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Psychology of sustainable travel behavior
Transportation Research Part A 48 (2013) 19–24
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Editorial
Psychology of sustainable travel behavior 1. Introduction Organizing the way people travel in a more sustainable way is a key challenge. This changes the definition of transportation problems, the influencing factors as well as the types of solutions that need to be considered. It also influences the transport research agenda. The new challenge furthermore places in focus the psychology of the transport user who is now perceived as an active agent in the transport system. Thus, transport policy measures will be more successful if taking into account users’ capabilities and perceived constraints. The influence of psychology on transportation research is not new. Already in the 1970s attitude theory developed in social psychology by Fishbein and Ajzen (1975, 2010) had an impact on travel behavior analysis and research (e.g., Golob et al., 1979; Koppelman and Lyon, 1981). This impact was subsequently overruled by discrete-choice modeling, pioneered by Nobel laureate Daniel McFadden (2001). The development of stated preference methods (e.g., Hensher, 1994; Louviere et al., 2000) is a parallel, related achievement that likewise diminished the impact of attitude theory. The common theoretical foundation was random utility theory (Ben-Akiva and Lerman, 1985), an outgrow of expected utility theory that is the foundation of micro-economic choice theory. Ben-Akiva et al. (1999), Gärling (1998), Gärling et al. (1998), and Svenson (1998) argue that more recent developments of attitude theory as well as of behavioral judgment and decision making research should have an impact. Li and Hensher (2011) and van de Kaa (2010) provide reviews of such recent developments. The work on behaviorally realistic computational process models of activity-based travel choice (e.g., Axhausen and Gärling, 1992; Gärling, 2004; Ettema and Timmermans, 1997; Jones et al., 1983) is also an outcome of these and similar appeals. Since sustainable travel has become a major concern it has motivated a plethora of research on travel behavior focusing on how to make people change to more sustainable travel. This research started with the analysis of behavioral responses to particular transport policy measures and technologies such as pricing instruments (e.g., Gehlert et al., 2008; Gerike et al., 2008; Loukopoulos, 2007; Steg and Schuitema, 2007), traveler information systems (e.g., Chorus et al., 2006; Dziekan and Kottenhoff, 2007), and methods of voluntary travel behavior change (e.g., Bamberg et al., 2011; Bamberg and Möser, 2007; Möser and Bamberg, 2008). The recent boost in the electrification of transport has further promoted a renewed focus on the underlying psychological principles of individual travel behavior. In contrast to conventional car use, electric vehicles (EVs) impose more severe constraints on use and therefore on EV users. In addition the integration of EVs into the overall energy grid requires active user participation. The special issue aims at providing a spotlight on this third generation of psychological research applied to travel behavior. It includes selected papers from the symposium ‘‘Psychology of Sustainable Mobility’’ convened by us at the 9th Biennal Conference of Environmental Psychology in September 2011, Eindhoven, The Netherlands. The aim of the special issue is to demonstrate how theories, methods, and results of psychological research may contribute to transport research with the aim of designing and implementing sustainable transport policies. The papers in this special issue reflect the fact that transport is an interdisciplinary field. Transport psychologists are often collaborating with scholars in other disciplines such as transport engineers, transport economist, and transport planners. The papers thus also highlight the value of an interdisciplinary approach. In this introduction we first present a conceptual framework which aids in organizing the papers included in the special issue. Each paper is then briefly summarized. We finish the introduction by highlighting some promising lines of future research. 2. Conceptual framework Several theories in social and environmental psychology as well as travel behavior research help to explain how users act and react in the transport system. Individual mobility is determined by an interaction of driving factors that are both internal to a person and external. A hierarchy of decisions are made by travelers where decisions at a higher level determine the 0965-8564/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tra.2012.10.001
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scope of actions at lower levels. For example, travel behavior is determined by long-term spatial decision such as choosing place of residence or workplace. If people choose to live in the suburbs without public transport, they cannot choose public transport as an option for travel. Within situational constraints person factors determine travel behavior. These personal factors are the main focus of the special issue. Fig. 1 shows the conceptual framework which integrates relevant theoretical concepts along the decision process from planning to travel to actually traveling. Users need to acquire and process information about the transport system and their travel options as well as the consequences of choosing them. Information is frequently evaluated in biased ways. For example, prospect theory (Kahneman, 2011) posits that people react more strongly to information about potential losses. Travel behavior is also influenced by norms and values that describe social expectations about behavior. For instance, the norm-activation model (Schwartz, 1977; Schwartz and Howard, 1981) and the value-belief-norm theory (Stern et al., 1999) propose that the driving force of behavior is a strong intrinsic feeling of obligation, referred to as a personal norm. The influence of attitudes on behavior is most prominently treated in the theory of planned behavior (Ajzen, 1991; Fishbein and Ajzen, 2010). If people have a positive attitude towards the behavior outcome, if they think that significant others approve that they perform the behavior, and if they believe they will successfully perform the behavior, then the intention to perform the behavior is strong. Several factors may still interfere with performance of the behavior (Fujii and Gärling, 2003). One such factor is habit, making it difficult to implement intentions to change a behavior (Verplanken et al., 1994, 1997). Also as argued by Gärling et al. (2002b) based on self-regulation theory (Carver and Scheier, 1998), behavioral change options are chosen on the basis of a psychological cost/benefit ratio. Psychological costs include increased planning efforts, activity suppression, and increased time pressure. 3. Overview of papers In this special issue papers are selected that draw on theories and constructs related to information, norms, values, attitudes, and actual behavior. They illustrate some theoretical foundations of the psychology of sustainable travel behavior and their application in the design and implementation of transport measures and policies. 3.1. Information Information about transport options include travel times, travel distance, travel costs, fuel consumption, CO2 emission and more. Based on research in psychology and behavioral economics, it is to be expected that this information is processed differently depending on how it is presented. For example, it has been found that people have difficulty in understanding travel costs (Gehlert and Nielsen, 2007) or long term environmental consequences such as carbon dioxide (CO2) emissions (e.g., Coulter et al., 2007). Two papers in the special issue investigate effects of design and presentation of travel-related information. Francke and Kaniok analyse how differentiated pricing information influence people’s travel decision-making process. In a laboratory experiment the degree of price differentiation is systematically varied. From these results the authors make recommendations for an optimal price structure. Avineri and Waygood show the influence of valence framing (describing an outcome as positive or negative) on how much people perceive that different travel modes emit CO2. They discuss the potential to apply valence framing to influence travel mode choice as well other travel choices. 3.2. Norms and values Motives for travel express norms and values. In many approaches to travel behavior such motives are believed to be exclusively instrumental, including travel costs, travel time, and reliability. In more recent research affective motives (e.g., pleasure to drive) and symbolic (self-presentation) motives have been shown to be important for understanding car use (Gatersleben, 2007; Jakobsson Bergstad et al., 2011; Steg, 2005; Steg et al., 2001). In this vein Schuitema, Anable, Skippon, and Kinnear investigate the role of attributes related to instrumental, affective, and symbolic motives for intentions to
Fig. 1. Conceptual framework identifying person factors influencing sustainable travel behavior.
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purchase an electric vehicle (EV). They show that the effect of instrumental motives (performance, running costs, flexibility, range) are partially or completely mediated by affective and symbolic attributes. Adoption of an EV is also associated with a pro-environmental self-identity but not with a ‘‘car-authority’’ self-identity. The new understanding of motives for adopting EVs is clearly important in informing marketing strategies for promoting EV adoption. Their contribution also shows that ‘‘instrumental’’ attributes (e.g., speed) may in fact fully reflect affective and symbolic motives. 3.3. Attitudes Negative public attitudes towards transport policies have been widely considered to be a key challenge to their implementation. Especially for non-voluntary measures such as pricing policies, ensuring public acceptability is crucial for their implementation (Schade and Schlag, 2003). Research has identified several determinants of public acceptability such as problem awareness, perceived fairness, and perceived effectiveness (e.g., Eriksson et al., 2006). Thus, public acceptability should be understood and taken into account in the design and implementation of road pricing. Kim, Schmöcker, Fujii, and Noland extend this knowledge by analysing how trust in governments influences public acceptability of road pricing policies compared to environmental taxation. They emphasize that citizens’ trust in institutions and their general awareness of environmental and societal problems determine public acceptability besides how the road pricing scheme is designed. New transport infrastructure often faces public-acceptability problems as well. The so-called ‘‘Not in my backyard’’ (NIMBY) phenomenon describes residents’ opposition against a new infrastructure nearby by simultaneously acknowledging the collective utility on a regional or national scale (Dear, 1992). New transport infrastructure usually demands large investments and long-term planning. Public opposition prolonging the implementation would have severe financial consequences. Hujits, De Groot, Molin, and van Wee analyse whether people living close are in favor or against a hydrogen refueling station and which factors influence their attitudes. Specifically, they find that both moral concerns and self-interests are important. Thus, policy makers should not assume that citizens are only driven by self-interest, but that they also have moral concerns associated with infrastructure developments. Bolstering the latter would be important. Participative approaches are recommended for increasing public acceptability of transport policies (e.g., Rupprecht Consult, 2011). Transport professionals may have different views on transport issues than the public. Xenias and Whitmarsh shed light on the question of how attitudes towards sustainable transport options differ between affected citizens and transport professionals. Their results illustrate that citizens follow a pragmatic approach based on their own experience when evaluating transport options. In contrast, transport professionals apply a top-down approach based on their theoretical knowledge and expertise. These differences may explain weak public support for certain measures favored by transport researchers. These results are valuable for understanding expert-public gaps in views as well as ways of overcoming such gaps with participative approaches. 3.4. Behavioral intention Behavioral intentions are posit to be immediate antecedents of behavior (Fishbein and Ajzen, 1975, 2010). Therefore, analysing behavioral intentions and their antecedents may inform transport planners about people’s future transport choices in early phases of transport policy and transport infrastructure implementation when actual behavior cannot yet be studied. This either allows for adjustments of traveller’s expectations or the policy/infrastructure itself in advance. Nordlund and Westin analyze the intention to use a new major rail service on the north-east coast of Sweden, where it will become an entirely new travel mode for regional and national travel. The results show a hierarchical influence on train use intentions from basic values and general beliefs about cars and trains through specific infrastructure beliefs. The youngest age group is found to be more open to change by expressing a stronger intention to choose train over car and thus may be more likely to switch from car. The authors also highlight the importance of meeting expectations by potential future users for translating their intentions into actual behavior. 3.5. Behavior Explaining, forecasting, and changing travel behavior are important goals. The successful implementation of new transport policies, measures or technology depends on whether or not people adapt their travel behavior as intended by these developments. Several of the psychological theories that have been applied to explain travel behavior, most notably the Theory of Planned Behavior (Ajzen, 1991) and the Value Belief Norm Theory (Stern et al., 1999) have difficulties in accounting for changes in behavior. Therefore, other theories have been proposed, including the trans-theoretical model (Prochaska and DiClemente, 1982) and self-regulation theories (Bamberg et al., 2011; Carver and Scheier, 1998; Gärling et al., 2002a). Different forms of behavior in transport have been studied, for instance car purchase (e.g., Peters et al., 2011), car-use reduction (Graham-Rowe et al., 2011), and habits (Verplanken et al., 1994, 1997). The recent boost in the electrification of transport has renewed the interest in electric vehicles (EVs). This has raised new questions concerning as behavioral adaptation to limited range or the prediction of one’s own mobility. Nayum, Klöckner, and Prugsamatz analyze the influence of socio-demographic and psychological factors such as attitudes and norms on the purchase of fuel-efficient cars. Their results indicate that the level of CO2 emission of a newly purchased
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car is jointly determined by the type of car, a strong intention to buy a fuel-efficient car, and place of residence. The authors conclude that people select cars with less CO2 emissions within a certain car-type class if their intention is to purchase a fuel-efficient car. Thus, new car classifications based on fuel efficiency may increase market penetration of fuel efficient cars. Furthermore, as traditional car classes based on engine size, power or drive system are already becoming difficult to maintain, psychological factors such as attitudes, intentions, and norms become more important for car purchase. This opens new perspectives for influencing car purchases. Franke and Krems analyze car driver’s behavioral adaption to the limited range of electric vehicles (EVs). Optimal range utilization in terms of trip planning, charging strategies, and energy-efficient driving style are regarded as important prerequisites for EV market penetration. The authors conceptualize range utilization as a control task to maintain a preferred state (e.g., staying within personal range comfort zone) with regulation processes being dependent on personality variables like control beliefs and environmental factors, for instance route characteristics. As a consequence, on average drivers utilize only 75–80% of the battery capacity. Enhancing individuals’ control beliefs in dealing with EVs, providing sufficient EV knowledge when purchasing the EV, and daily driving practice would likely lead to higher range utilization. The use of Intelligent Load Management Systems (ILMSs) would facilitate charging of EVs with electricity from renewable sources. ILMS would also make EVs a potential energy buffer to smooth peaks and to stabilize the energy grid. At the same time, effective implementation of ILMS requires active user participation in that drivers would need to predict departure times and lengths of upcoming trips. Hahnel, Gölz, and Spada report a field study to investigate how accurately drivers (of gas-powered cars) are able to make such predictions. In general participants predict departure times and trip lengths accurately, but they underestimate the number of trips. Predictions are more accurate for work than shopping and leisure trips, and they are more accurate when the trip is planned close in time. The authors discuss several implications for how to take their results into account in designing ILMS. 3.6. Behavior consequences Traditionally travel time and costs are regarded as important determinants of travel behavior. At an aggregate level these attributes are the backbone of transport policy appraisal through cost-benefit analysis (e.g., Emberger et al., 2008). This approach is based on random utility theory assuming that travelers balance travel costs against travel time to maximize personal advantage when making travel choices (Ben-Akiva and Lerman, 1985). This notion has been frequently criticized for neglecting subjective outcomes of travel choice such as comfort, convenience, and social interactions (Ben-Akiva et al., 1999; Gärling, 1998; Gärling et al., 1998; Svenson, 1998; van Wee, 2012). Adapting measures of subjective well-being (e.g., Busseri and Sadava, 2011; Diener et al., 1985; Pavot and Diener, 1993) provide an alternative method for assessing the value of different travel modes and appraising transport policies, respectively. In this vein Friman, Fujii, Ettema, Gärling, and Olsson evaluate the psychometric properties of a self-report measure of travel-related subjective well-being referred to as the Satisfaction with Travel Scale (STS). The scale comprises cognitive evaluations (e.g., ‘‘works poorly vs. well’’) as well as evaluations on two orthogonal affect dimensions referred to as valence and activation (Russell, 2003; Västfjäll et al., 2002), positive deactivation (e.g., ‘‘relaxed vs. stressed’’) and positive activation (e.g., ‘‘bored vs. enthusiastic’’). The results provide empirical support for the invariance of the structure and reliability of STS for measuring satisfaction with daily travel in general, satisfaction with commuting in different urban areas, and commuting by different travel modes. 4. Future research The papers in this special issue provide examples of how psychological theory, methods and results may improve the understanding of travel behavior, contribute to the design of transport policy measures, and enhance the effectiveness of transport policy as a whole. In this final section we want to highlight a few valuable directions for research by transport psychologists. Most of the papers in the special issue focus on policies or behavior related to private car use. The reason is probably that the private car is still the main travel mode but also the allocation of research budgets. Yet, increasingly in transport research there are research addressing how to combine travel modes. This is something transport psychologists should be aware of when formulating their research questions. Also, research of single travel modes such as walking, cycling or public transport is still rather sparse despite that there are many important research questions remaining. For example, what makes walking so different in people’s perception that it is hardly regarded as a transport mode and thus often underreported by people themselves – but also neglected in transport research and policy? Travel behavior is jointly determined by individual factors, social influences, and the transport environment. There has been much travel behavior research on the single impact of these factors. Future research should clarify theoretically and empirically how these factors interact in jointly impacting on travel behavior. Specifically, what are the causal links between psychological, social, spatial factors, and travel behavior? The aim is to gain a better understanding of the complexity of determinants of travel behaviour, and the behavioral adaptation process to changing circumstances. This is a challenge to interdisciplinary research in which transport psychologists should be involved.
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Acknowledgements We would like to express our sincere thanks to the following colleagues who reviewed the papers and thereby importantly contributed to the quality of the special issue: Anke Blöbaum, Peter Bonsall, Peter Cocron, Graham Currie, Thomas Franke, Margareta Friman, Satoshi Fujii, Birgitta Gatersleben, Carmen Hagemeister, Ulf Hahnel, Cecilia Jakobsson, Johan Jansson, Florian Kaiser, Christian Klöckner, Junghwa Kim, Josef Krems, Tony May, Annika Nordlund, Piet Rietveld, Jan-Dirk Schmöcker, Hans Spada, Steve Skippon, Geertje Schuitema, and Bert van Wee. References Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes 50, 179–211. Axhausen, K.W., Gärling, T., 1992. Activity-based approaches to travel analysis: conceptual frameworks, models, and research problems. Transport Reviews 12, 323–341. Bamberg, S., Möser, G., 2007. Why are work travel plans effective? 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Tina Gehlert German Insurers Accident Research, Traffic Behaviour/Traffic Psychology, Berlin, Germany Tel.: +49 30 2020 5822 E-mail address: [email protected] Katrin Dziekan Federal Environment Agency, Section Environment and Transport, Dessau-Roßlau, Germany Tel.: +49 340 2103 6555 E-mail address: [email protected] Tommy Gärling Department of Psychology, University of Gothenburg, Göteborg, and Service and Market Oriented Transport Research Group (SAMOT), Karlstad University, Sweden Tel.: +46 31 776 1881 E-mail address: [email protected]
Contents lists available at SciVerse ScienceDirect
Transportation Research Part A journal homepage: www.elsevier.com/locate/tra
Editorial
Psychology of sustainable travel behavior 1. Introduction Organizing the way people travel in a more sustainable way is a key challenge. This changes the definition of transportation problems, the influencing factors as well as the types of solutions that need to be considered. It also influences the transport research agenda. The new challenge furthermore places in focus the psychology of the transport user who is now perceived as an active agent in the transport system. Thus, transport policy measures will be more successful if taking into account users’ capabilities and perceived constraints. The influence of psychology on transportation research is not new. Already in the 1970s attitude theory developed in social psychology by Fishbein and Ajzen (1975, 2010) had an impact on travel behavior analysis and research (e.g., Golob et al., 1979; Koppelman and Lyon, 1981). This impact was subsequently overruled by discrete-choice modeling, pioneered by Nobel laureate Daniel McFadden (2001). The development of stated preference methods (e.g., Hensher, 1994; Louviere et al., 2000) is a parallel, related achievement that likewise diminished the impact of attitude theory. The common theoretical foundation was random utility theory (Ben-Akiva and Lerman, 1985), an outgrow of expected utility theory that is the foundation of micro-economic choice theory. Ben-Akiva et al. (1999), Gärling (1998), Gärling et al. (1998), and Svenson (1998) argue that more recent developments of attitude theory as well as of behavioral judgment and decision making research should have an impact. Li and Hensher (2011) and van de Kaa (2010) provide reviews of such recent developments. The work on behaviorally realistic computational process models of activity-based travel choice (e.g., Axhausen and Gärling, 1992; Gärling, 2004; Ettema and Timmermans, 1997; Jones et al., 1983) is also an outcome of these and similar appeals. Since sustainable travel has become a major concern it has motivated a plethora of research on travel behavior focusing on how to make people change to more sustainable travel. This research started with the analysis of behavioral responses to particular transport policy measures and technologies such as pricing instruments (e.g., Gehlert et al., 2008; Gerike et al., 2008; Loukopoulos, 2007; Steg and Schuitema, 2007), traveler information systems (e.g., Chorus et al., 2006; Dziekan and Kottenhoff, 2007), and methods of voluntary travel behavior change (e.g., Bamberg et al., 2011; Bamberg and Möser, 2007; Möser and Bamberg, 2008). The recent boost in the electrification of transport has further promoted a renewed focus on the underlying psychological principles of individual travel behavior. In contrast to conventional car use, electric vehicles (EVs) impose more severe constraints on use and therefore on EV users. In addition the integration of EVs into the overall energy grid requires active user participation. The special issue aims at providing a spotlight on this third generation of psychological research applied to travel behavior. It includes selected papers from the symposium ‘‘Psychology of Sustainable Mobility’’ convened by us at the 9th Biennal Conference of Environmental Psychology in September 2011, Eindhoven, The Netherlands. The aim of the special issue is to demonstrate how theories, methods, and results of psychological research may contribute to transport research with the aim of designing and implementing sustainable transport policies. The papers in this special issue reflect the fact that transport is an interdisciplinary field. Transport psychologists are often collaborating with scholars in other disciplines such as transport engineers, transport economist, and transport planners. The papers thus also highlight the value of an interdisciplinary approach. In this introduction we first present a conceptual framework which aids in organizing the papers included in the special issue. Each paper is then briefly summarized. We finish the introduction by highlighting some promising lines of future research. 2. Conceptual framework Several theories in social and environmental psychology as well as travel behavior research help to explain how users act and react in the transport system. Individual mobility is determined by an interaction of driving factors that are both internal to a person and external. A hierarchy of decisions are made by travelers where decisions at a higher level determine the 0965-8564/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tra.2012.10.001
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scope of actions at lower levels. For example, travel behavior is determined by long-term spatial decision such as choosing place of residence or workplace. If people choose to live in the suburbs without public transport, they cannot choose public transport as an option for travel. Within situational constraints person factors determine travel behavior. These personal factors are the main focus of the special issue. Fig. 1 shows the conceptual framework which integrates relevant theoretical concepts along the decision process from planning to travel to actually traveling. Users need to acquire and process information about the transport system and their travel options as well as the consequences of choosing them. Information is frequently evaluated in biased ways. For example, prospect theory (Kahneman, 2011) posits that people react more strongly to information about potential losses. Travel behavior is also influenced by norms and values that describe social expectations about behavior. For instance, the norm-activation model (Schwartz, 1977; Schwartz and Howard, 1981) and the value-belief-norm theory (Stern et al., 1999) propose that the driving force of behavior is a strong intrinsic feeling of obligation, referred to as a personal norm. The influence of attitudes on behavior is most prominently treated in the theory of planned behavior (Ajzen, 1991; Fishbein and Ajzen, 2010). If people have a positive attitude towards the behavior outcome, if they think that significant others approve that they perform the behavior, and if they believe they will successfully perform the behavior, then the intention to perform the behavior is strong. Several factors may still interfere with performance of the behavior (Fujii and Gärling, 2003). One such factor is habit, making it difficult to implement intentions to change a behavior (Verplanken et al., 1994, 1997). Also as argued by Gärling et al. (2002b) based on self-regulation theory (Carver and Scheier, 1998), behavioral change options are chosen on the basis of a psychological cost/benefit ratio. Psychological costs include increased planning efforts, activity suppression, and increased time pressure. 3. Overview of papers In this special issue papers are selected that draw on theories and constructs related to information, norms, values, attitudes, and actual behavior. They illustrate some theoretical foundations of the psychology of sustainable travel behavior and their application in the design and implementation of transport measures and policies. 3.1. Information Information about transport options include travel times, travel distance, travel costs, fuel consumption, CO2 emission and more. Based on research in psychology and behavioral economics, it is to be expected that this information is processed differently depending on how it is presented. For example, it has been found that people have difficulty in understanding travel costs (Gehlert and Nielsen, 2007) or long term environmental consequences such as carbon dioxide (CO2) emissions (e.g., Coulter et al., 2007). Two papers in the special issue investigate effects of design and presentation of travel-related information. Francke and Kaniok analyse how differentiated pricing information influence people’s travel decision-making process. In a laboratory experiment the degree of price differentiation is systematically varied. From these results the authors make recommendations for an optimal price structure. Avineri and Waygood show the influence of valence framing (describing an outcome as positive or negative) on how much people perceive that different travel modes emit CO2. They discuss the potential to apply valence framing to influence travel mode choice as well other travel choices. 3.2. Norms and values Motives for travel express norms and values. In many approaches to travel behavior such motives are believed to be exclusively instrumental, including travel costs, travel time, and reliability. In more recent research affective motives (e.g., pleasure to drive) and symbolic (self-presentation) motives have been shown to be important for understanding car use (Gatersleben, 2007; Jakobsson Bergstad et al., 2011; Steg, 2005; Steg et al., 2001). In this vein Schuitema, Anable, Skippon, and Kinnear investigate the role of attributes related to instrumental, affective, and symbolic motives for intentions to
Fig. 1. Conceptual framework identifying person factors influencing sustainable travel behavior.
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purchase an electric vehicle (EV). They show that the effect of instrumental motives (performance, running costs, flexibility, range) are partially or completely mediated by affective and symbolic attributes. Adoption of an EV is also associated with a pro-environmental self-identity but not with a ‘‘car-authority’’ self-identity. The new understanding of motives for adopting EVs is clearly important in informing marketing strategies for promoting EV adoption. Their contribution also shows that ‘‘instrumental’’ attributes (e.g., speed) may in fact fully reflect affective and symbolic motives. 3.3. Attitudes Negative public attitudes towards transport policies have been widely considered to be a key challenge to their implementation. Especially for non-voluntary measures such as pricing policies, ensuring public acceptability is crucial for their implementation (Schade and Schlag, 2003). Research has identified several determinants of public acceptability such as problem awareness, perceived fairness, and perceived effectiveness (e.g., Eriksson et al., 2006). Thus, public acceptability should be understood and taken into account in the design and implementation of road pricing. Kim, Schmöcker, Fujii, and Noland extend this knowledge by analysing how trust in governments influences public acceptability of road pricing policies compared to environmental taxation. They emphasize that citizens’ trust in institutions and their general awareness of environmental and societal problems determine public acceptability besides how the road pricing scheme is designed. New transport infrastructure often faces public-acceptability problems as well. The so-called ‘‘Not in my backyard’’ (NIMBY) phenomenon describes residents’ opposition against a new infrastructure nearby by simultaneously acknowledging the collective utility on a regional or national scale (Dear, 1992). New transport infrastructure usually demands large investments and long-term planning. Public opposition prolonging the implementation would have severe financial consequences. Hujits, De Groot, Molin, and van Wee analyse whether people living close are in favor or against a hydrogen refueling station and which factors influence their attitudes. Specifically, they find that both moral concerns and self-interests are important. Thus, policy makers should not assume that citizens are only driven by self-interest, but that they also have moral concerns associated with infrastructure developments. Bolstering the latter would be important. Participative approaches are recommended for increasing public acceptability of transport policies (e.g., Rupprecht Consult, 2011). Transport professionals may have different views on transport issues than the public. Xenias and Whitmarsh shed light on the question of how attitudes towards sustainable transport options differ between affected citizens and transport professionals. Their results illustrate that citizens follow a pragmatic approach based on their own experience when evaluating transport options. In contrast, transport professionals apply a top-down approach based on their theoretical knowledge and expertise. These differences may explain weak public support for certain measures favored by transport researchers. These results are valuable for understanding expert-public gaps in views as well as ways of overcoming such gaps with participative approaches. 3.4. Behavioral intention Behavioral intentions are posit to be immediate antecedents of behavior (Fishbein and Ajzen, 1975, 2010). Therefore, analysing behavioral intentions and their antecedents may inform transport planners about people’s future transport choices in early phases of transport policy and transport infrastructure implementation when actual behavior cannot yet be studied. This either allows for adjustments of traveller’s expectations or the policy/infrastructure itself in advance. Nordlund and Westin analyze the intention to use a new major rail service on the north-east coast of Sweden, where it will become an entirely new travel mode for regional and national travel. The results show a hierarchical influence on train use intentions from basic values and general beliefs about cars and trains through specific infrastructure beliefs. The youngest age group is found to be more open to change by expressing a stronger intention to choose train over car and thus may be more likely to switch from car. The authors also highlight the importance of meeting expectations by potential future users for translating their intentions into actual behavior. 3.5. Behavior Explaining, forecasting, and changing travel behavior are important goals. The successful implementation of new transport policies, measures or technology depends on whether or not people adapt their travel behavior as intended by these developments. Several of the psychological theories that have been applied to explain travel behavior, most notably the Theory of Planned Behavior (Ajzen, 1991) and the Value Belief Norm Theory (Stern et al., 1999) have difficulties in accounting for changes in behavior. Therefore, other theories have been proposed, including the trans-theoretical model (Prochaska and DiClemente, 1982) and self-regulation theories (Bamberg et al., 2011; Carver and Scheier, 1998; Gärling et al., 2002a). Different forms of behavior in transport have been studied, for instance car purchase (e.g., Peters et al., 2011), car-use reduction (Graham-Rowe et al., 2011), and habits (Verplanken et al., 1994, 1997). The recent boost in the electrification of transport has renewed the interest in electric vehicles (EVs). This has raised new questions concerning as behavioral adaptation to limited range or the prediction of one’s own mobility. Nayum, Klöckner, and Prugsamatz analyze the influence of socio-demographic and psychological factors such as attitudes and norms on the purchase of fuel-efficient cars. Their results indicate that the level of CO2 emission of a newly purchased
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car is jointly determined by the type of car, a strong intention to buy a fuel-efficient car, and place of residence. The authors conclude that people select cars with less CO2 emissions within a certain car-type class if their intention is to purchase a fuel-efficient car. Thus, new car classifications based on fuel efficiency may increase market penetration of fuel efficient cars. Furthermore, as traditional car classes based on engine size, power or drive system are already becoming difficult to maintain, psychological factors such as attitudes, intentions, and norms become more important for car purchase. This opens new perspectives for influencing car purchases. Franke and Krems analyze car driver’s behavioral adaption to the limited range of electric vehicles (EVs). Optimal range utilization in terms of trip planning, charging strategies, and energy-efficient driving style are regarded as important prerequisites for EV market penetration. The authors conceptualize range utilization as a control task to maintain a preferred state (e.g., staying within personal range comfort zone) with regulation processes being dependent on personality variables like control beliefs and environmental factors, for instance route characteristics. As a consequence, on average drivers utilize only 75–80% of the battery capacity. Enhancing individuals’ control beliefs in dealing with EVs, providing sufficient EV knowledge when purchasing the EV, and daily driving practice would likely lead to higher range utilization. The use of Intelligent Load Management Systems (ILMSs) would facilitate charging of EVs with electricity from renewable sources. ILMS would also make EVs a potential energy buffer to smooth peaks and to stabilize the energy grid. At the same time, effective implementation of ILMS requires active user participation in that drivers would need to predict departure times and lengths of upcoming trips. Hahnel, Gölz, and Spada report a field study to investigate how accurately drivers (of gas-powered cars) are able to make such predictions. In general participants predict departure times and trip lengths accurately, but they underestimate the number of trips. Predictions are more accurate for work than shopping and leisure trips, and they are more accurate when the trip is planned close in time. The authors discuss several implications for how to take their results into account in designing ILMS. 3.6. Behavior consequences Traditionally travel time and costs are regarded as important determinants of travel behavior. At an aggregate level these attributes are the backbone of transport policy appraisal through cost-benefit analysis (e.g., Emberger et al., 2008). This approach is based on random utility theory assuming that travelers balance travel costs against travel time to maximize personal advantage when making travel choices (Ben-Akiva and Lerman, 1985). This notion has been frequently criticized for neglecting subjective outcomes of travel choice such as comfort, convenience, and social interactions (Ben-Akiva et al., 1999; Gärling, 1998; Gärling et al., 1998; Svenson, 1998; van Wee, 2012). Adapting measures of subjective well-being (e.g., Busseri and Sadava, 2011; Diener et al., 1985; Pavot and Diener, 1993) provide an alternative method for assessing the value of different travel modes and appraising transport policies, respectively. In this vein Friman, Fujii, Ettema, Gärling, and Olsson evaluate the psychometric properties of a self-report measure of travel-related subjective well-being referred to as the Satisfaction with Travel Scale (STS). The scale comprises cognitive evaluations (e.g., ‘‘works poorly vs. well’’) as well as evaluations on two orthogonal affect dimensions referred to as valence and activation (Russell, 2003; Västfjäll et al., 2002), positive deactivation (e.g., ‘‘relaxed vs. stressed’’) and positive activation (e.g., ‘‘bored vs. enthusiastic’’). The results provide empirical support for the invariance of the structure and reliability of STS for measuring satisfaction with daily travel in general, satisfaction with commuting in different urban areas, and commuting by different travel modes. 4. Future research The papers in this special issue provide examples of how psychological theory, methods and results may improve the understanding of travel behavior, contribute to the design of transport policy measures, and enhance the effectiveness of transport policy as a whole. In this final section we want to highlight a few valuable directions for research by transport psychologists. Most of the papers in the special issue focus on policies or behavior related to private car use. The reason is probably that the private car is still the main travel mode but also the allocation of research budgets. Yet, increasingly in transport research there are research addressing how to combine travel modes. This is something transport psychologists should be aware of when formulating their research questions. Also, research of single travel modes such as walking, cycling or public transport is still rather sparse despite that there are many important research questions remaining. For example, what makes walking so different in people’s perception that it is hardly regarded as a transport mode and thus often underreported by people themselves – but also neglected in transport research and policy? Travel behavior is jointly determined by individual factors, social influences, and the transport environment. There has been much travel behavior research on the single impact of these factors. Future research should clarify theoretically and empirically how these factors interact in jointly impacting on travel behavior. Specifically, what are the causal links between psychological, social, spatial factors, and travel behavior? The aim is to gain a better understanding of the complexity of determinants of travel behaviour, and the behavioral adaptation process to changing circumstances. This is a challenge to interdisciplinary research in which transport psychologists should be involved.
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Acknowledgements We would like to express our sincere thanks to the following colleagues who reviewed the papers and thereby importantly contributed to the quality of the special issue: Anke Blöbaum, Peter Bonsall, Peter Cocron, Graham Currie, Thomas Franke, Margareta Friman, Satoshi Fujii, Birgitta Gatersleben, Carmen Hagemeister, Ulf Hahnel, Cecilia Jakobsson, Johan Jansson, Florian Kaiser, Christian Klöckner, Junghwa Kim, Josef Krems, Tony May, Annika Nordlund, Piet Rietveld, Jan-Dirk Schmöcker, Hans Spada, Steve Skippon, Geertje Schuitema, and Bert van Wee. References Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes 50, 179–211. Axhausen, K.W., Gärling, T., 1992. Activity-based approaches to travel analysis: conceptual frameworks, models, and research problems. Transport Reviews 12, 323–341. Bamberg, S., Möser, G., 2007. Why are work travel plans effective? 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Tina Gehlert German Insurers Accident Research, Traffic Behaviour/Traffic Psychology, Berlin, Germany Tel.: +49 30 2020 5822 E-mail address: [email protected] Katrin Dziekan Federal Environment Agency, Section Environment and Transport, Dessau-Roßlau, Germany Tel.: +49 340 2103 6555 E-mail address: [email protected] Tommy Gärling Department of Psychology, University of Gothenburg, Göteborg, and Service and Market Oriented Transport Research Group (SAMOT), Karlstad University, Sweden Tel.: +46 31 776 1881 E-mail address: [email protected]