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 |
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| Affiliation: | 1. Urban Planning Group, Department of the Built Environment, Eindhoven University of Technology, Vertigo 8.22, P.O. Box 513, 5600MB Eindhoven, The Netherlands;2. Urban Planning Group, Department of the Built Environment, Eindhoven University of Technology, Vertigo 8.25, P.O. Box 513, 5600MB Eindhoven, The Netherlands;3. Urban Planning Group, Department of the Built Environment, Eindhoven University of Technology, Vertigo 8.18, P.O. Box 513, 5600MB Eindhoven, The Netherlands;1. Eindhoven University of Technology, Department of Urban Science and Systems, Urban Planning Group, PO Box 513, 5600MB Eindhoven, The Netherlands;2. Eindhoven University of Technology, Department of Urban Science and Systems, Urban Planning Group, PO Box 513, Vertigo 8.18, 5600MB Eindhoven, The Netherlands;1. COHERE, University of Southern Denmark, Odense, Denmark;2. Institute for Transport Studies, University of Leeds, UK;1. Institute for Transport Studies & Choice Modelling Centre, University of Leeds, UK;2. Oak Ridge National Laboratory, Center for Transportation Analysis, USA;3. RheinMain University of Applied Sciences, Germany;4. ETH Zurich, Switzerland;1. Urban system Laboratory, Centre for Transport Studies, Department of Civil and Environmental Engineering, Imperial College London, United Kingdom;2. Department of Geography, SUNY New Paltz, United States |
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| Abstract: | ![]()
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. |
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| Keywords: | Social influence Car-sharing Hybrid choice model Egocentric approach Sequential stated adaptation experiment Random regret minimization |
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