bigger items,
so they're penalizing us. So that's one area where we're not exactly meeting
their standards and we're getting a slap on the wrist for somebody else
who might not be performing as well but they have a smaller item."
“Another form of retaliation that Amazon reportedly engaged in was showing
publishers’ titles as out of stock or with delayed shipping times.” (Nadler & Cicilline,
2022)
A 2022 seller survey reported that 67% of them are concerned about Amazon
changing search results to favour paid results over organic results (Jungle Scout,
2022b)
- Unreliable enforcing of
rules
“Amazon shut down that listing… they have a set percentage of what they'll
allow, sometimes they don't even like at the same price. It just depends on
how moody Amazon is that day.”
“Among the most egregious examples of Amazon’s arbitrary treatment of sellers are
its abrupt suspensions of their accounts, frequently made without explanation.”
(Nadler & Cicilline, 2022)
“I can't say who they pick and choose to pick on, you know, some people
Abrupt account or listing suspension is a constant concern for sellers. In four
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Essays on Power in Digital Platforms
- Inconsistent policing of
seller’s misbehaviour and
legal obligations
get away with things that other people don't.”
surveys conducted between 2020 and 2022, between 41% and 76% of respondents
shared this preoccupation (ILSR, 2022; Jungle Scout, 2020, 2021, 2022b)
“Amazon put their head in the sand and ignored it. Because at the end of
the day, they're still making money.”
"These people are doing like really bad stuff, their account gets shut down
for like, two weeks, and then they're back again, how do they manage this?"
“Subcommittee staff uncovered evidence during the investigation that Amazon has
used its ability to police counterfeits more or less aggressively by as leverage in
contract negotiations with brands who attempt to resist Amazon pressure to sell on
its platform.” (Nadler & Cicilline, 2022)
“They make no efforts until the government kind of forced them to sort of
go overseas sellers that weren't collecting VAT, which obviously, is a
massive cost advantage.”
A 2022 survey of sellers shows that 68% of respondents consider that Amazon does
not do a good job policing unscrupulous and fraudulent Marketplace sellers (ILSR,
2022)
Source: Based on interviews and archival sources
Table 8. Amazon’s undeclared governance practices (2): Profit from an asymmetric position. Evidentiary support
Practice
Governance
Mechanism
Exemplary excerpts from interviews
Other supporting evidence
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Essays on Power in Digital Platforms
- Impose the
- Force sellers
to use
optional
services
use of
services to
sellers
- Lock-in
sellers
through the
use of
services
- Copy sellers’
products
- Unfair
competition
with sellers
- Elude rules
for Amazon's
products
“We're having an increasingly difficult time finding appointments
for our carriers… you can get an appointment very quickly if you use
their shipping service. They're kind of funnelling you into using their
shipping service, which is a little bit more expensive.”
“Amazon has recently monetised the degradation of its seller services, rolling out a program where
sellers can pay an extra fee for a dedicated account representative. Sellers are supposed to pay for
representatives to help them solve the very problems that Amazon created in the first place.” (Nadler
& Cicilline, 2022)
“We understand that it's not going to be effective if we're not
advertising.”
“Advertising services have become “less of an option and more of a requirement for sellers to
compete” on the platform, Amazon’s ads have also become more expensive.” (Nadler & Cicilline,
2022)
“They offer me an account manager, it's $4,000 a month... it was
pretty much nothing that they can do… It gives you one extra day to
think about how you're going to answer Amazon's things and
maybe give you some even indication of why you've been
suspended, which is something that Amazon don't do.”
"Italy's watchdog said in a statement that Amazon had leveraged its dominant position in the Italian
market for intermediation services on marketplaces to favour the adoption of its own logistics
service - Fulfilment by Amazon (FBA) - by sellers active on Amazon.it." (Nadler & Cicilline, 2022)
“It starts like, oh, here's a new scheme, you can get first mover
advantage. But actually, what you're doing is you're committing to it,
you can't move to a non-prime model… but actually, I'm just a guinea
pig. I'm dealing with all the system challenges and problems that go
and get ironed out and rolled out and then the market becomes
hooked on it like a drug and mounting that competitive advantage is
eroded."
“More than 73% of all Marketplace sellers worldwide reportedly rely on FBA Numerous thirdparty sellers told the Subcommittee that they feel they have no choice but to pay for FBA to
maintain a favourable search result position, to reach Amazon's more than 112 million Prime
members, and to win the Buy Box.” (Nadler & Cicilline, 2022)
"They find really high selling items… we have our [product A], they
started selling a very similar product, that they're always near the top.
And, you know, they don't really have to advertise for their own
products”
“Armed with [the sellers'] information, it appears that Amazon would copy the product to create a
competing private-label product.” (Nadler & Cicilline, 2022)
"They can sell it for a lesser price because... they are not paying
certain fees and commissions, and the margin itself."
“In March 2020, Amazon announced that it would begin temporarily delaying shipments of all
non-essential products from its warehouses, regardless of whether they were sold by Amazon or
by competing third-party sellers. Amazon reportedly excepted this policy and continued to ship
non-essential items sold by Amazon Retail from its warehouses.” (Nadler & Cicilline, 2022)
"I know [M] actually email blasts them, due to fake reviews. He's
called out a lot of like Amazon basics items. There's definitely not a
fair standard."
A 2021 investigation from Reuters, based on Amazon's internal documentation, shows the
company ran a systematic campaign of creating knockoffs and manipulating search results to
boost its own product lines in India. In 2022, the UK's CMA launched an investigation under
similar allegations.
In a 2022 seller survey, 74% of them considered that search results are manipulated to benefit
Amazon's products over those of sellers (ILSR, 2022)
In 2022, The US House of Representatives antitrust subcommittee asked for an investigation into
Amazon’s preferencing of its own brands and exclusive products in search results.
- Exploit
sellers’ data
“That does create conflicts, particularly when they start to bring in
own-brand products where they've obviously got a rich data set to
harvest. They obviously say "no, no, we don't do anything there."
“European Commission's investigation “focuses on the use by Amazon of accumulated,
competitively sensitive information about marketplace sellers, their products and transactions on
the Amazon marketplace, which may inform Amazon's business decisions.” (Nadler & Cicilline,
2022)
“One of the widely reported ways in which Amazon treats third-party sellers unfairly centres on
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Essays on Power in Digital Platforms
Amazon’s asymmetric access to and use of third-party seller data” (Nadler & Cicilline, 2022)
Source: Based on interviews and archival sources
67
Create an unpredictable and precarious environment for sellers.
We observe that Amazon has created an unpredictable and precarious environment for sellers, in line with the
findings of previous research on entrepreneurs operating on digital platforms (Curchod et al., 2019; Cutolo &
Kenney, 2021). Our interviewees describe that the main challenge they face is the high uncertainty surrounding
fundamental aspects of their activities in the Marketplace. This uncertainty pertains to how the platform rules are
applied, how they are changed, if they can continue to use their account, how unprotected they are from
emerging issues, and how hard it is to solve these problems. This unpredictable environment sustains and
increases the asymmetry of bargaining power between Amazon's and the sellers' positions, implies less platform
management costs, and provides Amazon with opportunities to profit. We distinguish three primary governance
practices in creating this environment:
Lack of platform support for complementors
Finding answers, solutions, or support as a seller in the Marketplace is very hard. The reasons behind warnings and
account blocks are not always clear or even communicated, and seller support is largely automated, sometimes
prompting responses unrelated to the specific query. Contacting a human representative is not necessarily better:
Sellers describe that the service support is often uncooperative, claiming a lack of authority or suitability for
addressing the issue. Further, Amazon's internal teams seem to be highly siloed and competing with each other.
Lastly, this lack of clear communication channels and responsibilities favours Amazon in passing the error costs to
sellers.
Rules uncertainty
While sellers are required to follow the Marketplace’s rules, this duty is hard to fulfil because rules are unclear and
constantly changing. First, the terms of use of the different services and the characteristics of their functionalities
are frequently updated, making it hard to keep up with and avoid infringement. Sellers also describe that the
wording is not always direct and straightforward when a new policy or procedure is in place. Further, some
policies’ aspects might not be declared (for example, a parameter of exclusion), with sellers finding out only when
it affects them. This creates blind spots, making sellers unsure about their compliance with rules and leaving the
decision to Amazon’s interpretation.
Discretionary policing
We observe that Amazon’s policing of the Marketplace is discretionary, which creates unfair differences in the
treatment of sellers and how they compete. Sellers denounce that rule enforcement is unreliable and inconsistent.
On the one hand, sudden account or product suspension is a shared concern. Appealing a suspension is tricky
because the reasons for infringement are usually unclear, and Amazon’s seller service is not responsive. Sellers
describe that it is not rare to receive suspensions with allegations entirely unrelated to their businesses. At the
same time, sellers complain that Amazon does not do a good job policing fraudulent sellers. These might be
performing attacks on other sellers through account or product page hacks, infringing the Marketplace’s rules to
obtain a competitive advantage, or engaging in illegal activities.
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Essays on Power in Digital Platforms
Profit from an asymmetric position
We find that Amazon uses its position as the platform owner to profit from sellers by imposing the use of optional
services and unfairly competing with them. We identify two main governance practices that allow the platform to
profit from its asymmetric position:
Impose the use of services to sellers
While all of Amazon’s services are legally optional, sellers describe several ways through which they find
themselves forced to use them. For example, sellers that try to use non-Amazon shipping services have been
penalised or put in abnormally long waiting queues to release their inventory. The use of paid advertising has
become almost a requirement to keep a position in search results. More generally, we observe that Amazon has
been able to monetise problems in the platform that it has created itself, such as the lack of seller support or late
delivery pickups. In addition, sellers denounce that they are locked-in in using services once they start to use
them, as they cannot move back without fundamentally compromising their competitive position.
Unfair competition with sellers
The fact that Amazon both manages the Marketplace and sells on it creates numerous possibilities for unfairly
competing with sellers: Amazon has a distinctive competitive advantage by having access to all of the
Marketplace’s data. Further, Amazon has been found to systematically identify successful sellers’ products and
launch a similar version while favouring its positioning in search results. Amazon also competes unfairly with
sellers by eluding the platform’s rules for its products, for example, favouring its positioning in search results.
3.4.1.3. Discrepancies between the platform’s declared and undeclared governance practices
Overall, we observe sustained discrepancies between Amazon’s declared and undeclared governance. Table 9
shows examples of these discrepancies: we observe a stark contrast between what Amazon claims about its intent,
role, and values, what they do, and how they try to limit its own liability.
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Table 9. Comparison between Amazon’s claims, legal responsibilities, and actual practices
What Amazon claims
about its intent, role, and values
How Amazon claims to support sellers
“Every day, our global teams work to provide selling
partners with the strategies, answers, guidance,
programs, and solutions they need to succeed in our
store… We have more than 24,000 Amazonians
focused on supporting and inventing for selling
partners”1
How Amazon claims to create a trustworthy
environment for sellers
“Amazon strives to be Earth’s most customer-centric
company, offering vast selection, low prices, and fast
delivery. We deliver on that vision by creating
shopping experiences that customers, sellers, and
brands can trust”2
How Amazon claims to support policing
“In 2020, we invested over $700 million and employed
more than 10,000 people to protect our store from
fraud and the abuse of customers and sellers.”3
How Amazon claims to offer the best services for
sellers to choose
“We know sellers have lots of options, and we work
hard to make Amazon the best partner to help drive
their success.”4
How Amazon depends on sellers’ success
“Our success depends on the success of our selling
partners. Amazon’s work with third-party sellers is one
of the greatest partnership stories in retail. Together,
we make a great team.”5
Amazon’s legal responsibilities as defined by its
contractual agreements
Amazon’s practices
What Amazon actually does
Amazon does not warrant a service level.
“We do not warrant that the functions contained in the Amazon sites
Lack of platform owner’s support for complementors
Finding answers and solutions is very hard because:
- Amazon is a highly siloed organisation
- Seller support is largely automated or operated by usually under-resourced
offshore teams that lack authority.
- The reasons behind warnings and account blocks are not always clear and
usually are not explained or even communicated
In addition, this lack of response facilitates passing the error costs to the sellers.
Amazon reserves the right to change services and the platform
Amazon reserves the right to modify the Agreement at any time with
immediate effect. Continued use of the services constitutes acceptance
Rules uncertainty
When a new policy or procedure is in place, the wording is not always direct and
straightforward. Further, some specific aspects are not declared (for example, a
parameter of exclusion), with sellers finding out only when it affects them.
The constant update of the terms of service and new functionalities makes it hard
to keep up and don't infringe on them.
and the services will meet your requirements or be available, timely,
secure, uninterrupted, or error-free, and we will not be liable for any
service interruptions”6
7
of the changes. Amazon reserves the right to change and suspend
services, websites, and content (including seller’s products and
listings).
8
Amazon has no responsibilities for policing seller abuse
Sellers must comply with the Seller Code of Conduct, while no Amazon
9
Code of Conduct exists. Amazon is not responsible for policing
counterfeit, tax evasion, or other illegal activities on the platform.
10
The agreement states that all the services are optional
“Amazon Services Business Solutions, a suite of optional services for
sellers including Selling on Amazon, Fulfilment by Amazon, Amazon
Advertising, Transaction Processing Services, and the Selling Partner
11
API.”
The agreement provides Amazon with leverage against sellers’
legal action
All disputes will be settled by binding arbitration instead of court
through a request letter sent to Amazon's registered agent. Disputes
will not be conducted by class/consolidated/representative action.
12
Discretionary policing
There is an unreliable and inconsistent enforcement of rules, creating differences
between sellers.
This difference is also created because of some sellers' legal obligations and
misbehaviour overlooking.
Impose the use of services to sellers
Sellers have been penalised for not using optional services and forced to pay for
advertising to keep a position in the search results.
More generally, Amazon has used the problems it creates (like lack of seller
support or late Amazon pickup) to sell additional services (like an account
representative or the use of Amazon warehouses)
Unfair competition with sellers
Amazon has been found to exploit sellers’ data to obtain a competitive advantage,
copy sellers’ products, and elude platform rules for Amazon products (like selfpreferencing in search results)
In addition, it increases its margin by avoiding platform fees and commissions for
its own products while defining price rules for the seller’s products.
Sources: 1) 2021 Amazon Small Business Empowerment Report; 2) 2020 Amazon Brand protection report; 3) 2021 Amazon Small Business Empowerment Report; 4) 2021 Amazon Small Business
Empowerment Report; 5) 2021 Amazon Small Business Empowerment Report; 6) Amazon Services Business Solutions Agreement, section 7.a.; 7) Amazon Services Business Solutions Agreement,
section 15.a., 15. b & 15. c; 8) Amazon Services Business Solutions Agreement, section S-6; 9) Amazon Services Business Solutions Agreement, section 3 & Selling Policies and Seller Code of Conduct;
10) Amazon Anti-Counterfeiting Policy & Tax Policies; 11) Amazon Services Business Solutions Agreement, General Terms; 12) Amazon Services Business Solutions Agreement, section 18.
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Essays on Power in Digital Platforms
While Amazon displays at the core of its official mission a vision to create a trustworthy environment, the
agreement allows them to change the services and the platform with short or no notice. We find that the legal
agreement plays a critical role in setting up the tensions between the two governance faces: It dismisses Amazon
from responsibilities related to its undeclared practices. For example, while Amazon declares how much effort and
resources it puts into supporting sellers, the agreement states that a service level is not warranted. Amazon also
declares to make significant investments to prevent fraud and abuse, but the legal agreement states that Amazon
bears no responsibility for policing them.
3.4.2. Sellers’ adaptive ecosystem participation practices
We found that sellers’ behaviour is shaped by both the declared and the undeclared set of Amazon’s governance
strategies. We identify three patterns in how sellers respond to navigate the often-contradictory Marketplace’s
governance: (1) Play by the rules of the platform’s declared governance; (2) Address and exploit the platform
governance contradictions; (3) Fight platform dependence (see Table 10 for a summary of sellers’ adaptive
participation and Table 11 for exemplary excerpts).
Table 10. Sellers’ adaptive participation: Examples, mechanisms, practices, and outcomes
Sellers’ Adaptive Participation:
Examples of Activities and Processes
(1st-Order Concepts)
- Assign a job position exclusively to
deal with policy updates
- Deploy compliance verification
activities in all Amazon-related
processes
- Invest in brand recognition; Launch
new products
Sellers’ Adaptive
Mechanisms
(2nd-Order Themes)
- Keep updated on
Amazon’s policies and
rules changes
- Assure compliance with
Amazon’s rules
- Product and brand
development
- Optimise sourcing; Develop demand
forecasting; Improve packaging.
- Optimise supply chain
operations
- Outsource marketing, shipment
management, data analytics,
administration, etc.
- Bend description or picture rules to
increase the position in search results
and improve product display
- Use fake or paid-for reviews,
sabotage other sellers’ accounts and
products, sell counterfeit products
and manipulate review scores.
- Develop procedures to revert
unexpected account suspensions and
blockings by Amazon
- Learn about Black Hat tactics and
possible remedies
- Outsource activities
- Drive sales through sellers’ websites;
Use other transaction platforms;
Partner with traditional distributors
- Sell the account to specialised funds
- Sales channel
diversification
- Attach notes inside the products
encouraging direct communication
with sellers
- Drive buyers to the seller’s website to
collect data
- Create alternative
communication channels
with customers
- Collect and own
customer data
Sellers’ Adaptive
Practices
(3rd-Order Themes)
Sellers’ Adaptive Practices:
Outcomes
(Aggregate Dimensions)
- Adapt to the
platform’s rules
and requirements
- Play by the rules of the
- Develop and profit
platform’s declared
governance
within the
platform’s declared
rules
- Use ‘Grey Hat’ tactics
- Use ‘Black Hat’ tactics
- Bend, elude, or hack
the platform’s rules
- Address and exploit the
- Learn to deal with
Amazon’s undeclared
governance
- Defend from other
sellers' attacks
- Sell the Amazon account
platform governance
contradictions
- Defend from the
ecosystem’s
undeclared
practices
- Reduce
exposition to the
platform
- Evade the
- Fight platform
dependence
platform’s
intermediary role
Source: Based on interviews, participatory observation, and multiple archival sources
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Essays on Power in Digital Platforms
Table 11. Sellers’ adaptive ecosystem participation practices: Evidentiary support
Participation practice
Strategy
- Adapt to the
platform’s rules
and
requirements
Play by the
platform’s
declared rules
- Develop and
profit within the
platform’s
declared rules
- Bend, elude, or
- Keep updated on Amazon’s
policies and rules changes
- Assure compliance with
Amazon’s rules
- Product and brand
development
- "My job revolves around making sure I'm keeping up on the new policy changes that Amazon has in the marketplace."
- Optimise supply chain
operations
- “I built an FBA forecasting tool… not to sound like I'm bragging but I know our forecasting tool for FBA is pretty robust.
- Outsource activities
-
- Use ‘Grey Hat’ tactics
-
- Use ‘Black Hat’ tactics
-
hack the
platform’s rules
Address and
exploit
governance’s
contradictions
- "We've made every mistake in the book, we've gotten hit with things that weren't really a mistake. And now we know how
to address those problems."
- "We're constantly looking to add new SKUs and branch off and define the brand"
-
-
- Learn to deal with Amazon’s
undeclared governance
- Defend from the
- Defend from other sellers'
attacks
- Reduce
exposure to the
platform
-
ecosystem’s
undeclared
practices
Fight platform
dependence
Exemplary excerpts from interviews
- Sales channel diversification
- Sell the Amazon account
-
Like we put like five years of work into it.” "We manufacture our own items, you're able to control the cost a little bit more.
And we were able to market it better that ties into PPC spend also, to be able to sell more and just make more money."
"Administration is outsourced. All the like things like sorting out shipments going into Amazon stock levels, inventory
levels, I've got somebody who looks after that…we've got someone who looks after FBA orders, someone who basically
processes our website orders via Amazon... I have three people who do my social media as well."
“I don't do anything that I'm not supposed to. I mean, I might bend the rules slightly, so I might change my title and not
follow the exact, you know, Amazon formula, because it doesn't work as well… I do bend the rules as much as I can, in
terms of listings, images, EBC, but I don't ever do anything that's actually dodgy.”
"One big, big problem is the black hat tactics take for recent companies… there was a period where we got attacked 16
times with false patterns, false images, false counterfeit claims just to stop momentum. And that's very hard for a seller."
"I know people who do black hat techniques, I know of them. I've met them in conferences and things like that and they
do stuff that's highly dodgy, highly illegal. But then they make a lot of money, so they don't care so much, and they
probably don't get called."
"It doesn't matter what category you're in, this is going on… there's two different sorts of things, people that are attacking
you, specifically… And then there's other people that aren't attacking you directly but they're doing things to cheat you
out of sales"
"I guess it is a sense of firefighting... you can't really work in a strategic sense if you're just putting out fires all the time."
"One of the things that probably holds me back from growing my business the most is the amount of time I have to spend
on sorting out Amazon crap."
“I have a lot of plans of action that we've had to do typically, within 24 hours. I have to spend a couple hours and figure
out why… and then plan, do check, adjust kind of thing. I have to call into Amazon and try to explain to somebody who
might be… he doesn't really care. So, you're kind of at their mercy… you kind of have to eat crow at the first one and then
just go down the list.”
“To contest or to reply to this Blackhat you have to resort to Amazon, or you have to know how to handle yourself, you
have to just email harass them two or three times.”
“We've been around since 20[XX], we got [Y] brands. One of them we don't sell on Amazon deliberately, so you may see
that.”
“We are looking to diversify to other channels, because I would say 90% of our profit comes from Amazon exclusively.”
“I think the position that we're at in our journey… we're probably not going to do this forever. When I come to sell this
company, I'm conscious of two things, what our profit is, and what multiple we could command for that, then I think that
we have a business that's probably worth a reasonable amount of money.”
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Essays on Power in Digital Platforms
- Evade the
platform’s
intermediary
role
- Create alternative
communication channels with
customers
- Collect and own customer data
- “Amazon is trying to remove the ability for sellers to have any contact and real relationship with what it considers its
customers… The way I get around that is I make sure that I put personality into the packaging… I use a very personal
stroke”
- “The market values customers and retention, you know, when you can get valued on a multiple of sales as opposed to
EBITDA. I think that shows there's actually a real importance to having that customer data.”
Source: Based on interviews
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Play by the rules of the platform’s declared governance
First, to a large extent, sellers play by the platform’s declared rules, adapting to them and following the defined
activities to develop their businesses and make a profit. This includes adapting to the platform’s rules and
requirements and developing and profiting within the platform’s declared rules
Adapt to the platform’s rules and requirements
Sellers describe that one of the keys to success is constantly being on top of the Marketplace’s rules. This requires
them to assign enough resources to remain up to date on Amazon’s policies and rules changes. More importantly,
sellers must then ensure compliance with the rules, which requires specialised experience and training.
Develop and profit within the platform’s declared rules
Participation in the Marketplace has been fundamental in growing all our informants’ businesses. Within the
framework and tools offered by Amazon, sellers engage in different business development activities, such as
attaining visibility and differentiation by investing in marketing and brand development, optimising supply chain
operations, and adequately balancing the outsourcing of activities. The platform facilitates this through its own
additional services and by enabling third parties through API integration.
Address and exploit the platform governance contradictions
We observe that sellers both address and exploit contradictions between the declared and the undeclared
governance. In doing so, they introduce new practices into the platform ecosystem and adopt additional roles
than those set in the declared governance. We observe two sets of practices:
Bend, elude or hack the platform’s rules
We find evidence that sellers systematically engage in forbidden activities for profit and obtain competitive
advantages in the platform. Within the Marketplace, these practices are known as ‘Grey Hat tactics’ and ‘Black Hat
tactics’ (see Table 12 for detailed examples). Grey Hat tactics consist of subtly bending or eluding platform rules to
obtain minor advantages, such as infringing product descriptions or picture rules to increase the position in search
results. On the other hand, Black Hat tactics involve practices explicitly prohibited by the platform, including illegal
ones, for example, paying customers for favourable reviews. These practices are ubiquitous in conversations with
our informants, events and online forums, and industry reports. For instance, in two surveys to sellers in 2020 and
2021, between 12% and 16% of respondents declared engaging in some sort of Black Hat tactic to help their
Amazon business (Jungle Scout 2020, 2021). Further, some of these specific practices, like the use of fake product
reviews and how markets are organised around them, have been studied in previous research (Choi, 2020; He
et al., 2022).
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Essays on Power in Digital Platforms
Table 12. Detail of Sellers’ adaptive practices for bending, eluding, or hacking the platform’s rules
Type of practice
- Grey Hat (subtly
bending or eluding
platform rules to obtain
minor advantages or
otherwise gaming the
system)
- Black Hat (explicit
violations of Amazon’s
Terms of Service,
including illegal
practices)
Practice
- Optimising product
images
- Optimising product
description wording
- Using special
characters and emojis
in the product
description
- Using review
services/farms
- Using review
groups/rings
- Request customers for
a specific type of
feedback
- Selling counterfeit
products
- Use of Zombie
accounts
- Listing Hijacking
Description
- Adding banners, texts, and callouts on images to catch the eye of
shoppers, which infringes Amazon’s rules for product images.
- Amazon defines strict rules for the order in the wording of product titles
and descriptions. Sellers have found that changing this order can be
beneficial for driving consumers’ attention.
- Amazon restricts the use of special characters. Using emojis can attract
customers, and using the slash after the first words can help with Google
SEO optimisation
- Companies hired by sellers to acquire their products and leave
favourable reviews (or unfavourable reviews to competitors)
- Groups of sellers that leave each other favourable reviews
- Asking explicitly for positive reviews is forbidden by Amazon. Some
sellers include discounts or coupons for future purchases in exchange for
a positive review
- The existence of knockoff goods of various quality has been a constant
in the Amazon Marketplace.
- Creating fake accounts to search for and buy products, which influences
Amazon’s algorithms. Use of these accounts might include attacking
other sellers by buying their products, returning them, and leaving
negative reviews
- If a product sold on Amazon is not registered with a brand and
protected by intellectual property rights, other sellers can access the
product listing description and change it. A seller can then change the
product's image or description by including offensive language to get
the listing suspended.
Source: Based on interviews, participatory observation, and multiple archival sources
Defend from the ecosystem’s undeclared practices
Sellers adopt defensive practices in the face of Amazon’s unreliable rules enforcement. One part of this involves
learning how to deal with Amazon’s undeclared governance. In particular, our informants highlight the importance
of preparing for unexpected account suspensions by Amazon and learning how to revert them. The extent of this
problem for sellers has led to the appearance of specialised actors in the ecosystem, providing accountsuspension-specific legal advice and account-suspension insurance. At the same time, sellers learn to defend
themselves from other sellers’ attacks, as Amazon fails to meet its responsibilities in protecting them. Several Black
Hat tactics, mentioned before, aim to block a competitor’s account or product in the Marketplace, for example, by
sabotaging a product’s page or intimidation through false claims of intellectual property rights infringement.
Surveys to sellers show that protecting from Black Hat tactics is a constant preoccupation, with answers ranging
from 40% to 66% (Jungle Scout 2020, 2021, 2022).
Fight platform dependence
We observe that even sellers with large and steady sales volumes engage in activities to fight their dependence on
Amazon to reach their customers. In addition to Amazon having durable market power in some of the markets in
which it participates (Nadler & Cicilline, 2022), dependence is attested (and enhanced) by the fact that unless
there is a problem with the transaction, sellers are almost invisible and unreachable by consumers: sellers names
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Essays on Power in Digital Platforms
are barely displayed on the product page, and Amazon strictly forbids sellers to attempt to communicate directly
to customers. We find that sellers try to fight this dependence by:
Reduce exposure to the platform
A common trend among sellers is the attempt to reduce their exposure to Amazon. First, they look for ways to
diversify their sales channels, as the Marketplace tends to represent a very high percentage of their total income.
In addition, we observed in 2018 the emergence of funds specialised in acquiring and operating third-party
Amazon seller accounts, creating an additional feasible exit strategy for sellers.
Evade the platform’s intermediary role
Even when the legal agreement states that Amazon is not an intermediary between the sellers and its buyers,
Amazon tightly controls that interaction. Because of this, sellers attempt to create alternative communication
channels with their customers, even when this risks rule infringement, and look to drive buyers to their own sites
to collect and own customers’ data.
3.4.3. Two-faced governance
In our study of the Amazon Marketplace, we observed two opposed yet coexisting “worlds” (consistent sets of
modalities of engagement): One is based on collaboration, clear rules and roles, precise and automated processes,
and transparent behaviour metrics, leading to collective value creation. The other is conflicting and oppressing,
with uncertain rules and changing roles, an unreliable and uncertain decision-making environment, where opaque
processes lead to collective rule transgression. The active creation and maintenance of the contradictions between
these two worlds are the fundamental activities that sustain the platform’s two-faced governance as a deliberate
strategy to increase platform power. This uncertain space, rife with contradictions, facilitates the platform owner’s
lack of accountability and weakens participants’ position as they do not know which face of governance they will
encounter next.
We have therefore shown that the platform ecosystem’s dynamics are only partially described by relying on the
declared governance. The platform owner and its complementors follow this declared governance to some extent,
but their behaviours are also guided by practices that contradict it. To build a complete picture, we integrate these
different elements in a process model of what we call “two-faced platform governance” (See Figure 5).
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Figure 5. Two-faced platform governance: A process model
Platform Firm’s
practices
Declared
Facilitate
and expand
value
creation
- Attract and keep complementors by
creating opportunities for profit
- Attract and keep consumers by
controlling and improving its buying
experience
- Ensure favourable conditions for
value creation
Ecosystem’s Governance
Complementors’
practices
Undeclared
-
Lack of complementor support
Rules uncertainty
Discretionary policing
Create an unpredictable and
precarious environment for
complementors
-
Impose use of services to
complementors
Unfair competition with
complementors
Profit from
asymmetric
position
-
- Unwritten rules
- Transformed
roles
- Declared rules
and roles
Play by the platform’s
declared rules
Favors
Address and exploit
governance’s contradictions
- Adapt to the platform’s rules and
requirements
- Develop and profit within the
platform’s declared rules
-
Bend, elude, or hack the platform’s
rules
Defend from the ecosystem’s
undeclared practices
Fight platform dependence
- Reduce exposition to the platform
-
Evade platform’s intermediary role
Two-faced platform governance refers to the platform owner’s practice of pursuing simultaneously seemingly
contradictory governance practices, creating ambiguous conditions for platform participation. We observe that
this practice serves various objectives: it sustains and increases the power asymmetries between the platform
owner and the complementors; it is a way for the platform owner to balance between value capture and value
creation; and it is a way for both the platform owner and the complementors to engage in practices that are
potentially illegal or that would otherwise raise authorities’ attention.
In the two-faced platform governance, the platform owner engages in declared and undeclared governance
practices. On the one hand, the declared governance aims to facilitate and expand the value-creation processes. It
defines the proposed rules and roles that platform participants are expected to follow. On the other hand, the
undeclared governance practices aim to increase the asymmetry of power with the complementors and profit
from it. The two-faced platform governance seems consistent with a platform owner’s deliberate generating and
sustaining of a form of superior bargaining power over complementors. In turn, the discrepancies between the
declared and the undeclared governance favour complementors’ practices that address and exploit these
contradictions. Overall, both the platform owner and the complementors’ undeclared practices reshape the
ecosystem’s governance, transforming the roles and creating unwritten rules for participation.
3.5. Discussion
Our study of governance in the Amazon Marketplace holds important theoretical and practical implications for
platform research.
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Our study offers four main contributions: First, it contributes to the platform strategy literature by providing new
evidence that challenges central claims in this literature, such as the assumptions that it is always in the best
interest of platforms to satisfy all their sides when designing their governance, that governance rules should be
clearly defined, or that the platform owners should enforce the governance rules they set. Second, it enriches the
construct of platform governance by identifying that there are two types of governance practices: declared and
undeclared. It also analyses how the two interact. Third, it enriches our understanding of how platform power can
be identified and exploited. It provides evidence that platform power can be exerted in ways not previously
identified by focusing on the strategic mismanagement of the rules and the creation of uncertainty. Fourth, it
offers managerial and policy implications and opens up avenues for future research.
3.5.1. Contribution to the platform strategy literature
By integrating the undeclared practices as part of the platform governance and analysing how they interact with
the declared governance, we have provided challenging evidence to the central claims of the platform strategy
literature described in the literature section. This evidence holds significant implications for theory, which we
summarise in Table 13 and develop in detail below. Overall, our findings contribute to refining thinking on what
“good platform governance” means, including which criteria are relevant for measuring governance performance
and the related trade-offs.
Table 13. Challenging evidence to the literature’s central claims on platform ecosystem governance and
consequences for theory
Literature Claims
- It is in the platform
owner’s best interest to
design the governance
in a way that satisfies all
the platform sides
Challenging Evidence
-
We observe platform sides’
members operating constrained in
an unpredictable environment, and
this proves beneficial to the
platform owner
- Rethink to what extent and how the platform
owner keeps each side satisfied and balances
conflicting interests, how virtuous the cycles of
value creation really are, and to what extent
complementor participation is voluntary
-
Platform rules might not be clearly
defined by the platform owner, be
often changed by the platform
owner, and prove hard to
understand and to follow by
members of the platform’s sides
- Governance rules and roles can be deliberately
made to be unclear and generate uncertainty
without necessarily creating coordination issues.
-
Complementors have to assume
roles not included in the declared
governance
-
We observe the platform owner
not consistently enforcing their
own declared rules and not
meeting their role’s
responsibilities.
- Platform owners not consistently enforcing the
governance rules they set can benefit themselves
and some complementors.
-
In our study, sustained violation of
the governance arrangements has
not hindered seller participation
- Sustained violation of the governance can be part
of sustainable platform owners’ and participants’
strategies.
-
Inobservance of the declared
governance can be used as a
competitive strategy
- Reassessment of the platform owner’s challenges
and strategies for enforcing governance of
aligning interests and resolving conflicts
- Governance rules and
roles should be clearly
articulated and precisely
defined
- Platform owners should
enforce the governance
rules that they set
- Sustained violation of
the governance will lead
to platform failure
Consequences for Theory
- Reconsider the roles typically assigned to the
platform owner as an enforcer and its incentives to
do so.
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Literature claim 1: It is in the platform owner’s best interest to design the governance to satisfy all the platform
sides.
Our study indicates that Amazon sellers are frequently unsatisfied (they feel constrained, operate in an
unpredictable environment, and are subject to substantial power asymmetries), therefore showing that having
some sides constrained can prove beneficial to the platform owner. These results call for a revision in our theories
of to what extent and how the platform owner keeps each side satisfied and balances conflicting interests and to
what extent complementor participation is voluntary (Adner, 2017; Kretschmer et al., 2022). As we observe one of
the platform sides struggling while the others profit, our findings also suggest the need to reconsider how
virtuous the cycles of value creation really are (Parker et al., 2016).
Literature claim 2: Governance rules and roles should be clearly articulated and precisely defined.
We offer evidence that platform rules governing some of its sides might not be clearly defined and that by
changing frequently, they can be harder to understand and follow by complementors. In addition, we show
evidence of complementors having to assume roles not included in the declared governance to participate
successfully in the platform. These results imply that uncertainty and lack of clarity in rules and roles can be part of
the governance design (Eisenmann et al., 2009; Saadatmand et al., 2019).
Literature claim 3. Platform owners should enforce the governance rules that they set.
Our study offers evidence of the platform owner purposely not consistently enforcing the rules they declare to
abide by, not meeting their role’s responsibilities, further creating an ambiguous and uncertain ecosystem
environment. Moreover, we show that this practice can benefit the platform owner and some complementors.
These findings challenge the prevailing idea that certainty stemming from rules being properly enforced is always
a good thing for the platform and its ecosystem. These results also pose questions about what we know about the
roles typically assigned to the platform owner, its incentives to enforce rules, and what its informal authority is
built upon (Tiwana et al., 2010).
Literature claim 4: Sustained violation of the governance will lead to platform failure.
Our study shows that sustained violations of some of the governance arrangements in the Amazon Marketplace
have not hindered seller participation. On the contrary, between 2018 and 2021 (the period of our analysis), the
gross merchandise volume (GMV) sold by sellers grew 135%, or USD 216 billion, even more than Amazon’s own
GMV growth (83%, USD 96 billion) (Amazon, 2019, 2020, 2021, 2022a). We also find evidence that the
inobservance of the declared governance has been used to profit both by the platform owner and by part of the
complementors. These observations re-signify the platform owner’s challenges in enforcing governance and
resolving conflicts (Adner, 2017; Parker et al., 2016). In the platform governance literature, the owner plays this
role as both a self-interested and benevolent agent (Hurni et al., 2021). We offer a different view, where the owner
might deliberately explore how conflict plays out and impacts the platform’s dynamics and act accordingly to
profit from the outcome.
3.5.2. Enriching the construct of platform governance
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Our study enriches the construct of platform governance by identifying and integrating a new set of practices (the
undeclared governance practices) that were hitherto ignored. We know of no other studies that identify and
analyse the consequences of ambiguous or seemingly contradictory governance practices. By explaining how
actors engage in seemingly contradictory governance practices, we suggest that these practices are better
interpreted as abuses of the declared governance, yet at the same time, can be an intrinsic part of the platform
governance. We argue here that two-faced governance is a deliberate practice that can serve the platform owner
and participants to a lesser extent. Consequently, unclear and changing rules and unreliable enforcement can be
part of a high-performing governance strategy rather than a flawed governance design or failed governance
implementation. In this way, our model offers a way to understand how different governance practices – some of
them seemingly contradictory – interact towards achieving some of the platform agents’ goals. Our model can,
therefore, be useful to integrate into a platform governance framework extant research describing deceiving and
concealed platform practices, such as the use of “dark patterns” to manipulate user choice (Gawer & Srnicek,
2021) or the production of “reputational insecurity” in gig platform workers as a way to increase the platform
owner’s power (Wood & Lehdonvirta, 2022).
3.5.3.
Contributions to the literature on platform power
Our study contributes to the literature on platform power, offering an enriched understanding of how such power
can be identified and expressed. Previous research has provided different theories explaining the sources of
platform power and how it affects competition. Scholars identified three main foundations of platform market
power – gatekeeping, leveraging of resources, and information exploitation - (Jacobides, 2021; Khan, 2018) and
explained how the power accumulated by large platforms can then lead to abusive practices, such as imposing
supra monopoly prices or discriminatory clauses (Busch et al., 2021; Jacobides, 2021; Khan, 2018), restricting
access to the platform, or using data to create barriers to competition (Crémer et al., 2019; Furman, 2019; Stigler
report, 2019).
Our model of two-faced governance illuminates a different way platform power operates. Typically, platform
power abuse involves the owner inclining the playing field set in the declared governance, for example, by
changing a rule or a parameter or charging higher prices. Our study focuses instead on how maintaining rule
uncertainty or the discretionary enforcing of rules can be used as a source of power, which does not fit into the
previous conceptualisation. We highlight the practice of strategically mismanaging the rules rather than abusing
the ability to set the rules. This approach expands the focus of inquiry from how power gets exerted as a clear
bargaining power imbalance in terms of transactions or exchanges to how the conditions created for that
exchange influence its outcome: in our two-faced governance model, the lack of platform owner’s support for
complementors, the creation of an unpredictable environment and the discretionary policing are creating an
environment that facilitates imposing the use of services to, and unfair competition with, the platform’s
complementors. Our study extends the construct of platform power by providing evidence that it can be exerted
in ways that hadn't been previously identified. Consistent with the conceptualization from Chapter 2, we also find
evidence of activities through which platform ecosystem participants can exert a kind of counter-power. We
contribute to this stream of literature by adding to the repertoire of such activities the complementors’
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exploitation of the platform governance’s contradictions and their attempts to diminish their dependency on the
platform owner.
3.5.4. Managerial and policy implications
Our study implies that platform owners may get away with not satisfying all of their platform sides’ members, at
least in the short term. We do not advocate that platforms should do so, but we observe no evidence of swift
“discipline of the market” that punishes the platform if it chooses to do so. Consequently, platform owners might
explore which sides can be left, at least temporarily, unsatisfied – and to what degree – without compromising the
platform’s business model. Second, our study suggests that for the platform owner to leave certain aspects of the
governance deliberately uncertain or unclear can provide it with a certain kind of manoeuvrability. Participants, in
turn, might be able to resist and proactively shape part of their own roles, even within ecosystems where large
platforms operate with significant power asymmetries. Third, acting on the evidence that platforms seem to
operate successfully, at least in the short term, without consistent rule enforcement has practical consequences.
For example, platform owners might exploit this finding by reducing policing activities, which would reduce their
costs. Finally, if rule infringement does not necessarily lead to platform failure, platform owners might explore and
find “buffer zones” of rule violation, that is, spaces of activities where rule violation is tolerated. These can provide
flexibility in adjusting governance, capturing value, or changing the platform's design. These findings are likely to
be more applicable, at least in the short term, for platforms that enjoy market power. The more durable the
platform’s market power, the more the platform will be able to get away with these practices without a “swift
discipline of the market”.
At the same time, our research also holds important consequences for policymakers. In order to regulate
platforms effectively, policymakers need to have a nuanced understanding of how platform power is expressed.
Our empirically based, precise description of the various forms of platform practices that lead to the accumulation
of platform power and our nuanced discussion of the dynamic and interdependent consequences on
complementors can usefully enrich the empirical basis upon which regulatory enforcers may enforce existing law.
Our contribution to policy is particularly timely in a context where the behaviour of digital platforms is under
increasingly great scrutiny worldwide and where policy for the regulation of digital markets and their associated
platform ecosystems has been evolving rapidly, for example, with the approval of the new Digital Markets Act by
the European Parliament in 2022.
3.5.5. Limitations and avenues for future research
As with any empirical study based on one case study, our work has limitations. They can be addressed in future
research.
One of the main limitations of our investigation is that our case consists of a unique platform, Amazon, which has
unique characteristics. As such, it has durable market power and has been identified as a “gatekeeper” or
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company with “strategic market status” by regulatory agencies in Europe and in the UK (European Commission,
2022). This raises the question of the generalizability of our findings and opens up avenues for new research.
Further research could, therefore, examine multiple cases of platform governance over time and develop insights
on the conditions under which two-faced governance is viable and opportune for the platform owner and possibly
for the complementors. Other lines of investigation might explore how uncertainty and a lack of clear rules impact
different types of platforms and might affect each platform side differently. In addition, our findings invite us to
explore the conditions under which rules enforcement can be discretionary.
Digging deeper into the practice of enforcement, further studies might explore whether the appearance of a
certain degree of enforcement might be sufficient to align participants. For example, such studies could examine
whether a recurrent change of rules and a partial degree of rule enforcement create an environment where
policing efforts might be reduced while still being tolerated. Other studies might also engage in methodological
development to better observe undeclared governance practices.
Finally, future research could also examine how our findings relate to the organisational theory of decoupling
(Bromley & Powell, 2012; Meyer & Rowan, 1977; Scott, 2008). This theory suggests that organisations often
decouple by overtly adopting policies that conform to expectations regarding formally stated goals and
operational practices but that, in reality, there is often a discrepancy between formally stated goals and actual
behaviour. This theory, therefore, appears to offer a set of concepts that seem to illuminate the conducts we
observed and pose the question of whether the unique organisational characteristics of platform ecosystems
might bring new dimensions to decoupling.
3.6. Conclusion
Our investigation of the Amazon Marketplace has revealed dimensions of platform governance hitherto
unidentified in the literature and has provided evidence that challenges central claims in the platform strategy
literature. We defined two-faced platform governance and found evidence that it occurs in platform ecosystems. It
contains both declared and undeclared governance practices, which have significant effects. We characterised
two-faced governance and offered a process model describing how both sets of governance practices interact.
Our findings illuminate new aspects of how platforms govern ecosystems and also how, to some extent,
governance is transformed by participants’ practices.
We have shown that for platform owners, it can appear to be sustainable and even narrowly beneficial, at least in
the short term, to sustain uncertainty and lack of clarity as to the rules they impose on complementors. We argue
that the platform owner can strategically mismanage its own rules and mismanage its enforcement as an integral
part of how it governs its ecosystem. Our two-faced governance model for platform ecosystems expands the
notion of governance to new dimensions and practices and contributes to a more precise and nuanced
understanding of how platform power gets expressed. We have also derived contributions to the literature on
platform strategy, platform governance, and platform power.
As digital platforms and ecosystems become the dominant organisational form of the digital economy (Kenney &
Zysman, 2016; Gawer, 2022), the subject of platform ecosystem governance is bound to become more central.
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Whether in strategy, information systems, and organisation studies, scholars’ focus is shifting away from the
clarification of platform business models and the identification of their success factors toward a more complete
and dynamic exploration of platform firms’ behaviour, which will lead to a deeper understanding of platform
governance. We hope that scholars will find the results and discussion presented in this paper helpful in providing
further insights on platforms’ impact on competition and innovation and that our research will be relevant to both
management
practitioners
and
policymakers.
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4. The evolutionary dynamics of platform orchestration6
4.1. Introduction
Platform ecosystems have unique ways of coordinating constitutive agents and facilitating transactions among
them, leading to novel forms of value creation triggered by network effects (Parker & Van Alstyne, 2017; Rochet &
Tirole, 2003). Complementors are fundamental actors in platform ecosystems since they build on the basic
functionalities provided by the platform owner (PO) to multiply the value creation process (Gawer & Henderson,
2007). Consequently, one of the critical decisions in platform design is how to adequately balance the incentives,
rules, and tools available for complementors so they can create value and thrive in the platform, i.e., how to set
the conditions for successful complementors’ business model (Hagiu, 2006; Parker et al., 2016). Overall,
complementors’ participation and success depend on how the PO designs the ecosystem’s architecture and
orchestrates the ecosystem (Adner & Kapoor, 2010; Autio, 2021).
Complementor orchestration has been identified as one of the PO’s key tasks for making or breaking success in
platform ecosystems (Adner, 2017; Gawer & Cusumano, 2014b). Extant research has identified some of the key
trade-offs orchestrators face, such as between securing control and enabling generativity (Cenamor &
Frishammar, 2021; Eaton et al., 2015) or facilitating platform growth and capturing value themselves (Lan et al.,
2019). A burgeoning stream of research is exploring how PO orchestrates complementors and the consequences
of orchestration activities for the platform and the complementors. These studies have contributed to building a
robust understanding of how complementor orchestration influences platform growth and performance
(Cennamo & Santalo, 2013; Liang et al., 2022) and explored some of its critical consequences over
complementors, such as how it influences their performance (Rietveld et al., 2020), engagement (Saadatmand
et al., 2019), and participation practices (Zhang et al., 2022).
Despite these considerable efforts, some intriguing aspects of platform orchestration remain unstudied. In
particular, there has been so far a lack of attention to the possible connections between orchestration and the
appearance of new complementors’ business models in the platform. In other words, if the PO’s orchestration can
go beyond influencing complementors’ outcomes and manage to change the complementors themselves over
time. In addition, I know of no studies that explore how changes in the complementors’ business models can, in
turn, affect back the PO.
In this article I ask: How do platform owners orchestrate the appearance of new complementors’ business models?
And how does the platform owner benefit from this?
To answer this question, I studied the Amazon Marketplace from its launching in 2000 to 2021, using an inductive
grounded approach based on semi-structured interviews, participatory observation, and secondary data sources. I
focused on Amazon’s orchestration activities and how sellers from the Marketplace adapt and respond to those
This chapter was presented as a conference paper in the PhD workshop of the 2023 EU-DPRN conference and
accepted to be presented at the 2023 ICIS Conference.
6
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activities. I find evidence that Amazon successfully orchestrated the appearance of new sellers’ business models.
Further, I discover a pattern of dynamic adjustments between Amazon and the sellers’ business models, resulting
in an evolutionary interplay where both are transformed. This interplay is triggered by Amazon’s orchestration
activities, which, by providing functionalities, structuring seller competition, and increasing the competitive
intensity sellers face, influence the sellers’ business model transformation. In turn, this transformation is
instrumental to improving Amazon’s value proposition and increasing and creating new ways in which it captures
value in the platform.
This study makes two main contributions to platform research: First, by showing that a PO can orchestrate the
change of its complementors’ business models, I contribute to expanding our understanding of the PO’s set of
capabilities and responsibilities. Second, I contribute to the stream of literature focused on complementor
orchestration by identifying new orchestration activities and illuminating new complexities and trade-offs of
orchestration.
The remaining of this chapter is structured as follows: in the next section, I review the conceptual foundations
underpinning the research problem and discuss previous contributions on complementors and platform
orchestration. This is followed by the research methods, describing the empirical setting, data sources, and
analysis methods. Next, I present the findings, describing the appearance of new sellers’ business models,
Amazon’s orchestration activities, and how they interact. In the final section of this chapter, I offer a discussion on
how my findings contribute to extant research on platforms and provide some concluding remarks.
4.2. Literature - Related Research
Platform ecosystems have been described as novel organisational forms that facilitate the coordination of
autonomous agents towards achieving system-level goals without relying on formal authority (Adner & Kapoor,
2010; Gawer, 2014). Platforms harness great potential for value creation, both by facilitating innovation (such as
Android or iOS) and by enabling and coordinating transactions (such as Shopify or Uber) (Cusumano et al., 2019).
This potential is founded in two properties characterising platform ecosystems: a modular design and a networked
structure where interactions occur. A modular design is a defining aspect of a platform’s technological
architecture (Gawer, 2014), characterised by the existence of a group of fundamental and stable “core”
functionalities (typically provided by the platform owner) that are used in combination with complementary
functionalities (typically provided by third parties, also called complementors) to generate a family of products
(Ulrich, 1995). Interfaces are the rules governing interactions among the parts (Baldwin & Clark, 2000); they
contribute to reducing a system’s complexity and greatly simplify the scope of information required to develop
each functionality (Gawer, 2014). Consequently, modular architectures lead to economies of scale (through the
production of greater volumes of core functionalities, fixed costs amortisation, and recombinant innovation) and
economies of scope (through reducing the cost of new product development), both of which are strong incentives
to use modular design strategies (Baldwin & Woodard, 2009). Critically, the extent of the economies achieved, and
the platform's potential to foster innovation will depend on adequately defining the modular design. Next,
platforms coordinate transactions by acting as intermediaries that bring together (match) and facilitate exchanges
between different groups of networked actors (Caillaud & Jullien, 2003; Rochet & Tirole, 2003). As an
intermediary, a platform can drastically reduce transaction costs by configuring an adequate price-setting system,
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providing secure means of exchange, generating a reliable reputational system, and establishing rules for good
behaviour (Evans, 2003; Parker et al., 2016). By providing a transactional space and facilitating interactions, a
platform also creates value through network effects insofar the value derived from platform usage increases
exponentially with each additional user (Katz & Shapiro, 1985).
Complementors are fundamental actors in the platform ecosystem, as they contribute by creating, expanding, and
delivering value, which results in a complex set of relations with the PO (Gawer & Henderson, 2007). Because in
platform ecosystems consumers can usually choose among functionalities and – sometimes – how they are
combined (Jacobides et al., 2018), PO rely on complementors and have to strategically decide when to cooperate
and when to compete with them (Yoffie & Kwak, 2006). Further, complementors’ actions can substantially affect a
platform, for example, as they might dispute the platform’s leadership by building on the PO’s resources
(Cusumano & Gawer, 2002; Gawer & Henderson, 2007), and by how complementors define their offering within
and across different platforms (Tavalaei & Cennamo, 2021). Nevertheless, in large platform ecosystems, the POcomplementor relationship is typically characterised by a significant power asymmetry, as complementors depend
on the PO to access their customers, and the PO controls the technological infrastructure and defines the rules for
interaction (Curchod et al., 2019; Cutolo & Kenney, 2021).
Complementor orchestration has been identified as one of the PO’s key tasks for making or breaking success in
platform ecosystems. As argued by Agarwal et al. (2023), a central problem in platform research has been how, in
addition to designing the “ecosystem value blueprint” and creating adequate conditions for participants, PO
actively manage complementors. Orchestration can be defined as "the set of deliberate, purposeful actions
undertaken by the hub firm as it seeks to create value (expand the pie) and extract value (gain a larger slice of the
pie) from the network" (Dhanaraj & Parkhe, 2006, 659). To succeed in establishing the platform ecosystem, these
PO’s actions to orchestrate third parties need to follow a set of coherent strategic options concerning firm scope,
technology design, type of relations with the complementors, and internal organisation design (Cusumano &
Gawer, 2002; Gawer & Cusumano, 2014a). Further, the absence of formal authority in the ecosystem means that
orchestration involves managing the tensions arising among participants and persuading them to join and behave
in a way aligned with the PO’s offering (Adner, 2017; Autio, 2021).
Table 14 summarises the main complementor orchestration issues raised in the literature review and its key
findings.
Extant research has identified some key trade-offs orchestrators face and how these change according to the
ecosystem’s stage. One fundamental tension is between securing control (over participants’ behaviour and
outputs) and enabling generativity (understood as the ecosystem’s ability to facilitate unprompted innovative
outputs from participants [Zittrain, 2009]) (Cenamor & Frishammar, 2021; Cennamo & Santaló, 2019; G. Parker &
Van Alstyne, 2017; Wareham et al., 2014). Orchestrators also need to balance between facilitating platform growth
and capturing value themselves (Lan et al., 2019), mediate among multiple sides with divergent interests, and
propitiate complementors’ investment in the ecosystem while granting them autonomy (Jacobides et al., 2022). In
early or nascent ecosystems, orchestrators’ primary responsibilities have been associated to optimising
connectivity and maximising generativity while attracting participation and driving network effects within a
“coopetitive” environment (Autio, 2021; Daymond et al., 2022). In contrast, in mature ecosystems, the PO’s
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priorities should be controlling bottlenecks (i.e., complementors aiming to occupy a strategic and irreplaceable
position in the ecosystem) and creating the conditions for contained contestation to achieve fruitful outcomes
from conflicts arising among participants (Autio, 2021; Daymond et al., 2022).
A burgeoning stream of research is exploring how PO orchestrates complementors and the consequences of
orchestration activities for the platform and the complementors.
Part of this research has focused on the outcomes in terms of platform growth and performance of different
complementor orchestration strategies. For example, some of these studies discuss the platform performance
trade-offs when pursuing growth-oriented versus differentiation-oriented orchestration strategies (Cennamo &
Santalo, 2013) or when employing different strategies for complements’ development and commercialisation
(Cenamor & Frishammar, 2021). Other scholars have identified the key orchestration activities required to build
ecosystem competitive advantages (Williamson & De Meyer, 2012) and how these change in different platform
configurations (Liang et al., 2022; Zeng et al., 2021). Given the challenges in aligning and securing complementors’
contributions to the ecosystem, the design of incentives plays a central role in orchestration. Researchers have
explored the best strategies to incentivise high-quality complements while edging low-quality ones (Claussen
et al., 2013), the outcomes of alternative incentives design for complementors - including no payment for their
contributions - (Boudreau & Jeppesen, 2014), and identified the optimal configurations of platform openness and
duration of complementors’ property rights (Parker & Van Alstyne, 2017). Finally, another way for PO to
orchestrate complementors is by deciding whether to promote complements and which ones, resulting in
alternative strategies that involve complement quality, exclusivity, and timing considerations (Rietveld et al., 2019),
as well as how to avoid creating complementor bottlenecks (Agarwal et al., 2023).
Another group of studies have focused instead on how complementors are affected by the platform’s
orchestration. First, complementor performance and how it changes with different orchestration strategies has
recently received more scholarly attention. Some studies have explored, for example, the changes in
complementors’ performance and behaviour as they obtain a certification or badge by the PO (Rietveld et al.,
2021) or when the PO’s governance strategies shift according to their market position dominance (Rietveld et al.,
2020). PO and complementors sometimes share the same market space, and different approaches to orchestration
have been shown to influence the PO’s modes of entry, thus affecting complementor performance (Young Kang &
Suarez, 2022). Next, one of orchestration’s main goals is achieving high levels of complementor engagement, as
this means mobilising their resources for value creation within the platform ecosystem. Complementor
engagement has been found to vary according to how the interplay of platform architecture and governance is
configured (Saadatmand et al., 2019) and how platform boundary resources are deployed (Engert et al., 2022).
Finally, recent research has started to explore how some of the complementors’ participation practices are
impacted by orchestration activities, showing, for example, how changes in platform access control can transform
complementors’ interactions among themselves (Zhang et al., 2022) and how complementors struggle to adapt
during technological transitions, increasing the risk of platform failure (Ozalp et al., 2018).
In summary, extant research has highlighted the centrality of platform orchestration, contributed to building a
robust understanding of how complementor orchestration influences platform growth and performance, and
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explored some of its key consequences over complementors, such as how it influences their performance,
engagement, and participation practices.
Despite these considerable efforts, some intriguing aspects of platform orchestration remain unstudied. In
particular, there has been so far a lack of attention to the possible connections between orchestration and
changes in the complementors’ business models. In other words, if the PO’s orchestration can go beyond
producing changes in complementors’ outcomes and manage to change the complementors themselves. Recent
studies have begun to recognise the importance of the complementor pool’s composition, heterogeneity, and
characteristics (McIntyre et al., 2021; Rietveld et al., 2021; Zhang et al., 2022). These studies mainly discuss the
consequences of complementor heterogeneity, such as what type of contributions and offerings different types of
complementor bring to the platform (Cennamo & Santaló, 2019; Deilen & Wiesche, 2021; Wang & Miller, 2020),
how participation strategies vary with complementor size (Hukal et al., 2022), or how complementors’
organisational form and size impact their ability to capture value (Miric et al., 2019; Nambisan & Baron, 2013).
Other articles leave open questions, such as whether the degree of heterogeneity in an ecosystem implies limits to
its growth (Wareham et al., 2014) or how platforms can attract the right kind and mix of complementors (McIntyre
et al., 2021).
In addition, I know of no studies that explore how complementors’ transformation can, in turn, transform back the
PO. In particular, there are no references to this problem in the studies discussing either the relations between the
PO and the complementors (Deilen & Wiesche, 2021; Heimburg & Wiesche, 2022), how orchestrators manage
processes of emergence (Daymond et al., 2022), or how platform ecosystems evolve (Alaimo et al., 2019;
Holgersson et al., 2022; Rietveld et al., 2020; Srinivasan & Venkatraman, 2020; West & Wood, 2014).
Given the importance of complementors and their business models for platform ecosystems, understanding the
possible drivers of complementor transformation and its consequences for the PO constitutes a significant gap in
the literature.
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Table 14. Complementor orchestration: main findings and issues raised in the literature reviewed
Focus
Trade-offs faced by
orchestrators
Orchestration’s
impact on the
platform
Orchestration’s
impact on the
complementors
Orchestration issues raised
Main findings
Examples in the literature
- Securing control vs. enabling
generativity
Identification of orchestration mechanisms to manage desirable and undesirable
generativity and how they change with platform maturity
Wareham et al. (2014), Cennamo &
Santaló (2019
- Aligning potentially conflicting
interests
Identification of the types of platform failures that orchestration can address and
those that it risks provoking
Adner (2017), Lan et al. (2019),
Jacobides et al. (2022)
- Changes in orchestrators’ role
according to the ecosystem’s
stage
Distinction between the main orchestrator’s responsibilities in nascent ecosystems
(optimising connectivity and maximising generativity) and in mature ecosystems
(controlling bottlenecks and creating the conditions for contained contestation)
Autio (2021), Daymond et al. (2022)
- Impact on platform performance
Recognition of performance outcomes of different coexisting innovation, growth,
and innovation orchestration strategies
Cennamo & Santalo (2013),
Cenamor & Frishammar (2021)
- Building the platform’s
competitive advantages
Identification of the key orchestration activities required to build ecosystem
competitive advantages and how these change in different platform configurations
Williamson & De Meyer (2012),
Liang et al. (2022), Zeng et al. (2021)
- Effective incentives design
Expand the orchestrator’s toolbox on how to incentivise high-quality complements
while edging low-quality ones, configure platform openness and duration of
complementors’ property rights, or identify the conditions under which not paying to
complementors remains advantageous for the platform
Claussen et al. (2013), Boudreau &
Jeppesen (2014), Parker & Van
Alstyne (2017)
- Whether to promote complements
and which ones
Identification of the strategic trade-offs to take into consideration in determining
whether and when to promote individual complements, and the tools to balance
between complementors’ product adoption and avoid creating complementor
bottlenecks
Rietveld et al. (2019), Agarwal et al.
(2023)
- Impact on complementor
performance
Impact of the platform’s owner governance strategies shifting according to its market
position dominance, of its different modes of entry to complementors’ market space,
and of different complementor certification programs
Rietveld et al. (2021), Rietveld et al.
(2020), Young Kang & Suarez (2022)
- Impact on complementor
engagement
Impact of different configurations of platform architecture and governance and how
platform boundary resources are deployed
Saadatmand et al. (2019), Engert et
al. (2022)
- Impact on complementors’
participation practices
How complementors struggle to adapt during platform’s technological transitions,
and how changes in platform access control can transform inter-complementor
interactions
Ozalp et al. (2018), Zhang et al.
(2022)
Source: Based on the literature reviewed
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4.3. Research methods
I studied the Amazon Marketplace from its launch in 2000 to 2021. I used an inductive grounded approach based
on multiple data sources, including semi-structured interviews, participatory observation, and secondary data
sources. I focused on Amazon’s orchestration activities and how sellers adapt and respond to them. I adopted an
inductive grounded approach, which is best suited for analysing a phenomenon in an exploratory manner
(Charmaz & Bryant, 2008; Eisenhardt, 1989). It is oriented towards theory development rather than proving
existing hypotheses (Thornberg & Charmaz, 2014).
4.3.1. Empirical setting: The Amazon Marketplace and its sellers’ business models
Amazon is a US-based technological company, founded in 1994 as an online bookstore retailer and later
diversified into a broad offering of product categories like media, toys, electronics, furniture, and fresh food,
among others. As of 2023, Amazon has retail websites in twenty-eight countries, including the United States and
the United Kingdom, and is one of the largest Internet-based retailers in the world. In addition, Amazon provides
advertising, fulfilment, and cloud computing services, and produces entertainment media content consumer
electronics, and is one of the leading providers of smart-home appliances.
The Amazon Marketplace is the platform used by Amazon to run its retail business, where consumers can
purchase products sold both by Amazon and by sellers. Sellers can be considered Amazon’s complementors
because they contribute to expanding and delivering Amazon’s primary value proposition: offering “unlimited
selection” and “low prices” to its customers. While Amazon and the sellers often compete with each other,
ultimately the presence of both is crucial for attracting customers. Sellers pay Amazon a combination of fees
(subscription, referral, closing, high-volume listing, and refund administration) for maintaining a professional
account on the platform and listing and selling their products. In addition, Amazon offers several additional
services to sellers, such as storage and fulfilment, advertising, and export, among others (see Annex A for a
description of all the functionalities– called “programs” by Amazon – mentioned in this article).
The Amazon Marketplace is a well-suited empirical setting to conduct this research, being simultaneously one of
the longest-standing, largest and most important platform ecosystems worldwide. First, it was launched in 2000,
when Amazon allowed third parties to offer their products on the platform Amazon used for its own retail
business. This provides a long observation period to study the orchestration activities in place and how they
affected sellers over time. Second, gross sales in the Marketplace grew from USD 2.7 billion in 2000 (97% Amazon,
3% Sellers) to USD 590 billion in 2021 (36% Amazon, 64% Sellers), and counts with over 2 million sellers of varying
sizes and longevity in the platform. Most of these businesses’ income depends on selling on the platform,
implying that sellers are largely affected by changes in the Marketplace.
This research focuses on understanding how Amazon influenced the appearance of new sellers’ business models.
The field’s informants and the specialised industry media (such as Jungle Scout and Feedvisor) recognise six
different types of business models. The models are described in Table 15, where following Chesbrough's (2006)
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definition of business model7, I summarise their key value creation activities and their value capture strategies. I
also present the year in which each business model appeared in the Marketplace and the estimated distribution of
sellers for 2021 (Jungle Scout, 2021). There is no available information on the evolution of this distribution. The
description of the business models is aimed at building ideal types; in practice, sellers might deviate from the
description or use more than one business model at the same time.
While all the business models are based on selling products through the Marketplace, substantial differences exist
in how they create and capture value. One fundamental difference is that some business models are price
competition-based (Arbitrage and Wholesale), while others compete based on product differentiation (Private
Label, Handmade, and Aggregator). These different competitive strategies are also expressed in which key
activities support each business model: pricing and sourcing for price-based competition and marketing,
advertising, and quality assurance for differentiation-based competition. Another difference is the minimum scale
required: while most business models require a small initial capital investment and can potentially be handled by a
single person (Arbitrage, Private Label, Dropshipping, and Handmade), some require larger investments
(Wholesale) and a dedicated and professional large team (Aggregator). Finally, there are significant differences
regarding the moment when each business model first appeared in the Marketplace: Arbitrage and Wholesale
appeared in the first half of the Marketplace’s existence, while in 2012, sellers using Private Label and
Dropshipping models joined the platform, followed later by the Online Arbitrage (a variation of the original
Arbitrage model), Handmade and Aggregator business models.
“At its heart, a business model performs two important functions: value creation and value capture. First, it
defines a series of activities that will yield a new product or service in such a way that there is net value created
throughout the various activities. Second, it captures value from a portion of those activities for the firm
developing the model” (p. 108)
7
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Table 15. Types of sellers’ business models in the Amazon Marketplace
Business Model
Arbitrage /
Online Arbitrage
Description
Purchasing bargains and
discounted goods in
retailers/online stores for reselling
on Amazon.
Wholesale
Buying products in bulk from
suppliers or manufacturers for
reselling on Amazon.
Private Label /
Brands
Creating a label/brand for a
product niche that is sourced from
a manufacturer.
Dropshipping
Handmade
Aggregator
Selling niche products that are
directly fulfilled by a supplier or
manufacturer
Selling products designed and
manufactured by the seller
Acquiring other sellers’ businesses
(typically Private Label) and
operating them at a larger scale.
Key value creation activities
-
Price comparison of well-known products.
-
Sourcing and listing management.
Maintaining product consistency and restocking can be a challenge
-
Demand forecasting, sourcing, inventory
management, and pricing.
-
Products chosen are often well-known (do
not require branding or advertising) and with
a steady demand (simplifies supply chain
management)
-
Marketing, sourcing, and quality assurance
-
Branding and advertising
-
Market research and advertising
-
Simplifies the operations by avoiding dealing
with inventory management, packaging, and
shipping products. However, this implies a
lack of control over product quality control
and shipping times.
Value capture strategy
-
Price competition based on opportunity
purchases
-
Overall margins are usually low
-
Price competition based on reduced
acquisition costs
-
Individual margins tend to be low; the
key is setting large-volume and
efficient operations
-
Differentiation strategy based on
identifying product niches, leading to
comparably higher margins.
-
Based on product niche identification
and a minimum cost structure
-
Margins tend to be lower than private
label but higher than wholesale and
arbitrage
-
Product design and development
-
-
Manufacturing / Handcrafting and quality
assurance
Differentiation strategy based on
offering unique or customised products
-
-
Marketing, branding, and advertising
While individual margins can be
comparably higher, volumes tend to be
small and uncertain
-
Same as private label, focusing on the
professionalisation of activities.
-
-
Product and brand development
Differentiation strategy based on highmargin private label products and
efficiency gains derived from scaling up
operations
Appearance
Share*
(2021)
2000 / 2015
19% / 17%
2002
26%
2012
67%
2012
9%
2015
6%
2018
5%
Source: Based on specialised industry reports (Jungle Scout, 2021). *Total exceeds 100% because some sellers use more than one business model simultaneously
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4.3.2. Data collection
This research was conducted between 2019 and 2023; I collected data from multiple sources describing the
Marketplace’s activities between 2000 and 2021 (see Table 16).
Table 16. Detail of the data sources
Data Source
Cases
Hours
37
23
Sellers
20
12
Amazon
2
2
Service providers*
9
5
Interviews
Industry experts & media**
6
4
17
109
Events
9
93
Forums & social media
8
16
Documents
Pages
635
5627
Financial statements
28
2163
Legal agreements
424
1734
Reports and studies
Guides and educational materials
30
4
1123
95
Media articles
141
428
5
3
75
9
Participatory observation
Archival
Legislation
Other documents
Use in the analysis
- Detailed understanding of the Marketplace’s
characteristics and dynamics
- Identification of Amazon’s orchestration
activities and sellers’ responses
- Understanding of sellers’ characteristics and
general challenges
- Triangulation and validation
- Timeline of the Marketplace’s functionalities
offering and key Amazon’s policy decisions
- Understanding of the Marketplace’s
operations
- Identification of the Marketplace’s changes
and stages
- Triangulation and validation
* Four of the service provider informants were formerly sellers
** Three of the industry experts & media informants were formerly sellers
First (October 2019 to April 2020), I reviewed Amazon’s financial statements and industry reports to study the
evolution of Amazon’s business and its performance. I also sought to understand the fundamentals of how the
Marketplace operates, its fee structure, and the specific role of the Marketplace in Amazon’s overall business. Next
(May 2020 to November 2020), through participatory observation in online events and forums, secondary survey
data, and educational materials oriented to sellers, I started to identify sellers’ characteristics, and to create
strategies for differentiating them. I shortlisted sellers with the initially desired characteristics to interview in the
United Kingdom for convenience. I reached other informants from the United States, China, and Germany through
snowballing (Parker et al., 2019).
The first round of 23 interviews (December 2020 to November 2021) was conducted online (due to the COVID-19
pandemic), averaging 40 minutes each. I used a common questionnaire but kept an open-ended format. I asked
how the sellers’ experiences in the Marketplace and their relationship with Amazon changed over time.
In this research stage, I assembled an archive containing a yearly reconstruction of Amazon’s functionalities
offering, fees, policies, and other relevant activities for each year. This information was gathered mainly using the
Internet Archive, a resource that keeps records of websites over time. Based on this, media articles, and specialised
reports, I built a database containing contracts such as the participation agreement, policies such as the
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community rules, the sellers’ code of conduct and performance requirements, functionalities descriptions and
availability, and fees charged by Amazon.
The next phase of data collection (December 2021-March 2022) consisted of participatory observation through
the researchers’ involvement in large, in-person sellers’ conventions and meetups. These events counted with
several hundred participants consisting mainly of sellers with multiple backgrounds, product offering, size, and
seniority in the marketplace, in addition to specialised media and ecosystem service providers. I participated by
attending talks, learning about the services being offered to sellers, and engaging in conversations with
participants. These events were crucial to triangulate information, validate preliminary findings, and recruit new
informants.
I then conducted a second round of interviews (March 2022 to May 2022) consisting of 14 cases and averaging 40
minutes in duration. In these interviews, I increased the variety of sellers I interviewed and talked to industry
experts with and extended participation in the Marketplace and to Amazon representatives. I focused the
questions on the specific periods and activities of interest identified from my previous data. Once I reached
saturation in the themes discussed (Rheinhardt et al., 2018), I stopped recruiting participants.
Overall, the interviewees’ composition was highly heterogeneous: I counted with informants with direct experience
in all the business models mentioned above except Handmade, located in the UK, the USA, and China, and
belonging to organisations with very different sizes, varying from unipersonal businesses to large companies with
hundreds of employees. Regarding the informants’ experience in the Marketplace, 17% joined before 2004, 17%
between 2005-2009, 14% between 2010-2014, and 51% between 2015-20208.
4.3.3. Data analysis
I analysed the data following an inductive grounded approach (Charmaz & Bryant, 2008; Gioia et al., 2013;
Rheinhardt et al., 2018; Thornberg & Charmaz, 2014).
I first analysed the archival resources to understand the Marketplace’s essential characteristics and immersing in
the field. I then proceeded to transcribe and analyse the interviews. I open-coded them (Corbin & Strauss, 2008)
to identify Amazon’s orchestration activities and processes of sellers’ change and their possible causes. The core
of the analysis activities consisted then of triangulating and consolidating the data from the multiple sources in a
timeline. This step revolved fundamentally in linking sellers’ characteristics and activities to relevant changes in the
Marketplace. Once I identified and described the process of the appearance of new sellers’ business models and
the key orchestration activities used by Amazon, I identified the periods where the interaction between them was
more clearly expressed. I gathered additional data about these periods and described them. Finally, I built the
model to summarise the interaction mechanisms.
8
A detailed description of the interviewees’ characteristics is kept confidential to prevent potential harms.
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4.4. Findings
I organise my findings in three parts. First, I describe the process through which new sellers’ business models
appear in the Marketplace. Second, I discuss how Amazon influenced this process by identifying and describing
the specific orchestration activities used by Amazon and by illustrating how Amazon influenced the appearance of
sellers’ business models in two periods. Finally, I discuss the consequences of how Amazon’s orchestration
activities and the appearance of sellers’ business models played out throughout the period of the study and
summarise it in a model.
4.4.1. Why do sellers adopt new business models?
Throughout the period of this study, I observed a remarkable transformation of the business models that sellers
adopt in the Marketplace. I describe this process next (see Figure 6):
I find that the appearance of new business models requires two conditions. In the first place, feasibility, i.e., the
availability of the functionalities needed to support the business model’s key activities. For example, Fulfilment by
Amazon made the Private Label and Handmade models possible, as they typically are one-person businesses
created by entrepreneurs or creators who do not count with fulfilment capabilities. At the same time, the
availability of the required functionalities is not enough for the appearance of a business model in the
Marketplace. The Aggregator model appeared in 2018, but the advertising and brand development functionalities
essential for its activities were released years before, from 2012 on.
The second is the existence of changes in the competition intensity faced by sellers in the Marketplace that turn
existing profitable business models into struggling ones. Increases in competition intensity can be driven
endogenously by the arrival of new sellers, attracted by the existing business models’ profitability, and
exogenously by Amazon’s actions, as described in the next section.
When facing high competition intensity, I observe three typical responses from sellers: the first option is to exit the
Marketplace. The second is improving performance to cope with competition, for example, by improving
customer service, increasing supply chain service levels, or developing new products. These improvements
typically imply using additional optional functionalities offered by Amazon. The third is adopting a new business
model. I observe that adoption occurs when both the business model is feasible and pre-existent models' value
capture strategies and profitability prove insufficient. My evidence shows that initially, the development and
renewal of the business models are done by actors who know the platform well and are capable of identifying and
seizing the opportunity. However, once these new strategies are known, the popularisation of the new business
model is driven by new entrants. The interviewees describe how these transitions are motivated to overcome the
limitations of pre-existing business models:
“When I was reselling branded products, I’d say that had a few years where that was a good business to
be involved in but then obviously, a lot of people started doing it… And then you’ve got the kind of
private label phase” (Ecosystem service provider and former seller)
“There’s been a natural kind of selection process of smaller micro brands that have survived and have put
themselves in positions in Amazon that is competitive, sort of say. But that doesn’t escapes the fact that
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in order to run an Amazon brand, you need a number of different things that are difficult to muster up in
hard times.” (Seller)
“Entrepreneurs are creators of some of these businesses, they are typically reaching the capacity of their
time, their knowledge, or their capital.” (Seller)
Figure 6. How new sellers’ business models appear on the Marketplace
Platform
conditions
Functionalities
availability
Existing Business Model
Competitive Fit
Optional
functionalities
Minimum for
feasibility
Enables
Improves performance
Higher
usage
Struggle
Profitability
Minimum for
feasibility
Develops new
model
Adoption
Higher competition
intensity
Attracts
Exit
New sellers
Causality
New Business Model
Sellers’
responses
Functionalities
availability
Attracts
Business model’s
competitive fit
4.4.2. Amazon’s role: orchestrating change
4.4.2.1. Orchestration activities
I find that Amazon had a decisive impact on the transformation of the sellers’ business models through the
combination of three sets of orchestration activities: 1) functionality provisioning, 2) structuring seller competition,
and 3) increasing competition intensity faced by sellers. I describe these activities next and provide detailed
examples and summarise them in Table 17.
Functionality provisioning
It consists of providing platform functionalities that enable new configurations of sellers’ activities for value
creation. As described above, each seller business model is characterised by a group of key value-creation
activities. Sellers perform some of these activities in the platform using the functionalities provided by Amazon. I
denote as compulsory functionalities those that Amazon requires to be used by anyone selling on the platform,
such as the payment, basic listing, and order management systems, and the currency converter (for international
operations). Most functionalities available in the Marketplace are nevertheless stated as optional by Amazon, and
thus sellers decide whether to use them or not. Optional functionalities range from marketing and data analytics
tools to fulfilment, international logistics, or tax calculation services, among others. The interviewees describe that
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optional functionalities can contribute to developing and improving sellers’ activities, as they equip them with
professional tools tightly integrated with the compulsory functionalities.
“[T]his increased complexity, it's also something which it's beneficial or upgrading your business.” (Seller)
“…it was all incremental. We were like "this is fantastic" and I'd actually say Amazon improved us in the
early years because we weren't sophisticated.” (Seller)
The provision of optional functionalities gives sellers the flexibility to decide how to perform their value-creation
activities and to create new ways to configure them. While all the sellers’ business models are based on the
compulsory functionalities, these only cover a small part of all the activities. Sellers can thus decide which part of
the remaining activities to perform through their own capabilities and processes and which through Amazon’s. By
expanding the offering of optional functionalities, Amazon increases the possible configurations of activities and
thus augments the potential for the appearance of new seller business models. This possibility to customise the
sellers’ activities is recognised by the interviewees, who describe Amazon’s role in augmenting business model
generativity:
“I think what [Amazon] realised very quickly is if you just give people the building blocks to build their
own brand, what you end up with is this hyper competitive marketplace, where people are able to
challenge the status quo of existing brands and actually build their own brands.” (Seller)
In addition to providing sellers with functionalities that support their key value creation activities, I find that
Amazon’s activities also affect sellers’ value capture strategies by structuring how sellers compete and managing
the competition intensity they face.
Structure seller competition
First, as the platform owner, Amazon plays a central role in structuring competition in the Marketplace. I observe
that this is done through different mechanisms: firstly, by introducing functionalities that compare and sort sellers’
competitive positions. The Buy Box is an example of this, as it ranks sellers who offer the same product and
assigns the highest-ranking seller as the default provider when a customer purchases. By changing the ranking
criteria, Amazon changes inter-seller competition. Second, by changing criteria for how products are ordered and
displayed. For example, while initially, Amazon served search results based on searched terms and product
rankings, from 2017 on, search results began to show a larger proportion of advertised products. This changes
sellers’ key parameters for competition from price, product quality, and delivery performance to marketing and
advertising optimisation. Finally, Amazon also structures competition through rules constraining sellers’
competitive decisions, such as the Fair Pricing policy (so-called “most favoured nation” – MFN – rules), requiring
sellers not to price their products on Amazon higher than they price them anywhere else.
Increase competition intensity faced by sellers
Next, I observe that some of Amazon’s activities can increase the competition intensity faced by sellers. On the
one hand, Amazon can increase the threat of new entrants by lowering entry barriers to new sellers (for example,
by offering fulfilment or brand design functionalities) and by changing rules that regulate access to the
marketplace (notably expanding the list of countries admitted for a seller’s location). Second, I find that Amazon
increases competitive rivalry by increasing performance requirements for sellers’ eligibility for distinctive platform
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features such as the Prime badge or the Featured Merchant status (required to rank for the Buy Box) and by
directly entering a sellers’ product category with Amazon’s own branded products. Finally, Amazon can increase
competitive intensity by leveraging its bargaining power as a provider for sellers, for example, by increasing fees
for services that become essential for competing in the Marketplace.
Table 17. Amazon’s orchestration activities: Examples, practices, and outcomes
Orchestration activities:
Examples
(1st order concepts)
-
-
Forcing use of Amazon Pay to process
payments, or Amazon Currency
Converter for international operations
Introducing functionalities that
expand the range of possible seller
activities, such as with marketing
(Amazon Accelerator) or export (FBA
Export)
-
Launching the Buy Box, Match Low
Price, or Automatic Pricing tools.
-
Prioritizing advertised products in
search results
-
Requiring sellers not to price their
products on Amazon higher than they
price them anywhere else (so-called
“most favoured nation” – MFN – rules)
Orchestration activities:
Activities
(2nd order themes)
-
Defining the compulsion and
optionality of the platform’s
functionalities
-
Introducing optional
functionalities associated with
sellers’ activities
-
Introducing functionalities that
compare and sort sellers’
competitive position
-
Changing criteria for how
products are ordered and
displayed
-
Defining rules that constrain
sellers’ competitive decisions
-
Provision of services such as Fulfilment
by Amazon or Global Selling
-
-
Accepting new product segments and
sellers from countries previously
excluded from the Marketplace,
notably China in 2015
Lowering entry barriers to new
sellers
-
Changing rules that regulate
access to the marketplace
Tightening the requirements to be
eligible for distinctive platform
features, like the Prime and Featured
Merchant badges.
-
Increasing performance
requirements for sellers
-
Entering a seller’s product
category
-
Increasing fees for optional
services that become essential
for competing
-
-
Launching of Amazon Basics and
other Amazon-owned brands
-
Increasing the fees for Fulfilment by
Amazon or for advertising tools like
Sponsored Products and Sponsored
Brands
Orchestration activities:
Outcomes
(Aggregate dimensions)
Functionality provisioning
Structure seller competition
…increasing the threat
of new entrants
Increase
competition
intensity
by…
…increasing
competitive rivalry
…leveraging the
platform’s bargaining
power
Source: Based on interviews, participatory observation, and multiple archival sources
In Figure 7, I show how Amazon’s orchestration activities influence the process of appearance of new sellers’
business models described in the previous section. First, Amazon makes different business models feasible by
providing functionalities that sellers use to support their business models’ key activities. By providing new
additional functionalities, Amazon makes new business models, or variations of existing ones, feasible. Second, I
observe that changes in the business models in the marketplace occur when the value capture strategies and
profitability of pre-existent models prove insufficient. Amazon affects sellers’ profitability by changing the
structure of competition and by increasing competition intensity.
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Figure 7. Amazon’s orchestrating role in the appearance of new business models
Platform
conditions
Existing Business Model
New Business Model
Functionality provisioning
Functionalities
availability
Enables
Competitive Fit
Optional
functionalities
Minimum for
feasibility
Improves performance
Struggle
Profitability
Attracts
New sellers
Higher
usage
Minimum for
feasibility
Develops new
model
Adoption
Higher competition
intensity
Structure
competition
Exit
Attracts
Increase threat of
new entrants
Increase rivalry
Leverage
bargaining power
Causality
Sellers’
responses
Functionalities
availability
Business model’s
competitive fit
Orchestration
activities
4.4.2.2. Orchestration over time: the appearance of the Private Label and Aggregator business models
In Table 18, I summarise my observations on Amazon’s orchestration activities over time, detailing the evolution of
functionalities availability and the key changes in seller competition. I highlight three trends from this table:
First, while the provision of compulsory functionalities has not changed significantly over time, Amazon
continuously expanded the offering of optional functionalities, both in the number of functionalities for specific
activities (such as delivery or advertising) and in the range of activities involved (see detail in Table 19). As
discussed above, this in turn increases the number of feasible seller business models.
Second, I observe that Amazon changed the focus of the new functionalities’ area of application from supply chain
management (SCM) to marketing and advertising (MA): Between 2006 (when Amazon launched Fulfilment by
Amazon) and 2014, Amazon launched 18 SCM and 9 MA new functionalities (respectively 2 and 1 per year on
average). Between 2015 and 2021, the focus shifted, launching 6 SCM and 25 MA new functionalities (0.9 and 3.6
per year on average). This shift in focus indicates what type of sellers’ business models Amazon aims to develop in
the Marketplace in different periods. For example, functionalities supporting brand development and advertising
activities are not relevant for the Arbitrage or Wholesale business models but are crucial for Private Label,
Handmade, and Aggregator. In contrast, pricing functionalities such as Match Low Price and Automated Pricing
are fitted for Wholesale and Online Arbitrage business models. At the same time, optional functionalities launched
in one moment can be generative of the appearance of a business model later. Notably, this is the case of
Fulfilment by Amazon, launched in 2006 in a context where sellers used Arbitrage and Wholesale business models,
but that years later became the watershed for the emergence of Private Label and Handmade.
Third, I recognise a pattern in how the most impactful Amazon’s orchestration activities are sequenced, starting
with the provisioning of key functionalities (such as Fulfilment by Amazon) and reducing entry barriers to new
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sellers (like introducing Global Selling and accepting sellers using China’s IP), followed by actions that structure
seller competition (such as introducing the Buy Box or prioritising advertised products in search results), and
finally increasing competitive rivalry (like increasing performance requirements) and leveraging Amazon’s
bargaining power (increasing fees and advertising costs).
I identify two periods where the impact of Amazon’s orchestration activities on the appearance of new sellers’
business models is clearly illustrated:
The first one is 2012-2013, when the Arbitrage and Wholesale business models faced challenges coping with the
increasing competition intensity (Figure 8). After the release of Fulfilment by Amazon in 2006, the platform
experienced the fastest-growing period of sellers’ sales in the Marketplace, which ten-folded between 2006 and
2012. In parallel, Amazon launched the Buy Box in 2008, which became a mechanism that structured competition
between sellers who offered the exact same products and thus competed only by price. In addition to higher
competition rivalry due to additional sellers joining the platform, three Amazon actions in 2012 contributed to
increase the competitive intensity: the increase in the requirements to qualify for competing for the Buy Box and
the launching of Global Selling, a program that enabled sellers located in other countries to operate in Amazon’s
largest marketplaces. High competition intensity forced existing sellers to streamline their operations or exit. At
the same time, some of the existing sellers and new entrants developed new business models based on product
differentiation (Private Label and Dropshipping) in response to the high competition intensity created by the Buy
Box. These business models originated the so-called “Amazon-native brands”, created in the Marketplace
exclusively to differentiate an otherwise generic product.
Figure 8. The appearance of the Private Label business model in the Marketplace
Platform
conditions
Arbitrage & Wholesale
Private Label
Functionality provisioning
Functionalities
availability
- Payments
- Product page
creation
Enables
Competitive Fit
Improves performance
New sellers
Higher
usage
Struggle
Profitability
Attracts
- Brand registry
- Sponsored
products
- Match Low
Price
Develops new
model
Adoption
Higher competition
intensity
Introduction of
Buy Box (2008)
Exit
Attracts
Introduction of FBA
& Prime (2006)
Introduction of
Global Selling (2012)
Increasing
requirements to win
Buy Box (2012)
Causality
Sellers’
responses
Functionalities
availability
Business model’s
competitive fit
Orchestration
activities
The second period is 2017-2018, when the large number of Amazon-native brands started to create a challenge of
product discoverability. Previous to this, Amazon allowed in 2015 sellers located in China to use the Global Selling
program to sell worldwide – contributing to the increase in Amazon-native brands - and in 2017, started to favour
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the position of advertised products in search results. High competition intensity and the change in competition
structure forced existing Private Label and Dropshipping sellers to renew their differentiation strategy. This posed
challenges both in terms of capabilities (such as branding and advertising campaign design and management)
and capital requirements (to invest in advertising and brand development). In this context, in 2018 emerged the
Aggregator business model, based on acquiring existing sellers’ accounts and operating them on a larger scale
through capital injection and the professionalisation of activities.
Figure 9. The appearance of the Aggregator business model in the Marketplace
Platform
conditions
Private Label & Dropshipping
Aggregator
Functionality provisioning
Functionalities
availability
Enables
Competitive Fit
- Seller fulfilled
prime
- Lighting Deals
- Brand registry
- Sponsored
products
Improves performance
Struggle
Profitability
Attracts
New sellers
Higher
usage
- Sponsored
products
- Campaigns
Develops new
model
Adoption
Higher competition
intensity
Ads prioritized in
search (2016)
Exit
Attracts
Chinese Sellers’ IP
accepted (2015)
Increasing advertising
costs (2017)
Higher capital
requirements to
compete (2012)
Causality
Sellers’
responses
Functionalities
availability
Business model’s
competitive fit
Orchestration
activities
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Table 18. Summary of Amazon’s orchestration activities over time: evolution of functionalities availability and key changes in seller competition
Amazon's orchestration activities
Type
Sellers' activities
involved
Sales services
Functionality
provisioning
Supply Chain
Compulsory Management
Marketing &
Advertising
Sales services
Optional
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Supply Chain
Management
Marketing &
Advertising
Number of available functionalities
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
1
1
1
1
1
1
2
4
4
4
4
4
4
4
4
4
4
0
0
0
1
1
1
5
8
9
9
10
10
13
15
18
19
19
21
22
22
23
23
0
0
0
0
0
0
0
1
2
3
3
3
8
8
9
12
14
20
24
28
32
34
Key changes in seller competition
Structure competition
Increase threat of new entrants
Increase
competition
Increase competitive rivalry
intensity
Leverage bargaining power
│Launch of Buy Box
│Ads prioritized in search results
│Launch of Fulfilment by Amazon │Launch of Global Selling and Amazon Seller Central
│Chinese Sellers' IP accepted
│Amazon Basics │Increasing requirements to win Buy Box
│Increasing FBA fees
│Increasing advertising costs
Sources: The number of available functionalities is based on a yearly reconstruction of Amazon’s offering based on the Internet Archive, including the use of contracts such as the participation
agreement, policies such as the community rules, code of conduct, and performance requirements, and functionalities descriptions. The changes in seller competition are based on interviews,
specialised industry reports and media articles, and by a reconstruction of the fees evolution based on the Internet Archive.
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Table 19. Detail of functionalities available for sellers in the Marketplace over time
Functionality provisioning
Type
Sellers' activities
involved
Detailed area of application
Number of available functionalities
Payments
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Currency converter
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
Supply Chain
Management
Order management
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Marketing &
Advertising
Listing management
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Loyalty programs
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Tax calculation
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
Lending
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
Sales development
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
Delivery
0
0
0
1
1
1
2
3
3
3
3
3
3
3
4
5
5
5
6
6
7
7
Pick, Pack, Handle
0
0
0
0
0
0
1
1
1
1
1
1
2
3
4
4
4
4
4
4
4
4
Returns
0
0
0
0
0
0
1
1
1
1
1
1
1
1
2
2
2
3
3
3
3
3
Storage
0
0
0
0
0
0
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
Order management (optional)
0
0
0
0
0
0
0
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Inventory optimization
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Export
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
Disposition
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
Inbounding
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
Warehouse distribution
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
Warehouse optimization
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
Advertising
0
0
0
0
0
0
0
1
2
3
3
3
4
4
4
5
5
6
8
9
10
11
Brand development
0
0
0
0
0
0
0
0
0
0
0
0
1
1
2
3
5
5
7
7
9
10
Bundling
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
Market reach
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
Pricing
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
2
2
3
3
3
Promotions
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
4
4
5
6
6
Listing management (optional)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
Market research
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
Sales services
Compulsory
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Sales services
Supply Chain
Management
Optional
Marketing &
Advertising
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4.4.3. Evolutionary interplay between Amazon and the Sellers
Having described the specific mechanisms by which Amazon influenced in the appearance of new sellers’ business
models, I now turn to how the interactions between these actors played out throughout the period of the study.
I recognise a pattern of dynamic adjustments between Amazon’s and the sellers’ business models, resulting in an
evolutionary interplay where both are affected. I summarise these dynamics in the model in Figure 10: I observe
that changes in the sellers’ business models and in Amazon’s value proposition, value capture, and orchestration
activities mutually respond and adapt to each other, in a cyclical process.
Figure 10. Interplay between the sellers’ business models evolution and Amazon’s value proposition,
orchestration, and value capture strategies
Revenue from
transactions
Increases
Amazon
Structure
competition
Increase
competition
intensity
Customer
service
Profitability
Sellers’
Business
Models
Struggle
Forces
performance
improvement
Adoption
Expands
Product
selection
Enables
Increases
Functionality
provisioning
Increases
New revenue
streams
Evolution of
sellers’ business
models
Sellers’ impact
on Amazon
Amazon’s value
proposition
Amazon’s value
capture
Amazon’s
orchestration
On the one hand, Amazon’s orchestration activities contribute to pushing the sellers’ business models through its
stages of profitability, struggle, and the adoption of new models. While the appearance of a new business model
does not replace the pre-existing ones, I observe that Amazon’s activities lead to the appearance of increasingly
sophisticated models. In each case, they can sustain more value-creation activities by combining more
functionalities and withstand higher competition intensity. The comparison between the first and last business
model to appear in the Marketplace is illustrative of this: while Arbitrage is simply purchasing a bargain to sell it
locally at a slightly higher price, Aggregators count with dedicated product development and marketing teams,
operate in multiple countries, and are typically backed by large financial funds.
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At the same time, the sellers’ business model transformation also impacts Amazon by improving the platform’s
value proposition to customers and creating new monetisation opportunities that increase Amazon’s revenues
and value capture. First, the increasing importance of sellers for delivering Amazon’s value proposition is
expressed in how Amazon has changed its participation in the Marketplace: while initially, Amazon acted as the
main provider and sellers only complemented the product selection, as of 2021, sellers provide two every three
products sold, the other third being provided by Amazon (Figure 11). Further, my informants acknowledge that
sellers cope with the Marketplace’s increasing competition intensity by improving their performance, customer
service, product selection, and quality, which is at the core of Amazon’s value proposition of “unlimited selection
and fast delivery”.
“Everything is focused on the end buyer. And it's done by every company, improving the product listings,
etc. It's a way for Amazon to target other people invest in getting the work done.” (Ecosystem service
provider)
“The standards are going up all the time. And Amazon's attitude is very simple: this is what consumers
expect.” (Industry expert)
Second, the changes experienced by the sellers contribute to increase Amazon’s revenue and value capture. On
the one hand, as thriving sellers deliver Amazon’s value proposition, they attract additional customers, increasing
the volume of transactions and consequently Amazon’s revenue (Figure 11). On the other hand, the increasing
variety and sophistication of the sellers’ business model is based on a higher usage of optional functionalities, for
which sellers pay a fee. I observe that Amazon significantly increased the share of the sellers’ revenue it captures,
reaching 36% of it in 2021: from 2008 on, the fees for compulsory functionalities (referral and other basic fees)
remained relatively stable, the increase in value capture is explained by the use of optional services by sellers.
Figure 11. Changes in the sellers’ importance in the Marketplace and of Amazon’s sources for value capture
70%
64%
60%
50%
38%
40%
36%
9%
30%
19%
20%
2%
12%
6%
10%
6%
12%
0%
15%
5%
Amazon's capture of sellers' revenue - Advertising services
Amazon's capture of sellers' revenue - Fulfilment and other services
Amazon's capture of sellers' revenue - Referal and other basic fees
Sellers' share of total sales in the Marketplace
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Source: Based on financial statements and specialised industry reports
4.5. Discussion and conclusions
In this article, I have shown how Amazon’s orchestration activities influenced the appearance of new sellers’
business models and how that change affected Amazon. First, I describe the process by which new seller business
models appear in the Marketplace. Next, I identify the specific orchestration activities by which Amazon influenced
the change in the sellers’ business model – functionality provisioning, structuring seller competition, and
increasing competition intensity – and explain how they operate. Finally, I present a process model summarising
the interactions between Amazon’s and the sellers’ value creation and capture activities. I observe that Amazon’s
orchestration activities lead to the sellers' adoption of increasingly sophisticated business models, which in turn
contributes to improving Amazon’s value proposition and capture from the Marketplace. Overall, I identify a
pattern of dynamic adjustments between Amazon’s and the sellers’ business models, resulting in an evolutionary
interplay where both Amazon and the sellers are transformed.
This study makes two main contributions to platform research: first, by showing how a PO can orchestrate its
complementors’ transformation, I contribute to expanding our understanding of the PO’s set of capabilities and
responsibilities. Second, I contribute to the stream of literature focused on complementor orchestration by
explaining the dynamic interplay between the PO’s orchestration activities, the complementors’ transformation,
and the consequences for value creation and value capture of this transformation. My study also holds
implications for practitioners and for regulatory purposes.
4.5.1. Contributions to platform research
My first contribution with this study is to expand current views on what POs are capable of and responsible for by
showing that they can in fact orchestrate changes in their complementors’ business models. PO have a unique
capability to mobilise and align resources that are not formally under their control (Adner & Kapoor, 2010; Gawer,
2014). So far, extant research has recognised the profound economic impact of platform orchestration in how it
facilitates value creation by both enabling interactions and fostering innovation (Cusumano et al., 2019; Parker
et al., 2016). In addition to creating value, I argue that the PO’s orchestration activities can have another type of
economic impact, producing a transformative effect on its participants’ characteristics. Furthermore, I argue that
this transformation is not simply a by-product of the activities performed in the platform but a planned output of
the PO’s orchestration. Consequently, this research illuminates PO’s capabilities linked to the long-term planning
of the ecosystem’s design. I know of no studies addressing this important effect of platform orchestration in
complementors’ characteristics and, consequently, in the platform ecosystem itself.
Recognising these PO’s capabilities is also relevant for research on platform power (Cutolo & Kenney, 2021;
Jacobides, 2021), as it identifies ways in which PO can create forms of complementor dependence: if a firm relies
on a platform to exert or develop at least one of its core competences (Prahalad & Hamel, 1990), it then becomes
highly vulnerable to changes on features or rules stipulated by the PO. This form of PO power to shape its
complementors’ characteristics can also have competition effects in the form of a reduced variety in
organisational forms and organisational innovation by firms, ultimately harming consumers.
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Second, I contribute to the stream of research exploring complementor orchestration in several ways. Firstly, I
have shown that Amazon’s activities increased its complementors’ heterogeneity, as I find evidence of the
successive emergence of new seller business models. This contributes to previous research on complementor
heterogeneity (McIntyre et al., 2021; Rietveld et al., 2021) by showing and explaining how orchestration can, in
fact, drive heterogeneity. Next, I illuminate new complexities and trade-offs in platform orchestration by
recognising the dynamics through which PO can orchestrate the change in the complementors’ business models.
As PO might be using orchestration activities to aim for specific compositions of the complementors’ pool, this
creates unequally distributed challenges to the different types of complementors, favouring some of them while
penalising others. Third, previous research highlighted that PO typically faces a trade-off between platform growth
and value capture (Cennamo & Santalo, 2013; Lan et al., 2019). The set of options through which this trade-off can
be handled is increased if we include complementors’ characteristics within the scope of the orchestration
activities, as I have shown for the Amazon Marketplace. Finally, my results also make visible other important tradeoffs, such as deciding the degree of the platform ecosystem’s technological complexity. I have shown how
increasing the offering of optional functionalities was fundamental for driving an increase in the variety of sellers,
an orchestration activity I call “functionality provisioning”. By increasing the number of functionalities and the
possible interdependencies, the ecosystem’s technological complexity is likely to increase as well. This can create a
trade-off between complementor generativity and platform growth, as extant research has identified a
decelerating effect of technological complexity on the ecosystems’ value creation (Cennamo, 2016; Cennamo
et al., 2018).
4.5.2. Limitations and avenues for future research
This study has limitations, some of them derived from using a single empirical case, which opens opportunities for
future research. One of the limitations of this study is whether the results are generalisable for different types of
platform ecosystems. In particular, it is foreseeable that in different ecosystem configurations and under different
bargaining power relations among the actors, the PO might not be able to structure complementors’ competition
and manage the competition intensity they face. Further, in my empirical setting, the interdependencies between
the PO and the complementors are built over key complementors activities. It is yet to be explored if the PO will
successfully orchestrate the complementors’ business models in ecosystems where these interdependencies are
built in non-essential or secondary complementor activities. In addition, while this paper focused on the
competitive dynamics within the platform, some of the mechanisms I described are likely to be affected by
external factors, such as changes in tastes and maturity of the consumer or inter-platform competition. Future
research efforts can address some of these limitations and further explore other problems illuminated by this
study. For example, while I have shown how a PO can transform its complementors’ business models, other
researchers can explore whether orchestrating other complementor characteristics - like size and organisational
form - would require different orchestration activities. Other lines of research can study the competitive outcomes
of the PO’s orchestration of complementors’ transformation and the consequences this might have for public
agencies and regulatory efforts.
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5. Discussion and general conclusions
This thesis seeks to explain the characteristics and dynamics of power within digital platforms, particularly as they
emerge as new organisational forms. I approached this problem by structuring the research around three distinct
dimensions. The initial dimension pertains to the structure of social interactions, endeavouring to discern how
platforms shape power relations and autonomy by influencing agents’ interactions and modulating participatory
practices. The subsequent dimension is centred on the platform's governance, with the aim to contrast the
principles guiding the governance and how it is enacted, and how this shapes power dynamics within the
platform. Lastly, the third dimension turns its focus to the interplay between firms, with the intent to assess the
extent of influence wielded by the platform's owner in directing shifts in the value creation and capture strategies
of participant firms.
The studies in chapters 2, 3 and 4, in addition to making specific contributions already discussed in each chapter,
contribute overall to address this thesis’ objectives, advance our knowledge on how we understand platforms, and
provide new ways to characterise platform power, its dynamics, and its consequences. In this chapter, I discuss
these contributions (summarised in Table 20), as well as this study’s implications for policy, its limitations, and the
avenues it opens for future research. I conclude the thesis with some final remarks about the potential practical
implications of this research for platforms.
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Table 20. Contributions of this thesis to research on platforms and platform power
Area of
contribution
Conceptualisation
of platforms
Characterisation
of platform power
Platform power
dynamics
Consequences of
platform power
Contribution
Main consequences
Examples of literature related
to the contribution
- Identifying and explaining the process by which platforms
in their organising role transform fields of practice and
replace pre-existing practices with new ones
Recognising how agentic dynamics in platforms involving individuals and
organisations are shaped and how platforms work.
Adner (2017); Gawer (2014);
Kretschmer et al. (2022); Stark & Pais,
(2020)
- Explaining the processes by which the platform owner
produces, encloses, and coordinates agents’ practices. This
illuminates new aspects of how hierarchies and relations of
ownership and value capture are formed in platforms
- Explaining the relationship between structure and agency
in platforms and showing how they are mutually
transformed through the differences in the platform
constituents’ practices and positions of power.
I argue that platforms can be more usefully described as spaces of
coordination and production of practices that facilitate controlling
outside activities and resources and profiting from them.
Langley & Leyshon (2017); Srnicek
(2016); Zuboff (2019)
View of platform power that is multifaceted (i.e., multiple forms of
powers coexist) and multidirectional (i.e., interaction of multiple agents
with different motivations and strategies).
Integrates social, cultural, and symbolic dimensions of platform power
Culpepper & Thelen (2020); Jacobides
(2021); Khan (2018)
Explains power not as an instrument within an asymmetric structure but
as a web of interactions resulting from the situated agents’ practices and
strategies.
Andreoni & Roberts (2022); Cutolo &
Kenney (2021); Srnicek (2016); Zuboff
(2019)
- Illuminating the role of uncertainty and ambiguity as
strategies of platform power
Expand explanations of power strategies from abusing the ability to set
the rules to strategically mismanaging the rules.
Busch et al. (2021); Jacobides (2021);
Lianos & Carballa-Smichowski (2022)
- Illustrating platform organising dynamics that achieve
system-level goals not only directly by influencing on
behaviours leading to specific outcomes but also by the
means of influencing change in the participants'
characteristics and its pool’s composition.
- Identifies and explains the coexistence of dynamics of
platform power and counterpower accumulation
Expand current views on what platforms can achieve as organisational
technologies…
Daymond et al. (2022); Gawer (2014,
2021)
what distinguishes them from other organisational forms…
Jacobides et al. (2018, 2022)
and how they build hierarchical structures within industries
Rikap & Lundvall (2021); Srnicek (2016)
A conceptualisation of platform power that is dynamic and grounded on
the agents’ practices, positions, and strategies.
Busch et al. (2021); Khan (2018)
- Explaining how power changes vis a vis the platform
evolution by power accumulation and power contestation
Enriches previous findings on how power dynamics change as the
platform changes
Cutolo & Kenney (2021); Zuboff (2019)
- Providing evidence that challenges central claims in the
literature pertaining to mechanisms assumed to keep
some of the existing platform power asymmetries under
check
- Explain the platform’s organising role in producing and
reproducing the delegation of autonomous decisionmaking on individuals
Show that the balance of incentives and control can coexist with a
sustained mismatch between the governance the platform declares to
abide by and its actual practices
Constantinides et al. (2018); Kretschmer
et al. (2022); Saadatmand et al. (2019);
Teece (2018)
Identify the conditions under which agency is shaped in platforms by
their specific structure and its power dynamics
Calo & Rosenblat (2017); Lanier (2018);
Scherer & Neesham (2020); Stark &
Pais (2020)
- Identify and explain forms of platform dependence
constraining business autonomy and decision-making
Show how dependence is rooted not only in the platform’s owner
gatekeeping position but also in its decisions about functionalities
provision related to complementors’ key value creation activities
Curchod et al. (2019); Cutolo & Kenney
(2021); Eaton et al. (2015); Khan (2018)
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Essays on Power in Digital Platforms
5.1. On the nature of platforms as organising agents
By exploring power dynamics, this research illuminates new dimensions of platforms and contributes to enriching
how we conceptualise them.
This thesis first deepens our understanding of platforms as organising agents by highlighting their importance as
spaces of coordination and production of practices. The organisational view on platforms has stated the relevance
of bringing agency to the forefront of platform studies (Gawer, 2014). Further, this view characterises platforms
based on how they organise the participation of autonomous agents based on balancing incentives and rules
within the context of a digital infrastructure (Kretschmer et al., 2022). I contribute to this stream by identifying and
explaining the process by which platforms in their organising role, transform fields of practice and replace preexisting practices with new ones (see sections 2.3.1.1 & 2.3.4). Paying attention to the organising of practices
contributes to refining our understanding of the conditions by which agency is shaped and how platforms work. A
focus on practices also supports studying agentic dynamics in platforms involving both individuals and
organisations.
Describing platforms as spaces of production of practices also illuminates new aspects of how hierarchies and
relations of ownership and value capture are formed in these organisational contexts, contributing to political
economy approaches (Langley & Leyshon, 2017; Srnicek, 2016; Zuboff, 2019). In section 2.3.1.1, in addition to
describing how a platform transforms existing fields by introducing new ways of practice, I argued that this
process also involves the platform owner’s attempt to enclose those practices: by encoding the activities to be
performed and controlling the technological infrastructure in which they are performed, the platform owner
creates control rights (i.e., ownership, Boyle, 2003) over the practices. In other words, since actions performed in
platforms can be considered runtime products - i.e., produced in real-time while performed (Yoo, 2023) –
ownership of the product design and the infrastructure confers control over the actions. The process of enclosure
is analogous to that of “incursion” described by Zuboff (2019), with the difference that in her approach, the focus
of the control is data rather than the agents’ practices. My perspective consequently expands on studies focusing
on the role of data control and infrastructure ownership to create new ways to capture value (Srnicek, 2016, 2021;
Zuboff, 2019). Instead, I argue that platforms can be more usefully described as spaces of coordination and
production of practices that facilitate controlling external activities and resources and profiting from them.
5.2. On the characterisation of platform power
This thesis contributes to enriching previous characterisations of platform power in multiple ways.
First, this study builds a more complete and integrative understanding of platform power by exploring the
relationship between structure and agency in platforms. I addressed this problem both when discussing the
conceptual relationship between the digital habitus and the logic of the field (sections 2.3.1.3, 2.3.4, and 2.4.2) and
when exploring empirically the Amazon Marketplace sellers’ interactions with the platform’s governance (sections
3.4.2 and 3.4.3) and with Amazon’s orchestration activities (sections 4.4.2 and 4.4.3). In these discussions, I show
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how both structural and agency conditions are mutually transformed through the differences in the platform
constituents’ practices and positions of power. Overall, I provide a view of platform power that is multifaceted (i.e.,
in which multiple forms of powers can coexist) and multidirectional (i.e., as it results from the interaction of
multiple agents with different motivations and strategies). On the one hand, this view contributes to integrating
social, cultural, and symbolic dimensions of platform power, enriching previous conceptualisations (Culpepper &
Thelen, 2020; Kenney et al., 2021; Khan, 2018). On the other hand, it also explains power not as an instrument
within an asymmetric structure (Andreoni & Roberts, 2022; Cutolo & Kenney, 2021; Srnicek, 2016; Zuboff, 2019)
but as a web of interactions resulting from the situated agents’ practices and strategies.
Second, to my knowledge, this research is the first to illuminate the role of uncertainty and ambiguity as strategies
of platform power. Typically, platform power has been associated to the owner inclining the playing field, abusing
its control over the technological infrastructure (Calo & Rosenblat, 2017; Khan, 2016; Srnicek, 2016). When I
identify and describe the “two-faced governance” in the Amazon Marketplace (sections 3.4.1.2, 3.4.3, and 3.5.3), I
highlight the crucial role of uncertainty, ambiguity, and unreliability as factors explaining Amazon’s power over
sellers. This shifts power strategies from abusing the ability to set the rules to strategically mismanaging the rules.
Extant research has explored the circumstances that allow platform owners to increase their power based on the
lack of transparency, focusing on how algorithms create “black boxes” that conceal processes behind actions and
defer responsibilities (Introna, 2016; Pasquale, 2015). Digital technologies can thus hide rationalities, biases, and
decisions and exert a structuring effect over the interactions (Alaimo & Kallinikos, 2017; Beer, 2017). These studies
provide useful theories that explain how the platform’s technological infrastructure enables abusive practices. This
research contributes to these views by describing how the platform owner, based on this lack of transparency,
increases its power by actively creating contradictory conditions for participation.
Thirdly, this study expands current visions on the scope and reach of platform power, illuminating capabilities
linked to the long-range planning of the ecosystem’s design. By showing how Amazon exerts an influence to
change the sellers’ business models (section 4.4.2), I illustrate platform organising dynamics that achieve systemlevel goals not only directly by influencing on behaviours leading to specific outcomes (as was already thoroughly
identified in previous literature, e.g., Cennamo & Santalo, 2013; Rietveld et al., 2019, 2021), but also by the means
of influencing change in the participants' characteristics and its pool’s composition. Illuminating these capabilities
contribute to discussions on what platforms can achieve as organisational technologies (Daymond et al., 2022;
Gawer, 2014, 2021), what distinguishes them from other organisational forms (Gawer & Cusumano, 2014a;
Jacobides et al., 2018), and how they build hierarchical structures within industries (Rikap & Lundvall, 2021;
Srnicek, 2016).
5.3. On platform power dynamics
This study also contributes to a more precise understanding of how power dynamics play out in platforms.
In the first place, consistent with the multidirectional characterisation of power described above, this research
identifies and explains the coexistence of dynamics of platform power and counterpower accumulation. While
previous studies have described actions of resistance and contestation in platforms (Calo & Rosenblat, 2017;
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Essays on Power in Digital Platforms
Curchod et al., 2019; Eaton et al., 2015), these expressions are often absent in the efforts that systematise
explanations of platform power (Busch et al., 2021; Khan, 2018; Zuboff, 2019). I discuss the dynamics of power and
counterpower under different forms (sections 2.3.3 and 2.3.4) and also in the empirical context of the Amazon
Marketplace, showing that while Amazon abuses its control of the governance to increase its bargaining power
over sellers (sections 3.4.1.2 and 3.4.1.3), sellers in turn adapt and respond to Amazon by eluding and hacking the
governance rules (section 3.4.2). Overall, this contributes to a conceptualisation of platform power that is dynamic
and grounded on the agents’ practices, positions, and strategies.
In addition, this thesis also makes contributions to understanding how power changes vis a vis the platform. My
results and arguments are consistent with previous research on how power relations evolve in platforms,
particularly the studies describing the change in power asymmetries as users become habituated and increase
platform usage (Cutolo & Kenney, 2021; Zuboff, 2019). I discuss these problems when describing the power
accumulation dynamics that characterise the different stages of platform evolution (section 2.3.4) and when
showing how Amazon influences in the appearance of new sellers’ business models (section 4.4.2). At the same
time, this study enriches previous explanations by theorising how platforms change both by power accumulation
and power contestation (for example, by changing governance and creating “unwritten rules” for participation)
and raising questions about the sustainability of platform owners’ power abuses (for example, as I show how
discontent can eventually raise ecosystem members’ incentives to resist the platform owner’s actions).
In third place, this study provides evidence that challenges central claims in the literature pertaining to
mechanisms assumed to keep some of the power asymmetries existing in the platform under check. While
scholars have clearly documented the existence of power asymmetries and power abuses by the platform owner
(Khan, 2016; Stigler report, 2019), the consensus in the governance literature is that because of the way platforms
create value, there are mechanisms limiting this power and how it is used. This is expressed in four central,
interconnected claims, described in section 3.2.2: overall, abuses of the power to set the governance are supposed
to be partially offset by the lack of hierarchical authority over participants and the need of them to create value. I
find, however, that within the organising dynamics of platforms, the balance of incentives and control can coexist
with a sustained mismatch between the governance the platform declares to abide by and its actual practices. This
is shown when discussing the governance of the Amazon Marketplace in 3.4.1, with the evidence and its
consequences for theory summarised in Table 13. The existence of abuses “hiding in plain sight” (evident for some
participants -e.g., sellers- but unknown to others -e.g., consumers) evidence power asymmetries and limits to it
work differently than previously assumed.
5.4. On the consequences of platform power
This research identifies and explains new consequences of platform power, both on individuals and organisations.
Regarding the impact on individuals, this study contributes by explaining how platform power dynamics have an
organising role in producing and reproducing the delegation of autonomous decision-making. Previous research
has explored the impact of digitalisation on individual autonomy from different perspectives and conceptual
frameworks (Calo & Rosenblat, 2017; Curchod et al., 2019; Lanier, 2018; Scherer et al., 2020; Stark & Pais, 2020;
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Zuboff, 2019), discussed in detail in sections 2.1 and 2.2.2. This study builds on and contributes to this research by
showing how power struggles lead to an emergent process of autonomy delegation and how the conditions of
agency are shaped by the specific structure of the platform and its power dynamics.
Second, this research also recognises new aspects of how platform power dynamics can shape the relationships
between organisations. Similarly to the consequences over individuals described above, I explain how business
autonomy and decision-making processes can be constrained. I illustrate this by showing how Amazon’s
orchestration activities influence sellers' business models (section 4.4.2). I describe the consequences for sellers,
both in terms of performance (related to the platform owner capturing a larger share of value), strategy (options
for value creation), and internal processes (molded to conform to platform standards). These results are in line
with previous contributions describing how continued participation in platforms creates forms of organisational
dependence and can constrain decision-making (Curchod et al., 2019; Cutolo & Kenney, 2021; Eaton et al., 2015). I
contribute to these studies by showing how this dependence is rooted not only in the platform’s owner
gatekeeping position and control of the complementors’ access to customers (Cutolo & Kenney, 2021; Khan,
2016) but also by the impact of decisions about functionalities provision related to complementors’ key value
creation activities. This effect is in line with the notion of practice ownership resulting from the process of field
enclosure, discussed above in sections 2.3.1.1 and 5.1.
5.5. Policy Implications9
This thesis provides conceptual tools and empirical evidence that can help policymakers and regulatory agencies
identify and set limits on power abuses, especially in the light of platform domination.
Informing policymakers of the strategic management of platforms and contributing to the finer understanding of
platform power constitutes, I believe, a vital contribution of this work, which inscribes itself in a larger attempt to
enrich the current regulatory debate on regulating the power of platforms and ecosystems (Cusumano et al., 2021;
Heimburg & Wiesche, 2023; Jacobides & Lianos, 2021). This is because up until recently, regulators and antitrust
enforcers have mostly been (perhaps even disproportionately) influenced by economic industrial organisation
perspectives that tended to consider market power rather narrowly, as solely observable in terms of high prices,
only within specified markets (as opposed to across markets), and which paid little attention to the strategic
consequences of platforms’ differentiated business models. In other words, platform power was, in the earlier
discussions on the relevance of introducing new platform regulation, mostly considered through the lens of
pricing power and its consequences evaluated exclusively in terms of consumer harm. This framework and its
inadequacy when applied to competition issues involving platforms have been highlighted by prominent scholars,
some of whom have been commissioned for the highest positions in competition agencies in the USA and Europe
(Khan, 2016; Scott Morton & Athey, 2021; Scott Morton & Kades, 2021). While the thinking in regulatory circles
has evolved in recent years to tackle some of the specificities of digital technologies and multi-sided markets,
9
This section is based on unpublished drafts prepared with supervisor Annabelle Gawer for Chapter 3.
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there is still a lack of consensus in terms of developing a complete framework of how platform power is actually
expressed and how these various expressions may constitute harm.
In this context, this thesis provides, in the first place, a conceptual framework with an integrated and nuanced
explanation of platform power, its dynamics, and consequences. Because platforms transform society on multiple
levels and across industry and market boundaries (on which regulation is typically based), holistic assessments of
the social consequences of platforms are essential to inform the design of more effective regulation and
regulatory scrutiny. An enriched understanding of the consequences of organising our practices through
platforms, how they are embedded in social structures, and expressed in the transformation of fields can be
challenging to translate into specific regulation but is nonetheless fundamental to start effectively addressing this
issue.
At the same time, this research offers tools and evidence that can be more directly considered for regulatory
purposes. First, empirically derived constructs, such as the “two-faced platform governance” strategy of platform
power, can be easily operationalised and assessed in different platforms and regions. In addition, the evidence
provided here on Amazon and its complementors’ practices and the discussion of their consequences indicates
that the practices identified can also be used by other platforms, especially those that enjoy market power. The list
of practices and mechanisms discovered and organised can be helpful to policymakers worldwide as they grapple
with the question of platform power. Overall, the empirically based, precise description of the various forms of
platform practices that lead to the accumulation of platform power, as well as the nuanced discussion of the
dynamic and interdependent consequences on complementors, can usefully enrich the empirical basis upon which
regulatory agencies may enforce existing law. It can also inform policy-making in other regions, such as the USA
or developing countries.
5.6. Limitations and future research
This research has limitations that must be acknowledged when considering the implications of our findings and
contributions. At the same time, these limitations can be addressed in coming studies and open new grounds for
future research.
Some of the limitations of this study are derived from the characteristics of the case chosen. While the pertinence
and benefits of selecting the Amazon Marketplace for this study have been argued in detail in sections 1.1.2, 3.3,
and 4.3, this selection can also present drawbacks, as some of this platform’s characteristics can veil relevant
aspects of the problem in consideration. In particular, the fact that Amazon is one of the largest companies in the
world and a dominant platform with durable market power in different regions, while greatly facilitates the task of
studying platform power and identifying its dynamics, it also poses questions regarding the generalizability of the
findings. Future studies can pursue similar aims as this research but in different platform contexts and explore the
validity of the findings. Further, even if the conclusions of this study are not fundamentally challenged by new
evidence, it is still highly relevant to understand how the constructs and dynamics described in this work play out
in different settings.
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Other limitations of this study are related instead to its focus. First, in the conceptual development of Chapter 2
and the empirical cases in Chapters 3 and 4, most of the attention is directed to how already powerful actors
accumulate more power. While one of the contributions of this study is precisely to highlight both dynamics of
power and counterpower accumulation by different agents, it is still possible that overall, this thesis builds a
depiction of platforms - and particularly their owners – as immensely powerful agents without significant
weaknesses. Nevertheless, however powerful an actor might currently be, it is necessary to assess that power's
boundaries and understand how conditions might change. Consequently, a fruitful area for future research is
identifying and explaining the specific processes and mechanisms by which, in addition to being contested,
platform owners lose power and how these processes relate to the platform’s characteristics.
Second, in line with the main trends in platform studies so far, this thesis has focused on the informational aspect
of digital technologies. However, some of the current tendencies in how digital innovation is developing, such as
the location and construction of data centres or the scale required for the evolving competition on computing
power, highlight instead the importance of the technology’s physical dimensions. Consequently, factors such as
the scale of physical investments, access to raw materials, and control of territories with strategic importance for
connectivity might become increasingly relevant to understanding platform power dynamics in the future. This
calls for further research on the interfaces between platforms' informational and physical dimensions and how this
affects power.
This thesis also uncovers opportunities for methodological development when empirically studying platforms.
First, the study on platform governance in Chapter 3 introduces new constructs that are useful to characterise
platform dynamics. While my inductive research was focused on identifying the phenomenon for theory building,
it also creates opportunities for methodological contributions on how to gather information on platform
governance and to create ways for measuring it. Second, Chapter 4 studies the long-term changes in the
platform’s characteristics and interactions. This long-term approach, while holding great potential for research
contributions, is however not abundant in the literature. It is to be noted the paradox that while data abundance is
one of the defining aspects of digital platforms, the availability of longitudinal data remains a significant challenge
for research, particularly data that might be used to assess agents’ practices and accountability. Indeed, gathering
data on how a platform firm - with the importance of Amazon - formally defines the rules for participation over
time involved an arduous and meticulous reconstruction through multiple sources and triangulation. These
challenges illuminate, however, the importance for researchers and regulatory agencies to devise new methods to
systematically collect information to build longitudinal databases on platform activities.
Finally, my empirical study of the Amazon Marketplace also illuminates the importance of developing new
frameworks for assessing performance in platform ecosystems. In platform research, overall platform performance
is usually evaluated in terms of network size (e.g., number of consumers and providers), value creation (e.g.,
volume of transactions or rate of product innovation), and market share -for inter-platform competition-.
However, while an analysis of the evolution of these metrics in the Marketplace would suggest a highly successful
platform ecosystem, I also find evidence of governance practices that enable and further favour misbehaviour
(section 3.4.3), tendencies of concentration of value capture, and mechanisms that drive organisational
dependence (section 4.4.3). These findings call for contributions that expand the current frameworks on how
platform ecosystem success is defined and assessed.
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5.7. Final remarks: repurposing platforms for social change
This thesis commenced by arguing that the profound and abrupt economic transformation brought by digital
platforms, along with expectations of higher social cohesion, increased freedom, and power distribution, was soon
shadowed by the increasing evidence of platform power concentration and abuse. Whereas a significant part of
academic research and public policy is now focused on understanding how to create effective regulation to curve
platforms’ power – efforts to which this thesis aims to contribute -some scholars have pioneered a different
approach, asking what platforms can mean for development (Bonina et al., 2021). While not disregarding the
current and potential threats of platform power, these researchers focus instead on how to rethink platforms so
they may deliver positive benefits for development and the common good (Bonina et al., 2021; Katsamakas et al.,
2022).
In line with this motivation, I suggest that this thesis’ contribution to a more precise understanding of digital
platforms’ power and organising role can contribute to rethinking the role of platforms in society. Power abuse in
platforms can lead to addiction and over-dependence, consumerism, mental health issues, polarisation and hate
speech, and democracy impoverishment. However, platforms can also promote integral human development
through sustainable consumption, mental well-being, and civic and political enhancement.
Can the processes that lead to organised immaturity be “hacked” by society and reoriented towards organised
enlightenment? If immaturity is the delegation of individual reasoning to external authority, enlightenment is
sapere aude (i.e., having the courage to use our own understanding, Kant, 2019 [1784]).
For digital platforms to become vehicles for human development would involve repurposing them as systems
reinforcing autonomy and socially desirable values by promoting digital habitus of emancipation. Purposing
platforms for development requires identifying designs that can balance successful business models with other
non-economic forms of value creation (Katsamakas et al., 2022). This means understanding how to give a voice
and articulate the specific constellation of actors involved in different development goals while keeping the
potential for open interaction and growth that characterises platforms (Bonina et al., 2021; Chamakiotis et al.,
2021). Further, it requires understanding how platforms can address the differences between developed and
developing countries’ specific challenges and offer new, situated ways for creating value, something that academic
research has only started to acknowledge (Jia & Kenney, 2021; Zhang, 2020). Overall, it requires exploring how to
channel digital platforms’ unique problem-solving capabilities and our current knowledge on practices of platform
design and governance towards creating mission-oriented platforms.
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Appendix
A.
Glossary of Amazon’s programs and policies
Name
Description
A+ Content
Amazon Accelerator
Amazon Anti-Counterfeiting Policy
Amazon Brand Registry
Amazon Currency Converter
Amazon Custom
Amazon Exclusives Program
A+ Content, also known as Enhanced Brand Content (EBC), is a feature offered by
Amazon to enhance product detail pages on their platform. It allows brand
owners and sellers to create more engaging and visually appealing content to
showcase their products and provide additional information to customers.
An initiative by Amazon that partners with manufacturers and brands to create
and launch products directly on its platform, offering increased visibility, datadriven insights, and promotional support.
A policy designed to ensure that products sold on Amazon are authentic and
genuine. Amazon prohibits the sale of counterfeit items and takes steps to
remove counterfeit listings and take action against sellers who violate this policy.
A program that allows brand owners to protect their intellectual property and
create an accurate and trusted experience for customers on Amazon. It provides
tools to help brand owners search for potentially infringing products, report
violations, and manage their brand's presence on the platform.
A service that allows international customers to see product prices in their local
currency and make purchases. The converter automatically calculates exchange
rates, enabling customers to shop in their preferred currency, with the final
conversion being done at the time of purchase.
A service that allows sellers to offer personalized products to customers. Through
Amazon Custom, sellers can provide customization options such as engraving,
printing, or embroidery, enabling customers to create unique, tailored items
based on their preferences.
A program where selected brands and innovators showcase their unique
products, available only on Amazon or through the brand's own website and
physical locations. This offers these brands a platform for increased visibility and
marketing support while giving customers access to a curated collection of
distinctive products.
Amazon Giveaway for FBA
A promotional tool that allowed sellers to set up sweepstakes-like giveaways for
their products to increase product visibility and generate buzz. By using Amazon
Giveaway in conjunction with Fulfillment by Amazon (FBA), sellers could easily set
up contests, with Amazon handling prize fulfillment. However, as of 2019,
Amazon announced the discontinuation of the Amazon Giveaway service.
Amazon Imaging Services
A service offered to sellers to help them obtain high-quality, professional images
of their products for their Amazon listings. With this service, sellers can enhance
their product listings with clear and detailed photos, helping to improve the
online shopping experience for customers and potentially increase sales.
Amazon Launchpad Program
Amazon Outlet
Amazon Partnered Carrier options
Amazon Payments
A program designed to assist startups and innovative brands in launching,
marketing, and distributing their products on Amazon. It provides tools,
expertise, and a platform for emerging brands to showcase their unique
products, helping them reach a wider audience and gain traction in the market.
A section on Amazon where customers can find discounted overstock items,
markdowns, and clearance products from various categories. It offers a place for
sellers to reduce their inventory of slow-moving products and for shoppers to
find deals.
A shipping program where Amazon partners with specific carriers to offer
discounted shipping rates to sellers sending inventory to Amazon's fulfillment
centers. By using Amazon's Partnered Carrier options, sellers can benefit from
reduced shipping costs and streamlined logistics when participating in the
Fulfillment by Amazon (FBA) program.
A payment service that allows customers to use the payment methods stored in
their Amazon account to pay for goods and services on third-party websites and
applications. By integrating Amazon Payments, merchants can provide a familiar
130
Essays on Power in Digital Platforms
Name
Description
checkout experience for Amazon customers, potentially increasing conversion
rates and customer trust.
Amazon Prime
A subscription service offering members a range of benefits, including free twoday shipping on eligible items, unlimited streaming of movies and TV shows with
Prime Video, access to Prime Music, Kindle e-book rentals, and other features.
The program aims to enhance customer loyalty and encourage more frequent
shopping on Amazon.
Amazon Services Order Notifier
A tool that notifies sellers of new orders in real-time. The Amazon Services Order
Notifier provides instant alerts to help sellers manage and fulfill their orders
promptly, ensuring timely delivery and improved customer satisfaction.
Amazon Vine
A program where select reviewers, known as Vine Voices, receive products for
free in exchange for writing honest and unbiased reviews. Brands can enroll their
products in the Vine program to generate early reviews, which can help potential
buyers make informed decisions and improve the product's visibility on Amazon.
ASIN creation rules
A set of guidelines provided by Amazon for creating Amazon Standard
Identification Numbers (ASINs). ASINs are unique blocks of 10 letters and/or
numbers used to identify items. The rules ensure that products are correctly and
uniquely identified on the platform, preventing duplicate listings and ensuring
consistency in the product catalog. This helps in maintaining the integrity of the
marketplace and providing a streamlined shopping experience for customers.
A-to-Z Guarantee
A protection offered to buyers who purchase items from third-party sellers on
Amazon. If a buyer's order never arrives or if it does but is significantly different
than described, the A-to-Z Guarantee provides a way for the buyer to seek a
refund. It aims to enhance trust in the marketplace by ensuring a safe and secure
shopping experience.
Automated pricing
A tool provided by Amazon that allows sellers to automatically adjust their
product prices based on predefined criteria. Sellers can set pricing rules, such as
matching the lowest price or undercutting competitors by a certain amount. The
tool continuously monitors prices and adjusts listings accordingly, helping sellers
remain competitive and maximize sales.
Brand Analytics
A feature available to brand owners registered with Amazon Brand Registry.
Brand Analytics provides detailed insights and data about a brand's products on
Amazon, including search terms, conversion rates, and competitive data. This
information helps brands understand customer behaviour, optimize their listings,
and make informed marketing and sales decisions.
Brand Referral Bonus
Buy Box
A program where brand owners can earn a bonus by driving external traffic to
their Amazon listings. When shoppers are directed from external sources to
Amazon and make a purchase, the brand owner receives a referral bonus,
effectively reducing the overall selling fees. The program incentivizes brands to
promote their Amazon listings through external marketing channels.
A feature on Amazon product detail pages that allows customers to quickly add
items to their shopping carts. Multiple sellers can offer the same product, but
only one seller at a time "wins" the Buy Box, making their offer the default for the
"Add to Cart" button. Winning the Buy Box is crucial for sellers as it significantly
impacts sales, and Amazon determines the winner based on factors like price,
fulfillment method, and seller performance.
Campaign managing & optimization
A set of tools and practices offered by Amazon to help sellers and advertisers
create, monitor, and refine their advertising campaigns on the platform. This
includes Sponsored Products, Sponsored Brands, and other ad types. Through
campaign management and optimization, sellers can set budgets, adjust bids,
target specific keywords or audiences, and analyse performance data to improve
the effectiveness and ROI of their advertisements.
Community rules
A set of guidelines and standards established by Amazon for user interactions
within its community spaces, such as product reviews, discussion boards, and
Q&A sections. These rules are designed to maintain a positive and respectful
environment, prevent misuse, and ensure that content contributed by users is
helpful and relevant to other shoppers. Violations can lead to removal of content
or further actions against the user's account.
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Condition Guidelines
A set of standards provided by Amazon to help sellers accurately describe the
condition of items they list for sale, especially for used or refurbished products.
These guidelines ensure consistency and transparency in product listings, helping
buyers to know exactly what to expect when making a purchase. The conditions
range from "New" to various levels of used or refurbished states, each with
specific criteria about the item's appearance and functionality.
Coupons
A promotional tool offered by Amazon that allows sellers to provide discounts on
their products. Sellers can create digital coupons for specific items, which
shoppers can "clip" and apply during checkout. This feature helps sellers boost
visibility, drive sales, and incentivize purchases, while shoppers benefit from
savings on their desired products.
Create Product Page
A feature on Amazon's seller central platform that allows sellers to list new
products not currently found on Amazon. Sellers provide detailed information
about the product, including title, brand, price, and product details, to create a
unique product detail page. This ensures that customers have all the information
they need to make informed purchasing decisions. Properly crafted product
pages can enhance visibility and improve sales conversions.
Drop shipping policy
A policy set by Amazon that allows sellers to list and sell products that they do
not physically have in stock. When a customer orders a drop-shipped product,
the seller purchases the item from a third-party supplier, who then ships it
directly to the customer. Amazon's policy requires that sellers be responsible for
the entire customer experience, ensuring items are delivered on time and match
the product description. Additionally, the seller must identify themselves as the
seller of record and not the third-party supplier.
Event Notification Service
A service provided by Amazon that sends real-time notifications to sellers about
specific events related to their Amazon storefront. These notifications can include
updates about orders, shipments, listings, and other pertinent information. By
receiving timely alerts, sellers can manage their operations more effectively and
respond quickly to any changes or requirements.
Environmental marketing guidelines
Guidelines established by Amazon to ensure that sellers make accurate, clear,
and substantiated environmental claims about their products. This includes
claims related to sustainability, recyclability, energy efficiency, and other ecofriendly attributes. The guidelines aim to prevent greenwashing (misleading
claims about the environmental benefits of a product) and ensure that customers
receive accurate information about the environmental impact of the products
they purchase.
Fulfillment by Amazon (FBA)
Fulfillment by Amazon (FBA) is a service where sellers store their products in
Amazon's fulfillment centers. When orders are placed, Amazon handles storage,
packaging, and shipping on the seller's behalf. Additionally, FBA products
become eligible for Amazon Prime and other Amazon services. This allows sellers
to scale their business and reach a wider customer base while outsourcing the
logistics to Amazon.
FBA Export
FBA Inventory Placement Service
FBA Labelling
A feature of the Fulfillment by Amazon (FBA) program that allows sellers to offer
their products to customers outside their home country. Amazon handles the
international shipping, customs duties, and customer service for these orders.
This enables sellers to easily expand their market reach to international
customers without the complexities of cross-border logistics and customer
support.
A service within the Fulfillment by Amazon (FBA) program that allows sellers to
ship their inventory to a single Amazon fulfillment center. Amazon then
distributes the inventory across its network as needed. This can simplify the
inbound shipping process for sellers, but there might be associated fees for
using the service, especially if Amazon has to distribute the inventory across
multiple locations.
A part of the Fulfillment by Amazon (FBA) program that requires products to
have specific labels to be processed and handled correctly within Amazon's
fulfillment centers. Sellers can either label their products themselves according to
Amazon's guidelines or, for a fee, have Amazon handle the labeling. Proper
labeling ensures accurate tracking, storage, and delivery of products to
customers.
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FBA New Selection
FBA Onsite
FBA Prep Service
FBA Repackaging Service
A program within Fulfillment by Amazon (FBA) designed to support and
incentivize sellers to launch new products on Amazon using FBA. It offers
benefits such as free monthly storage, free removals, and free return processing
on eligible new ASINs (Amazon Standard Identification Numbers). This program
aims to reduce the initial costs and risks for sellers introducing new products to
the marketplace.
An initiative that combines Fulfillment by Amazon (FBA) and Seller Fulfilled Prime
(SFP). With FBA Onsite, sellers store and pack their products in their own facilities,
but the inventory is treated as if it's part of Amazon's own fulfillment network.
This means items can be listed with Prime 2-day shipping, and Amazon handles
the shipping logistics using its own transportation network. The program aims to
expand Prime eligible inventory and reduce shipping times.
A service offered by Amazon where they handle the preparation and packaging
of a seller's inventory to meet the specific requirements of the Fulfillment by
Amazon (FBA) program. This can include tasks like bagging, bubble wrapping,
and labelling products. Sellers are charged a fee for this service, but it ensures
that products are correctly prepared for storage and shipment from Amazon's
fulfillment centres.
A service within the Fulfillment by Amazon (FBA) program where Amazon
repackages a seller's returned products, if deemed sellable, so they can be placed
back into the seller's active inventory. This helps to reduce waste and allows
sellers to resell products that are still in good condition. The service ensures that
items are appropriately repackaged to meet Amazon's standards before being
made available for sale again.
FBA Returns Processing Fee
A fee charged to Fulfillment by Amazon (FBA) sellers when Amazon processes a
return on their behalf. The fee covers the handling, repackaging, and restocking
of the returned product in Amazon's fulfillment center. The amount charged
depends on the size and category of the item. This fee ensures that returned
products are efficiently processed and made available for resale if they are in
sellable condition.
FBA Small and light
A program within the Fulfillment by Amazon (FBA) service specifically designed
for sellers who offer small and lightweight products that are typically priced
under $7. By using FBA Small and Light, sellers can benefit from reduced
fulfillment costs and offer fast, free shipping options to their customers. The
program aims to make it more cost-effective for sellers to offer low-cost
products through FBA.
FBA Subscribe & Save
A program that allows sellers using Fulfillment by Amazon (FBA) to offer their
products as part of Amazon's Subscribe & Save service. Customers can choose to
receive regular, scheduled deliveries of eligible products at a discount. Sellers
benefit from increased customer loyalty and recurring sales, while customers
enjoy convenience and savings on products they frequently purchase.
Featured Merchant Status
A designation given to certain sellers on Amazon based on their performance
metrics and customer service track record. Having Featured Merchant Status can
increase a seller's chances of winning the Buy Box. The criteria for achieving this
status includes factors like order defect rate, shipping punctuality, and customer
feedback. Being a Featured Merchant enhances a seller's reputation and can lead
to increased sales on the platform.
Feedback rating
A system on Amazon where buyers can rate and leave feedback for sellers based
on their experience with a purchase. Feedback is given on a scale of 1 to 5 stars,
with 5 being the best. The feedback rating is an average of all the ratings a seller
has received over the past 12 months. It provides potential buyers with an
indication of the seller's reliability and service quality, influencing purchasing
decisions.
Fulfilling and Shipping Credits
A credit system on Amazon for sellers who handle their own order fulfillment
rather than using Fulfillment by Amazon (FBA). When a sale is made, sellers
receive a shipping credit based on the product's category and the shipping
method chosen by the buyer. This credit is meant to help offset the shipping and
handling costs incurred by the seller. The actual cost to ship the item may be
more or less than the provided credit, depending on various factors.
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Global selling
An Amazon program that allows sellers to list and sell their products across
Amazon's international marketplaces. Through Global Selling, sellers can expand
their business into new regions, reaching customers in countries around the
world. Amazon provides tools and resources to help with listing translations,
currency conversions, international shipping, and understanding local regulations
and customs duties. This program enables sellers to tap into a broader customer
base and grow their international sales.
Headline Search Ads / Brands
A type of sponsored advertisement on Amazon, primarily available for brand
owners. These ads appear at the top of Amazon search results, providing high
visibility for promoted products. Advertisers can create custom headlines, select a
set of products to showcase, and choose relevant keywords to trigger their ads.
When shoppers click on a Headline Search Ad, they are directed to a product
detail page or a branded Amazon Storefront. This ad format helps brands
increase product visibility and drive sales.
Intellectual Property Policy for Sellers
Inventory reports
A policy set by Amazon to protect intellectual property rights, including patents,
trademarks, copyrights, and trade secrets. Sellers are required to sell only
genuine products and avoid infringing on the intellectual property rights of
others. Amazon's policy provides a process for rights owners to report and
request the removal of listings that they believe infringe on their intellectual
property. Sellers who repeatedly violate this policy may face account suspension
or other penalties. This policy aims to maintain trust in the marketplace and
protect both sellers and rights owners.
Inventory reports are documents provided by Amazon to sellers, offering
detailed information about their inventory stored in Amazon's fulfillment centers.
These reports contain data such as the quantities of each product, their storage
locations, historical sales data, and other relevant information.
Lighting Deals
Lightning Deals are limited-time promotions offered by Amazon that allow
sellers to offer their products at a discounted price for a short period of time.
These deals are typically available for a few hours and are featured prominently
on Amazon's Deals page. Lightning Deals can help sellers increase product
visibility, drive sales, and attract more customers to their listings. Sellers need to
meet certain criteria to be eligible for Lightning Deals.
Listing Photos
Listing photos are images of products that sellers upload to their product listings
on Amazon. These photos provide visual representations of the items for sale
and play a crucial role in attracting the attention of potential buyers. Amazon's
guidelines specify the size, format, and quality of listing photos to ensure a
consistent and appealing shopping experience for customers.
Long term storage
Long-term storage in the context of Amazon refers to the storage of a seller's
inventory in Amazon's fulfillment centers for an extended period. Amazon
charges additional fees for items that remain in storage for an extended duration,
typically for items that have been in the fulfillment center for more than 365
days.
Manage Your Experiments
A feature enabling businesses and developers to run A/B tests on their product
listings to understand the impact of different variables, such as product images
or descriptions, on customer behavior and sales, with the goal of optimizing their
listings for better performance.
Manage your order
Managing Inventory (FBA)
Match Low Price
Multi-channel fulfillment (FBA)
A tool for third-party sellers on Amazon's platform, enabling them to oversee
and process customer orders, update shipping details, handle returns, and
respond to customer inquiries related to their sales.
A tool for Fulfillment by Amazon (FBA) sellers to oversee and handle their
inventory stored in Amazon's fulfillment centers. This includes tracking stock
levels, restocking products, forecasting inventory needs, and handling stranded
or unfulfillable inventory to ensure efficient operations and timely order
fulfillment.
A feature for sellers to automatically adjust their product prices to match the
lowest price on Amazon for the same item. This helps sellers stay competitive by
ensuring their items are priced in line with current market rates on the platform.
A service offered to Fulfillment by Amazon (FBA) sellers where Amazon fulfills
orders coming from sales channels outside of the Amazon marketplace. This
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means sellers can store their inventory in Amazon's fulfillment centers, and when
orders are received from other platforms or websites, Amazon handles the
picking, packing, and shipping.
One-Day Delivery
A shipping option provided to Amazon customers that ensures the delivery of
eligible items within one day of placing the order. This service aims to offer fast
shipping times, increasing convenience for customers who need their purchases
quickly. Availability may vary based on location and product.
Opportunity Explorer
A tool that provides insights and analytics for Amazon sellers to identify potential
product opportunities, market trends, and customer demand within the Amazon
marketplace. By analyzing sales data, reviews, and search frequency, it helps
sellers make informed decisions about expanding their product range or entering
new market segments.
Packaging Guidelines
A set of standards and recommendations provided by Amazon to sellers and
manufacturers regarding how products should be packaged for shipment and
storage. These guidelines ensure that items are protected during transit, are easy
to open by the consumer, and minimize waste. Compliance can also impact a
seller's standing with Amazon and customer reviews.
Participation agreement
A formal document outlining the terms and conditions that sellers must agree to
when using Amazon's platform and services. It covers a range of topics including
listing procedures, payment terms, intellectual property rights, dispute resolution,
and other essential aspects of doing business on Amazon. Adhering to this
agreement is mandatory for all sellers.
Policies for bundling
Popular Brand Indicator
Guidelines provided by Amazon for sellers who wish to create product bundles,
which are multiple complementary items sold together as a single package.
These policies specify how bundles should be listed and presented, including
rules about relatedness of items, listing accuracy, and packaging, to ensure clear
and coherent product presentations for customers.
A feature on Amazon's platform that highlights well-known and frequently
purchased brands, helping customers quickly identify and trust those brands. The
indicator serves to differentiate popular brands from others in search results and
on product detail pages, enhancing their visibility and indicating their reputation
among shoppers.
Premium Shipping
A set of expedited shipping options available to eligible Amazon sellers who
consistently meet high performance and reliability standards. These options
include Two-Day, Next Day, and Same Day shipping. Sellers who offer Premium
Shipping must adhere to strict shipping and delivery performance requirements
to ensure customer satisfaction.
Pricing conditions
A set of guidelines and terms set by Amazon that sellers must follow when
setting prices for their products on the platform. These conditions aim to ensure
fair competition, prevent price manipulation, and maintain customer trust. They
include rules against price fixing, below-cost selling, and other pricing strategies
that could mislead or harm consumers.
Prime Exclusive Discount
Refunds policy
A promotional offer exclusively for Amazon Prime members where eligible
products are offered at a reduced price. Sellers can use this feature to attract
more Prime customers by offering special discounts, thereby potentially
increasing sales. Products with this discount display a unique badge,
differentiating them in search results and on product detail pages.
Amazon's guidelines detailing the circumstances under which customers can
return products and receive a refund. It specifies the conditions items must meet
upon return, the time frame within which returns are accepted, and the process
for issuing refunds. The policy aims to balance sellers' rights with the
commitment to customer satisfaction and trust.
Return and Disposal of FBA
Inventory
A set of procedures and options available to Fulfillment by Amazon (FBA) sellers
for managing inventory that is unsellable or unwanted in Amazon's fulfillment
centers. Sellers can choose to have these items returned to them or disposed of
by Amazon.
Seller Fulfilled Prime
A program that allows eligible sellers to display the Prime badge on their listings
while handling their own order fulfillment. These sellers must meet Amazon's
rigorous delivery and performance standards, ensuring Prime members receive
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the same benefits, like two-day shipping, they would when purchasing from
Amazon's own inventory.
Seller Lending Program
A financing option provided by Amazon to eligible sellers on its platform. It
offers short-term loans, based on sales history and other performance metrics, to
help sellers grow their business, increase inventory, or address other operational
needs. The loan amount and terms are determined by Amazon, and repayments
are typically automated from the seller's account.
Seller Offenses / Code of Conduct
A set of rules and guidelines that sellers on Amazon must adhere to while
operating on the platform. It outlines prohibited behaviours and practices, like
listing counterfeit products, manipulating reviews, or violating intellectual
property rights. Violations can result in penalties ranging from listing removals to
account suspensions, ensuring a trustworthy marketplace for consumers and fair
competition among sellers.
Seller Performance Measurement
A system by which Amazon evaluates the performance of sellers on its platform
using various metrics like order defect rate, pre-fulfillment cancel rate, and late
shipment rate. These metrics reflect a seller's reliability, customer service, and
overall compliance with Amazon's standards. Meeting or exceeding specific
benchmarks is crucial for maintaining account health and eligibility for certain
Amazon programs.
Seller's Best Practices
Recommendations and strategies provided by Amazon to help sellers optimize
their operations and listings on the platform. These practices cover various
aspects, from effective product listing techniques, pricing strategies, and
inventory management, to customer service guidelines. Following these best
practices can enhance a seller's visibility, sales, and customer satisfaction on the
platform.
Selling Coach
A tool that offers personalized recommendations to Amazon sellers to help them
identify growth opportunities and improve their business on the platform. It
provides insights, such as potential products to stock, pricing suggestions, and
inventory restocking reminders, all based on sales data, market trends, and
customer behaviors.
Shipping expectations
A set of guidelines provided by Amazon that outline the expected time frames
and standards sellers should adhere to when shipping items to customers. These
expectations ensure that customers receive their purchases within the promised
delivery window and in good condition. Adhering to these standards is crucial for
maintaining customer trust and seller reputation on the platform.
Sold by Amazon
A program where Amazon takes over the pricing decisions for a seller's products
while guaranteeing a certain amount of payout for each sale, regardless of the
sale price. This allows sellers to offer competitive prices without risking
profitability. Amazon adjusts the product prices dynamically based on its
algorithms.
Sponsored Display
An advertising solution allowing Amazon sellers and vendors to create display
ads that appear both on and off Amazon, targeting specific audiences. These ads
can appear on product detail pages, search results, and other sites/apps in
Amazon's advertising network, aiming to drive traffic, increase brand visibility,
and boost sales.
Sponsored Products
A pay-per-click advertising solution that helps Amazon sellers promote individual
product listings. These ads appear in search results and on product pages, giving
products higher visibility. Advertisers bid on keywords, and when a customer's
search matches the keyword, the ad may be displayed. Sellers only pay when
their ad is clicked by a shopper.
Storefront
A customizable page on Amazon where brands can showcase their product
range, tell their brand story, and create a curated shopping experience for
visitors. It provides brands with a unique URL, allowing them to drive external
and internal traffic. Features like videos, images, and text can be used to enhance
the visual appeal and engage customers.
Tax Collection Services
A service provided by Amazon to automatically calculate, collect, and remit sales
tax on behalf of sellers for orders shipped to customers in jurisdictions that have
enacted Marketplace Facilitator laws. This relieves individual sellers from
managing sales tax collection in these areas, ensuring compliance with local tax
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regulations.
Unplanned Prep Services
A service by Amazon where they handle any necessary preparation of inventory
sent to Fulfillment by Amazon (FBA) centers that doesn't meet their inbound
requirements. If inventory arrives at a fulfillment center and requires additional
prep or labeling, Amazon may perform these services for a fee, which is then
charged to the seller's account.
Virtual Dash Buttons
A digital version of Amazon's physical Dash Button. These virtual buttons allow
Prime members to quickly reorder frequently purchased products directly from
their Amazon home page or the Amazon app. Each button is associated with a
specific product, streamlining the purchasing process and increasing
convenience for repeat orders.
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