Transportation Research Part D 41 (2015) 288–305
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Transportation Research Part D
journal homepage: www.elsevier.com/locate/trd
Behavioural economics, travel behaviour
and environmental-transport policy
Marta Garcia-Sierra a,⇑, Jeroen C.J.M. van den Bergh a,b,c, Carme Miralles-Guasch a,d
a
Institute for Environmental Science and Technology, Universitat Autònoma de Barcelona, Edifici Z – ICTA-ICP, Cn-Campus UAB, 08193 Bellaterra, Barcelona, Spain
ICREA, Barcelona, Spain
c
Faculty of Economics and Business Administration, and Institute for Environmental Studies, VU University Amsterdam, Amsterdam, The Netherlands
d
Department of Geography, Universitat Autònoma de Barcelona, Barcelona, Spain
b
a r t i c l e
i n f o
a b s t r a c t
The transport sector creates much environmental pressure. Many current policies aimed at
reducing this pressure are not fully effective because the behavioural aspects of travellers
are insufficiently recognised. Insights from behavioural economics can contribute to a better understanding of travel behaviour and choices, and the impact of these on policies.
Nevertheless, few studies have examined this issue. We review these and provide a
broader, more encompassing perspective on environmental policy focused on transport,
and taking into account bounded rationality as well as social preferences.
Ó 2015 Elsevier Ltd. All rights reserved.
Article history:
Keywords:
Behavioural economics
Environment
Sustainability
Transport policy
Travel behaviour
Introduction
Key challenges in attaining sustainable urban travel behaviour include physical-infrastructural, technological and behavioural issues. There is an ever growing number of studies noting that a transition to sustainable mobility is unlikely if technological improvements and changes in the built environment are not combined with behavioural change (Avineri, 2012;
Metcalfe and Dolan, in press; Steg and Vlek, 2009). Many studies have tackled these issues focusing on particular policy
strategies (e.g., physical planning and infrastructure supply, pollution standards, pricing mechanisms and information provision), but have in most cases assumed representative, rational agents. However, behaviour of travellers is heterogeneous
while their preferences are inconsistent (Anable, 2005; Barr et al., 2011). Moreover, socioeconomic factors are insufficient to
explain observed differences in behaviour.
Transport reality is often best described by behavioural approaches. They have already received some attention in recent
studies on travel behaviour. Two themes of behavioural economics are encountered in travel studies. One is bounded
rationality, addressed mainly by applying Prospect Theory to travel time uncertainty and interpretations of expected travel
time, which is relevant to valuation exercises in project appraisal, notably understanding WTP/WTA differences in estimating the value of time savings (Avineri and Bovy, 2008; Batley, 2007; van de Kaa, 2005, 2006; Schwanen and Ettema, 2009).
Several empirical studies aim to improve demand management by using real-time information about travellers in transport
networks (Avineri and Prashker, 2003; van de Kaa, 2008; Nakayama and Kitamura, 2000). This is of importance to
re-distribute traffic and reduce congestion, which affects local air quality. Most of these studies adopt an experimental
⇑ Corresponding author. Tel.: +34 93 586 8773.
E-mail addresses:
(C. Miralles-Guasch).
marta.garcia.sierra@uab.cat
http://dx.doi.org/10.1016/j.trd.2015.09.023
1361-9209/Ó 2015 Elsevier Ltd. All rights reserved.
(M.
Garcia-Sierra),
jeroen.bergh@uab.es
(J.C.J.M.
van
den
Bergh),
carme.miralles@uab.cat
M. Garcia-Sierra et al. / Transportation Research Part D 41 (2015) 288–305
289
approach within controlled settings so that the effects of targeted factors can be analysed in isolation. Insights are then used
to improve demand modelling.
A special issue within this theme of bounded rationality of travellers is that of habitual behaviour (Bamberg et al., 2003;
Bamberg and Schmidt, 2003; Gardner, 2009; Klöckner and Matthies, 2004; Thøgersen, 2006; Verplanken et al., 1998). Habits
reflect time-inconsistent preferences that lead to seeking immediate rewards. Most daily travel choices are largely habitual
and automatic, involving low information processing (Verplanken et al., 1997). Habitual travel behaviour violates rational
choice principles through the absence of a process of cognitive deliberation – involving preference formation, deliberate
information processing and preference-based choice (Gärling et al., 2001).
The second theme is social preferences, which include altruism, fairness, norms, reputation and status seeking concerns.
Social preferences have received most attention in studies explaining modal choice (Abrahamse et al., 2009; Anable and
Gatersleben, 2005; Johansson-Stenman and Martinsson, 2006; Sohn and Yun, 2009). There is a long history of applying social
psychology to travel studies dealing with the feelings of moral obligation, perceived social pressure and control beliefs.
In parallel, behavioural economics has recently seen much application to environmental economics. This has given rise to
studies of sustainable consumption, voluntary cooperation in public goods like the conservation of natural resources or recycling, environmental valuation, and the implications of these for environmental and climate policy (for surveys, see Brown
and Hagen, 2010; Gsottbauer and van den Bergh, 2011; Jackson, 2005; Shogren and Taylor, 2008; and Venkatachalam, 2008).
These studies support the idea that explicitly accounting for behavioural biases due to both bounded rationality and social
preferences, increases the understanding of complex environmentally-relevant behaviour, and so provides an improved
basis for environmental policy design.
The present study reviews empirical evidence on behavioural biases in travel choices (long- and short-term choices) and
their implications for environmental-transport policy. Van de Kaa (2008) and Li and Hensher (2011) offer a review of applications of Prospect Theory to transport policy, while Avineri (2012) and Metcalfe and Dolan (in press) offer broader surveys
of the implications of bounded rationality and social preferences for travel behaviour and policy. However, none of these
studies deals in detail with environmental policy issues related to transport, which is the focus of our review.
The remainder of this article is structured as follows. Section ‘Behavioural economics and transport’ offers a literature
review of insights from behavioural economics that are applicable to travel behaviour. Section ‘Lessons for
environmental-transport policy’ discusses policy implications and provides guidelines for environmental-transport policy
design. Section ‘Conclusions’ concludes the study.
Behavioural economics and transport
Behavioural economics
Behavioural economics merges the fields of economics and psychology to provide a better understanding of choice behaviour (Camerer, 1999; McFadden, 1999; Rabin, 1998). Realistic behaviour of individuals is often not well captured in traditional models of economic policy.
When choices are complex and involve probabilistic outcomes, individuals tend to use heuristics, establish false associations, or incur logical leaps due to mental shortcuts and calculation mistakes. These deviations from rational agent behaviour are due to imperfect information and individuals’ limited computational abilities. On the other hand, the way in which
alternatives are presented (i.e. framed) influences choices, as individuals tend to exhibit choice persistence or inertia, so as to
avoid possible losses, and make conservative choices when outcomes are framed as gains and risky choices when outcomes
are framed as losses. These biases are a consequence of the asymmetric valuation of gains and losses, loss aversion, and probabilities being weighted non-linearly. Hyperbolic discounting (i.e. overvaluation of the present over the future), myopic
behaviour, self-control problems and habit formation are due to immediate rewards being more heavily weighted than
future gains, thus denoting time-inconsistent preferences. Finally, individuals show limited self-interest (e.g., altruism
and fairness) and inter-dependency of choices due to social and self-identity concerns.
These biases create inconsistencies in behaviour that are generally classified under two broad categories, namely
bounded rationality, and social or other-regarding preferences (Gsottbauer and van den Bergh, 2011). Table 1 offers a summary of some of the various behavioural anomalies and systematic biases relevant to the transportation context.
Systematic behavioural biases have implications for policy design. Indeed, several authors have translated insights of
behavioural economics into general policy rules. Notable examples of this are NUDGE (Thaler and Sunstein, 2008) – a mnemonic for iNcentives, Understand people’s heuristics, use Defaults, Give feedback information, and Expect errors of judgement –, the seven principles from the NEF report (Dawnay and Shah, 2005) – use of normative incentives, commitments,
defaults, framing and heuristics, while taking into account habits and routines –, and MINDSPACE (Metcalfe and Dolan, in
press) – a Mnemonic for Incentives, Norms, Defaults, Salience, Priming, Affect, Commitment, and appeal to Ego –, the latter
being focused on travel behaviour and transport policy. A difference between this study and Metcalfe and Dolan (in press) is
that we provide a more complete review of the set of travel choices (short- and long-term choices) and associated insights
from behavioural economics, which result in lessons for environmental-transport policy.
Bounded rationality and Prospect Theory
JUDGEMENT ERRORS: imperfect information, complexity
and individuals’ limited computational abilities; use
of heuristics and judgement biases
Choices are based on feelings and emotions, as well as on a person’s mood
Anchoring and
adjustment
Lexicographic
preferences (‘‘car effect”
bias and ‘‘selfselection”)
People make an initial guess of probabilities, based on substandard cues, and stick close to their initial guess. They
ignore additional information that contradicts their initial hypothesis
Simplification of a decision choice set by focusing on only one (or few) attribute(s). A particular type of lexicographic
preference affecting travel mode choice is the so-called ‘‘car effect” bias, which denotes individuals showing a marked
preference for the car, even when this alternative is risky and does not necessarily involve the minimisation of total
costs. In this situation, car choice is favoured by prioritising affective factors over economic (‘‘rational”) ones. Selfselection regarding residence location and travel mode choices means that people choose a house location prioritising
their anticipated travel mode decisions – whether walking, cycling, public transport or driving a car
Linearity heuristic consists of erroneously assuming a linear relation between two variables/measures. Larrick and Soll
(2008) describe it and provide evidence of this ‘‘linear reasoning” by travellers when assessing vehicle fuel efficiency
as measured in ‘‘miles per gallon” (MPG). As a consequence, people undervalue the benefits of small efficiency
improvements on inefficient vehicles. ‘‘Gallons per mile” (GPM), on the other hand, implies a linear relation between
miles driven and fuel consumption, which allows for intuitive calculations and vehicle comparisons
When travellers are provided with information about headways, they can erroneously take the average waiting time
(i.e. half the headway) as a reference. However, this would only hold if the bus was a fully reliable mode and variance
was zero. Users often have to wait longer than the average waiting time. By setting such a low value as reference (half
the headway), additional waiting time can give the feeling of having to wait too long for the bus, hence the ‘‘waiting
time paradox”
People choose the default option in a complex choice set, thus disregarding other alternatives’ attributes or choice
outcomes
People use information to justify their initial guesses and choices. They may ‘‘filter” information to such an end
(filtering effect). In a similar way, people may assess past choices on the basis of new information they did not have
when choices were made (hindsight bias)
Average (waiting time)
heuristic
Default bias
Confirmatory bias
(illusory correlation,
hindsight bias,
‘‘filtering”)
Mental accounting
Salience and vividness
heuristics, ‘‘hot stove”
effect
Framing
Loss aversion
Endowment effect
Status quo effect
(‘‘choice persistence” or
‘‘inertia”)
Certainty effect
(‘‘reliability bias”)
People keep mental accounts for different expenses. This violates the fungibility property of money
Individuals weight extraordinary evidence disproportionately against the odds, even when information about actual
probabilities is available. Recent events are more heavily weighted (i.e. more salient), while negative experiences are
retained in memory for a longer time (i.e. more vivid). The availability of this information, which can be readily
retrieved from our memories, reduces the probability that a risky choice is repeated but impedes learning about the
actual value of the alternative –the ‘‘hot stove” effect
The way a set of options in a decision problem is formulated (i.e. ‘‘framed”) influences individuals’ preferences
Individuals have asymmetric preferences for gains and losses (Kahneman and Tversky, 1979). People put a higher
value on losses than on same-sized gains, and dislike taking (even) small risks. In addition, people are risk averse over
gains and risk seeking over losses
Individuals are loss averse and value more the things they own than those they do not. This effect can be immediate
and arbitrary (i.e. recently owned things), though the longer the tenure, the higher the value assigned
People stick to their original choices (i.e. status quo), even if change would cause substantial improvement, thus
showing choice persistence or inertia. This is a consequence of losses being disproportionately valued and the
endowment effect
People prefer certain (reliable) over uncertain or probabilistic outcomes (Tversky and Kahneman, 1981). As a
consequence, choice outcomes that are framed as sure losses lead to risk seeking behaviour (overestimation of low
probability outcomes or rare events), while choice outcomes framed as sure gains lead to risk aversive behaviour
(underestimation of high probability outcomes)
M. Garcia-Sierra et al. / Transportation Research Part D 41 (2015) 288–305
Affect heuristic
Linearity heuristic
CHOICE UNDER RISK AND UNCERTAINTY: contextdependent preferences, alternatives framed as either
gains or losses, and probabilities weighted nonlinearly
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Table 1
Summary of concepts and insights from behavioural economics.
Preference reversal
TIME-INCONSISTENT PREFERENCES AND SELF-CONTROL
PROBLEMS: inter-temporal choice and habit
formation
Hyperbolic discounting,
immediacy effect
(Lack of) self-control
Habits
Fairness, equity, justice
People dislike unequal allocations of goods
Altruism, ‘‘warm glow”,
reciprocal altruism
People value the well-being of others. A distinction is made between ‘‘pure” altruism (i.e. when an action is taken on a
generous way and without receiving anything in return) and ‘‘impure” altruism (i.e. when the action produces some
sort of benefit to the altruistic individual; warm glow and reputational altruism). Altruism can further take the form of
(direct or indirect) reciprocal altruism, namely individuals expect to be treated well by a person they have treated well
People usually care about others’ behaviour and seek to behave appropriately. Social and personal behaviour are
guided by norms and rules, which are (often) developed socially. Social norms are injuctive (i.e. describing a socially
accepted behaviour) or descriptive (i.e. a norm that describes an extended behaviour) (Cialdini, 2003, 2007)
Status denotes a social position often signalled by more wealth relative to others. The consumption of positional goods
which show one’s relative wealth (i.e. conspicuous consumption) is one way in which individuals derive status.
Individuals further gain reputation from showing membership to high status, relevant reference groups
Norms
Status, relative income,
positional goods,
conspicuous
consumption
Role models and peer
effects
Role models are ‘‘salient” members of relevant reference social groups (i.e. well positioned socially), which may
influence the behaviour of those individuals who value becoming a member of such social groups. In this vein, the
behaviour of friends, family and peers (i.e. relevant others) can also influence one’s behaviour, since they can be taken
as role models for desirable behaviour
Note: Classification of behavioural economic insights inspired by Gsottbauer and van den Bergh (2011). Unless indicated otherwise, insights on behavioural biases were retrieved from Ariely (2009), Camerer
(1999), Kahneman (2011), McFadden (1999), Rabin (1998), and Shogren and Taylor (2008).
M. Garcia-Sierra et al. / Transportation Research Part D 41 (2015) 288–305
Social preferences and self-identity concerns
SOCIAL PREFERENCES AND SELF-IDENTITY CONCERNS:
limited self-interest and self-identity concerns
Individuals with stable, well-defined preferences can end up choosing an option that is not the one they value the
most. Preference reversal can be induced by a change of the reference point or by the introduction of a decoy option
into a set of options. The latter will tip the balance towards the non-decoy option, not chosen otherwise
People value present rewards much highly than future gains. As a result, individuals sometimes make decisions which
are not in their best long-run interest (i.e. myopic behaviour). This deviation partly explains procrastination, addictions
and habitual behaviour
The ‘‘need” over the ‘‘will” or lack of self-control is explained by people placing more value on present gains than
future ones
Habits are automatic, non-deliberated responses formed through the repetition of a satisfactory course of action that
is stored in memory. Habitual behaviour can be explained by having time-inconsistent preferences, but habits can also
(positively) be seen as mental shortcuts or simplification heuristics that save costs such as searching for information,
information processing and deliberating a decision
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Application of behavioural economics to transport
Travel choices can be divided into long-term and short-term choices (Table 2). Long-term choices are not travel choices per
se, but entail long-term commitments with strong determinants of daily travel behaviour, namely residential and employment locations and engagement with travel modes such as getting a driving license and car ownership. Such commitments
have a lasting effect and constrain short-term or daily choices. A similar distinction is made in van de Kaa (2008). Fig. 1 offers
a summary of the empirical evidence on behavioural biases in travel choices.
Long-term choices
Residential and employment location choices: Travellers express bounded rationality in their residential and employment
location choices. They face imperfect information about job and residence offers, as well as incurring both searching and
transaction costs (pecuniary and non-pecuniary) that impede relocation and contribute to inertia (van Ommeren and
Fosgerau, 2009; van Ommeren and van Leuvensteijn, 2005; van Ommeren and van der Straaten, 2008). The latter leads to
the inefficient situation of having excess commuting (e.g., cross-commuting trips). Inertia in turn provides the necessary stability for habits to form and persist (Ouellette and Wood, 1998). In choosing residence, the effect of price anchoring has been
described in real estate market studies (Epley and Gilovich, 2005). This effect is most clearly observed when people relocate
to a new city, as they tend to go for the same price they were paying before, even when housing prices are lower in the new
location (Ariely, 2009). Choices further depend on the way alternatives are presented, known as framing. Studies by Tversky
and Kahneman (1991) and Axhausen et al. (2001) support the idea that in choosing a job or a house, households take their
prior status as a reference and thus value alternatives and their attributes in a loss-aversive manner.
At the intersection of location choices and travel mode choices self-selection bias plays a role. Individuals may opt for caroriented environments if they are inclined to drive, or choose pedestrian-oriented environments if they are committed to
walking or cycling (Axhausen et al., 2001; Cao et al., 2002; Handy et al., 2005; van Wee et al., 2002). Self-selection bias is
found to have a greater effect on people who have relatively strong preferences for driving (Handy and Mokhtarian, 2005).
Regarding the choices ‘‘obtaining a driving license”, ‘‘car ownership” and associated ‘‘car purchasing”, factors like emotions, status and norms can encourage engagement with the car. We consider these choices next.
Obtaining a driving license has a strong symbolic and emotional component, like a ritual of adulthood initiation. Haustein
et al. (2009) report a high importance of symbolism and affective socialization constructs in the formation of driving habits
Table 2
Set of travel choices that individuals and households face.
Set of travel choices
Long-term choices
Residential and employment locations
Driving license
Car ownership and car purchasing
Short-term choices
Destination
Departure time
Route
Travel mode
Fig. 1. Behavioural biases and anomalies in short- and long-term travel choices.
M. Garcia-Sierra et al. / Transportation Research Part D 41 (2015) 288–305
293
and positive personal norms about driving among adolescents. These constructs are learned from parents and peers who
serve as role models, transmitting (pre-existing) social norms regarding car use.
Car ownership: Travellers commit themselves to particular travel behaviours through the ownership of cars and seasontickets for public transport; they accept a large one-off payment for a low or zero marginal cost at the point of use (Simma
and Axhausen, 2001, 2003), and can incur mental accounting. Moreover, such commitments influence modal use to a greater
extent than past behaviour (or habit). Studies generally find high stability in car-ownership. There seems to be a greater
resistance or status quo effect to change car ownership than to reduce the level of car usage (Brindle, 2003). This may have
to do with loss aversion and a related concept, namely the endowment effect. In addition, Ellaway et al. (2003) found that car
access provides psychological and social benefits, such as mastery, self-esteem, and feelings of autonomy, protection and
prestige, which public transport users do not derive from their transport modes. These benefits are in turn associated with
longevity and better health. Self-esteem depended on the type of car in the case of men but not women, while driving provided more benefits than being a passenger.
Car purchasing: Advertisement in mass media favours these positive associations affecting car purchasing. Bradsher
(2002) notes that in the case of SUVs versus compact cars, marketing strategies have played a crucial role in making SUVs
appealing to insecure, self-centred people, who want to appear frightening to others. Also, regarding car purchasing,
Larrick and Soll (2008) provide evidence that information on fuel efficiency framed as ‘‘miles per gallon” (MPG) can be misinterpreted. The reason for this is that people rely on linear reasoning (i.e. linearity heuristic) about MPG, which leads them
to undervalue the benefits of small efficiency improvements on inefficient vehicles. In other words, people undervalue the
benefits of replacing the most inefficient cars by new cars with higher MPGs and thus better performance in terms of fuel
consumption (money savings) and carbon emissions (see also Schouten et al., 2014). A simple change, such as using ‘‘gallons
per mile” (GPM) – fuel per distance –, would allow consumers to understand exactly how much fuel they are using and, with
additional information, how much carbon they are emitting.
Cars, as well as houses, are both typical conspicuous goods that signal wealth (Hirsch, 1976). Travellers show status seeking behaviour through the purchase of conspicuous goods and services as a way to signal reputation and social position. They
further copy those relevant to them who seem successful. Car ownership, in fact, increases with income (Dargay, 2001).
Johansson-Stenman and Martinsson (2006) found non-conscious concerns about self-image to be significant in car purchasing and related to the consumption of luxury cars signalling social position and wealth. They also found that subjects generally care about the environment, but not as much as they care for status. Interestingly, certain social subgroups derive
reputation and status from showing environmental concern. In these cases owning a bike or a hybrid car may thus be a sign
of status. Sexton and Sexton (2011) show that the willingness to pay for a Toyota Prius varies significantly with the environmental concerns of one’s neighbours, which is a sign of peer effect, conspicuous generosity or impure altruism (i.e. warm
glow). Indeed, other hybrid car models were not as effective as the Prius in communicating environmental concern. The Prius
was found to be superior as a symbol of environmental concern, possibly because it was the first commercially successful
hybrid car and because it has a design that is easily distinguished from other cars (see Maynard, 2007).
Short-term choices
Destination: Probably the first decision to study should be whether to travel at all. Travel is necessary for reaching destinations and to participate in daily activities. Some travelling may be difficult to avoid, like commuting, unlike other types
like socially induced trips. Some socially induced trips (e.g., assisting someone going to a doctor or participating in joint
activities) have been considered a form of altruistic behaviour which can be influenced by social norms and expectations that
others will reciprocate (Goulias, 2007; Goulias and Henson, 2006).
Most short-term travel choices are repetitive and the result of daily routines, with fixed combinations of destination,
departure time, route choice and travel mode. Indeed, travel-activity patterns are organised around a small number of fixed
activities or stops (Hanson and Huff, 1982, 1988). Repetitive trips to habitual destinations stimulate automatic travel
responses.
Regarding the combination of choices ‘‘departure time” and ‘‘route selection”, auto-commuters surveyed in Taiwan leave
home at the same time 82% of the time and take the same route as the previous day 90% of the time (Jou et al., 2008). Most
commuters are not likely to change their departure times and routes, suggesting either that the commuters are very familiar
with their commutes (i.e. show habit) or that the combination of departure time and route taken is already optimal or at
least satisficing.
Departure time: Reference-dependency, loss aversion and diminishing sensitivity, can explain departure time adjustments
among commuters (Jou and Kitamura, 2002; Jou et al., 2008; Senbil and Kitamura, 2004). Travellers may have several reference points (e.g., earliest permissible arrival time, preferred arrival time, and starting time of work) and therefore early
arrivals (i.e. gains) can still be valued negatively, even though late arrivals (i.e. losses) would certainly be valued (more) negatively. Jou and Kitamura (2002) noticed diminishing sensitivity to time gains: for example, the subjective value of gains of
0–5 min is higher than that of gains of 20–25 min. Hjorth and Fosgerau (2012) moreover demonstrated that this diminishing
sensitivity effect is stronger for travel expenses than for time costs, for both car and public transport journeys.
Route selection: The way information about travel time distributions is framed affects route choice. Travellers dislike
uncertainty regarding travel time (i.e. travel time variability) more than they dislike long travel times (Bates et al., 2001;
Noland and Polak, 2002; Senna, 1994). They are bad at computing probabilities, and so use simplification rules and are more
inclined to reliable alternatives. In an experiment on route selection, Avineri and Prashker (2004) found evidence of certainty
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effect (i.e. underweighting of high probabilities) due to risk aversion, and risk-seeking behaviour for choice settings implying
low-probability, high-reward outcomes. In addition, de Palma and Picard (2005) found that absolute risk aversion is constant
and larger for public transport users than for car users with regard to both expected travel time and travel time variability.
Reference-dependency and judgement errors can further explain suboptimal choices between bus lines following different routes, as well as the ‘‘waiting time paradox”, according to which public transport users perceive that they always have
to wait too long for the bus (Avineri, 2004). For the case in which travellers are provided with information about headways,
they may erroneously take the average waiting time (i.e. half the headway) as a reference and by setting such a low value as
reference, additional waiting time is usually framed as a loss. This misconception can in turn favour a particular form of preference reversal, namely the selection of a suboptimal bus route, only because the frequency of that particular bus line seems
to be comparatively lower and not have many delays.
For particular choices, and under certain conditions, results from iterative tasks with immediate feedback, such as choices
in transport contexts, are biased but go in the opposite direction of those predicted by Prospect Theory (i.e. one-shot tasks
based on a full description of the choice problem); loss aversion is the only bias that appears robust in both iterative and oneshot tasks choice contexts (see Barron and Erev, 2003). Under imperfect information travellers learn about travel time distributions from their experiences. Choices are repetitive and they get immediate feedback on actual travel time. However,
their estimates about travel time distributions can be inaccurate in some cases (not leading to the best choices), for instance,
if estimates are based on recent bad outcomes or small samples of outcomes, or if payoff distributions have large variances.
The latter stimulates exploration (i.e. more random choices) and slows learning, thus, leading, on average, to more suboptimal choices in the medium-term (see Erev and Barron, 2005). Mahmassani and Srinivasan (2004) noted that subjects
without reliable information overreacted to negative experiences, such as being stuck in traffic in the previous period, by
switching their departure times and routes more in response. Recent events are more heavily weighted, while bad experiences are retained in memory for longer times (salience and vividness heuristics), which reduce the probability that a risky
choice is repeated but impede learning about the actual value of the alternative – the so-called ‘‘hot stove” effect (Denrell
and March, 2001). Avineri and Prashker (2005) found evidence of this payoff variability effect. Moreover, they noted that
in some cases increasing the travel time variability of the route with the highest expected travel time could increase its perceived attractiveness, thus implying an underweighting of low probability outcomes and preference reversal.
Travel mode choice: (Mis)perceptions about reliability also affect travel mode choice, even when some information is provided as in the previous case regarding the ‘‘waiting time paradox”. Bates et al. (2001) acknowledges that with regard to subjective perceptions of travel time variability or the reliability of different travel modes, there are relevant differences
between the car and public transport; notably, the car is perceived to be comparatively more reliable than public transport.
As Bates et al. point out, in the case of public transport, the presence of a schedule involving some potential waiting time or
trip-duration favours establishing comparisons among the actual and the scheduled waiting/journey time, and so any discrepancy may be interpreted as unreliability and incurring time losses, even though a certain delay might be constant, which
would imply no variability. Hence, for advertised public transport services, reliability and punctuality (i.e. adherence to
schedule) are closely related. Indeed, misconceptions about travel time costs (and systematic underestimation of carrelated expenses) can explain choosing the car over public transport (Bonsall et al., 2004; Gardner and Abraham, 2007).
Van Exel and Rietveld (2009a), in a study for Amsterdam, found that on average car travellers’ perceptions of public transport
travel time exceeded objective values by 46%, and that if perceptions were more accurate, two out of three car users that
currently do not see public transport as an alternative would include it in their choice-set, and use it from time to time.
In addition, individuals with marked preferences for cars tend to use information on punctuality and actual travel times
to reinforce car choice (i.e. confirmatory bias) and show travel mode persistence, namely undergoing the ‘‘car effect” bias
(Innocenti et al., 2013). Nevertheless, information on public transport schedules can indeed lead to more use of public transport. Rietveld (2003) argues that the problem is not so much to inform public transport users, but how to frame the information provided so that biases connected to reference-dependency (e.g., loss aversion) are minimised and public transport
use is encouraged as a reliable means of transport. For example, as full reliability of schedule information cannot be guaranteed, providing information about probability distributions of arrivals or of travel times may be useful.
Habits are also a key factor in travel mode choice and can be generalised across choice contexts (Aarts et al., 1998; Aarts
and Dijksterhuis, 2000; Gardner, 2009). Travel mode habits lead to misperceptions about non-habitual modes (e.g., systematic underestimation of performance attributes like reliability and disregard of cost differences) (Anable and Gatersleben,
2005). Strong travel mode habits moderate and even preclude the effect of deliberated intentions to change behaviour
(Aarts and Dijksterhuis, 2000), that is, create problems of self-control. It seems that habits also moderate the effect of moral
obligations to behave pro-environmentally (Klöckner et al., 2003; Klöckner and Matthies, 2004). Indeed, Anable (2005)
noticed that habitual car drivers do not feel any moral obligation to decrease their car use.
Travel mode alternatives include other than utilitarian attributes, namely symbolic-affective and social ones. Anable and
Gatersleben (2005) found that while utilitarian attributes are more important in explaining modal choice in commuting, for
personal trips both utilitarian and affective factors are equally important. Yet, Steg (2005) notes that what best captures car
use by young male commuters are emotions evoked by driving (notably, freedom, independence, comfort and apparent
control), perceived social pressure favouring car use, and status seeking. The car is used by these commuters as a way of
self-representation and to show membership to (i.e. imitate) certain reference social groups. These feelings give the car a
comparative advantage over public transport (Steg, 2003; Steg and Gifford, 2005). Whereas positive feelings ascribed
to the car predict its use, negative ones like guilt and disappointment predict intentions to use public transport
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(Abrahamse et al., 2009; Carrus et al., 2008). Friends and family (i.e. relevant others), and a supportive social context, play a
key role in transmitting the negative effects of car use and the positive ones of public transport, its reliability, lack of stress
and possibility of undertaking a productive commute (i.e. working while travelling), which increase preferences for public
transport use (Haustein et al., 2009; Murray et al., 2010; Popuri et al., 2011).
Lessons for environmental-transport policy
Here we discuss implications of the insights reviewed in Section ‘Behavioural economics and transport’ for
environmental-transport policy. In doing so we distinguish between policy lessons that are connected to bounded rationality
and to social preferences. Table 3 provides an overview and summary.
Bounded rationality
Travellers being emotional
Travellers associate car use with positive affective feelings. Marketing and mass media have a high responsibility in promoting affective aspects of vehicles and hence publicising them might be prohibited or discouraged through taxation (see
Avineri and Goodwin, 2010). A study on ‘‘dirty” advertising, namely advertising that encourages the consumption of pollutive goods, derives optimal rules, not just for setting a tax on dirty advertising, but also a subsidy on clean advertisement, and
an optimal pollution tax and information provision by the government (e.g., Gsottbauer and van den Bergh, 2014). These
findings can be applied to the case of advertising for cars, and transportation means in general.
A different side of emotions is illustrated by observations that negative feelings of shame and guilt encourage public
transport use (Bamberg et al., 2007; Carrus et al., 2008). The literature in environmental psychology notes that public transport use can be promoted through the activation of pro-environmental values (Gärling et al., 2003; Lindenberg and Steg,
2007). Such values are ascribed to responsibility and awareness of environmental impacts, which trigger feelings of moral
obligation or personal norms to behave pro-environmentally. Results from O’Connor et al. (2002) show that people who
can accurately identify the causes and risks of climate change are more likely to reduce emissions voluntarily and support
strong policy initiatives. Education is thus crucial in order to increase levels of environmental concern and a positive attitude
towards frugality (i.e. to form strong personal norms) (Fujii, 2006; de Young, 1996). Although the positive role of environmental education is recognised as relevant by many transport planners, these insights from psychology studies give extra
weight to it, notably in terms of how environmental awareness is translated into feelings of responsibility. In addition to this,
social psychology studies noticed that personal norms result from internalising social norms that criticize car use. Indeed,
environmental and social values are positively correlated with one another in cases where environmental and social
objectives go in the same direction (de Groot and Steg, 2008), for instance in social dilemmas about public goods. In
Section ‘Travellers taking norms as mandates and following relevant others’ several ways in which to encourage cooperation
through norms against car use are outlined.
Last but not least, financial incentives affect moral obligations to behave pro-environmentally (i.e. personal norms)
through so-called crowding out effects. This denotes that when altruistic actions are paid people can be deprived of the feeling of having done something good and thus can become less motivated intrinsically to behave in this way. Paying to compensate the effects of their behaviour can give them the feeling that they have a right to deviate from pro-environmental
behaviour (Clark et al., 2003; Frey, 1992; Frey and Oberholzer-Gee, 1997), namely ‘‘the right to pollute” (see also Section ‘Loss
aversion and negative framing’ about framing). Heymen and Ariely (2004) found that in the absence of prices people’s
choices and efforts are guided by social principles, which are not sensitive to compensation, in contrast to monetary
exchange in formal markets. Hence, when environmental norms are high, social incentives can be used instead of monetary
ones. Of course, when pro-environmental behaviour is insufficient to solve the associated problem and financial incentives
can do the job even if they cause some crowding out, then there is a good reason to go for such incentives. In other words, it
is wise to consider the net effect rather than principally refrain from policies that cause crowding-out.
Travellers sticking to the status quo and choosing the default option
Travellers show a tendency to stick to the status quo. Such inertia can tip the balance towards polluting alternatives when
presented as the mainstream or default option (e.g., gasoline and diesel cars, single housing and dwellings blocks with parking). A straightforward way to take advantage of default bias is by presenting ‘‘green” alternatives as defaults. Examples of
green defaults in the context of transport include electric and hybrid cars, and compact housing without parking. Appropriately setting defaults could further encourage certain departure times and routes to alleviate congestion. One way to do this
is to designate environmental zones with limits on high-pollutant vehicles. Their entrance to these zones could be either
prohibited or subject to taxation, which would send a clear message on what is to be favoured. Thaler and Sunstein
(2008) argue that the effect of defaults could be reinforced if they are supported by norms and framed as the recommended
action to take.
In addition, opt-out defaults (i.e. when the passive response means sticking to the default) increase the probability that
the (green) default option is chosen (Johnson and Goldstein, 2003). Turning ‘‘green” cars into opt-out defaults would actually
Travellers’ biases
Evidence from behavioural economics studies
Bounded rationality, Prospect Theory and Time-inconsistent preferences
Being emotional
Valuing both utilitarian and affective attributes of jobs, houses and travel modes
(vehicles)
Sticking to current choices, particularly if these are socially accepted
Having separate
mental accounts
Use of separate accounts for fixed and variable costs of driving
Self-selection bias
Self-selection bias affecting location choices in favour of (private) travel modes
Using heuristics and
misinterpret
information
Use of simplification heuristics (e.g., linearity heuristic, average waiting time heuristic,
lexicographic preference for the car or ‘‘car effect”, salience and vividness) and errors
regarding travel time and money costs that suggest a systematic bias towards the car,
disregard for information that does not match one’s preference (filtering) or for
information at all in the case of strong habits and status-seeking behaviour
Learn about travel
contexts
Learning does not guarantee more optimal choices in the medium-term
Loss aversion and
negative framing
Taking previous status as a reference, value asymmetrically gains and losses relative to
it, and responding to framed information by showing loss aversion
Being creatures of
habit
Acting moved by habits, which moderate the effects of norms and deliberated
intentions to change behaviour, and lead to misperceptions about the performance of
non-habitual travel modes
Implications for environmental-transport policy
Positive emotions ascribed to the car favour car use and habit formation, and should be
discouraged
Public transport use may be triggered through feelings of guilt and shame associated
with car use, which, in turn, can be promoted by educating people to take
responsibility for one’s impact
Travellers with strong pro-environmental motivations are more prone to adopt (new)
sustainable alternatives
Green alternatives (e.g., electric and hybrid cars and compact housing without
parking) can be presented as defaults
Opt-out defaults increase the probability that the green option is chosen
Defaults are more effective when travellers are unfamiliar with green alternatives
Increasing the variable costs of driving has a greater effect than increasing the fixed
costs
The introduction of new pricing schemes can reduce the effect of mental accounts in
controlling consumption
Instruments can be designed that simultaneously discourage car use, while
encouraging sustainable location choices
Land planning policies focusing on sustainability
Some descriptive information can be framed to account for travellers’ particular
reasoning, something that would increase the likelihood of changes
Removing barriers to information, and finding ways of presenting information that
seems complex at first (e.g. information about probability distributions, energy
efficiency and other emission-related concepts)
Information plays a crucial role during incident conditions (e.g., strikes, accidents,
break-downs), avoiding the ‘‘hot stove” effect
Information has its limits – due to habits and status – and so more stringent policy
forcing modal change is necessary in these cases
Feedback is a necessary learning tool and helps redressing misperceptions
Overall, descriptive information about travel time distributions has positive effects,
though inexperienced travellers benefit more from information than experienced ones
There is potential for external provision of feedback/information about environmental
performance (i.e. CO2 emissions)
Choice outcomes can be framed as either gains or losses to persuade travellers towards
a desired choice
Negative frames have a relatively greater influence on behaviour (retained for longer
times)
Experience can diminish the effects of loss aversion
Pricing mechanisms can be understood as giving ‘‘the right to pollute” instead of
signalling that ‘‘the polluter pays” and regulations can be understood as taking away
freedom of choice
Unsustainable habits can be ‘‘unfrozen” through interventions that induce conscious
deliberation of current choices and alternatives
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Sticking to the status
quo and choosing the
default option
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Table 3
Environmental-transport policy analyses for the set of long-term and short-term travel choices.
Table 3 (continued)
Travellers’ biases
Evidence from behavioural economics studies
Implications for environmental-transport policy
Habits break when there are life-changing events (job and residential relocations);
travellers are more receptive to information during these moments
Sustainable travel habits can be encouraged through economic incentives
Other changes in the choice context, such as temporary road closures and the
withdrawal of parking spaces, force a change of travel mode and are highly effective
If habits create an undesired consumption externality optimal Pigouvian taxation
needs to be adjusted
Status seeking and
caring about selfimage
Wanting to show their wealth and appear generous in front of others
Norms can encourage both pro-self and pro-environmental behaviours depending on
the social context, and so it is necessary to create a social environment that favours
sustainable travel alternatives
The effectiveness of information can be raised by capturing travellers’ normative
concerns; and injunctive and descriptive norms promote cooperation in social
dilemmas
Pro-social and pro-environmental behaviours are positively correlated in cases where
objectives line up
Social rewards and punishment (e.g., public disclosure) help to raise contributions and
induce voluntary changes
If norms create an undesired consumption externality, optimal Pigouvian taxation
needs to be adjusted
Reputation and status concerns can favour car use over public transport; feebates can
be used to deal with this
Status-seeking behaviour creates a consumption externality and optimal Pigouvian
taxation needs to be adjusted
Status seeking can be used to promote pro-environmental behaviour, particularly
when green products cost more than their non-green counterparts
Status seeking behaviour and self-image concerns can lead to conspicuous generosity
or impure altruism (warm glow)
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Social preferences and self-identity concerns
Being motivated to behave appropriately and fit within their social contexts, and
Taking norms as
caring about what nearby people do and think
mandates and
following relevant
others
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mean increasing electric and hybrid market shares and perhaps force retailers to only publicise and showroom these car models. At the same time, limits are needed on the proliferation of low-density building. Two ways to avoid this are direct prohibition or increasing the costs for promoters of their construction. Overall, policies need to be more stringent when polluting
default effects in the market are strong (Carlsson and Johansson-Stenman, 2012). Notwithstanding this, Löfgren et al. (2009)
found that when individuals are familiar with green alternatives, and as long as the cost of switching is low, they may actively
pick the environmentally-friendly option. This result is encouraging as it means that a green option can spread in an environmentally educated population without further persuasion, even though defaults may be necessary to encourage early adoption.
Travellers having separate mental accounts
Travellers use different mental accounts for fixed and variable time costs and money expenses derived from transport. Studies suggest that to decrease car use, it may be more effective to increase variable expenses of driving than fixed ones (Dargay,
2008). Thus, raising fuel prices and setting emission taxes per kilometre driven or road pricing schemes may be good policy
alternatives to discourage car use. Travellers even differentiate between travel modes. One consequence of this is that the costs
and expenses of driving are generally underestimated relative to those of using public transport, which creates a competitive
disadvantage for alternatives to the car. Mental accounts influence product choice, in that accounts and budgets are used as
self-control devices to avoid overconsumption, which is a positive trait, maintaining driving levels low once variable costs
of driving have increased (e.g., through policy). However, Cheema and Soman (2006) found that for ambiguous expenses, this
self-control mechanism may fail because these can be assigned to more than one account which often justifies spending. Thus,
from a policy perspective it may be a better strategy to simply raise current fuel taxes, tolls, etc. rather than introducing new
pricing schemes that might be ambiguous to travellers without previous experience of such schemes.
Self-selection bias
Travellers select residential locations favourable to their travel mode preferences. Self-selection related to car lovers may
be a problem here. Hence, it may be important to design mechanisms that simultaneously discourage car use and encourage
sustainable location choices. Næss (2009), however, argues that self-selection bias highlights the importance of location
choices; that is, there is a remaining effect on modal choice of the location of a residence and the neighbourhood typology
(i.e. favourable or not favourable to car use) after controlling for self-selection bias. These findings support our previous suggestion on limiting low-density building (Section ‘Travellers sticking to the status quo and choosing the default option’ about
defaults) and emphasize the relevance of land planning policies that design neighbourhoods with attributes that discourage
positive attitudes of households to the car, and thus car ownership and use.
Heuristics and information
Travellers use heuristics when interpreting descriptive information, which can lead to errors of judgement. However,
adjusting information to travellers’ reasoning can raise the effectiveness of information. In this vein, measures of fuel efficiency need to be the expressed in ‘‘gallons per mile” (GPM) – fuel per distance – so that information is framed consistently
with people’s linear reasoning. Regarding information about expected travel time and the various measures of variability/
reliability, it is unclear how people perceive mean–variance concepts and other characteristics of travel time distributions;
most people are not even familiar with the concept of variance (or standard deviation) (Bates et al., 2001; Noland and Polak,
2002). Indeed, reference points are easily influenced by framing, yet are not completely understood by researchers, who
think that may be endogenously set (see van Wee, 2010). A realistic recommendation to cope with the ‘‘waiting time paradox” would be to set countdown markers. When it comes to the ‘‘car effect”, namely unreasonably disregarding alternatives
to the car, there is much to be done to improve the image of public transport in terms of its reliability. Under incident conditions altering the normal functioning of public transport services, information plays a crucial role in avoiding the ‘‘hot
stove” effect (Chorus et al., 2006). Take the example of public transport strikes. These can have a negative and lasting effect
on the number passengers using the service (i.e. ridership), which can be minimised if travellers are well informed and in
advance, reducing the impact on the perceived reliability of the service while also giving them the opportunity to arrange
alternatives (van Exel and Rietveld, 2001, 2009b). The lesson is that (better framed) information decreases uncertainty
and eases decision-making, meaning that travellers make more optimal choices (i.e. choose the alternative yielding the highest payoff, whether minimising travel time, travel costs, or environmental impact). However, there are still barriers to information. Travellers with strong habits, for instance, who disregard travel information. Recommendations on how to deal with
habits are put forward in Section ‘Travellers being creatures of habit’.
Likewise, the effect of information about car alternatives in triggering change is limited due to both drivers’ preferences
for reputation and status, and the ‘‘car effect”, which leads to biased choices. Satisfied car users are unlikely to seek information regarding alternatives that they perceive to perform poorly. Indeed, information about modal alternatives to the
car will only have an effect provided alternatives clearly outperform the car in terms of travel times, expenses (i.e. costs),
image, and costs of information acquiring and eventual adaptation (i.e. changing the choice with all its consequences)
(Chorus et al., 2006). More stringent policy forcing modal change is thus necessary in these cases (see Section ‘Status seeking
and caring about self-image’ about status).
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Feedback affects learning by travellers
There is a further role information can play. Many studies indicate that feedback is a necessary element in learning for
travellers. Travellers already receive immediate feedback on actual travel times and trip expenses, especially in the case
of public transport where they have to pay for a ticket, and to a lesser extent in the case of cars (because of fixed costs). However, the effect of information in travel contexts where travellers also learn through experience is limited. Several studies
have investigated this issue for the case of travel time minimisation through route choice (Avineri and Prashker, 2006;
Ben-Elia et al., 2008; Selten et al., 2007). It seems that, initially, information about travel time distributions has positive
effects – increases initial risk-seeking behaviour, reduces initial exploration and increases between-subject differences –,
but as travellers become more experienced, behaviour moves towards the predictions of the payoff variability effect
(Ben-Elia et al., 2008). Inexperienced travellers thus benefit more from information than experienced ones (see also
Section ‘Travellers being creatures of habit’ about habits). These results are further confirmed for travel mode choices, even
in the more realistic case when information is costly (Denant-Boèmont and Petiot, 2003). Travellers, however, do not get
immediate feedback from their choices in terms of actual CO2 emissions, which they do get in terms of actual travel times,
etc. Learning is thus complicated, and external feedback/information is necessary. Coulter et al. (2008) investigated the role
of carbon calculators in shaping people’s understanding, attitudes and behaviours; participants could experiment with a
range of carbon calculators, though. They noticed that most people have a limited understanding of emissions-related
concepts and cannot connect emissions with their own behaviour very well. Particularly, in the case of travel behaviour,
a high resistance to change is associated with perceptions about limited alternatives, reliability, time and costs being more
important than environmental concerns, as well as with blaming others for the increase in emissions. Emission meters could
alternatively be adapted for their installation into cars. In this vein, Ericsson et al. (2006) show the possibility of including
information on fuel-efficient routes in innovative navigational systems, which would reduce CO2 emissions of car journeys.
Although there is still scope for improvement –further research with vehicle navigation companies is necessary– results
from a pilot case in Lund (Sweden) show that route optimization to the lowest total fuel consumption (and the lowest
emissions) can result, on average, in 8.2% reduction in fuel consumption. The potential for improvement is thus significant;
in Lund 46% of all journeys over 5 min are not adjusted to the most fuel-efficient route.
Loss aversion and negative framing
Travellers dislike losses. Choice outcomes can be framed as losses to persuade travellers towards a desired choice. Avineri
and Prashker (2004) showed how negatively framed information about travel time distributions could trigger route changes
towards reliable routes. However, learning can reduce loss aversion in view of uncertainty about travel time costs (Avineri
and Prashker, 2005; Ben-Elia et al., 2008). Avineri and Waygood (2013) found that negative framing is actually more effective
than positive framing in highlighting differences between travel modes in terms of associated CO2 emissions. They compared
sets of modes including the bicycle, a full car, and single occupancy of a SUV vehicle, and framed information on emissions as
‘‘lower” or ‘‘higher” to signal whether a travel mode was ‘‘better” or ‘‘worse”, respectively. Negative framing though has sideeffects, notably on how pricing mechanisms are understood. Nash (2006) investigates these effects on consumers, voters,
business community, and environmental NGOs, and finds that pricing mechanisms can be understood as giving the ‘‘right
to pollute”. This perception can lower their effectiveness. Accordingly, pricing mechanisms could be better framed as
‘‘penalties” to avoid such misinterpretation. In addition, this frame of ‘‘right to pollute” explains differences in the opposition
to pricing and regulation, with the latter being more opposed as it is perceived to restrict freedom of choice. This insight has
implications on how to present some policies to both travellers and politicians to seek maximum acceptability, especially if
policies are necessary.
Travellers being creatures of habit
Strong travel habits pose obstacles to behaviour change. Gärling and Axhausen (2003) argue that habits need to be ‘‘unfrozen” to allow conscious deliberation of behaviour if change is to occur. Both Garvill et al. (2003) and Eriksson et al. (2008)
notice positive results of so-called ‘‘deliberation intervention”, where participants are induced to deliberate about alternatives to their habitual choices. The intervention was particularly successful for car users with a strong car habit and a strong
moral motivation (or personal norm) to reduce personal car use. Deliberation can also be prompted through changes in the
choice context. Verplanken et al. (2008) found for modal choices that residential relocations allow conscious renegotiation of
past habits, activating pro-environmental intrinsic values that guide behaviour towards sustainable alternatives. Habits can
also be broken and formed through financial incentives, with long-lasting effects (Charness and Gneezy, 2008; Fujii and
Kitamura, 2003). Bamberg (2006) tested the synergic effects of these insights through an intervention carried out after residential relocation. This involved providing a 1-day free ticket and personally tailored information about public transport
services. The intervention caused an increase in public transport use from 18% to 47%. Car use habits significantly decreased
after relocation and behavioural changes took place for both habituals and non-habituals. Moreover, participants significantly changed their attitudes and beliefs about the feasibility and adequacy of using public transport. In this case, no
crowding-out effects were described (see also Hunecke et al., 2001). Alternatively, interventions such as temporary road closures (Fujii et al., 2001) and the withdrawal of parking spaces (Brown et al., 2003), necessarily force a change of travel mode.
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These measures are more in line with insights from behavioural economics in that the habitual response is interrupted.
Behaviour change was effectively achieved in these two cases. As in the case of incentives, public transport usage was maintained because the tryout experience was satisfactory while the negative perceptions held about public transport were
shifted. Finally, some studies suggest that when habits create a negative environmental externality, the environmental
tax must be increased beyond the traditionally optimal (Pigouvian) level to make change possible (Fuhrer, 2000; Leith
et al., 2012; Löfgren and Nordblom, 2006).
Social preferences and self-identity concerns
Travellers taking norms as mandates and following relevant others
Most pro-environmental behaviours can be explained by peoples’ motivation to behave appropriately and fit within their
social contexts (Dawnay and Shah, 2005; Lindenberg and Steg, 2007). Studies from social psychology reveal that we learn
how to behave and what is appropriate by observing and copying the behaviour of others, called ‘‘social proof”. In this vein,
schemes such as congestion charging in central London reduce the ‘‘social proof” of car use acceptability, while highlighting
the desirability of using sustainable alternatives for environmental reasons. These price-based mechanisms are however
quite contested, and hence difficult to implement; people are insecure about how these interventions affect their daily life
in terms of personal losses (less car use and higher financial costs). Yet, findings from Schuitema et al. (2010) show that experiencing the benefits of congestion charging during trial periods increases their acceptability.
Norms can also play a relevant role in increasing the effectiveness of information provision. Cialdini (2003, 2007) suggests
using messages with injunctive norms (perceptions about socially-approved behaviours) when the intention is to change an
environmentally undesirable but socially-extended behaviour; and using descriptive norms (perceptions about behaviours
socially-extended) to reinforce pro-environmental behaviour that is sufficiently extended. Thus, if car use is the majority,
then disapproval messages should be emitted (use of the injunctive norm). If, on the contrary, the majority of the population
uses public transport, then this is what needs to be communicated (use of the descriptive norm). These types of normative
messages can indeed be publicised in traffic panels to discourage driving, just the same way as information on congestion
and accidentability is publicised.
The effect of norms on social dilemmas has been extensively researched. Refrain from driving has frequently been
regarded as a social dilemma; while driving a car (i.e. to free-ride) may be in the interest of the individual, less driving
(i.e. to cooperate) is in our collective interest and makes everyone better off (Vlek, 2000). Biel and Thøgersen (2007) review
the application of norms in iterative dilemmas, such as travel decisions. They argue that what others do is likely to influence
individual behaviour based on expectations about reciprocity and conditional cooperation. In this regard, Gaker et al. (2010)
found, through an experiment, that information of peer compliance with pedestrian laws has a stronger influence on pedestrian safety behaviour than descriptive information (e.g., accident statistics or citation rates). Still some people may feel that
their contribution is irrelevant compared to that of others (Lorenzoni et al., 2007).
To free-ride is considered a violation of the equity norm. Violations of social norms in dilemmas are often responded to by
sanctions. Social punishment and rewards encourage cooperation. Public disclosure is a form of social punishment that
includes reputation concerns. Examples applicable to transport include publicising car or individuals’ emissions and energy
use, placing signals on pollutive cars, and labelling these (Rand and Nowak, 2009). Yet, while publicising personal information can be complicated due to privacy policy, implementing a labelling scheme for cars is something realizable.
Status seeking and caring about self-image
A travel mode such as the car is valued in both utilitarian (time and money costs) and social terms (reputation and status).
The presence of status-seeking behaviour means that the level of optimal correcting taxes for conspicuous goods that damage the environment needs to be raised (Howarth, 1996). However, under status seeking prices may sometimes send the
wrong message and so it may be more efficient to deal with status through income taxes (Aronsson and JohanssonStenman, 2008; Ireland, 1998). An alternative in the context of transport is proposed by Verhoef and van Wee (2000), namely
feebates on new cars dependent on emissions/fuel consumption. That is, the amount of the feebate is determined by the relative fuel efficiency of a vehicle; the fee is applied to more heavily polluting cars, whereas less polluting cars receive a financial incentive (i.e. the rebate). An elaborate discussion of the effects of feebate schemes and design options is offered by de
Haan et al. (2009), Mueller and de Haan (2009), and Peters et al. (2008). Status, however, does not depend only on material
wealth but on social reputation. We have already mentioned that some social groups derive utility from showing environmental concern. Linking these social preferences, namely status seeking and reputation, could alter behaviour in an environmentally favourable direction. Griskevicius et al. (2010) actually demonstrated that eliciting status motives can be an
effective way to promote pro-environmental behaviour. Status motives increased desire for green products (including hybrid
or electric cars) when shopping in public (but not private) and when green products cost more (but not less) than non-green
products, so that green products can simultaneously signal one’s ‘‘care” for the environment and ‘‘wealth”. The experiment
assessed different products and their green counterparts, including cars (traditional versus hybrid models). Environmental
studies further point to ‘‘conspicuous generosity”, namely the desire to appear generous in front of others, as a way to
get people to cooperate in social dilemmas (Andreoni, 1989; Andreoni and Petrie, 2004; Alpizar et al., 2008).
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Conclusions
Much of transport reality is better described by behavioural approaches than by rational agent models. Behavioural economics offers alternative and comprehensive answers to the questions of why people behave as they do and why it is difficult to change travel behaviour. The literature gives evidence for the following stylized facts about bounded rationality,
namely that travellers: (1) are emotional, (2) stick to their status quo and choose the default option, (3) separate accounts
to process costs of action, (4) self-select environments favourable to their preferences, (5) use heuristics, make errors and
misinterpret information, (6) learn about their travel contexts, (7) are influenced by negative frames, and (8) are creatures
of habit. Concerning social preferences, travellers (9) take norms as mandates and care about reputation, and (10) seek status
and follow relevant others. In addition, some reinforcing effects among biases are worth mentioning, notably the amplified
effect of ‘‘reliability bias” and the ‘‘car effect”, and the effect of social norms on status and affect heuristics favouring car
usage.
These characteristics of travellers produce systematic biases in their behaviour that interfere at all the stages of decision
making. Behavioural anomalies can be described either for long-term choices affecting day-to-day travel choices (residential
and employment locations, owning a driving license and car purchasing), or short-term daily travel choices (destination or
activity choice, departure time, route and travel mode choice). Behavioural deviations are a source of ineffectiveness in traditional environmental policy and so the recognition of them in policy design is highly recommendable. It even allows for
testing types of instruments other than traditional ones, such as a tax on ‘‘dirty” advertising, different defaults, newly framed
messages, deliberation interventions, and social incentives and disincentives (public disclosure).
Policies to address bounded rationality involve penalising the promotion of positive feelings attributed to driving, while
encouraging negative ones of guilt and shame. Supportive norms and environmental education motivate people to behave
pro-environmentally. In addition, green alternatives can be presented as the recommended default option; e.g., providing
‘‘social proof” of hybrids and electric vehicles. Regarding social preferences and self-identity concerns, social pressure favouring green alternatives and behaviours can be very effective; people mostly want to fit within their social contexts and appear
generous. Defectors can be punished through public disclosure (e.g., car labelling). Peers and neighbours have a great influence on individuals’ behaviour. Thus, green behaviours and attitudes of peers and neighbours can be published to provide a
positive reinforcement and ease behavioural change. Finally, reputation and status concerns could work together through
the promotion of social status over material wealth to favour sustainable alternatives. Marketing strategies could improve
the social image of green alternatives and make them fashionable; the ‘‘Prius effect” can be taken as a successful example.
Reinforcing effects can be obtained if role models became involved and people copied them.
Traditional policy instruments need to be adapted whenever systematic biases affect the effectiveness of measures. The
effects of information in triggering behaviour change are limited when alternatives to the car do not outperform at utilitarian
(time and money costs) and social levels (e.g., provide reputation and status). Providing accurate and reliable information
during incidents is cost-effective and corrects misperceptions that can lower public transport use; public transport users
show relatively higher degrees of risk aversion due to time losses than car users. Adapting information to travellers’ heuristics can aid decision-making, while normative messages can increase the effectiveness of information by providing ‘‘social
proof”. Furthermore, polluting alternatives can be discouraged through negative frames that focus on their poor environmental performance. Framing can further affect the support for price-based mechanisms, which need to be presented as
environmental penalties. For pricing mechanisms entailing major opposition, such as road pricing schemes, trials can help
increase their acceptability. Financial incentives can crowd-out intrinsic motivations to behave pro-environmentally but
they seem to have a positive effect on the formation of sustainable habits. Travel mode habits can break when context
changes are forced. The presence of norms, habits and status seeking behaviour favouring polluting travel behaviour affect
the size of any optimal corrective tax. In the case of status seeking, prices could send the wrong message anyway. In this case,
correction could be considered through income taxation and feebates.
All in all, policy strategies need to be perceived as fair and just. Policies need to involve all actors (travellers, car producers, the automotive lobby, public authorities and the media sector) so that travellers feel that everyone is contributing and
thus reciprocate. This paper has shown that insights from behavioural economics can play an important role in understanding how the effects that heuristics, information filtering, norms and status have on travellers can be effectively addressed
through transport policy.
Finally, a few comments are necessary regarding potential future research. Little is known about how people perceive
mean–variance concepts and other characteristics of travel time distributions, even though these are likely to affect their
perceptions of reliability and the time costs of public transport. Experiments can be designed to systematically explore
the effectiveness of different frames to inform travellers about expected travel times and the frequency of the service
(e.g., countdown, information about probability distributions of arrivals or of travel times). This is of crucial importance
as reinforcing effects amongst ‘‘reliability bias” and the ‘‘car effect” have been observed. Notably, the car is constantly
and invariably perceived to be comparably more reliable than any public transport alternative (metro or bus). Providing
information about the service of public transport is necessary in order to improve its image in terms of reliability. Yet,
how such information is framed is crucial given that information about punctual delays can be filtered and used to further
justify car choice. At the same time, the car is also favoured because of its connection to people’s reputation and self-esteem.
This connection does not exist for public transport, which creates a comparative disadvantage with the car in social and
302
M. Garcia-Sierra et al. / Transportation Research Part D 41 (2015) 288–305
affective terms that adds up to that of perceived reliability. While ways in which this can be addressed have been highlighted, more effective interventions could still be tested. Last but not least, research could identify additional heuristics that
have not been detected yet. Thereby, further research in this line is also encouraged.
Acknowledgements
The authors acknowledge the support of the Spanish Ministry of Economy and Competitiveness under the program Plan
Nacional de I+D+i, and the Universitat Autònoma de Barcelona (UAB). We would also like to thank an anonymous reviewer
for detailed and constructive comments.
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Behavioural economics, travel behaviour and environmental-transport policy
The transport sector creates much environmental pressure. Many current policies aimed at
reducing this pressure are not fully effective because the behavioural aspects of travellers
are insufficiently recognised. Insights from behavioural economics can contribute to a better
understanding of travel behaviour and choices, and the impact of these on policies.
Nevertheless, few studies have examined this issue. We review these and provide a
broader, more encompassing perspective on environmental policy focused on transport,
and taking into account bounded rationality as well as social preferences....Read more
