This article examines peer influences from network relationships within a social network game (i.e., embeddedness) and across such games (i.e., multiplexity). Drawing on social influence theory, we develop a bivariate Poisson model of users’ repeated visits and latent attrition that accommodates peer interaction after controlling for homophily. We estimate the model using data from two social network games with considerable overlap among network members. We find that friends who are only multiplex across games exert greater peer influence on users’ game visits than members who are embedded within a single game. We also determined that ignoring network multiplexity across games may lead firms to mistarget users due to biased peer influences of embedded friends. This result provides an unresearched explanation—strength of peer influence—for the mixed findings in previous literature on network embeddedness. We utilized our results to conduct several scenario analyses to demonstrate how firms can effectively manage users’ engagement and target users in multiple social network games.

本文研究了社交网络游戏（即嵌入性）和此类游戏之间（即多重性）的网络关系对同伴的影响。借鉴社会影响理论，我们开发了一个用户重复访问和潜在流失的双变量泊松模型，该模型在控制同质性后适应了同伴互动。我们使用来自两个社交网络游戏的数据来估计模型，网络成员之间有相当大的重叠。我们发现，与嵌入单个游戏的成员相比，仅在游戏中复用的朋友对用户游戏访问的同伴影响更大。我们还确定，由于嵌入式朋友的有偏见的同伴影响，忽略游戏中的网络多重性可能会导致公司错误地定位用户。这一结果为先前关于网络嵌入的文献中的混合发现提供了未经研究的解释——同伴影响的强度。我们利用我们的结果进行了多个场景分析，以展示公司如何有效地管理用户参与度并在多个社交网络游戏中定位用户。