Modeling social influence from a perspective of shift: an elaborated model

Xiaofeng Pan (Corresponding author), Soora Rasouli, Harry J.P. Timmermans

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

This paper follows authors’ previous work, which measured social influence in travel behavior using a sequential stated adaptation experiment, and aims to investigate issues that are not discussed in the previous one. Specifically, this paper supplements the previous work in two aspects. On the one hand, the previous work tried to model respondents’ sequential choice in terms of a choice task with and without social network member’s choice, and estimated the model sequentially without any clear evidences to show the difference between sequential and simultaneous estimation. Therefore, this paper first provides the comparison of these two estimation approaches. On the other hand, the previous work did not clearly address two specific issues that come with the use of sequential choice experiments to measure social influence. The first issue is that respondents have a tendency to keep their choices consistent in sequential choice tasks, which may mask the effect of social influence; the second one is that the stochastic nature of utility implies that respondents may still reveal a shift in their choices even if no information about the choice of social network members is provided, which will be mixed with the effect of social influence, depending on the similarity of alternatives in the choice set. Therefore, this paper aims to take these two issues into consideration. The results of this study reveal that estimating the model simultaneously may lead to confounding bias and that taking the issues caused by the sequential choice experiment could improve the performance of the model and provide more insights about social influence.
Original languageEnglish
Number of pages33
JournalTransportmetrica A: Transport Science
VolumeXX
Issue numberXX
DOIs
Publication statusAccepted/In press - 13 Feb 2021

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