The influence of information-based Transport Demand Management measures on commuting mode choice. Comparing web vs. face-to-face surveys

We test the effect of different contextualization, scaling, framing and formatting of environmental impacts and health benefits information on commuting mode choice. For this, a stated preference (SP) survey was designed. To also test survey mode effect, the survey was administrated both online and face-to-face. We find statistical differences across the two samples in terms of transport preferences, attitudes and perceptions towards the environment, health and social norms. These could be attributed both to differences in the levels of education and professional occupation and self-selection bias. The results in the models estimated from the SP hint the existence of irrational answers in the web-based sample. Information about global CO2 emissions appears to be ineffective in influencing mode choice whereas self-centric information about calories consumption is effective

Applying valence framing to enhance the effect of information on transport-related carbon dioxide emissions

The provision of information about transport-related carbon dioxide (CO2) emissions to the traveler can be seen as an instrument to increase the likelihood of more sustainable choices being made by individuals. However, as transport-related CO2 emissions are largely seen as a 'social' cost rather than a 'private' cost to the individual, the behavioral engagement with and response to information on environmental effects of travel choices may be limited. It is argued that framing, studied in a range of contexts, can be used to enhance the evaluation of choice attributes and promote more sustainable choices. An experiment is reported that examines the effect of valence framing of amounts of CO2 emissions on the perceived differences between alternative amounts. Through the use of positive and negative terms, the information is framed to focus attention either on the potential of a travel mode to provide environmental benefit (positive frame) or on its potential to reduce environmental loss (negative frame). Survey participants' estimates of CO2 amounts were compared for positive and negative framing of the same information using an ordered logit model. The findings imply that negative framing is more effective than positive framing in highlighting differences between CO2 amounts of alternative travel modes and therefore is likely to influence travel-related choices. © 2012 Elsevier Ltd

Improving the behavioral realism of global integrated assessment models:An application to consumers’ vehicle choices

A large body of transport sector-focused research recognizes the complexity of human behavior in relation to mobility. Yet, global integrated assessment models (IAMs), which are widely used to evaluate the costs, potentials, and consequences of different greenhouse gas emission trajectories over the medium-to-long term, typically represent behavior and the end use of energy as a simple rational choice between available alternatives, even though abundant empirical evidence shows that real-world decision making is more complex and less routinely rational. This paper demonstrates the value of incorporating certain features of consumer behavior in IAMs, focusing on light-duty vehicle (LDV) purchase decisions. An innovative model formulation is developed to represent heterogeneous consumer groups with varying preferences for vehicle novelty, range, refueling/recharging availability, and variety. The formulation is then implemented in the transport module of MESSAGE-Transport, a global IAM, although it also has the generic flexibility to be applied in energy-economy models with varying set-ups. Comparison of conventional and ‘behaviorally-realistic’ model runs with respect to vehicle purchase decisions shows that consumer preferences may slow down the transition to alternative fuel (low-carbon) vehicles. Consequently, stronger price-based incentives and/or non-price based measures may be needed to transform the global fleet of passenger vehicles, at least in the initial market phases of novel alternatives. Otherwise, the mitigation burden borne by other transport sub-sectors and other energy sectors could be higher than previously estimated. More generally, capturing behavioral features of energy consumers in global IAMs increases their usefulness to policy makers by allowing a more realistic assessment of a more diverse suite of policies

What Explains the Gender Gap in Schlepping? Testing Various Explanations for Gender Differences in Household-Serving Travel*

Using data from the American Time Use Survey (ATUS), researchers at UCLA and Rutgers find the gender gap in household-serving travel still exists — women are indeed more likely to take these trips than men. To explain this persistent division in household-serving travel, researchers explore the ATUS data using three perspectives: (1) time availability, (2) microeconomic, and (3) gender socialization. Their findings can help transportation planners and researchers better understand travel patterns within households

The Value of Green in Transportation Decisions

To address issues of climate change, information about greenhouse gas emissions is more and more often being presented to people. For example, labels and signs displaying pounds and kilograms of CO2 are showing up in trip planners, in car advertisements, and even in restaurant menus. This is being done under the assumption that the information about the environmental impacts of different alternatives will encourage more sustainable behavior. However, little is known about whether or not this strategy affects the choices people make. In order for people to change their behavior for the benefit of reduced emissions, they first need to place positive value on those reductions. This research aims to answer three questions regarding the efficacy of presenting people with this information: first, do people place significant value on reducing their greenhouse gas emissions, second, can people consistently value a pound of CO2, and third, how does this value of green vary across the population? To answer these questions, five experiments were designed and conducted using discrete choice experiments, a framework typically used to investigate how people value reducing their travel time. UC Berkeley students and residents of the San Francisco Bay Area made stated and revealed preference transportation choices from a set of alternatives. With knowledge of the attributes of their chosen alternative as well as those of their available alternates, their choices were analyzed using logit, mixed logit, and hybrid choice models. The findings include that not only can people consistently interpret and place value on the pounds of CO2 associated with their transportation alternatives, but also that there exists a discrete distribution in the value of green. For all except one experiment, the best models indicate that while a majority of the population does not act as though they care about reducing their greenhouse gas emissions, there is a small group with a willingness to pay of $2.68 per pound of CO2

The Value of Green in Transportation Decisions

To address issues of climate change, information about greenhouse gas emissions is more and more often being presented to people. For example, labels and signs displaying pounds and kilograms of CO2 are showing up in trip planners, in car advertisements, and even in restaurant menus. This is being done under the assumption that the information about the environmental impacts of different alternatives will encourage more sustainable behavior. However, little is known about whether or not this strategy affects the choices people make. In order for people to change their behavior for the benefit of reduced emissions, they first need to place positive value on those reductions. This research aims to answer three questions regarding the efficacy of presenting people with this information: first, do people place significant value on reducing their greenhouse gas emissions, second, can people consistently value a pound of CO2, and third, how does this value of green vary across the population? To answer these questions, five experiments were designed and conducted using discrete choice experiments, a framework typically used to investigate how people value reducing their travel time. UC Berkeley students and residents of the San Francisco Bay Area made stated and revealed preference transportation choices from a set of alternatives. With knowledge of the attributes of their chosen alternative as well as those of their available alternates, their choices were analyzed using logit, mixed logit, and hybrid choice models. The findings include that not only can people consistently interpret and place value on the pounds of CO2 associated with their transportation alternatives, but also that there exists a discrete distribution in the value of green. For all except one experiment, the best models indicate that while a majority of the population does not act as though they care about reducing their greenhouse gas emissions, there is a small group with a willingness to pay of $2.68 per pound of CO2

Revealing the Value of “Green ” and the Small Group with a Big Heart in Transportation Mode Choice

sustainabilit

Experimental Economics in Transportation: A Focus on Social Influences and the Provision of Information

A major aspect of transportation planning is understanding behavior: how to predict it and how to influence it over the long term. Behavioral models in transportation are predominantly rooted in the classic microeconomic paradigm of rationality. However, there is a long history in behavioral economics of raising serious questions about rationality. Behavioral economics has made inroads in transportation in the areas of survey design, prospect theory, and attitudinal variables. Further infusion into transportation could lead to significant benefits in terms of increased ability to both predict and influence behavior. The aim of this research is to investigate the transferability of findings in behavioral economics to transportation, with a focus on lessons regarding personalized information and social influences. We designed and conducted three computer experiments using UC Berkeley students: one on personalized-information and route choice, one on social influences and auto ownership, and one combining information and social influences and pedestrian safety. Our findings suggest high transferability of lessons from behavioral economics and great potential for influencing transport behavior. We found that person- and trip-specific information regarding greenhouse gas emissions has significant potential for increasing sustainable behavior, and we are able to quantify this Value of GREEN at around $0.24/pound of greenhouse gas avoided. Congruent with lessons from behavioral economics, we found that information on peer compliance of pedestrian laws had a stronger influence on pedestrian safety behavior than information on the law, citation rates, or accident statistics. We also found that social influences positively impact the decision to buy a hybrid car over a conventional car or forgo a car altogether