讲座信息(8月21日)
发布时间:2018-08-20  点击数:
题目:PLATFORM-BASED FUNCTION REPERTOIRE, REPUTATION, AND SALES PERFORMANCE OF E-MARKETPLACE SELLERS
时间:2018年8月21日(星期二) 上午10:00
地点:信息管理学院205
报告人:林开,香港城市大学讲席教授、AIS Fellow
 
报告人简介:
Kai H. Lim, Yeung Kin Man Chair Professor of Information Technology Innovation and Management and Director of Research and Ph.D. Program at the Information Systems Department, City University of Hong Kong. His research interests include cross-cultural issues related to information systems management, IT-enable business strategy, e-commerce, social media, mobile commerce and human-computer interactions. He served two terms (2011-2016) as a Senior Editor of MISQ and has served on the editorial board of ISR, MISQ, and JAIS. His research has appeared in MISQ, ISR, JMIS, and JAIS. Prior to joining CityU, he was on the faculty of Case Western Reserve University and the University of Hawaii. He has won numerous teaching and research awards, and is one of the top-ranking teachers teaching in the CityU’s EMBA program. He has conducted executive training in Beijing, Guangzhou, Shanghai, and Hong Kong. He is or has been an Honorary Professor at Wuhan University and Fudan University, China.
 
报告简介:
In today’s emerging and competitive e-marketplaces, sellers must take competitive actions to improve their sales performance. E-marketplace platform operators offer sellers a portfolio of platform-based functions that are intended to enhance competitiveness. However, little is known about how these platform-based functions can be used at the repertoire level to improve the sales performance of e-marketplace sellers. Extending competitive repertoire theory to the e-marketplace context and integrating it with the e-commerce literature on reputation, we posit that a seller could improve sales performance by using these functions as a repertoire, featuring such structural characteristics as large volume, high complexity, and heterogeneity. We also posit that the performance impact of this repertoire approach to function use varies depending on seller reputation, manifested as customer ratings. We empirically examined the hypotheses with a unique longitudinal dataset consisting of 43,992 seller-week observations from Taobao, one of the largest e-marketplaces in the world. Our analyses yield a set of interesting findings that unveil more nuanced theoretical relationships between different structural characteristics of the platform-based function repertoire and sales performance under different levels of seller reputation. We elaborate on how these findings contribute to the e-marketplace literature in the information systems field and the competitive action research in the strategy field. We also discuss implications for practice and make suggestions for future works.