Analyzing social influence through network simulations in choice modeling
Editor: Udo Lindemann, Srinivasan V, Yong Se Kim, Sang Won Lee, John Clarkson, Gaetano Cascini
Author: Tian, Peilin; Chen, Wei
Institution: Northwestern University, United States of America
In this paper, we study how to capture social influence on customer choice based on rich consumer data. The created choice model helps achieve a better understanding of consumer preferences in product design. Social influence attributes are employed to quantify the social impact a customer receives from interactions with other individuals in product selection. Data analysis technique is first adopted to identify critical social profile attributes based on a large amount of consumer information. To quantify social influence at the individual level, the paper presents a data-driven approach that integrates social network simulation based on consumersâ social profile attributes in product choice modeling. Later the network is simulated to estimate the social influence on individual consumerâs choice behavior. This paper provides new understanding of how consumers are socially influenced. A Hybrid Electric Vehicle case study is implemented to demonstrate the proposed methodology using National Household Travel Survey data. Choice modeling prediction results and consumers green attitude towards hybrid electric vehicle are examined over multiple years.