Product and Ancillary Pricing Optimization: Market Share Analytics 

via Perturbed Utility Model

Speaker: Prof. Chung Piaw Teo

Time: 14: 30-16:30, 13th July 2022 (Beijing time)

Tencent ID: 785-915-445

Code: 706708

Abstract: Consider a firm that sells some primary and ancillary products (services) to heterogeneous customers. The challenge is to determine the prices for all the products and services simultaneously, to optimize profits to the firm. This problem is notoriously difficult as it involves choice over subsets (primary product + ancillary services). We consider random utility model for customers’ choice problem, and show that the choice model can be reformulated into a perturbed utility model (PUM) over the convex hull of the feasible solutions. Furthermore, we demonstrate how we can obtain a good approximation to the PUM using an additive perturbed utility model (APUM). This allows us to establish a set of closed-form relationships between prices, expected market shares, and interestingly, expected slacks in the constraint matrix of the customer choice problem. This opens up a new way to calibrate the APUM using market share shift information obtained from varying the prices of the products and services. Using piecewise linear approximation, we show that the resulting data-driven pricing problem can be solved as mixed integer linear programs. We show further that the constant markup pricing strategy is within a logarithmic factor of the optimal revenue in our framework, and use this strategy as one of the benchmarks to calibrate the performance of our method. Extensive experimental results demonstrate the superiority of our approach to the state-of-the-art benchmark methods. We finally showcase how this approach can be extended to address competition, and discuss how to solve the quantity discount problem under this framework.

Bio: Prof. Chung Piaw Teo是新加坡国立大学运营研究与分析研究所（IORA）的教务长讲座教授和执行院长，此前曾任新国立商学院系主任/副院长/执行院长等职位。Prof. Teo获得美国西北大学Eschbach学者，台湾元智大学杰出访问教授，新加坡国立大学Provost ChairProfessor等荣誉称号，是教育部长江讲座教授，INFORMS Fellow。Prof. Teo研究方向包括服务和制造运营、供应链管理、离散优化和数据驱动优化等方面，在OR,MS,MSOM,POM等国际主流期刊发表高水平论文70多篇。目前担任Management Science的部门主编, 曾担任Operations Research的区域主编。