Multi-Dimensional Observational Learning in Social Networks: Theory and Experimental Evidence

Abstract

The prevalence of consumers sharing their purchases on social media platforms (e.g., Instagram, and Pinterest) and the use of this information by potential future consumers have substantial implications for online retailing. In this study, we examine how product characteristics and the type of information provider jointly moderate the purchase decision in a social network setting. We first propose an analytical observational learning framework integrating the impact of product differentiation and social ties. Then, we use two experimental studies to validate our analytical results and provide additional insights. Our key findings are that the effect of learning from strangers is stronger for vertically differentiated products than for horizontally differentiated products. However, the effect of learning from friends does not depend on whether the underlying product is horizontally or vertically differentiated. What is more interesting is the nuanced role of social ties: For horizontally differentiated products, the effect of learning increases with the strength of social ties. In addition, “contact-based” tie strength is more important than “structure based” tie strength in accelerating observational learning. These findings provide a motivation for online retailers to generate alternative strategies for increasing product sales through social networks. For example, online retailers offering horizontally differentiated products have strong incentives to cooperate with social media platforms (e.g., Instagram and Pinterest) in encouraging customers to share their purchase information.

Keywords: Multi-Dimensional Observational Learning, Social Ties, Product Differentiation