Wednesday 27 September 2023, 1:00pm to 2:00pm
VenueMAN - Mngt School LT19 WPB002 - View Map
Open toPostgraduates, Public, Staff
RegistrationRegistration not required - just turn up
Dr Xishu Li will present a seminar to the Management Science Department
Abstract: In this seminar, I will present three of my papers on the gig & sharing economy. The primary objective of my research is to explore ways to create a labor market that is fair, just, and accessible to all participants, while also promoting economic opportunities and benefits for workers. This is achieved through the implementation of information sharing and revenue sharing strategies. With a particular emphasis on trust among suppliers, buyers, and companies, as well as fairness concerns for each player, my research addresses three key questions. First, I explore the one-time contracting process within share-based platforms, focusing on the extent of information disclosure and the proportion of revenue shared with suppliers . The second research question expands the analysis to a repeated-game setting, examining the optimal long-term information sharing and revenue sharing strategies for a gig-based platform . The third research question incorporates all three key players involved in the platform economy---the platform, the supplier, and the buyer---to analyze the drivers of trust and trustworthiness on each side of the platform and explores the dynamics of trust-building among the three players . By addressing these questions, I aim to provide insights into the design of effective labor market mechanisms that promote transparency and cooperation within the gig & sharing economy. I also aim to make a significant contribution to the field of contracting theory and the examination of emerging economic models. Specifically, I aim to establish the critical role of trust and fairness in shaping the operational dynamics of platforms. In terms of methodology, I have adopted a multi-methodological approach in these projects. I integrated game theory, (partially observable) Markov decision process, and simulation techniques to capture the complexity and dynamics of labor supply in these sectors. Additionally, I incorporated behavioral and field experiments as complements to the quantitative methods, allowing for a deeper understanding of the potential value of our model. It is worth noting that while machine learning, optimization, and simulation methods are often viewed as distinct from behavioral science, my research emphasizes their complementary nature in solving crucial operations management problems.
In this seminar, I will also discuss my experiences collaborating with researchers from diverse disciplines such as economists and marketing researchers for publications in operations management. In addition, I will share my collaborative effort with Uber Mobility (RIDES) and Delivery (EATS) divisions in the EMEA region for these projects.
 Yin, Ying, Xishu Li. 2023. Trust and fairness: Contracting on a share-based platform. Available at SSRN 4331819.
 Yin, Ying, Xishu Li, Rob Zuidwijk. 2023. Once bitten, twice shy? strategic information disclosure on sharing economy platforms. Working paper
 Pan, Yihan, Xishu Li, Edward Malthouse. 2023. Triangle of trust for growth and retention in two-sided markets. Working paper.
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