Abstract
Consider a situation when an on-demand service platform uses earnings-sensitive independent providers with heterogeneous reservation price (for work participation) to serve its wait-time and price sensitive customers with heterogeneous valuation of the service. As such, both the supply and demand are “endogenously” dependent on the price the platform charges its customers and the wage the platform pays its independent providers. In this lecture, the speaker will present a queueing model with endogenous supply (number of participating agents) and endogenous demand (customer request rate) to model this on-demand service platform. To coordinate endogenous demand with endogenous supply, the speaker and his collaborators use the steady state performance in equilibrium to characterize the optimal price and wage rates that maximize the profit of the platform (as well as the total welfare). They first analyze a base model that uses a fixed payout ratio (i.e., the ratio of wage over price). They then extend their model to allow the platform to adopt a dynamic payout ratio. Due to the fact that the exact analysis based on an M/M/k system is intractable, they develop an approximation scheme to generate some analytical results. In addition to the fact that their approximation scheme performs well, they find that it is optimal for the platform to charge a higher price, pay a higher wage, and offer a higher payout ratio when the potential customer demand increases. Furthermore, when customers become more time-sensitive, the platform should also pay a higher wage and offer a higher payout ratio, but the price rate is not necessarily monotone. They used a set of actual data from a large on-demand ride-sharing to illustrate some of their main insights. This is a joint work with Jiaru Bai and Kut C. So of the University of California at Irvine, Xiqun Chen of Zhejiang University, and Hai Wang of Singapore Management University.
About the speaker
Prof Christopher Tang received his BSc in mathematics from King’s College at the University of London in 1983, and his PhD in operations research from Yale University in 1985. He is a UCLA Distinguished Professor, and used to serve as the Dean of the Business School of National University of Singapore and the Senior Associate Dean at UCLA Anderson School of Management.
As a world renowned scholar in operations management, Prof Tang is highly influential in the academic circle. He has co-edited four books, co-written one book, and published over 100 academic articles in top research journals such as Management Science and Operations Research to name a few. Currently, he is also the Editor-in-Chief of Manufacturing and Service Operations Management, and the editor of the Springer book series on Supply Chain Management.
Prof Tang is a Lifetime Fellow at the Manufacturing and Service Operations Management Society, the Institute of Operations Research and Management Sciences, and the Production and Operations Management Society. He has received the Dean’s Excellent Service Award and multiple teaching excellence awards at UCLA Anderson School of Management.
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