„Management and Business Administration. Central Europe”
Vol. 23, No. 2/2015: p. 61–91, ISSN 2084-3356; e-ISSN 2300-858X
Towards Behaviorally Informed Public Interventions
Karol Olejniczak1, Paweł Śliwowski2
Primary submission: 04.02.2015. Final acceptance: 27.04.2015
Abstract
Purpose: This article informs readers about the theoretical and practical origins of the behaviorally
informed interventions (BIPI), analyzes examples of the BIPI from different policy sectors and
strategies they offer for policy and regulatory design, and discusses applications and implications
of BIPI for public interventions
Methodology: This paper is based on a review of literature, as well as an inspection of administrative practices in OECD countries. It encompasses a systematic analysis of scientiic papers from
the SCOPUS database and a query carried out at the library of George Washington University.
Findings: The traditional approach to public policy research is based on rational choice theory. It
offers limited support, because by assuming perfect rationality of policy decisions, it overlooks
existence of systematic errors and biases of human decision-making. The authors argue that behaviorally informed public interventions (BIPI) might contribute to improving the effectiveness of
a number of public measures – regulation, projects, programs, and even entire policies.
Practical implications: The behavioral approach allows decision-makers to better understand the
decisions and behaviors of citizens, as well as to design more effective interventions with minimum
effort by adapting the existing solutions to real decision mechanisms of citizens.
Originality: By combining the concepts of traditional approach with the growing behavioral
approach, the authors aim to propose a new theoretical framework (BIPI) to be used as a tool for
policy design, delivery and evaluation.
Keywords: heuristics, biases, behaviorally informed interventions, NUDGE, THINK, STEER, MINDSPACE, public policy design, public policy evaluation
JEL: D03
University of Warsaw Correspondence address: University of Warsaw, Centre for European Regional and Local Studies, Krakowskie
Przedmieście 30 St., 00-927 Warsaw, e-mail: k.olejniczak@uw.edu.pl.
2
University of Warsaw Correspondence address: University of Warsaw, Centre for European Regional and Local Studies, Krakowskie
Przedmieście 30 St., 00-927 Warsaw, e-mail: p.sliwowski@uw.edu.pl.
1
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Introduction
Public interventions are intended to shape the economy and society in desirable ways
(Shair, 2013a, p.1). They are responses of decision-makers to emerging socio-economic
problems and challenges. Interventions are designed to trigger certain change mechanisms that, in turn, should lead to expected effects. In a complex world, it is “a trial
and error, problem-solving process” (Bardach, 2006, p. 350) that depends on an in-depth
understanding of the problem in question and the context of policy and human behavior, since behaviors are usually the drivers of change mechanisms. In policy analysis
jargon, this is called “unpacking [the] black box between policy input and its outputs”
(Astbury and Leeuw, 2010).
The understanding of effective policy mechanisms can be developed through the use
of research indings – empirical studies, evaluations of public interventions, and
regulatory impact analyses. This practice has been developing in public administrations across the world as „evidence-based policies” (Davies et al., 2009; Saussois, 2003;
Shillabeer et al., 2011; Yanow, 2007). The European Union and the OECD have been
strongly promoting it as a good practice (OECD, 2007).
Unfortunately, the traditional approach to public policy research, based on rational
choice theory, does not offer a reliable explanation for the real mechanism that determines the effects of public interventions. It assumes that people have an unchanging
set of preferences; they are guided by personal utility and make insightful, well-calculated decisions based on prior careful planning (Amadae, 2007). The latest empirical
indings of cognitive psychology reveal that these assumptions do not match reality
(Kahneman, 2013b). Actual behaviors are the result of heuristics and “rules of thumb”
that can lead to systematic errors and biases. Choices can be constructed rather than
elicited by social situations (Sunstein, 2000, p. 1–10). Those indings seem to be universal in different socio-economic and institutional contexts. Therefore, a new approach
to research on public intervention is needed.
This emerging approach to policy analysis is called „applied behavioral science”
(Kahneman, 2013a, p. ix). By combining cognitive psychology with sociology, law and
economics, it offers promising insight into the real decision-making of addressees of
the interventions.
This new approach has already had an impact on practice. Administrations of the
United States, United Kingdom, Denmark, The Netherlands, and France have been
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successfully experimenting with Behaviorally Informed Public Interventions (BIPI)
(Lunn, 2014, p. 25–38).
However, this approach is still in its early stages of development, and it suffers all the
shortages typical of early stages of idea development. Although there is an abundance
of promising examples of uses of this approach, an overview of the practice is missing.
Moreover, some researchers criticize this approach by claiming that there is a lack of
robust evidence on the effectiveness of nudging strategies. In this view, contrasting
with Kahneman’s assertions, the ‘slow thinking’ (the analytical mode) allows citizens
to take more accurate decisions (Osman, 2015). The approach also lacks a consistent
body of deinitions that could be applied to different types of interventions (project,
programs, regulations) and a coherent, interdisciplinary methodology. It is developed
only for certain ields, e.g., regulations. Behavioral interventions are often portrayed
in a simpliied and stereotypical way – as a tool with a magical button for manipulating
citizens (Mitchell, 2005). Finally, there is a dearth of systematic discussion on what
implications this approach will have for the practice of public interventions.
This article aims to contribute to the emerging discussion on the use of Behaviorally
Informed Public Interventions (BIPI). It: (1) informs readers about the theoretical and
practical origins of the behaviorally informed interventions, (2) analyzes examples of the
BIPI from different policy sectors and strategies offered by them for policy and regulatory
design, and (3) discusses applications and implications of BIPI for public interventions.
The authors argue that behaviorally informed public interventions (BIPI) might contribute to improving the effectiveness of a number of public measures – regulation,
projects, programs, and even entire policies. Just as with any new approach, however,
it is not free from unknowns and challenges, which should be the subject of pilot
studies and a serious discussion in the context of national public policy.
This paper is based on a review of literature3 pertaining to public policies and on applied
behavioral research, as well as an inspection of administrative practices in OECD
countries. It encompasses a systematic analysis of scientiic papers from the SCOPUS
database, a query carried out at the library of George Washington University and
participation in lectures held at the International Simulation and Gaming Association
at the University of Delft.
The authors would like to express their sincere appreciation to the Polish Agency for Enterprise Development that sponsored the literature
review. The research results were primarily presented in book chapter: Olejniczak, K. and Śliwowski, P. (2014). Nadchodzi rewolucja? Analizy
behawioralne w interwencjach publicznych. In: A. Haber and K. Olejniczak (eds.), (R)ewaluacja 2. Wiedza w działaniu. Warszawa: Polska
Agencja Rozwoju Przedsiębiorczości.
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The structure of the paper is consistent with its three main objectives. The irst part
outlines the genesis of the behavioral approach and the main indings of the psychology
of decision-making that form the cornerstone of this approach. The second part presents
examples of the practical applications of behaviorally-informed public interventions,
as well as a summary of behavioral strategies suggested for public programs and regulations. In the inal section, the authors examine the implications posed by behaviorally-informed public interventions for public policy practice, including evaluation.
Origins of Behaviorally Informed Interventions
Public authorities – central and local governments – implement public policies in order
to address important socio-economic problems and take advantage of numerous development opportunities available in the country (Hausner, 2008, p. 46–50; Chrabąszcz and
Zawicki, 2014).
Public interventions are the main tool of public policy (Tucker, 2005; Howlett, 2011).
They take on various forms – from small local projects to substantial government
investment programs, from regulations that shape public space within our communities
to laws deining our rights and obligations towards the state. Public interventions relate
to various aspects of citizens’ lives – from education and health services, to security,
labor market, economy, infrastructure, and protection of cultural and natural assets.
Interestingly, the logic of public inluence behind this great variety of themes and
forms is relatively simple. According to Bemelmans-Videc (2007), it boils down to “carrots, sticks, and sermons”, which means that interventions are based on positive incentives and sanctions/prohibitions and on providing information/raising awareness.
Schneider and Ingram (1990) formulated a more extensive list of public policy tools,
namely: (1) tools based on authority (prohibitions, orders), (2) incentives, (3) capacity-building tools (information, education, training, etc.), (4) persuasion, and (5) learning
tools (tools allowing members of the public to experiment with different solutions
and, eventually, to ind their own optimal solution to a problem).
All of the above types of interventions have one thing in common. Their objective is
to encourage speciic types of behavior. As assumed by the initiators of an intervention,
i.e. the legislator, the local government etc., these shall bring the desired outcomes,
conducive to prosperity and social order (Datta and Mullainathan, 2012; Shair, 2013,
p. 1). Past experience shows that the effectiveness of interventions is contingent upon
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understanding the mechanisms of human behavior and decision-making processes
(Shair, 2013, p. 1). In other words, measures taken by public authorities will bring
better results if the initiators of interventions adapt their form and logic to the methods
applied by citizens in their decision-making processes.
In the currently predominant public policy paradigm, the behavior of intervention
recipients is predicted and interpreted through the prism of neoclassical economics,
i.e. the so-called rational choice theory. According to this theory, people are rational,
their decisions are based on their own interests, and they seek to maximize their beneits while minimizing costs (Amadae, 2007). When we translate these principles into
public intervention, we must assume that citizens and stakeholder groups who are the
recipients of interventions are mostly egotistic and will react to incentives or prohibitions in a rational and thoughtful manner, calculating proits and losses and weighing
all pros and cons (Low, 2011, p. 1–2).
It is clear from the above description and from our own experience that the model of
homo economicus is idealistic. In normal circumstances, we have limited time for quiet
relection and cannot afford to thoroughly relect on each action or choice. Furthermore,
when the options we face exceed a certain number and a particular level of complexity,
instead of a greater freedom of action, we feel overwhelmed – and, paradoxically, our
possibilities become narrower as a result of our cognitive limitations (Schwartz, 2004).
In fact, as indicated by Jones et al. (2013, p. 3) and Beggs (2013), our decision-making
models resemble more the type of reasoning we would associate with the cartoon
character Homer Simpson than with homo economicus. The behavioral approach
attempts, therefore, to infuse realism into the assumptions of the choice theory and
to bring them closer to the actual decision-making process and human behavior.
Theoretical foundations of behaviorally-informed public intervention can be traced
back to the 1950s and to Herbert Simon’s work dedicated to decision-making processes
in organizations (Simon, 1997). Criticizing the assumptions of classical economics,
he introduced the concept of “bounded rationality” to describe how decisions are
made. He also formulated the model of “satisfactory minimum,” arguing that, in fact,
we are satisied with simpler, satisfactory, and adequate solutions instead of looking
for the best solution (i.e. the optimum), as homo economicus would do (Simon, 1956).
Although the work of Herbert Simon has been internationally acclaimed (Nobel Prize
in economics), it has never gained ground in mainstream economics or in public
policy dominated by the Chicago School.
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A breakthrough came with the results of empirical research conducted by psychologists Amos Tversky and Daniel Kahneman, devoted to the mechanisms of human
decision-making in situations of uncertainty (Tversky and Kahneman, 1974). This line
of research in cognitive psychology has been developing rapidly since the 1970s. Its
most important indings can be summarized in two points.
The irst discovery is the “dual system theory”, according to which we use interchangeably
two modes of thinking when making decisions on a daily basis (see Kahneman, 2013b):
System 1 (fast, intuitive, level-one thinking) works automatically, with minimal
effort and, basically, without our conscious control. This system is based on
mental shortcuts – heuristics. They allow us to save time and energy. Nevertheless, they come at a price: they are inaccurate and can result in biases.
System 2 (slow, relective, higher-level thinking) allows us to make more informed
decisions. It is based on critical reasoning, but requires effort and attention.
These two systems operate interchangeably. Given the number of decisions we make
every day, our minds constantly face a choice between saving time and energy on the
one hand, and ensuring a greater precision on the other hand.
From the perspective of human actions, including response to public intervention, the
problem is not the very existence of the dual system of thinking, but rather our reliance
on the irst system in situations that require the use of the second (Leong, 2011, p. viii–ix).
Another important inding of cognitive psychology is that human mistakes in decisionmaking are systematic – we are fairly predictable in our bounded rationality (Ariely,
2010). Research in the past few years on decision-making processes has identiied
dozens of simpliication strategies and heuristics, as well as cognitive biases that result
from them. The Table 1 shows the four basic heuristics that cause our limitations in
evaluation and decision-making.
Name
Mechanism
Examples
Affect
heuristic
Table 1. Examples of heuristics
In economic theory, it is believed that
there is a positive correlation between
future beneits and the level of risk that
market participants are willing to accept:
When a sexual offense is committed by
a well-known and widely-respected person
(e.g. a famous ilm director), some people tend
to minimize the negative consequences
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Anchor heuristic
(anchoring
effect)
Representativeness
heuristic
Availability heuristic
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“the greater the potential gains, the more
risk I am ready to take”.
Experiences conducted by psychologists
indicate, however, that the opposite is
true. When making decisions and
evaluating a situation, we refer to our
emotions, experiences and instinctive
beliefs. If a particular action (person or
situation) brings up positive memories or
emotions, we tend to associate it with
lower costs and a lesser burden.
Conversely, negative associations with
an object or phenomenon lead us to
assume that its consequences will be
more negative.
of the offense and defend the accused
(the respect, admiration or other positive
emotions that they have had for the offender
inluence their assessment of the prohibited
act). A rebours, if a similar offense is
committed by a widely disliked person
(e.g. a populist politician known for his roguish
ways), members of the public are much more
severe in their judgement. Earlier negative
feelings towards this person make then judge
the person more scathingly.
When assessing the probability of certain
phenomena, we subconsciously rake our
memory for similar events from the past.
Our opinion is not based on objective,
statistically measured probability, but
rather on our capability to recall certain
phenomena. Therefore, our assessment
of the likelihood of an event is determined
to a large extent by very recent, wellremembered events, or those that
received extensive media coverage,
stirred up intense emotions, were widely
publicized and discussed, and thus
became imprinted in our memory.
Tourist trafic usually diminishes in areas where
there have been recent terrorist attacks (even
though – with the exception of a few countries
– the threat of terrorism is incidental, we tend
to remember discussions and media buzz
around an incident, and are willing to change
travel plans). A good example is the impact of
recent events on tourism in Indonesia: after the
bombings at the start of the 21st century,
tourist trafic signiicantly decreased in this
part of Asia. The trend was later reversed,
following the popularity of the movie entitled
„Eat, Pray and Love,” whose main character
travelled in this region.
The same holds true for the subconscious fear
of a plane crash. Even though the probability of
a car accident is much higher, plane crashes
receive a lot of media coverage; they have also
been depicted in numerous movies. Therefore,
despite the fact that aircraft accidents are rare,
many people believe them to be a real threat.
We tend to believe that particular
phenomena, features of character or
objects are more likely to occur if they
remind us of the population they
represent.
This heuristic is the basis of the puzzles that
we referred to above: we are more likely to
believe that Stefan is a librarian, or that random
instead of successive numbers will be drawn,
because they are similar to the population that
we have had the opportunity to observe in our
lives.
If we are to assess the value of a feature
or determine the size of a group
(e.g. indicate how many of our neighbours
are unemployed), our assessment will be
quite different in two cases, i.e. when we
Anchor heuristic works even in situations,
in which we would not expect it. In an American
court experiment, it was found that
the punishment that the prosecutor requests for
the accused has an impact on the assessment
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Table 1 (Continued)
Name
Mechanism
Examples
are to suggest a value by ourselves
(without an anchor) and when an anchor
is provided (e.g. “Are there more than 20
unemployed or fewer?”).
In the latter case, our response will be
determined by the anchor value provided.
of guilt and on the sentence (which means that
the more severe the punishment requested by
the prosecutor, the greater the probability that
the jury will be convinced of the defendant’s guilt).
Another experiment showed how this heuristic
impacts boxing judges. A group of judges were
shown three rounds of a boxing match and were
asked to guess which contestant won. In the
irst version, the judges were shown the match
in a sequence in which player A was in top form
during the irst round, landing more punches
than his opponent. In the second version, the
sequence was arranged so that the ight began
with player B landing more punches. The inal
verdict was determined by a version that was
shown to the judges. When counting the blows in
subsequent rounds, the judges probably referred
to the anchor, i.e. the situation in the irst round,
and were more likely to attribute more points to
the boxer whose initial
performance was better.
Source: own study based on Baumeister and Vohs (2007) and Tyszka (2010).
Therefore, heuristics are subconscious cognitive strategies, insights, and mental shortcuts founded on our previous experience or observations. Heuristics induce us into
cognitive biases, which have a direct impact on our actions. These are the elements
that creators of behaviorally-informed public interventions strive to inluence. The
Table 2 presents several examples of biases from everyday life.
Table 2. Examples of cognitive/decision errors
Name of
cognitive bias
Bias mechanism
Hyperbolic
discounting
Most of us prefer instant proits that do not require waiting. We are therefore more
inclined to make decisions that will bring immediate beneits, even if putting certain
operations on hold or taking a different course of action would yield higher proits in
the future (e.g. the majority of US lottery winners opt for the immediate payment
of winnings, even if the amount is usually up to 50% lower compared to payment
in installments over the course of several years). This can be deined as “a-bird-inthe-hand-is-worth-two-in-the-bush” approach.
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Status
quo bias
We do not like change. We accept the status quo, even if changes could bring us
greater proits or result in other beneits. We prefer to stick to what we know until
faced with a strong incentive to act. Many of us believe that “the better is the
enemy of the good”. Therefore, we usually stick with our default settings
(e.g. every adult Pole is a potential organ donor unless he/she expressly objects to it).
Sunk costs
effect
When we buy a public transport pass valid for a long period of time, we are more
willing to use this means of transport – we feel that we have incurred costs and
wish to rationalize the expense, i.e. get the best return on investment (e.g. taking
buses more often than would normally be necessary). In traditional economic theory,
incurred costs do not affect decisions and only future expenses count.
Procrastination
(inertia)
We often postpone taking action, making decisions, expending efforts. Many
of us take the initiative only when faced with external pressure. An example are
thousands of declaration of Poles who wished to remain in the OFE system, which
were sent to the Social Insurance Company after the deadline.
Loss aversion
bias
We are afraid to risk losing what we have, even if it could bring sizeable beneits.
Studies show that discomfort due to a loss is twice as powerful as the pleasure
we feel after we have gained something.
Myopia
When making decisions about the future, we usually subconsciously reduce future
costs associated with these decisions (e.g. the burden of the interest that we would
need pay when taking out a long-term loan). We are so eager to get the desired
effect that we fail to take into account all possible future consequences.
Overoptimism
When thinking about our future actions, we tend to retain an overly optimistic
prognosis, e.g., we think that we will never overdraw our credit card or will always
pay the overdraft off on time. Another example is the tendency to buy clothes that
are a size smaller assuming that we will exercise regularly and keep a strict diet,
and will therefore become itter.
Conformist
biases:
“herd
behavior”
the effects of
social norms
In many situations, we behave differently depending on whether we are alone or
in a group. In the latter case, we generally adapt to the group’s behavior and we tend
to conform to others. When we make a decision, the awareness of what the majority
of our neighbors or family members would do is likely to convince us to act in
a similar manner. The most glaring examples are experiments in which participants
are asked to evaluate a situation (e.g., to compare the length of two pencils). While
some of them provide their answers spontaneously, several members of the group
follow the instructions of the researchers (e.g. instead of expressing their personal
assessment, they deliberately mislead others). Research have proven that we tend
to adapt our own opinions to those expressed by others, even if it means formulating
judgments that are against our actual observations. These mechanisms have been
used in political propaganda and in totalitarian systems.
Reciprocity
We are more willing to take action if we have been or can be beneiciaries
of a similar situation (e.g. lend money to a friend who has done a similar favor
for us). This rule can also apply in future situations: we will be more inclined to do
something (e.g., help an elderly person cross the street or carry their shopping
upstairs), expecting that we might need this kind of help in the future (for this
reason, middle-aged people are more likely than teenagers to give their seat to
an elderly person on the bus, as for teenagers the prospect of being in a situation
where they will need a similar favor is much further and less real).
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Table 2 (Continued)
Name of
cognitive bias
Bias mechanism
Conirmation
bias
When making choices or assessments on the basis of a great wealth of information,
data and evidence, we tend to rely on our intuition, convictions or prior knowledge.
This mechanism works clearly in the process of shaping and maintaining
stereotypes and prejudices, for instance with respect to other ethnic groups
or nationalities. The fact that prejudices are not merely the result of a lack
of information or knowledge, but result from innate thinking mechanisms makes
them dificult to eradicate.
Framing
effects
Our decisions and assessments tend to vary depending on the manner in which
alternatives are presented to us, or on the kind of information that we are provided
with. Research carried out in different countries and various cultural contexts
regularly conirm the existence of this effect in situations where patients must
decide on a therapy. Their decision tends to be inluenced by the manner in which
the consequences of a therapy are presented to them. For instance, if a patient
is told that a drug or a medical procedure has proven effective in 80% of cases,
he/she is more likely to choose this option than when – in the same situation
– they are told about that the treatment proved ineffective in 20% of cases.
Source: own study based on Baumeister and Vohs (2007), Frederick, Loewenstein and O’donoghue (2002), Groome
(1999), Ly, Mazar, Zhao and Soman (2013), Peng, Li, Miao, Feng and Xiao (2013) and Tyszka (2010).
This long list of decision-making mechanisms that distinguish a real person from the
idealized model of homo economicus can be categorized in three main groups (Jolls
et al., 2000, p. 14–16):
1) bounded rationality – simplifying heuristics and biases in assessing probability
and value;
2) bounded willpower – tendency to take actions that, in the long term, are likely
to prove disadvantageous;
3) bounded self-interest – making decisions founded on a sense of justice or on
cultural norms instead of striving to maximize one’s optimum outcome.
The above three constraints have practical implications for lawmaking processes and
designing public intervention. The irst constraint will prove consequential when
decisions are made in situations of uncertainty (assessment of probability) or when
the expected results are deined. The second will have an impact on decisions with
future consequences. The third will come into play in situations where the actions of
one of the parties are clearly inconsistent with conventionally acceptable behavior in
a given situation. In the latter case, other participants of the social interaction are
willing to bear the cost of punishing unfair behavior.
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Behaviorally Informed Public Interventions in practice
Cognitive psychology concepts have dynamically spread onto other ields and they have
also – albeit with a certain delay – impacted public policies. Interestingly, in 2005, a group
of researchers from prestigious American universities (Harvard, MIT, Princeton, Yale)
expressed their frustration with public policymakers reluctant to apply valid indings
of behavioral psychology as evidence and a source of inspiration in their domain; instead,
policymakers base their decisions on classic economic theories (Amir et al., 2005).
Four years later, the irst major changes in this area began to unfold. The main proponents of this approach were legal scholar Cass Sunstein and economist Richard
Thaler. Together, they authored “Nudge” (Thaler and Sunstein, 2009) – a popular science
publication in which they outlined the application of behavioral psychology principles
in public policy. The book quickly became a bestseller and has received extensive
media coverage, mainly in the United States and the United Kingdom. American
President Barack Obama and British Prime Minister David Cameron have referred to
it during their public appearances. Both politicians hired the authors of the book to work
in their respective administrations, which gave impetus to the development of practical
applications of behavioral approaches in public management and public policy. The
nudging strategy is discussed in more details in the next part of this article.
In the U.S., behavioral analysis was applied in the U.S. Ofice of Information and Regulatory Affairs (OIRA), which has operated for nearly 30 years. Instruments provided
by the behavioral analysis were used for the purposes of review and evaluation of new
regulations. It aimed to simplify their structure and improve the eficiency of operations (Sunstein, 2013). In the UK, a new ofice was established: the Behavioral Insight
Unit, reporting directly to the Cabinet of the Prime Minister. This team is primarily
in charge of experiments and pilot projects, which aim to help in assessing the future
effects of the proposed policies (Behavioral Insights Team, 2012). At present, the Nudge
Unit operates as a joint venture of the British government and the NESTA foundation.
Know-how is sold to entities around the world (e.g., governments in Australia, Singapore
and the World Bank) and the team continuously embarks upon new projects, including
a spectacular social experiment (one of the most extensive in British history): a randomized controlled trial (RCT) performed on eight groups with a total number of more
than a million participants (Rutter, 2014).
The so-called “nudging” has been developing also in other countries. At the time of
writing this paper (autumn 2014), a European network of behavioral policies (the
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European Nudge Network) was under construction. It is to include researchers, scientists, public policymakers and experts from European countries interested in using
solutions provided by this innovative approach to public management. The European
network is based on the experience of the Danish Nudging Network, initiated by the
University of Roskilde, and the University of Southern Denmark. At present, the network
encompasses over 70 academic institutions, government ofices, local government
units and NGOs. Their goal is to share experiences and practical knowledge in order
to help improve the use of behavioral analysis in public policy. Local authorities in
Paris (Cappelli, 2014) and Berlin (Plickert, 2014) have shown interest in the use of
knowledge about the mechanisms of human decisions and choices for effective public
management.
The concept is relatively new and is based on a variety of intellectual inspirations (Jones
et al., 2013, p. 43), which results in a multitude of practices, but also in a lack of methodical, or even terminological, consistency. “The Behavioral Foundations of Public Policy”,
edited by Shair (2013b), is an attempt at creating a structure upon which to develop
this new ield.
In “The Behavioral Foundations of Public Policy”, authors representing different disciplines strive to combine the existing research results and translate them into a set
of guidelines for the design and implementation of public interventions (with emphasis
on legal regulations). They suggest that the new ield be called “applied behavioral
research”. In this article, we adopt an interdisciplinary perspective formulated by the
authors of the publication. In the conclusion, we endeavor to associate it with progress
in the ield of program evaluation, sociology, and user-centered design.
Examples of BIPI
In the previous sections, we described in a synthetic manner the basic assumptions
and indings of behavioral psychology and touched upon their potential use in public
policies. In this section, we shall outline selected applications of these research indings
for inluencing citizens, i.e. affecting their behavior and decisions in a manner that
would ensure their positive impact on individuals, families as well as on entire communities and society.
The term “Behaviorally Informed Public Interventions” (BIPI) shall be used to describe
projects, regulations, and programs that are based on the behavioral approach, i.e.:
1. Clearly deine the recipient-intervention user, and adopt his/her perspective;
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2. Recognize that the user, as well as intervention creators themselves, have cognitive limitations;
3. Limited rationality, willpower, and self-interest;
4. Apply corrective solutions or use cognitive biases and limitations of recipients
in their design of change mechanism;
5. Use pilot schemes, experiments and simulations to test these solutions prior
to applying them on a large scale.
The practices outlined below were carried out in different countries and political
regimes, and in various social, economic, and cultural contexts.
They have been selected so that the measures presented correspond, to a certain extent,
to the challenges facing our country and its institutions.
Each of these practices indicates a problem (to be solved through an intervention),
behavioral mechanisms applied, and the manner of inluencing them (theory of change).
Table 3. Examples of BIPI
Name of BIPI
Personalized
and
simpliied
letters to
taxpayers
who have yet
to pay their
taxes
Element
BIPI construction
Behavioral
model
Although the British have almost nine months to pay their taxes
(submitting a tax declaration, payment), many put this chore off
and end up failing to meet the deadline. This results in a double loss
for the state budget (the value of unpaid taxes plus the costs
incurred in order to send reminders and recover receivables).
Cognitive
bias
Procrastination (inertia)
Choice
architect
HM Revenue and Customs (HMRC) and the Behaviour Intervention
Team (BIT)
Theory
of change
IF we send procrastinating taxpayers a letter indicating that the
majority of their district’s population have already paid their taxes
(instead of the traditional, impersonal reminder), we will activate
the social norm mechanism and, CONSEQUENTLY, taxpayers will pay
what they owe to the Inland Revenue Ofice, which will generate
savings for everyone.
Effects
The test was conducted on two groups of approximately 700 payers.
The irst group received a traditional, impersonal reminder, while
each member of the other group received a personalized letter
indicating the number of taxpayers in his/her district who have
already paid their taxes. Where reference was made to social norms,
15% more people fulilled their duty. If HMRC had carried out this
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Table 3 (Continued)
Name of BIPI
Element
BIPI construction
campaign across the country, approx. GBP 160 million would have
been recovered faster and HMRC would have saved resources
allowing it to generate additional GBP 30 million per year.
Convenient
ordering
of healthy
meals
in a school
canteen
„Pure love
for
Copenhagen”
Source
(Hanks, Just, Smith and Wansink, 2012)
Behavioral
model
We eat unhealthy, calorie-rich foods not because we are not aware
of their adverse effects for our health. In many cases, we tend to
reach for unhealthy foods because they are more easily available,
and therefore their consumption is more convenient (the status quo
mechanism) and we derive immediate beneits from them (sweets
or other snacks with artiicial lavors are a source of pleasure
– immediate beneit). This makes us chose them instead of healthy
snacks (postponed beneit – better health in the longer term).
Cognitive
bias
The status quo bias, time preference, delay discounting
Choice
architect
Management of one of the high schools in New York, researchers
from Cornell University
Theory
of change
IF we provide students with a convenient distribution mechanism
of healthy meals in the school cafeteria, the status quo mechanism
will be activated and, CONSEQUENTLY, students will choose healthy
foods that are more readily available instead of those with a higher
calorie content (less accessible).
Effects
A “convenient” distribution line of healthy dishes was installed
in a school canteen for eight weeks (it was one of the two operating
lines). At that time, researchers measured the share of healthy
products among food purchased by students, as well as their
consumption (i.e. how many of the selected products were
consumed, and how many were left over). In another eight-week
period, researchers explored the selection and consumption
structure of healthy dishes when two traditional lines operated
in the cafeteria, making it easier to order less healthy foods. Following
the introduction of the “convenient” distribution line for healthy
meals, students consumed approximately 28% less unhealthy food
(in grams) as compared to the traditional system of distribution.
Source
(Hanks, Just, Smith and Wansink, 2012)
Behavioral
model
Residents of Copenhagen and tourists visiting the city have been
throwing more and more trash onto the streets instead of putting
it into rubbish bins. The city is drowning in street garbage (paper,
cans, bottles).
Cognitive
bias
Self-control problems (consciously behaving in a manner that
is harmful and undesirable)
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Choice
architect
City authorities in Copenhagen and private companies operating
in the city
Theory
of change
IF we show people the way to the trash bin in a simple, visible,
engaging and funny manner, for example by sticking bright green
footprints leading to a trash bin on the sidewalk, it will have an impact
on their emotional commitment, enhancing their desire to act and,
CONSEQUENTLY, they will be more likely to dispose of their rubbish
in the bin, and contribute to keeping the city cleaner, thus generating
savings in the local budget of funds allocated to street cleaning.
Effects
The experiment was carried out by a member of the Danish Nudge
Network, Pelle Guldborg Hansen, on a group of a thousand pedestrians
on the streets of Copenhagen. Among pedestrians who came across
colorful footprints leading to brightly marked garbage bins, approx.
46% more threw paper in the bin instead of disposing of it on the pavement.
Source
(Webster, 2012)
Behavioral
model
Although people know that climbing stairs is healthier than using
a lift or an escalator, they are more likely to choose the latter option,
as the reward for walking up the stairs (improved physical condition,
health), is deferred with respect to the advantages of using the lift
(faster, easier, more convenient way of getting upstairs).
Cognitive
bias
Time preference, delay discounting
Choice
architect
Volkswagen Foundation
Theory
of change
IF users are provided with an extra incentive, i.e. an immediate
reward for the use of stairs (fun, the joy of generating sounds
by climbing the stairs), the effect of preferences associated
with immediate beneits (using the lift) will be minimized and,
CONSEQUENTLY, the likelihood of using the stairs will be increased,
resulting in more physical activity for subway users, as well as
reduced electricity costs for the operator.
Effects
The experiment conducted by the Volkswagen Foundation at the
Odenplan metro station in Stockholm consisted of installing a stereo
system on the stairs and painting steps to make them look like piano
keys. When walking up the stairs, passers-by would “play” music.
During the experiment, 66% more people took the stairs.
Source
http://www.rolighetsteorin.se/
Behavioral
model
Physical activity is getting more and more popular. Most of the
people train to gain long-lasting positive effects for themselves
– lose weight, gain better health or shape their bodies. As a result
they choose individual training in itness centers or individual
running schemes. Some of the NGOs started to think about how
to change those egoist motivations into altruists one.
Piano stairs
(Fun Theory)
Siła koloru!
Colors power
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Table 3 (Continued)
Name of BIPI
Managing
Trafic
Congestion
in Singapore
Element
BIPI construction
Cognitive
bias
Time preference, delay discounting
Choice
architect
AkzoNobel, Rak’n’Roll Fundation
Theory
of change
IF we offer people an instant award for their physical activity (each
minute of individual workout in the open air itness facilities results
in 0.77 liter of color paint donated for Oncology Centre in Warsaw)
and include the competition/fun factor (who can donate the most),
it will have an impact on their emotional commitment, enhancing
their desire to act and, CONSEQUENTLY they will be more eager
to change their training attitude and have one workout for altruist
reasons helping to collect paint for refurbishment of Oncology
Centre in Warsaw.
Effects
Organizers planned to collect 200 liters of color paint; instead, they
have collected more than 800 liters. The most active participant
of the game performed 2,5 hours of training.
Source
Siadkowski (2014)
Behavioral
model
When people are charged once for using public roads regardless
of the number of times they use roads (ixed price) the sunk costs
effects pushes them to use roads as often as possible without
thinking on the rationality of their actions (e.g. they use cars in rush
hours when they could actually wait till off-peak time).
Cognitive
bias
Sunk costs effect
Choice
architect
Ministry of Transport Singapore
Theory
of change
IF we change the ixed charge for roads with the pay-when-you-use
scheme, THEN we will overcome the sunk cost effect and strengthen
the hyperbolic discounting effect, people will try to avoid the places
and hours in which it will generate less immediate costs of using
public roads, and CONSEQUENTLY we will be able to minimize the
congestion in the Singapore.
Effects
The implementation of the ERP has generally reduced the trafic
volumes in the Central Area during the peak hours and off peak
hours by about 7–8% as compared to the previous system.
Source
(Yap 2005; Wai Yan Leong and Yii Der Lew, 2011)
Source: own study.
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Strategies for policy and regulatory design
The growing popularity of the behavioral approach in public policies has resulted in
a number of comprehensive strategies targeting the most common cognitive biases.
Some authors refer to them as behavioral change principles (Thaler et al., 2013). They
are sets of tips for “choice architects” – designers of public interventions. These rules
usually have the form of catchy mnemonic shorthand messages, organizing the main
methods of inluencing citizens’ decisions.
Undoubtedly, the most widely used and commented-on set of rules is NUDGE, developed by Sunstein and Thaler. The term perfectly captures the philosophy of this
behavioral strategy – to inluence and to lead the citizen towards the desired patterns
of behavior and choices (considered optimal by the regulator), while granting the
citizen the freedom to decide. Sunstein himself explains this rule with a simple example:
„Putting fruit at eye level [to attract attention and hence increase likelihood of getting
chosen] counts as a nudge. Banning junk food does not.”
The word “nudge” is an acronym for the main rules governing behavioral measures
in public regulations (Thaler et al., 2013). It is a simple set of rules (Thaler, Sunstein and
Balz, 2010):
iNcentives – create a system of incentives;
Understand choice mapping – understand the choice process;
Defaults matter – bear in mind the importance of indolence and negligence
(we tend to minimize efforts, choose the path of the least resistance, and apply
solutions that are most readily available and “pre-installed”, and therefore
“default settings” are of key importance;
Give feedback – help people understand by providing them with feedback –
inform, warn against potential failures, praise for successes;
Expect error – remember that people make mistakes – an eficient system takes
it into account and minimizes the negative consequences of such errors;
Structure complex choices – remember that if more options are available, the
choice becomes more problematic. Try to simplify the possibilities instead of
multiplying options.
Another set of rules is MINDSPACE (Dolan, 2013, p. 197), based on the following
assumptions:
Messenger – people are heavily inluenced by who communicates information;
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Incentives – our responses to incentives are shaped by predictable mental
shortcuts, such as strongly avoiding losses;
Norms – we are strongly inluenced by what others do;
Defaults – we “go with the low” of pre-set options, have recourse to the readily
available and easiest solutions;
Salience – our attention is drawn to what is novel and seems relevant to us
and our lives, or essential for our future;
Priming – our acts are often inluenced by subconscious cues, impulses that
we are not always aware of;
Defaults (default) – the most common-use “factory settings”, we use the most
readily available and simple solutions;
Affect (emotions) – our feelings and emotional associations can powerfully
shape our actions;
Commitments (declarations) – we seek to be consistent with our public promises,
and reciprocate acts;
EGO – we are focused on ourselves, trying to act in ways that make us feel better
about ourselves and boost our well-being and self-esteem.
MINDSPACE is a more descriptive strategy: by showing the mechanisms and principles of our actions, it provides ample ground for choices in designing public measures.
NUDGE is rather a set of simple recommendations on what to do and how to do it in
order to succeed.
Both NUDGE and MINDSPACE focus on quick thinking and designing interventions
that will take into account the heuristics and will lead us – the citizens – towards
optimal choices.
Two other approaches, STEER and THINK, are founded on a completely different
impact and change pattern. They attempt to activate each citizen’s System 2: free
thinking, which means turning our attention towards deeper relection. The names
of these approaches are not acronyms, as free thinking cannot be reduced to simple,
automated rules.
STEER is based on workshops during which participants learn how their brains operate, which raises their awareness of mental shortcuts used in everyday decisions.
STEER raises citizens’ awareness of their own limitations in decision-making processes and teaches them how to make important decisions in a more conscious way.
In short, it guides them towards making choices based on relection (Jones et al., 2013,
p. 177–182).
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THINK follows a similar path, but focuses on the process of shaping public opinion
and informed citizenship (John et al., 2011). In this approach, deliberation forms the
basis for overcoming cognitive errors and activating relective thinking. THINK postulates are enumerated as follows:
Let people understand the problem and acquire knowledge;
Create a platform for discussion, expression of thoughts and beliefs – when
discussing certain issues, we learn and change our views and attitudes;
Give people the opportunity to participate in the process they will co-create
and for which they will feel jointly responsible.
Thus, as opposed to NUDGE, THINK strategy involves intellectual engagement of
recipients in the discussion and, above all, refers to their beliefs, values and attitudes.
This strategy leaves no place for “libertarian paternalism”, but requires conscious and
partnership-based involvement of citizens in the process of deliberation on the direction
of social change. First experiences (though not as extensive as in the case of NUDGE)
indicate that THINK is a better strategy for inluencing the complex process of social
change with the participation of informed citizens (e.g., building social acceptance
and support for a low-carbon economy) (DEA, 2010). It is worth noting a signiicant
difference between NUDGE and MINDSPACE on the one hand, and STEER and THINK
on the other hand. The irst two strategies impact the environment of citizens and
create conditions affecting choices, and thus “nudge” us towards choices that are
socially desirable and positive both for the individual and society (Thaler and Sunstein, 2009). Meanwhile, the two latter strategies focus on establishing an appropriate
institutional framework (in the broad, sociological sense of the term), which allows
a conscious, critical and active participation of citizens in decision-making (John et al.,
2011, p. 18–20).
Implications for policy and regulatory practice
The growing popularity of the behavioral approach in several OECD countries carries
serious implications for the planning and evaluation of public interventions. Six key
issues deserve attention:
1. The need to rescale public policy objectives from abstract social processes to
speciic users’ perspectives.
2. The need to introduce new notions and terms to the language of public intervention.
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3.
4.
5.
6.
Karol Olejniczak, Paweł Śliwowski
Modifying the tools for designing and evaluating interventions.
Pilot projects and public measure testing.
Examining the ethical aspects of the “psychological state”.
Testing the effectiveness of BIPI in the Polish context.
Rescaling public policy objectives
Schneider and Ingram (1990, p. 513–514) note that effective public policy tools must
depart from the theory of individual decisions, and focus on those aspects of actions
and their psychological determinants that can be inluenced and modiied. This means
that our approach to thinking about public interventions needs to be rescaled from
abstract social processes to the decision-making mechanisms of individual citizens.
To some extent, this approach is similar to the famous opinion expressed by Margaret
Thatcher: “There is no such thing as society: there are individual men and women,
and there are families. And no government can do anything except through people
(...)”. In the case of BIPI, it is not about denying the existence of the social dimension
of an individual (certain solutions explicitly refer to mechanisms related to living within
a social group). This is a utilitarian shift, related to policies rather than a philosophical
change of vision of society and the citizen’s place within the state.
For the designers of public interventions – decision-makers establishing the legal framework and oficials designing programs, projects, or regulations – this means the need
for more in-depth understanding of intervention recipients and adopting a user-centered design. In practice, it is the question of searching for and designing citizenfriendly solutions, referring to decision mechanisms and also to contexts that inluence
these decisions (e.g. understanding why fathers are willing to take a short parental leave,
yet are reluctant to look after their children over longer periods of time). This process
is more dificult and more complex than “adjusting the service to the customer”.
Failure to take into account the motivations of recipients may result in social protests,
as evidenced by the attempts to adopt the Anti-Counterfeiting Trade Agreement (ACTA)
in Europe, or the decision to lower the compulsory school age to 6 years in Poland.
Another consequence is a high risk of ineffectiveness of speciic solutions (e.g., fathers
being less inclined to take parental leave than expected).
In the ield of public programs and projects undergoing evaluation, the perspective of
the “user” – that is, the recipient of interventions – have been taken into consideration
for a long time, although without particular focus on the “friendliness” of projects
from the point of view of applicants. However, from the perspective of legal regulations,
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this approach is very innovative. As noted by Sześciło (2012), Polish legal studies need
to build a bridge with contemporary management trends. These connections could
signiicantly enrich and improve the quality of the instrumental function of the law,
i.e. provide legal instruments necessary for effective public management.
The need to introduce new concepts to the language of public intervention
The behavioral approach requires expanding our public policy vocabulary with new
terms. We believe that the following are worth taking into account:
“Heuristics and cognitive biases” are the shortcomings of our decision system
and the effects of these shortcomings, which are predictable to a large extent.
Heuristics are simplifying decision rules used by our minds to save time and
energy. More often then not, they mislead us; as a result of cognitive biases,
we make decisions that are far from optimal, rational, and beneicial. Intervention creators must be aware of them – both with respect to themselves and to
intervention recipients;
“Models of behavior” explain human behavior in a particular situation, indicating the key factors, usually a combination of several cognitive biases and
contextual factors that determine our actions. They provide intervention creators
with information on factors that determine the behavior that is to be changed
through the implementation of public measures;
“Choice architects” is a new role for decision-makers creating the legal framework, oficials designing programs, projects or regulations. It means deliberately inluencing choices made by intervention recipients, based mainly on
persuasion stemming from knowledge about heuristics and models of behavior.
Choice architects construct the space around the recipient (both physical or
legal) and orient the latter towards the desired solution. At the same time, the
recipient is free to choose;
“Theory of change” also known as “the theory of change mechanism” is a speciic,
tailored method of changing the behavior of a given group of recipients. It is
a plan designed by a choice architect. It describes how, through which methods
and with reference to which cognitive limitations, we can inluence the recipient
of interventions in order to trigger the desired response and achieve the objective
of a regulation or a program, i.e. a change of behavior.
These terms are logically and practically interrelated. The easiest way to understand
them is to refer to the earlier BIPI example of personalized and simpliied letters to
taxpayers (see Table 3).
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Modiication of intervention design and evaluation tools
Logical models are commonly used in the current practice of public intervention
design and evaluation (usually programs and projects, much less often regulations).
They are the graphical illustration of the so-called “intervention theory”. The traditional
logical model is based on the following cause and effect sequence:
INPUTS allow ACTIONS that bring OUTPUTS, which generate RESULTS
and EFFECTS
Using this model to design and evaluate interventions, we assume an automatic transition from products to effects. For example, training provided to 20 people (OUTPUT
of a project) leads to their improved knowledge (expected RESULT) and, in turn, to their
employment (EFFECT).
In the behavioral approach to public intervention, this model needs signiicant modiications. The user’s perspective is adopted. We need to ask ourselves if the planned
outcomes will trigger the desired processes and behavior of recipients, which in turn
will bring the expected effects. This means that the traditional logical sequence needs
to be extended:
INPUTS allow ACTIONS that bring OUTPUTS, which trigger the CHANGE
MECHANISM that generates the EFFECT – a permanent change.
There needs to be an entire reaction chain between OUTPUT (providing training to
20 people) and the EFFECT (inding employment). Training participants should listen
to and understand trainers, internalize knowledge, put it into action, have the opportunity to prove their knowledge to the employer. The entire chain of events must be
included in the logical model, as the success of the project depends on the probability
of this sequence. Several proposals for the practical application of logic models in
behavioral approach have already been formulated by scholars (Olejniczak, 2014;
Olejniczak and Newcomer, 2014, p. 85–90; Pawson, 2013, p. 127–131).
Pilot projects and testing public measures
We have noted that the behavioral approach promotes user-oriented design. This
term has been borrowed from the ield of product development, based on a speciic
process technology. It usually follows this pattern: “Understand – Design – Test –
Modify” (Wendel, 2013). The cycle can be repeated several times, until the designer
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has managed to create a product that will prove intuitive and user-friendly in the subsequent test.
When applied to public policy, this approach brings two outcomes. First, there is
a clear shift of accents in the public policy cycle: from implementation, which used
to absorb most of our attention and energy, to planning and testing, i.e. designing
intervention. In the ield of evaluation, this means focusing on ex-ante evaluation,
although understood differently – not as a discursive process of modifying program
provisions, but as a critical, empirical veriication of a speciic behavioral change
theory applied in a given intervention. It seems that this may be an important ield in
which to improve Polish public programs. They tend to focus on a thorough diagnosis
of the current situation (usually in the form of descriptive statistics and main trends)
to indicate the direction of desired changes, but also all but disregard the mechanisms
that need to be triggered and factors that must be inluenced for these changes to
occur. Thus, programs often turn into a catalogue of demands rather than a clear
description of the logical sequence of actions to be taken in order to achieve a positive
change in society and the economy.
Second, this approach requires us to conduct tests, which allow the adaptation of the
original design (e.g., act, intervention, program) to actual behavior, motivation, and
decision mechanisms of intervention recipients. This approach enables us to determine
the following at a relatively low cost: which behavioral strategies are effective; what
should be changed or improved; and what are the shortcomings of the applied solution.
An example of such a test is the social initiative carried out in the UK to encourage
members of the public to register as organ donors. During the test, eight different
forms of incentives were applied in relation to eight groups of recipients; their effectiveness was then compared in order to determine which mechanisms best appealed
to citizens and encouraged them to register as organ donors.
At the technical level (i.e. the level of organization and research planning), experimental
research plans (randomized control trials) were applied in the majority of cases, followed
by quasi-experiments (comparison groups). These approaches provide very strong
evidence and are considered the gold standard of outcome evaluation methodology.
In some cases, very innovative solutions were applied (although already recognized
in social research methodology), namely simulations and games (Vermaas and Nieuwland, 2007). Their advantages are that they are much cheaper than experiments and
do not require extensive involvement of participants, they are not invasive, and they allow
for modiications of the solutions tested during the study – and, at the same time,
provide results that are nearly as reliable as the results of experiments (de Vaus, 2006).
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Examining the ethical aspects of the “psychological state”
An important implication of BIPI is the change of relationship between the state and
the citizen. In today’s complex and dynamic world, where knowledge about humans
and their limitations has been explored at the biological level, the issues of freedom
of the individual and respect for human rights are often emphasized in the context
of risks associated with the increasingly sophisticated methods of information control,
collection and processing.
In this context, the use of BIPI raises an important question – does it mean manipulating citizens? This issue has already been dealt with by showing the differences between
NUDGE and THINK. At the irst glance, the tool is very effective, but the instruments
resemble props from a ilm adaptation of George Orwell’s “1984”.
Consequently, the enthusiasm sparked by the irst positive results brought by the
application of this approach was followed by a number of less approving opinions of
those who referred to our freedom to be humans: fallible, weak, prone to mistakes.
And so, the debate revolves around the following questions: Are we witnessing the
birth of a psychological state? What are the consequences for the already highly asymmetrical relations between the state and its administration, and the citizen? Are we
moving towards the model of a state that manipulates its citizens? At present, it is
dificult to answer this question. However, arguments put forward by both advocates
and critics are worth analyzing. The topic should not be brushed aside – especially if
we take into account that, for quite some time now, private corporations have not
hesitated to explore it and use the possibilities offered inter alia by neuromarketing,
without any general regulations in place.
Testing the effectiveness of BIPI in the Polish context
Use of behaviorally-informed public interventions in the Polish context could make
a signiicant contribution to the development of management and public policy analysis
in Poland. We should note that attempts to explain the empirical effectiveness of
interventions through the prism of their recipients’ behavior (especially in the ield
of legal regulations) have been seldom explored by Polish researchers. Furthermore,
as evidenced by the above examples from other countries (e.g., solutions adopted in
Stockholm and Copenhagen), the introduction of the set of tools used in behavioral
analysis can encourage the public to explore complex issues of public management.
To put it colloquially, interesting pilot schemes and experiments are likely to sell better
than complex legal acts or intricate strategies.
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Conducting tests before shifting the systemic paradigm appears justiied for two reasons. Firstly, behavioral interventions have been carried out mainly in English-speaking countries. It is true that heuristics and cognitive biases are universal and we can
all fall into their trap, but their associations in speciic decision and behavior models
are context-sensitive. Examples from literature suggest that certain self-interest limitations have different incidence in different cultures. The question we need to answer
is whether all models of behavior and change mechanisms tested in the Anglo-Saxon
culture could work in a similar manner in the post-socialist context (we must not
forget that our heaviest baggage is an extremely low level of public trust).
Second, behavioral interventions are far from linear automatism. Human behavior is
the product of various factors that come together. A durable and effective behavioral
change usually requires constructing a “theory of change” (a mechanism) addressing
a number of cognitive biases (van der Linden, 2013, p. 210, 213). Scholars exploring
the subject have proven that a minor modiication of a single element may bring about
a great change. This is evidenced by the British experiment in which eight different
forms of incentives were used to encourage people to register as organ donors. It turns
out that it is not enough to appeal to one behavioral mechanism; instead, we need to
test which of the many mechanisms is the most effective in a given context.
Taking into account the above issues, we believe that the behavioral approach can be
tested in Poland in a relatively wide range of public interventions at different management levels.
Importantly, it can be used for both designing public interventions and explaining
their mechanism. The irst ield consists of projects and programs under the cohesion
policy. It seems that the “user’s perspective” and the “theory of change based on the
behavioral approach” are relatively easy to incorporate into the rich and advanced
evaluation research methodology, especially in the case of studies aimed at describing
the mechanisms that bring about certain effects of the intervention. It would be interesting to verify whether evaluations performed using the new approach provide a better
understanding of the usefulness of projects co-inanced by the EU, particularly those
that would have a direct impact on people (e.g., those associated with the activation
of the unemployed, preventing social exclusion or acquiring new competencies at
different stages of life).
Regulations and laws are another promising testing ield. They are currently subject
to regulatory testing and impact assessments. In this respect, quantitative tools of
economic analysis, including the cost-beneit analysis, play an important role. Good
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Karol Olejniczak, Paweł Śliwowski
examples from other countries (e.g., Singapore) have proven that expanding the traditional cost-beneit analysis with the behavioral approach is very valuable for those
public interventions in which citizens’ reactions and decision process are pivotal
(Low, 2011). In the case of Poland, yet another argument seems to be of great consequence. The strategic objective of the next edition of the Operational Programme,
dedicated to good governance, is to improve the quality of regulations (e.g., increasing
the transparency and accessibility of law to citizens). The behavioral approach, with
its philosophy of “user-friendly design” and choice architecture seems most propitious.
Regulations, projects, and initiatives aimed at space management – particularly urban
space management – are the third test area. The plethora of local initiatives and the
resilience of local governments open up many opportunities for testing innovative
solutions and replicating them elsewhere. It can be done with respect to local interventions, directly affecting residents. We know that Polish cities face numerous new
challenges: segregation, and disposal of waste, land development, use of public spaces
by local communities and the enforcement of local taxes. All of them can be inluenced
through Behaviorally Informed Public Interventions.
Conclusion
In the currently predominant public policy paradigm, the behavior of those targeted
by public interventions is predicted and interpreted through the prism of neoclassical
economics, i.e. the so-called rational choice theory. The design and evaluation of
public interventions is inluenced by the assumptions that people are rational, their
decisions are based on their own interest, and they seek to maximize their beneits
while minimizing costs. However, indings from recent breakthroughs in cognitive
psychology indicate that human decisions are impacted by heuristics and cognitive
biases. These indings are of key importance for public policy, as they help explain and
predict actual human responses to regulations and public programs.
Psychological research indings are increasingly applied in practice. The new approach
is referred to as “applied behavioral science”. Speciic projects, regulations and programs based on this approach are called “behaviorally informed public interventions”
(BIPI). They can be characterized as follows:
1. They clearly deine the recipient-intervention user, and adopt his/her perspective.
2. They recognize that the user, as well as intervention creators themselves, have
cognitive limitations.
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3. They refer to limited rationality, bounded-willpower and self-interest.
4. They apply corrective solutions or use cognitive biases and limitations of recipients in their design of change mechanism.
5. They use pilot schemes, experiments and simulations to test interventions
(including regulatory solutions) prior to applying them on a large scale.
Examples of such measures discussed in this article prove their high value for those
in charge of designing public policies. The behavioral approach allows decision-makers
(Leong, 2011, ix; Low, 2011, p. 5–6) to:
Better understand the decisions and behavior of citizens, e.g., their actual
everyday reactions to legal regulations and solutions implemented by public
administration.
Become aware of their own limitations, because public policymakers and those
who design regulations are also subject to the rules of inference and to cognitive errors.
Design more effective interventions with minimum effort by adapting the
existing solutions to real decision mechanisms of citizens.
As noted above, the BIPI cannot be regard as a ‘magic wand’ that will allow policymakers to change people’s behaviors and exert limitless inluence on their decisions.
Rather, this is a potentially effective tool to enrich the public policy process (from
formulation through implementation to analysis) with the broader perspective of ‘real
people’ instead of excessive reliability on the Weberian ‘ideal type’ (Idealtypus). It
should be, then, seen as another source of fruitful knowledge to be integrated with
those utilized previously. There is still much to be done in the course of building
a coherent and systematic approach, but the growing body of international experiences
allows us to look at those challenges with optimism while avoiding common biases
of over-optimism or myopia).
BIPI has no intention to eradicate the transparency of public or political actions, civil
education, dialogue, public deliberation or common responsibility that constitute the
basis of modern democracy. Remaining sensitive to any attempts to use this approach
in a manipulative manner, we should bear in mind that vivid public and academic
debate on the work of Kahneman, Sustein and Thaler provoked one of the most valuable
discussions on human decision-making processes in recent times. It allowed us to
critically reconsider some of the fundamental questions about human actions in individual and social contexts.
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