While past research on software platform has recognized the existence of cross-side network effects (CNEs) between the application side and the user side, little is known about the asymmetry between the CNEs of the two sides on each other. Informed by a perspective of complex adaptive systems, this study theorizes how the user-to-application CNE is temporally different from the application-to-user CNE, and how these CNEs may be influenced by the governance mechanisms of the platform. We empirically test our theoretical arguments using a longitudinal data about a leading software browser. Our first main finding is the temporal asymmetry between the user-to-application CNE and the application-to-user CNE. Specifically, while the increased installed base of end users has a primarily long-term impact on the growth of application number and variety, the increased number and variety of applications have primarily short-term impacts on the growth of end users. Our second finding is that the length of application review time weakens the long-term user-to-application effect, but not the short-term application-to-user effect. Third, we also find that frequent platform updating can significantly weaken both the long-term user-to-application CNE and the short-term application-to-user CNE. Our study generates important theoretical and practical implications.

T he buy-online-and-pickup-in-store (BOPS) service has been widely treated by retailers as an important omni-channel initiative. However, few studies have attempted to quantify the impact of BOPS usage on subsequent purchase behaviors or examine the critical roles of offline stores in the value generation of BOPS. Thus, through 25,724 BOPS instances used by 16,202 unique customers via a hybrid retailer, this study investigated the impact of customers' BOPS usage on their online and offline purchase frequency and purchase amount. The moderating effect of offline store factors was investigated based on data from a focal retailer consisting of 110 stores in four cities. Using a combination of propensity score matching and difference-in-difference (DID) identification, our research found the significant positive effects of BOPS usage on offline purchase frequency and online purchase amount. We also found nuanced moderating effects of offline store characteristics (i.e., store density, product variety, and competition intensity) in the influence of BOPS usage on purchase behaviors. Our study thus generates important theoretical and practical implications for omni-channel operations.

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