Consumer interactions and peer effects in socially-connected digital products
File(s)
Accepted version
Author(s)
Chen, Yijun
Nevskaya, Yulia
Type
Journal Article
Abstract
The paper explores peer effects in user churn within a digital socially-connected platform and investigates how firms can leverage peer effects and network structure
for customer relationship management (CRM). The data come from a massively multiplayer online game, where gamer social ties are endogenous. We build a two-stage
structural model to capture network formation and peer effects in churn. Unobserved gamer heterogeneity inferred from network formation corrects for endogeneity bias in
peer effects. The main findings are: (i) Peer effects substantially amplify intervention effectiveness, with an average social multiplier of 2.48. Critically, the full model with unobserved gamer heterogeneity reveals substantial cross-network variation in social multipliers that the restricted model largely masks. (ii) Users vary far more in how they influence peers’ retention than in their own likelihood of retention. (iii) User’s network value is driven primarily by network centrality measures, unlike user’s direct value which correlates more with individual characteristics.
for customer relationship management (CRM). The data come from a massively multiplayer online game, where gamer social ties are endogenous. We build a two-stage
structural model to capture network formation and peer effects in churn. Unobserved gamer heterogeneity inferred from network formation corrects for endogeneity bias in
peer effects. The main findings are: (i) Peer effects substantially amplify intervention effectiveness, with an average social multiplier of 2.48. Critically, the full model with unobserved gamer heterogeneity reveals substantial cross-network variation in social multipliers that the restricted model largely masks. (ii) Users vary far more in how they influence peers’ retention than in their own likelihood of retention. (iii) User’s network value is driven primarily by network centrality measures, unlike user’s direct value which correlates more with individual characteristics.
Date Issued
2026-06-16
Date Acceptance
2026-06-04
Citation
Journal of Marketing Research, 2026
ISSN
0022-2437
Publisher
SAGE Publications
Journal / Book Title
Journal of Marketing Research
Copyright Statement
© The Author(s) 2026. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Publication Status
Published online
Date Publish Online
2026-06-16