Which collective signals drive high performance in the E-marketplace? A configurational perspective

Abstract

In the rapid growth of the e-marketplace, it has become increasingly important for sellers to use multiple signals (e.g. reputation, pricing-oriented functions, and warranty) to address information asymmetry issues and achieve high performance. Extant signaling literature mainly focus on the attributes of multiple signals, however, with no investigation of which configurations of multiple signals lead to high performance in the e-marketplace. Drawing on configuration theory and signaling theory, we propose that sellers should release collective signals of both product quality and sellers' credibility to achieve high performance. By employing fsQCA, a rigorous approach for configuration analysis, we empirically test our hypotheses based on an observation dataset of 3,333 sellers in the apparel industry on Taobao.com. The theoretical and practical implications of this study are discussed.