Marketing Seminar（2018-12）

Topic:Information, Adaptation Costs and Bidding Behavior in Online Labor Markets

Speaker:Xiaolin Li, Assistant Professor of Marketing, University of Texas at Dallas

Time:Monday, 2 July, 13:30-15:00

Location:Room 216, Guanghua Building 2

Abstract:

Online labor marketplaces are characterized by incomplete contracts, either due to inherent uncertainty surrounding these contracts or due to poor design. This incompleteness places an enormous burden on sellers to anticipate the ex post adaptations in contract specifications. Despite the prevalence of incompleteness in online contracts no paper has examined how sellers infer the costs associated with adaptation and whether these adaptation costs affect bidding behavior. In this paper, we focus on the role of two types of incompleteness that arise due to poor specification and complexity and ex post adaptation costs on ex ante bidding behavior. Our dataset from an online labor marketplace, in addition to information on bidding behavior contains unique information on ex post contractual outcomes and communication between buyers and sellers. We develop and estimate a structural model of strategic interaction between buyers and sellers in a multi-attribute auction to recover the underlying costs. Our results show evidence for significant adaptation costs in this context primarily due to incompleteness that arises from poor provision of information ex ante.

Introduction:

Xiaolin Li, Assistant Professor at Naveen Jindal School of Management, University of Texas at Dallas. Li's research interest is B2B marketing, and her current portfolio is centered on inter-firm procurement ties and salesforce compensation. Methodologically, she is an empiricist who strives to bring the most appropriate data collection and analysis techniques to bear on the problem at hand. Her current projects employ data collection procedures ranging from archival data, questionnaire surveys, laboratory experiments, to field interventions, while her analysis procedures have ranged from mathematical modeling and regressions, to dynamic, structural micro-econometric methods.

Your participation is warmly welcomed!