Competition Among Virtual Communities and User Valuation: The Case of Investing-Related Communities

Abstract

Virtual communities are a significant source of information for consumers and businesses. This research examines how users value virtual communities and how virtual communities differ in their value propositions. In particular, this research examines the nature of trade-offs between information quantity and quality, and explores the sources of positive and negative externalities in virtual communities. The analyses are based on more than 500,000 postings collected from three large virtual investing-related communities (VICs) for 14 different stocks over a period of four years. The findings suggest that the VICs engage in differentiated competition as they face trade-offs between information quantity and quality. This differentiation among VICs, in turn, attracts users with different characteristics. We find both positive and negative externalities at work in virtual communities. We propose and validate that the key factor that determines the direction of network externalities is posting quality. The contributions of the study include the extension of our understanding of the virtual community evaluation by users, the exposition of competition between virtual communities, the role of network externalities in virtual communities, and the development of an algorithmic methodology to evaluate the quality (noise or signal) of textual data. The insights from the study provide useful guidance for design and management of VICs.