Public Money & Management
ISSN: 0954-0962 (Print) 1467-9302 (Online) Journal homepage: https://www.tandfonline.com/loi/rpmm20
Outcome, process and support: analysing aspects
of innovation in public sector organizations
Johanna Nählinder & Anna Fogelberg Eriksson
To cite this article: Johanna Nählinder & Anna Fogelberg Eriksson (2019): Outcome, process
and support: analysing aspects of innovation in public sector organizations, Public Money &
Management, DOI: 10.1080/09540962.2018.1559617
To link to this article: https://doi.org/10.1080/09540962.2018.1559617
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PUBLIC MONEY & MANAGEMENT
https://doi.org/10.1080/09540962.2018.1559617
Outcome, process and support: analysing aspects of innovation in public sector
organizations
Johanna Nählinder and Anna Fogelberg Eriksson
ABSTRACT
KEYWORDS
The authors present an analytical model to distinguish between different aspects and modes of
innovation. By showing how innovation in the public sector differs from the private sector, this
paper is an important stepping-stone to understanding and supporting innovation in the public
sector.
Innovation outcome;
innovation process;
innovation support; public
sector innovation; social
innovation
Innovation has been long studied in the private services
sector, and even longer in the private manufacturing
sector, but the study of innovation in the public sector
is a comparably new topic and is usually omitted from
studies of innovation in general (Djellal, Gallouj, &
Miles, 2013; Gallouj & Zanfei, 2013; Potts & Kastelle,
2010). However, the research field of innovation in the
public sector, also discussed under different labels
such as ‘public sector innovation’, ‘public service
innovation’ and ‘social innovation’, is growing.
The EU projects PUBLIN (Windrum & Koch, 2008),
MEPIN (Bloch, 2011) and LIPSE (De Vries, Bekkers, &
Tummers, 2016; Voorberg, Bekkers, & Tummers, 2014)
have been influential in forming and defining the field,
as have journal articles and journal special issues.
Research is ongoing in different academic fields,
particularly in public administration (Albury, 2005;
Bartlett & Dibben, 2002; Borins, 2001; Golden, 1990;
Hartley, 2005; Moore & Hartley, 2008; Mulgan, 2007;
Osborne & Brown, 2013) and innovation studies
(Djellal et al., 2013; Gallouj & Zanfei, 2013; Potts &
Kastelle, 2010).
At this stage, it is difficult to get an overview of the
field but some central themes in the study of
innovation in the public sector include barriers,
drivers and conditions for innovation (for example
Bekkers, Tummers, & Voorberg, 2013; Bloch, 2011;
Demircioglu & Audretsch, 2017; Potts & Kastelle,
2010). Voorberg et al. (2014) notice that this is a
dominant theme in the study of innovation in the
public sector, in particular on co-production: ‘most
studies focused on the identification of influential
factors, while hardly any attention is paid to the
outcomes’ (Voorberg et al., 2014, p. 1). Another
common theme is the measurement of innovation
in the public sector (Arundel & Huber, 2013;
CONTACT Johanna Nählinder
Bloch & Bugge, 2013; Kattel et al., 2013). Yet another
common theme is what is typical of public sector
innovation and what distinguishes it from innovation
in the private sector (De Vries et al., 2016; Halvorsen,
Hauknes, Miles, & Røste, 2005; Nählinder, 2013) or the
service sector (Djellal et al., 2013). Other, overlapping,
themes are open innovation (Fuglsang, 2008) and
social innovation (Bekkers et al., 2013).
Previous research has shown that research on
innovation in the public sector is scattered and tends
to be non-theoretical (De Vries et al., 2016). Kattel
et al. (2013) discuss how, using the term ‘public
sector innovation’, there is a large discrepancy in
defining the core concept. De Vries et al. (2016)
noted that the term ‘innovation’ is sometimes used to
describe different but related phenomena. For
example, in three papers with a clear focus on the
public sector as an innovator in its own right, Savory
(2009), Salge (2012) and Kallio, Lappalainen, and
Tammela (2013) all discuss innovation, but from
different perspectives, and each paper uses a
different terminology. Innovation is, for example,
discussed as ‘innovation modes’ (Salge, 2012),
‘innovation targets’ (Kallio et al., 2013) or ‘practicebased and research-based innovations’ (Savory, 2009).
Innovation processes are described as ‘knowledge
production processes’ (Savory, 2009) or ‘innovative’
searches (Salge, 2012). In addition, the three papers
all discuss how innovation in public sector may be
supported, but they do this using different
terminologies; they refer to different authors; and
they use different bodies of knowledge.
This lack of conceptual congruity complicates the
building of a theoretical foundation for the study of
public sector innovation. Distinguishing clearly
between different aspects of innovation clarifies existing
johanna.nahlinder@liu.se
© 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/bync-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or
built upon in any way.
2
J. NÄHLINDER AND A. F. ERIKSSON
knowledge. The research field would benefit from a
stronger theoretical base, and more coherence in
research and terminology.
We have found that, in using the term ‘innovation’,
reference is often made to innovation as a new
product, process or organizational change (innovation
as outcome). Sometimes reference is made to the
process of turning an idea into an innovation
(innovation process) and sometimes to the support
provided to facilitate such a process (innovation
support). Analytically distinguishing between these
three interrelated innovation aspects would help to
clarify and disentangle the contribution of previous
research and provide a basis for describing and
analysing innovation in the public sector.
This paper describes the development and testing
of an analytical model that distinguishes between
different aspects and modes of innovation. We then
discuss how this analytical model furthers our
understanding of how innovation in public sector
differs from innovation in private sector.
Theoretical background
In order to improve our understanding of how public
sector innovation differs from innovation in the
private sector, we need a theoretical background for
our analytical model. This background comprises two
themes: a conceptual translation of the innovation
concept for the purposes of studying innovation in
the public sector, and different modes of innovation.
Double translation
The understanding of innovation in the public sector
has developed in tandem with the understanding of
innovation in the private sector, in particular the
manufacturing sector. The study of innovation in
public sector has been heavily influenced by
innovation in the private sector. There has been
discussion about how innovation in public sector
should be related to innovation in manufacturing and
innovation in services (Bloch & Bugge, 2013; Djellal
et al., 2013; Nählinder, 2013; Osborne & Brown, 2013).
Sometimes researchers have regarded innovation in
the public sector merely as a special case of private
sector innovation. In so doing, innovation in the
public sector can never differ qualitatively from
innovation in the private sector.
The influence of research on the manufacturing
sector on the research on innovation in the public
sector has provided a basis upon which to study
innovation in the public sector, but it has also
produced a biased, normative view of the concept
of innovation (Alsos, Ljunggren, & Hytti, 2013;
Fogelberg Eriksson, 2014; Hobday, 2005; Wegener &
Tanggaard, 2013). Therefore, in order to study
innovation in the public sector, we need to make
two conceptual translations of the innovation
concept: the first translation is from innovation in
producing goods to innovation in delivering
services a shift which has given rise to a
considerable academic discussion (Miles, 2005;
Carlberg, Kindström, & Kowalkowski, 2014). The
second translation of the innovation concept from
the enterprise, market or private sphere to the
government or public sphere is more problematic,
although though some researchers do not consider
it a problem (Djellal et al., 2013).
Innovativeness in the public sector may differ from
innovativeness in the private sector. The problem,
articulated by the concepts ‘assimilist’, ‘demarcation’,
‘inversion’ and ‘synthesis’ (Coombs & Miles, 1999;
Djellal et al., 2013; Droege, Hildebrand, & Heras
Forcada, 2009) is how to reap the benefits of research
on innovation in manufacturing and innovation in
services (assimiliation), while at the same time being
open to sector-specific characteristics (synthesis
approach). A first problem is identifying how
innovation in the public sector differs from innovation
in the private sector. This is difficult because the public
sector is extremely heterogeneous: it is hard to find
the ‘public’ in the public sector. For example,
healthcare is sometimes organized as a public sector
industry, sometimes as a private sector industry and
often as a combination of the two. Studies of
innovation in healthcare do not always discuss the
degree to which findings apply to the whole
healthcare sector or the public or private part of it.
One important difference between the public and
the private sectors, however, is that the public
sector is steered by principles that do not apply in
the private sector. This impacts innovation.
Petersson and Söderlind (1993) argue that the public
sector typically can be described as based on three
principles democracy, ‘rechtsstaat’ and the welfare
state and that these principles conflict. The principle
of democracy is that a public sector organization
should ultimately be steered by politicians who have
been elected by citizens. The principle of rechtsstaat
is about rights and the limitation of a government’s
power by law and includes the principle of equal
treatment. The principle of the welfare state stands
for the provision (and production) of welfare to the
citizens and stresses the importance of the efficient
production and delivery of services. The private
sector is not subject to the principle of democracy,
nor by the principle of rechtsstaat. The only
principle applying to both sectors is the efficiency
inherent in the welfare state. Value creation thus
takes different forms in the public sector than in the
private sector, which likely also concerns
innovativeness (Nählinder, 2013). Hence the double
translation explained in Figure 1.
PUBLIC MONEY & MANAGEMENT
3
(2) There are differences in innovativeness according
to the sector (goods producing sector/services
producing sector).
(3) Institutional context (public sector/private sector)
matters.
(4) The public sector is guided by different principles
(rechtstaat, democracy and welfare state).
(5) Innovations may be divided in different innovation
modes (STI/DUI).
Figure 1. The double translation of the innovation concept
(Nählinder & Fogelberg Eriksson, 2017).
Innovation modes: not all innovations are
STI (science and technology based)
A widespread misunderstanding of innovation is that it is
based on R&D, it is tangible and highly visible. However,
this does not apply to all innovations. In 2007, Jensen
et al., building on Lundvall and Johnson (1994),
developed a distinction between two different types of
innovation modes. They labelled these ‘STI’ (science and
technology based) and ‘DUI’ (doing, using, interacting).
These labels may be used to broaden and qualify the
understanding of innovation and innovative differences
between the private and the public sectors.
The twin concepts of STI and DUI put important
differences into words see Table 1. STI needs
considerably more explicit support (which is also,
possibly, why this support typically is so well developed).
Innovations which are based on DUI processes are
difficult to count, support and diffuse. The dilemma of
DUI is that they tend to be spontaneous and ubiquitous,
but difficult to encourage. Comparing STI and DUI
makes it clear that they have very different properties:
something we elaborated upon in our analytical model.
Developing the analytical model
Thus far, it is clear that:
(1) Innovation has three aspects (outcome, process
and support).
The model in Table 2 shows that the three aspects of
innovation should ideally be aligned to create
favourable conditions for innovation: innovation cannot
be expected to be an outcome if the innovation process
is not supported accordingly. Support designed for STI
processes may fail to support, and even discourage, DUI
processes. This implies that the notion of a ‘trickle-down
effect’ (if a system is designed for big innovations, small
innovations will automatically follow) has important
flaws. It also implies that suitable support for DUI
processes must be developed and readily available.
An analytical model is, by definition, a simplification
and reduces complexity. It should be noted that our
model is not intended as a prescriptive one, nor is it
deterministic in the sense that one aspect cannot
follow another even if not aligned. The model, rather,
focuses on dimensions which may be of importance
in order to understand innovativeness. In practice,
innovation aspects and innovation modes may very
well be intertwined with each other and with the
institutional context. Many innovations have traits of
both STI and DUI, i.e. should not be understood as a
dichotomy where one excludes the other (Jensen,
Johnson, Lorenz, & Lundvall, 2007).
Applying the analytical model: PIMM
Our analytical model was applied to a Swedish public
health sector innovation project PIMM (product
development in the care sector) (Nählinder, 2010). PIMM
(2006–2010) was a joint regional innovation project
including business support organizations (ALMI and
HNV) and healthcare organizations (two municipalities
and a regional health council). The purpose of the PIMM
Table 1. A comparison of STI and DUI (Nählinder and Fogelberg Eriksson, 2017).
STI
Initiative
Relation to ordinary work
Resources needed
Visibility
IPRs (intellectual property
rights)
Diffusion
Typical support processes
DUI
Management (top-down)
Often organized in special units, such as projects
Essential. In order to execute, extra resources needs to be
summoned and organized
High: due to need of extra resources Resulting innovations
countable
Often applicable
Employees
Not separated from everyday work
Limited, since part of everyday work
Often diffusible, especially if protected by IPRs
Diffusion difficult, since inter alia the innovation need to fit into
an organizational context
Suggestion box Continual improvement Innovative/creative
climate
The linear model ‘Innovation management’ R&D projects
Low: since integrated into everyday work Resulting innovations
uncounted/ uncountable
Not applicable
4
J. NÄHLINDER AND A. F. ERIKSSON
Table 2. Analytical model: aspects of innovation (outcome, process, support) in relation to modes of innovation (STI and DUI).
Innovation aspect
STI
DUI
Innovation as outcome: The actual
innovation
Innovation process: The route an
innovation in development takes
Typically innovations which can be diffused and/or
protected
STI processes, based on know-why- knowledge and
indirectly on know-what
Innovation support: The measures
taken by an organization to support
its innovativeness
Require investments to be implemented and therefore
tend to be visible: R&D departments, organizational
structures, (innovation) projects
project was to increase innovation in healthcare
organizations, in particular among nurses and assistant
nurses. Therefore healthcare employees were the
innovators, turning their ideas into innovations. The
ideas were then to be out-sourced to firms, thus both
creating increased innovativeness in the public sector
and more regional jobs.
The backbone of PIMM was that it was co-ordinated
and mostly executed by an experienced business
support organization: ALMI. Innovation advisors from
ALMI helped qualify the ideas, finance prototypes, file
patents and scout for firms interested in licensing the
products. In the last step of the PIMM model, the
products would go to the market, where the regional
health council and the municipalities were important
potential customers.
Idea pilots (peers who held presentations, helped to
scout for ideas and supported the idea carriers
throughout the PIMM model) played an important
role. The idea pilots gave examples of (mostly goods)
innovations and encouraged their peers to recognize
their own innovativeness. Initially the idea pilots were
thought to engage only in the first phase of the
innovation support, but were later acknowledged for
their role also later on in the process.
Employees were encouraged to present ideas to their
idea pilot, who then assisted them in developing their
ideas. The ideas for innovations were to come from
their working practice and the development and
formalization of the ideas were made in their spare
time. Only on a few occasions were idea carriers
allowed to meet with the innovation pilot during
working hours.
An analysis of the ideas supported by PIMM showed
that, out of 306 ideas presented in November 2009, 21
ideas were service innovations, four ideas were
Typically innovations which are numerous, small and
invisible
DUI processes, based on know-how and know-who
knowledge. Often rather short and cannot always be
separated from innovation as outcome. A specific type
of learning process
Tend to be supported in idea generation, idea collection
or innovation climate. Could be supported through
deliberate attention to workplace learning
innovations which combined goods and services and
275 were goods innovation ideas. The nature of the
innovation was difficult to determine in six cases.
None of the ideas were organizational innovation
ideas (Nählinder, 2010).
The project ran into difficulties supporting
organizational innovations (these ideas were not even
registered). These were not at all compatible with the
PIMM model which made them, in a way, easy to
handle (exclude). The service innovations, on the
other hand, were trickier. On one hand, they
resembled goods innovations well enough to be
tweaked into the system. On the other hand they had
(at least) two properties which made them difficult to
support in the PIMM model. First, a new service
needed a customer in order to be developed, but the
municipalities and the regional health council were
not prepared to take on the role as customer. Second,
the service innovations could not be separated from
their idea carrier and out-sourced. PIMM presented
organizational innovation and service innovation tips
on their homepage to respond to the problem of how
to handle ideas presented to PIMM which could not
be supported by the PIMM model.
Analysing the case of PIMM
Table 3 clarifies how PIMM simultaneously had traits of
both STI and DUI. PIMM was primarily an innovation
support project. It was based on previous innovation
support in other industries which meant that it
reproduced the stylized image of an innovation
process. It has some resemblance to the linear model
(Godin, 2006; Kline & Rosenberg, 1986), which was
developed with STI processes in mind, including steps
to design prototypes. It was thus not tailor-made to fit
Table 3. PIMM summarized in the analytical model.
Innovation aspect
STI
DUI
Innovation as outcome: What
innovations were actually
supported?
Innovation process: What innovation
processes were actually supported?
The PIMM model typically supported diffusible
and protectable innovations
Innovation support: What
characterizes the innovation
support?
The PIMM model was based on previous
support of STI processes and focused goods
innovations
The PIMM model did not attract or result in organizational
innovations and only to a limited degree in service
innovations
DUI processes, based on how the ideas for the innovations were
meant to arise and the lack of resources provided to idea
carriers
The PIMM project also aimed at improving innovation climate,
but did not have the necessary mechanisms
STI processes, based on the design of the PIMM
model
PUBLIC MONEY & MANAGEMENT
the innovation processes of the innovations of the target
group (nurses and assistant nurses). The idea pilots
smoothed the edges of the PIMM model and made it
work for the idea carriers.
Although the PIMM project was very keen to
support different types of innovations, they did not
have the mechanisms to do so. Neither did they see
what possible mechanisms could be used to support
organizational and service innovations. Thus, the
design of the PIMM model gave a clear message as
to which innovations were desirable.
So it can be argued that the innovation support
team favoured certain innovation processes over
others (i.e. STI over DUI) and, in consequence, that
they directed and even excluded possible innovations.
The PIMM model focused exclusively on innovation
within the realm of the welfare state principle, to the
degree that it is difficult to see traces of democracy
and rechtstaat in the project. Although the specific
industry context has relevance here (ideas for goods
innovations are probably more frequent in healthcare
than in, say, social services), so has the public sector
as an institutional setting.
Discussion
Our analytical model meant that DUI could be
separated from STI, which is crucial for understanding
the aspects of innovation. STI and DUI processes give
rise to different types of innovation and require
different kinds of support. Institutional context was
also shown to be of importance to innovation.
Returning to Petersson and Söderlind’s (1993) three
principles, we observed that:
.
.
The range of innovation as outcome can differ by
sector. While innovation can take numerous forms
in both the private and public sectors, innovation
outcomes in democracy and rechtstaat are unique
to the public sector. Examples of these are evoting and law-making. More attention should be
paid to identifying and measuring these
innovations.
Innovation processes can differ between the private
sector and the public sector. In the public sector, the
three principles often interact and all three may
have an impact on how innovations develop. For
example, the Australian Department of Industry
has an online feasibility test for innovations in the
public sector. One of the questions (No. 9) asks the
responder to estimate the importance of political
support for an idea to be feasible. Another
question (No. 14) regards the feasibility of the idea
in relation to the budget cycle, planning cycle and
election cycle. Both these examples show how the
principle of democracy is of importance, not only
the principle of a welfare state.
.
5
In contrast to the private sector, innovation support
in the public sector needs to include the political
level and public transparency.
Innovation support must be aware in its design that
innovations as outcomes may take place in relation
to all three principles, but also that the three
principles may be in conflict with one another.
Hence, innovation support may take on different
forms to support different processes.
Jensen et al. (2007) developed and operationalized
the concepts of STI and DUI within the framework of
the private manufacturing sector. In order for the
concepts to reach their full potential in public sector
research, they too, must undergo the double translation.
STI may take different forms in the public sector as
compared to the private sector. R&D is a fundamental
in STI, but very scarce in both service sectors. The
concept of STI must therefore undergo the double
translation. For example, STI innovations associated
with democracy or reechtstaat (the legislation
process) may differ from these which are associated
with welfare production. This is a simplified example,
and will need further investigation.
Concerning DUI, we should expect to find both
similarities and differences in innovation as outcome,
innovation process and innovation support in the
private and public sector. One reason why we might
encounter similarities is that DUI occur at the
workplace level where the institutional context is less
important to the work process. However, in the public
sector, the three principles can affect DUI at the
workplace level. For example, two principles come to
the fore when a school bureaucrat is expected to treat
students equally and make decisions with legal
certainty (rechtstaat) and, at the same time, to attract
new students (welfare state). Having to navigate the
two principles affects which innovations can be made
(innovation as outcome) and how the innovations are
made (innovation process).
Concluding remarks
The analytical model presented here was a useful tool
for finding inconsistencies in, and distinguishing
analytically between, innovation as outcome,
innovation processes and innovation support. As a
result, we were able to see how innovations were
developed and how innovativeness was supported in
the PIMM case.
The analytical model demonstrated how STI
processes and DUI processes were connected to
different kinds of innovation support and produced
different outcomes. Drawing on the model, we can
conclude that ‘trickling down’ will not work, i.e.
innovation support aiming for STI innovation will not
automatically lead to DUI innovation. The design of
6
J. NÄHLINDER AND A. F. ERIKSSON
innovation support must take the differences between
DUI and STI into consideration in order to be effective.
The analytical model raises new questions for further
research in this area and stresses the importance of a
double translation of STI and DUI. It raises questions
about the impact of conceptualizations originally
developed for the private sector and it highlights the
need for the development of concepts specifically for
innovation in the public sector.
The question about what differentiates innovation
in the public sector from innovation in the private
sector still remains. In fact, two questions need to be
addressed:
.
.
What characterizes different STI and DUI processes in
the public sector? Public sector STI and DUI
processes need to be studied as innovation
processes. It is also important to discuss how STI
and DUI processes in the public sector are
operationalized and measured.
How do STI and DUI processes in the public and private
sector differ, and why? Are there specific conditions
in the public sector that hinder or facilitate STI and
DUI?
Our suggestions for further research include crossfertilizing academic research fields. The field of
workplace learning could deepen our understanding
of DUI and support systems. A possible avenue for
supporting DUI processes is to enhance the
conditions for workplace learning (Ellström, 2010;
Evans et al., 2015; Fuller et al., 2004; Gustavsson,
2009). This support is not easily arranged since
innovation activities are not separate processes but
part of everyday work (Ellström, 2010; Høyrup, 2010).
Such indirect support will have an impact not only on
the innovativeness of employees, but also on the
learning environment in terms of distribution of work
tasks, work place culture etc. This needs a broader
perspective on innovation support that cannot be
easily packaged or communicated, as, for example, an
R&D project.
Finally, more studies are needed in different parts of
the public sector. Since the public sector has to follow
principles that are not used in the private sector, this
should also be mirrored in their innovations
something which needs to be empirically and
theoretically grounded.
The analytical model presented provides a framework
for simultaneously capturing different aspects and
modes of innovation. Further, by introducing the three
principles, it is very clear that innovation can be
qualitatively different in the public and the private
sectors. The differences between the public and the
private sector are complex and cannot be analysed
and understood in their entirety. However, by using
the analytical distinctions developed and presented in
this paper, the most important differences become
clearer. Mainstream innovation research must be
translated into the public context, otherwise
innovation policy will be both ineffective and counterproductive.
Acknowledgement
This article was made possible through a grant from VINNOVA
(No. 2014-00908): the Swedish National Innovation Agency.
Impact
For public sector innovation support to be effective,
organizations must be aware of what types of
innovation they want to support and the nature of
the innovation processes. This paper provides a
model which will help public sector organizations
begin to do this.
Notes on contributors
Johanna Nählinder is a Senior Lecturer in the Division of
Project Innovation and Entrepreneurship (PIE), Department
of Management and Engineering, Linköping University,
Sweden.
Anna Fogelberg Eriksson is a Senior Lecturer in the Department
of Behavioural Sciences and Learning at Linköping University,
Sweden.
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