Generalized behavioral framework for choice models of social influence: Behavioral and data concerns in travel behavior

Abstract

a b s t r a c tOver the past two decades, transportation has begun a shift from an individual focus to a social focus. Accordingly, discrete choice models have begun to integrate social context into its framework. Social influence, the process of having one's behavior be affected by others, has been one approach to this integration. This paper provides a review and discussion of the incorporation of social influence into discrete choice models with specific application in travel behavior analysis. The discussion begins with a generalized framework to describe choice models of social influence. This framework focuses on the behavioral microfoundations of social influence and choice by separating the social influence mechanism from the source of its influence and by explicitly acknowledging the role of the social network in the model structure. This contrasts with prior work that focused on the measurement of contextual, endogenous, and correlated effects. Then, the state of the art in travel behavior research is reviewed using a taxonomy based on the generalized framework with research performed in sociology, social psychology, and social network analysis. The discussion then shifts to the importance of understanding the motivations for social influence, and the formation and structure of social networks are explored. Additionally, the challenges of collecting data for social influence studies are mentioned and the paper concludes with a look at the challenges in the field and areas for future research.

Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: A mode choice model and policy simulation for Taiyuan-China

“…In relation to built environmental and land use impacts, cycling-related infrastructures have attracted significant attention in the existing literature. Many studies have focused upon the importance of increasing the number of cycle lanes and bike-sharing stations in promoting the use of cycling or bike-sharing, in terms of reduced travel time, increased safety and convenience (Akar and Clifton, 2009;Larsen and El-Geneidy, 2011;Hankey et al, 2012;Daito and Chen, 2013;Kamargianni and Polydoropoulou, 2013;Deenihan and Caulfield, 2015;Kamargianni, 2015;Maness et al, 2015;Wang et al, 2015;Mateo-Babiano et al, 2016;De Chardon et al, 2017). However, there were also papers that found an insignificant relationship between the number of cycling facilities and cycling choice (Rodrıǵuez and Joo, 2004;Moudon et al, 2005;Xing et al, 2010).…”

A stated choice experiment to measure the effect of informational and normative conformity in the preference for electric vehicles

“…friend, colleague, neighbour, relative, family member, or other acquaintance). Maness et al (2015) discussed the micro foundations of social influence and choice by separating the social influence mechanism from the source of its influence and provided a general framework for choice models of social influence. They highlighted that differences in social influence types, motivations, tactics, and sources have important implications when applying these models for policy analysis and gathering data is an important area to properly study these effects.…”

Social influence in the global diffusion of alternative fuel vehicles – A meta-analysis

“…(2) Does social influence vary between countries as a result of cultural differences? We build on earlier work by Maness et al (2015) Potoglou and Kanaroglou (2008), Sharmeen et al (2014) and Sunitiyoso et al (2013), examining the importance of social and spatial interactions between individuals in making transport choices.…”