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This paper examines the relative importance of platform quality, indirect network effects, and consumer expectations on the success of entrants in platform-based markets. We develop a theoretical model and find that an entrant's success depends on the strength of indirect network effects and on the consumers' discount factor for future applications. We then illustrate the model's applicability by examining Xbox's entry into the video game industry. We find that Xbox had a small quality advantage over the incumbent, PlayStation 2, and the strength of indirect network effects and the consumers' discount factor, while statistically significant, fall in the region where PlayStation 2' s position is unsustainable.

We show that a two-sided matching platform can successfully compete by limiting the number of choices it offers to its customers, while charging higher prices than platforms with unrestricted choice. We develop a stylized model of online dating where agents with different outside options match based on how much they like each other. Starting from these microfoundations, we derive the strength and direction of indirect network effects and show that increasing the number of potential matches has a positive effect due to larger choice, but also a negative effect due to competition between agents on the same side. Agents resolve the trade-off between these competing effects differently, depending on their outside options. For agents with high outside options, the choice effect is stronger than the competition effect, leading them to prefer an unrestricted-choice platform. The opposite is the case for agents with low outside options, who then have higher willingness to pay for a platform restricting choice, as it also restricts the choice set of their potential matches. Moreover, since only agents with low outside options self-select into the restricted choice platform, the competition effect is mitigated further. This allows multiple platforms offering different number of choices to coexist without the market tipping. This paper was accepted by Bruno Cassiman, business strategy.

Consumer-to-consumer (C2C) platforms have become a major engine of growth in Internet commerce. This is especially true in countries such as China, which are experiencing a big rush toward e-commerce. The emergence of such platforms gives researchers the unique opportunity to investigate the evolution of such platforms by focusing on the growth of both buyers and sellers. In this research, we build a utility-based model to quantify both cross and direct network effects on Alibaba Group’s Taobao.com, the world’s largest online C2C platform (based in China). Specifically, we investigate the relative contributions of different factors that affect the growth of buyers and sellers on the platform. Our results suggest that the direct network effects do not play a big role in the platform’s growth (we detect a small positive direct network effect on buyer growth and no direct network effect on seller growth). More importantly, we find a significant, large and positive cross-network effect on both sides of the platform. In other words, the installed base of either side of the platform has propelled the growth of the other side (and thus the overall growth). Interestingly, this cross-network effect is asymmetric with the installed base of sellers having a much larger effect on the growth of buyers than vice versa. The growth in the number of buyers is driven primarily by the seller’s installed base and product variety with increasing importance of product variety. The growth in the number of sellers is driven by buyer’s installed base, buyer quality, and product price with increasing importance of buyer quality. We also investigate the nature of these cross-network effects over time. We find that the cross-network effect of sellers on buyers increases and then decreases to reach a stable level. By contrast, the cross-network effect of buyers on sellers is relatively stable. We discuss the policy implications of these findings for C2C platforms in general and Taobao in particular. Data, as supplemental material, are available at https://doi.org/10.1287/mksc.2016.0976 .

Two-sided markets are composed of platform owners and two distinct user networks that either buy or sell applications for the platform. The authors focus on multihoming—the choice of an agent in a user network to use more than one platform. In the context of the video game console industry, they examine the conditions affecting seller-level multihoming decisions on a given platform. Furthermore, they investigate how platform-level multihoming of applications affects the sales of the platform. The authors show that increased platform-level multihoming of applications hurts platform sales, a finding consistent with literature on brand differentiation, but they also show that this effect vanishes as platforms mature or gain market share. The authors find that platform-level multihoming of applications affects platform sales more strongly than the number of applications. Furthermore, among mature platforms, an increasing market share leads to more seller-level multihoming, while among nascent platforms, seller-level multihoming decreases as platform market share increases. These findings prompt scholars to look beyond network size in analyzing two-sided markets and provide guidance to both (application) sellers and platform owners.

Strategic prescriptions drawn from pooled cross-sectional evidence of firm performance effects are not necessarily warranted. This is because firm characteristics can influence both the mean and variance of firm performance. Strategic inferences are warranted if empirically observed effects reflect increases in mean firm performance. If they reflect increases in firm performance variance, however, such inferences are warranted only if the increased odds of achieving high performance compensate sufficiently for the concomitantly increased risk of realizing poor performance. Our simulation study, which contrasts firm performance effects in pooled cross-section and within-firm over time, counsels caution when basing strategic prescriptions on pooled cross-sectional studies of firm performance in general, and in the case of network effects in particular.

Many software firms offer a fully functional version of their products free of charge, for a limited trial period, to ease consumers' uncertainty about the functionalities of their products and to help the diffusion of their new software. This paper examines the trade-off between the effects of reduced uncertainty and demand cannibalization, uncovers the condition under which software firms should introduce the time-locked free trial software, and finds the optimal free trial time. As software firms have the option of providing free trial software with full functionalities but a limited trial time or limited functionalities for an unlimited trial time, we develop a unified framework to provide useful guidelines for deciding which free trial strategy is preferred in the presence of network externalities and consumer uncertainty.

Two-sided platforms connect two or more distinct user groups. Agents on such a platform not only value the participation of users from a different group but are also affected by the same-side network effects that arise from the participation of agents in their own group. We study how negative same-side network effects among sellers affect the participation levels and profit of a monopoly platform. We use a novel specification of the CES utility function to model our consumer preferences, where taste for variety and substitutability are not interrelated. We find that when the platform implements subscription pricing on both sides, an increase in the intensity of competition (higher negative same-side network effects) amongst sellers leads to more participation from both buyers and sellers and there is an increase in the profit of the platform. On the other hand, when the platform can only charge a fee from the seller, participation on both sides first rises and then falls. The platform’s profit also follows the same trend. We also briefly discuss how prices of competing platforms change when there is an increase in the intensity of competition amongst sellers.

This paper develops a framework for measuring \"tipping\"-the increase in a firm's market share dominance caused by indirect network effects. Our measure compares the expected concentration in a market to the hypothetical expected concentration that would arise in the absence of indirect network effects. In practice, this measure requires a model that can predict the counterfactual market concentration under different parameter values capturing the strength of indirect network effects. We build such a model for the case of dynamic standards competition in a market characterized by the classic hardware/software paradigm. To demonstrate its applicability, we calibrate it using demand estimates and other data from the 32/64-bit generation of video game consoles, a canonical example of standards competition with indirect network effects. In our example, we find that indirect network effects can lead to a strong, economically significant increase in market concentration. We also find important roles for beliefs on both the demand side, as consumers tend to pick the product they expect to win the standards war, and on the supply side, as firms engage in penetration pricing to invest in growing their networks.

Systems are composed of complementary products (e.g., video game systems are composed of the video game console and video games). Prior literature on indirect network effects has argued that in system markets, sales of the primary product (often referred to as \"hardware\") largely depend on the availability of complementary products (often referred to as \"software\"). Mathematical and empirical analyses have almost exclusively operationalized software availability as software quantity. However, though not substantiated with empirical evidence, case illustrations show that certain high-quality, \"superstar\" software titles (e.g., Super Mario 64) may have disproportionately large effects on hardware unit sales (e.g., Nintendo N64 console sales). In the context of the U.S. home video game console market, the authors show that the introduction of a superstar increases video game console sales by an average of 14% (167,000 units) over a period of five months. One in every five buyers of a superstar software title also purchases the hardware required to use the software. Software type does not consistently alter this effect. The findings imply that scholars who study the relationship between software availability and hardware sales need to account for superstar returns and their decaying effect over time, beyond a mere software quantity effect. Hardware firms should maintain a steady flow of superstar introductions because the positive effect of a superstar lasts only five months and, if need be, make side payments to software firms because superstars dramatically increase hardware sales. Hardware firms' exclusivity over superstars does not provide an extra boost to their own sales, but it takes away an opportunity for competing systems to increase their sales.

This study empirically analyzes the determinants of regional labor migration in Japan, where small towns are disappearing due to the shortage of labor. Using spatial models of origin–destination flows and considering network effects of labor and economic structures, we obtain results more consistent with the standard migration theory, compared to previous studies. In particular, we find that migration decisions are based on economic motivations and that high (low) unemployment rates in origin (destination) regions and low income in origin regions are important determinants of labor migration flows. Second, we report that network effects, which help reduce migration costs, play a significant role in the relocation of labor. Finally, considering different definitions of spatial weights based on distance, the volume of traded goods, and economic structures, we show that regional dependence is most appropriately defined by the similarity in economic structures. In other words, migration patterns are similar between regions that rely on analogous economic activities.