A Network Autocorrelation Model to Predict Repeat Purchases in Multi-Relational Social Networks: Evidence from Online Games

53 Pages Posted: 16 Sep 2018 Last revised: 23 Jan 2019

See all articles by Bin Zhang

Bin Zhang

Texas A&M University

Ruibin Geng

Independent; School of Management, Northwestern Polytechnical University

Xi Chen

Zhejiang University - School of Management

Paul A. Pavlou

University of Miami Herbert Business School

Date Written: August 22, 2018

Abstract

It is well established in the literature that customer retention is at least as important as customer acquisition, especially in the freemium-based virtual economy, in which individuals are connected by multi-relational social networks, such as the “friendships” and “guilds” (virtual teams) functions in the context of online games. Yet, we do not know how these multi-relational social network effects simultaneously affect repeat purchases. In this study, we seek to examine the interdependent nature of repeat purchases of online game players embedded in multi-relational social networks. We examine two types of social network effects in the “friendship” function: a reinforcement (positive) effect and an attenuation (negative) effect. We also examine the herding effect (behavioral conformity within a virtual team) in the “guild” function. We develop a new hierarchical Bayesian model that supports a response variable for repeat purchases and that follows a Poisson distribution, and we simultaneously include both the two social network effects (reinforcement and attenuation) from the “friendship” function and also the moderating role of the herding effect from the “guild” function. Our study shows that both the reinforcement and attenuation social network effects have a significant effect on repeat purchases; however, the direction of the behavioral correlation of these two social network effects is starkly distinct: the reinforcement effect leads to repeat purchases among direct friends; in contrast, the attenuation effect leads to a divergence of repeat purchases among players who are indirect friends but share common friends. Moreover, we find that the size of the reinforcement effect is attenuated when the herding effect is accounted for. Besides theoretically developing and empirically validating a new method to predict repeat purchases in multi-relational social networks, this study has managerial implications for online game providers to develop effective targeting strategies to encourage players to engage in repeat purchases by leveraging multi-relational social network effects. Broader theoretical and practical implications for encouraging repeat purchases by leveraging social network effects in other online platforms are also discussed.

Keywords: Repeat Purchases, Online Games, Herding Effect, Social Network Effect, Hierarchical Bayesian Model

Suggested Citation

Zhang, Bin and Geng, Ruibin and Chen, Xi and Pavlou, Paul A., A Network Autocorrelation Model to Predict Repeat Purchases in Multi-Relational Social Networks: Evidence from Online Games (August 22, 2018). Fox School of Business Research Paper No. 18-053, Available at SSRN: https://ssrn.com/abstract=3237058 or http://dx.doi.org/10.2139/ssrn.3237058

Bin Zhang (Contact Author)

Texas A&M University ( email )

210 Olsen Blvd
330E Wehner
College Station, TX 77843
United States
(979) 458-1759 (Phone)

Ruibin Geng

Independent ( email )

AZ
China
13299165591 (Phone)

School of Management, Northwestern Polytechnical University ( email )

27 West Youyi Road, Beilin District, Xi'an Shaanxi
Xi'an, Shaanxi 710072
China
13299165591 (Phone)

Xi Chen

Zhejiang University - School of Management ( email )

Hangzhou, Zhejiang Province 310058
China

Paul A. Pavlou

University of Miami Herbert Business School ( email )

P.O. Box 248126
Florida
Coral Gables, FL 33124
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
264
Abstract Views
1,557
Rank
250,210
PlumX Metrics