Learning from Your Friends' Check-Ins: An Empirical Study of Location-Based Social Networks

• 成果类型: Article
• 署名作者: Qiu, Liangfei; Shi, Zhan (Michael); Whinston, Andrew B.
• 署名单位: State University System of Florida; University of Florida; Arizona State University; Arizona State University-Tempe; University of Texas System; University of Texas Austin
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2017.0769
• 发表日期: 2018
• 页码: 1044-1061
• 关键词: Online Reviews; INFORMATION; product; diffusion; adoption; identification; strategies; experience; contagion; internet

摘要

Recently, mobile applications have offered users the option to share their location information with friends. Using data from a major location-based social networking application in China, we estimate an empirical model of restaurant discovery and observational learning. The unique feature of repeat customer visits in the data allows us to examine observational learning in trials and repeats and to separate it from non-informational confounding mechanisms, such as homophily, using a novel test based on the empirical model. The empirical evidence supports a strong observational learning effect. We also find that the moderating role of the geographical locations of users and their friends on the magnitude of observational learning is critical. These findings suggest a nuanced view for local merchants to boost observational learning with the advancement of location-based technology.