Do social norms regarding carbon offsetting affect individual preferences towards this policy? Results from a stated choice experiment

This study investigates the idea that people’s willingness to offset flight-related carbon emissions is a function of the collective participation rate, which can be regarded as a social norm, towards carbon offsetting. Additionally, we reveal people’s preferences toward two other environmental policies; a baggage allowance and airline eco-efficiency index. A discrete choice experiment is designed and administrated among a sample of air travelers. The results indicate that carbon offsetting generates utility, with people gaining more utility when the collective participation rate is high. Additionally, it was found that the baggage allowance and the eco-efficiency index strongly influenced respondents’ airline choices. People also became more sensitivity towards a baggage allowance and the eco-efficiency label, when the collective offsetting rate was high.     

Correcting for endogeneity in behavioral choice models with social influence variables

While psychologists and behavioral economists emphasize the importance of social influences, an outstanding issue is how to capture such influences in behavioral models used to inform urban planning and policy. In this paper we focus on operational models that do not require explicit knowledge of the individual networks of decision makers. We employ a field effect variable to capture social influences, which is calculated as the percent of population in the peer group that has chosen the specific alternative. We define the peer group based on socio-economic status and spatial proximity of residential location. As in behavioral economics and psychology, the concept is that one is influenced by the choices made by one’s peers. However, using such a social influence variable in a behavioral model causes complications because it is likely endogenous; unobserved factors that impact the peer group also influence the decision maker, yielding correlation between the field effect variable and the error. The contribution of this paper is the use of the Berry, Levinsohn, and Pakes (BLP) method to correct the endogeneity in a choice model. The two-stage BLP introduces constants for each peer group to remove the endogeneity from the choice model (where it is difficult to deal with) and insert it into a linear regression model (where endogeneity is relatively easier to deal with). We test the method using a mode choice data set from the Netherlands and readily available software and find there is an upward bias of the field effect parameter when endogeneity is not corrected. The procedure outlined presents a practical and tractable method for incorporating social influences in choice models.     

Social networks as a source of private-vehicle transportation: The practice of getting rides and borrowing vehicles among Mexican immigrants in California

We examine the role of social networks in enabling access to private-vehicle transportation, through getting rides and borrowing cars. Based on qualitative findings from ten focus group discussions with recent Mexican immigrants to California, half of whom have no car, we describe the extent to which participants depend on rides and borrowed cars for transportation. We highlight the unique aspects of informal access to cars, drawing on social exchange theory and related research to characterize the procurement process and likely levels of exchange. We discuss the implications of these findings for transportation services that might serve this and other community groups.     

Social influences on household location, mobility and activity choice in integrated micro-simulation models

Agent-based approaches to simulating long-term location and mobility decisions and short-term activity and travel decisions of households and individuals are receiving increasing attention in land-use and transportation interaction (LUTI) models to predict land-use changes and travel behaviour in mutual interaction. Social interactions between households and between individuals potentially have an influence on a wide range of the long-term and short-term choices involved in these systems. In this paper we identify the areas in which social interactions play a role and address the question how these influences can be modelled in the context of agent-based LUTI models. We distinguish impacts on activity participation (joint activity participation, support-and-help activities) and impacts on decision making (information exchange, social adaptation of preferences and aspirations) as the two main areas of social influence. A prototype of a LUTI model is proposed that accounts for impacts of the social network on longer-term mobility decision making through information exchange and social adaptation of preferences and aspirations. The model is demonstrated in a numerical simulation.     

Social marginal cost pricing and second best alternatives in partnerships for transport infrastructures

According to the economic theory, if all the first-best conditions are met, social optimality involves the prices to be set equal to social marginal costs. When it is not possible to set prices equal to social marginal costs, due to the presence of constraints within the transport sector or distortions elsewhere in the economy, the theory suggests corrections to the SMC principle (second-best alternatives). But the implementation of second best alternatives can give rise to serious problems when transferred from theory to practice. This chapter will discuss in particular the problems that might rise when investment cost are included (totally or partially) in the social marginal costs rules, and in particular when private operators are involved.     

The GRAAL of carpooling: GReen And sociAL optimization from crowd-sourced data

Carpooling, i.e. the sharing of vehicles to reach common destinations, is often performed to reduce costs and pollution. Recent work on carpooling takes into account, besides mobility matches, also social aspects and, more generally, non-monetary incentives. In line with this, we present GRAAL, a data-driven methodology for GReen And sociAL carpooling. GRAAL optimizes a carpooling system not only by minimizing the number of cars needed at the city level, but also by maximizing the enjoyability of people sharing a trip. We introduce a measure of enjoyability based on people’s interests, social links, and tendency to connect to people with similar or dissimilar interests. GRAAL computes the enjoyability within a set of users from crowd-sourced data, and then uses it on real world datasets to optimize a weighted linear combination of number of cars and enjoyability. To tune this weight, and to investigate the users’ interest on the social aspects of carpooling, we conducted an online survey on potential carpooling users. We present the results of applying GRAAL on real world crowd-sourced data from the cities of Rome and San Francisco. Computational results are presented from both the city and the user perspective. Using the crowd-sourced weight, GRAAL is able to significantly reduce the number of cars needed, while keeping a high level of enjoyability on the tested data-set. From the user perspective, we show how the entire per-car distribution of enjoyability is increased with respect to the baselines.     

Investigating heterogeneity in social influence by social distance in car-sharing decisions under uncertainty: A regret-minimizing hybrid choice model framework based on sequential stated adaptation experiments

The present study is designed to investigate social influence in car-sharing decisions under uncertainty. Social influence indicates that individuals’ decisions are influenced by the choices made by members of their social networks. An individual may experience different degrees of influence depending on social distance, i.e. the strength of the social relationship between individuals. Such heterogeneity in social influence has been largely ignored in the previous travel behavior research. The data used in this study stems from an egocentric social network survey, which measures the strength of the social relationships of each respondent. In addition, a sequential stated adaptation experiment was developed to capture more explicitly the effect of social network choices on the individual decision-making process. Social distance is regarded as a random latent variable. The estimated social distance and social network choices are incorporated into a social influence variable, which is treated as an explanatory variable in the car-sharing decision model. To simultaneously estimate latent social distance and the effects of social influence on the car-sharing decision, we expand the hybrid choice framework to incorporate the latent social distance model into discrete choice analysis. The estimation results show substantial social influence in car-sharing decisions. The magnitude of social influence varies according to the type of relationship, similarity of socio-demographics and the number of social interactions.     

Part II: Policy instruments for sustainable road transport

Without questioning the fact that to achieve efficiency emitters should pay for the true costs of their actions (a core principle of economic policies such as pollution taxes), we find sufficient evidence in the literature to demonstrate that many other policy instruments can be used in combination with taxes and permits to ensure that the transport needs of the present generation can be met without compromising the ability of future generations to meet any needs of their own.The policies and policy aspects considered in this paper broadly fall into three categories: physical policies, soft policies, and knowledge policies. All three aim to bring about changes in consumers’ and firms’ behaviour, but in different ways. The first category includes policies with a physical infrastructure element: public transport, land use, walking and cycling, road construction, and freight transport. We also consider the particular challenges for mobility in developing countries, and how these may be addressed. Soft policies, on the other hand, are non-tangible aiming to bring about behavioural change by informing actors about the consequences of their transport choices, and potentially persuading them to change their behaviour. These measures include car sharing and car pooling, teleworking and teleshopping, eco-driving, as well as general information and advertising campaigns. Finally, knowledge policies emphasise the important role of investment in research and development for a sustainable model of mobility for the future.The main findings can be summarised as follows.

Physical policies

An increase in the use of public transport, combined with a decrease in the use of private cars, can reduce traffic congestion and, more importantly, carbon dioxide (CO₂) emissions, as public transport generally causes lower CO₂ emissions per passenger kilometre than private cars. Public transport fares are subsidised in most places, which can be justified by economies of scale and by the fact that public transport can reduce total road transport externalities. London, Singapore, Portland and Curitiba are all examples of good practice at government level, having achieved reliable, frequent and integrated public transport.Policies to increase public transport use must be part of an integrated policy. Integrated policy refers to integration across different modes of transport, different government objectives (such as the economy, health and the environment), considering the needs of different social groups, and coordinating action between the relevant government institutions. There is evidence that a lack of coordination can jeopardise the achievement of policy objectives.A sustainable model for transport policy also requires integration with land-use policies. These may be somewhat limited within the bounds of existing cities, but as cities grow and new cities are built, urban planners must put more emphasis on land use for sustainable transport in order to reduce congestion and CO₂ emissions. Sustainable land-use policy can direct urban development towards a form that allows public transport as well as walking and cycling to be at the core of urban mobility.Walking and cycling, which improve general health and produce no tailpipe emissions, constitute an excellent alternative to motorised transport on short-distance trips within towns and cities. The policies which can incentivise walking and cycling include crime reduction to make streets safer, well-maintained and clean pavements, attractive street furniture, safe crossings with shorter waiting times, dedicated cycle paths, showers in offices, and lower speed limits, to name but a few.Road construction and expansion used to be seen as one of the most promising ways to reduce traffic congestion. However, in the mid-1990s, the issue was reassessed and it was found that building and expanding roads, increased, rather than decreased, congestion, and ultimately induced higher levels of travel demand. The reason for this is that the extra capacity reduces the general cost of travelling and the less expensive the travel, the more it will be demanded. Regarding freight modal shift, road transport is much more polluting than rail per tonne-km of goods transported and therefore a shift towards greater use of rail in freight transport is desirable. Inadequate infrastructure is the main obstacle preventing this modal shift taking place.Developing countries face great mobility challenges: rural areas are often extremely poorly connected to transport infrastructure, such that, in contrast to the situation in developed countries, the benefits of road construction can strongly outweigh the total costs (including environmental ones). The main challenge, however, is to develop a solution to the problems arising from the combination of urbanisation and motorisation. Integration of transport and land-use policy will be key to rising to this challenge.

Soft policies

Car sharing and car clubs can also potentially reduce CO₂ emissions, although the aggregate reduction in congestion and emissions has not been measured with an adequate degree of precision in the literature. Teleworking and teleshopping can potentially reduce congestion and also CO₂ emissions. However, the evidence for this reduction is rather mixed, as it is unclear whether these measures lead to overall reductions in road transport.Eco-driving campaigns aim to inform and educate drivers in order to induce them to drive in a fuel-efficient and thus environmentally friendly way. There seems to be some consensus in the literature that eco-driving could lead to reductions in CO₂ emissions of around 10 per cent.Information and education policies have often been advocated as instruments which may affect behavioural change. We find in this paper that these types of measures are necessary, but not sufficient for behavioural change. Advertising and marketing may go a long way in changing peoples’ behaviour. In California, for example, Kahn (2007) finds the “Prius” effect: the Toyota Prius is preferred by consumers relative to other similarly green vehicles, probably due to extensive marketing and celebrity endorsements. Family life changes are also found to trigger changes in behaviour ( [Goodwin, 1989] and [106]). People whose lives are being changed by some important development (birth of a child, retirement, etc) tend to respond more to changes in the relative attractiveness of different transport modes. Advertising campaigns promoting a modal shift towards public transport, for instance, may thus be more successful if targeted at people in the process of important life transitions.

Knowledge policies

Research and Development is crucial for developing sustainable and low-carbon transport for the future, and it is essential that governments provide incentives to undertake R&D, so that new low-carbon technologies in the transport sector can be demonstrated and applied at a large scale.Finally, we consider the issue of policy combination and integration. There is evidence that the combination and integration of policies can lead to positive side-effects and synergies. Policy integration is crucial in order to rise to the challenges we face in moving towards a sustainable mobility model. We conclude that classical economic policies may be successfully combined with a number of policy measures discussed in this paper in order to achieve sustainability in transport.     

Workshop report - Social inclusion

The topic of social inclusion is now maturing in the Thredbo conference series, being viewed as an important consideration in many aspects of land transport, the benefits extending beyond the socially excluded targeted population. The social inclusion workshop included presentations on new empirical evidence on the value of providing those at risk of social exclusion with mobility options, and how this links to improvements in personal wellbeing, often through mediating influences such as social capital. Work was presented on the role of transport services specifically targeted to those at risk of exclusion, particularly taxi services and school bus services, as well as how to modify fare structures to maximise inclusion in an efficient, mature transport system. The value of Universal Design principles to groups both at risk of being excluded as well as the current travelling public, was shown. The workshop affirmed the importance of including these wider benefits of inclusion in cost-benefit evaluations of transport. The issue of how best to move knowledge into strategic and operational policy, and the transferability of both knowledge and policy between different countries and settings, was discussed. This paper concludes with suggestions arising from the workshop in relation to policy and research, as well as recommendations for Thredbo 12.