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