Longitudinal Study On Competitive Action, Signal And Sales Performance In E-marketplace

This study focuses on an important practical problem that e-marketplace sellers are facing now-" How to compete and enhance their sales performance in the competitive environment?" To investigate this problem, we broke down it into the following three specific research questions:(1) How should e-marketplace sellers deploy platform-based functions as a repertoire so as to improve their sales performance?(2) What’s the role of e-marketplace sellers’reputation in changing the relationships between platform-based function repertoire and sales performance? And (3) What are the differential effects of signals on the actual sales performance of e-marketplace sellers? We addressed these questions in two sub-studies.Study1:E-marketplace sellers must take competitive actions to improve their sale performance in today’s crowed e-marketplaces. To help sellers enhance their competitiveness, e-marketplace platform operators provide sellers with a broad array of platform-based functions. However, little is known about the extent to which the usage of a repertoire of such platform-based functions could improve e-marketplace sellers’sales performances. Drawing on competitive repertoire perspective and signaling theory, we posit that e-marketplace sellers could improve sales performances by using a repertoire of platform-based functions featuring large volume, high complexity and heterogeneity, especially when they have better reputation. We used a longitudinal dataset consisting of38,920seller-week observations of sellers in China’s biggest e-marketplace, Taobao, to test the hypotheses.Study2:In today’s competitive e-marketplace, sellers use many signals to entice customers to make an online purchase. However, there has been no research to date into how well each of the different types of signals perform in terms of increasing sales. This study draws on signaling theory in the context of China’s largest e-marketplace, Taobao, to investigate the different effects of five commonly used signals on the sales performance of e-marketplace sellers. The research reveals that warranty has the highest effect on sales performance, followed by overall rating, mean detailed seller ratings, website quality, and percent of positives. The paper discusses the theoretical and practical implications of the research findings, as well as opportunities for future research.As an extension of this study, we plan to focus on understanding the "dynamic optimization" of e-marketplace sellers’competitive repertoire in future. In the end of this study, we briefly introduced specific research questions, theoretical foundations as well as the data collection methods to be used.