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Title: 

Decomposing the Congestion Effect and the Cross-Platform Effect in Two-Sided Networks: A Field Experiment

Authors: Tucker, Catherine - MIT Sloan School of Management
Zhang, Juanjuan - MIT Sloan School of Management
Keywords: Competition, Entry, Inference, Congestion, Decision-making Under Uncertainty, Two-Sided Markets
Issue Date: 2008
Series/Report no.: Net Institute Working Paper;08-12
Abstract: This paper highlights how the provision of information about user participation can serve as a strategic marketing tool for firms seeking to grow two-sided exchange networks. A two-sided exchange network is a business model (such as Ebay or Craiglist) where revenue is generated from persuading people to buy and sell items through that particular exchange. It is not immediately clear whether broadcasting information about the number of sellers will grow further seller participation. On the one hand, a strong rival presence may dissipate payoff (a 'congestion effect'). On the other hand, a large number of rivals may signal high buyer demand (a 'cross-platform effect'). We use field experiment data from a B2B web site that brings together buyers and sellers of used equipment and real estate. Before each seller made a posting request, the web site randomized whether to disclose the number of buyers and/or sellers, and the exact number to disclose. We find that when presented together with the number of buyers, a larger number of sellers makes sellers less likely to list their products, indicating a negative congestion effect. However, when the number of sellers is presented in isolation, its negative impact on entry is significantly reduced, indicating a positive cross-platform effect. Higher buyer search intensity amplifies the moderating role of demand uncertainty. The results suggest that information on the number of users can be an effective tool to grow two-sided networks but should be used strategically. A network can attract more users by advertising dense competition when demand is not transparent, especially in search-intensive markets.
URI: http://hdl.handle.net/2451/29458
Appears in Collections:NET Institute Working Papers Series

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