题　目：Economics of Analytics Services on a Marketplace Platform

嘉　宾：Zhe Wang, Ph.D. Candidate, Tsinghua University

主持人：徐海峰  助理教授  上海交通大学安泰经济与管理学院

时　间：2022年11月8日（周二） 14:00-15:20

地　点：腾讯会议 (校内师生如需会议号和密码，请发送电邮至xuziqing@sjtu.edu.cn获取)

内容简介:

Analytics services provided by marketplace platforms have become increasingly important for sellers to gain market insights. In this paper, we characterize the role of analytics services as improving sellers’ knowledge about the size of the consumer market, which in turn helps them make better decisions. Using a game-theoretic model, we analyze the platform’s pricing and the sellers’ adoption strategies for the analytics service. We identify two distinct effects of analytics services: The competition effect and the accuracy effect. Our results show that the competition effect manifests in opposite directions under different market scenarios, i.e., the competition-intensifying effect in the low-demand market and the competition-weakening effect in the high-demand market. With the analytics service, the sellers command a lower price in the low-demand market and a higher price in the high-demand market. Interestingly, the platform does not necessarily benefit from offering the analytics service; additionally, the service may hurt the sellers’ profits and the consumers’ surplus and is not necessarily welfare-enhancing. Furthermore, the transaction fee for the marketplace service plays an important role in the interaction between the analytics service and the marketplace service. Specifically, when the transaction fee is high, the platform should charge a lower (higher) subscription fee to induce more (fewer) sellers to adopt the analytics service in the low (high)-demand market. Moreover, sellers may lower the product price due to intensified competition when the platform charges them more for the marketplace service.

演讲人简介：

Zhe Wang is currently a Ph.D. candidate in Information Systems (IS) at the School of Economics and Management, Tsinghua University. His primary research interests lie in the area of economics of Information Systems (IS), with a particular focus on digital platforms. Zhe has employed a broad set of methodologies in his research, including analytical modeling and empirical analysis. Several of his papers are currently under review/revision in top-tier journals, including Management Information Systems Quarterly and Management Science. At ICIS 2020, one of his works was selected as Best Student Paper (as well as Best Paper) in Track “The Sharing Economy, Platforms, and Crowds,” and also nominated for Best Student Conference Paper (as well as Best Conference Paper). Moreover, one of his works was a finalist for the 2021 INFORMS Service Science Best Student Paper Award.

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