IEDA Seminar - Speed Up Service with Spotlight Products: Assortment Optimization with Service Rate Consideration
Quick-service restaurants, such as fast-food franchises and coffeehouse chains, are faced with a trade-off between profitability and efficiency. Spotlight menus are often used to shorten customers’ decision time and improve per-customer revenue. We study such spotlight recommendation problems where service rate is affected by the assortment and plays a role in the revenue rate objective. Formulated as a sequential recommendation problem in a queueing setting under the multinomial logit model, we develop a polynomial-time algorithm, characterize the impact of demand arrival rate and queueing capacity on the optimal assortment, and obtain optimality conditions for attractiveness-ordered or revenue-ordered nested policies. In the joint assortment and pricing problem, we show it is optimal to prescribe equal profits for products in (and out of) the spotlight menu. (Joint work with Kalyan Talluri and Shixin Wang)
Zhe Liu is an Assistant Professor in the Analytics & Operations group at Imperial College Business School, Imperial College London. His research lies in revenue management, with particular interests in the operations and design of sharing economy platforms, and supply chain management, with a focus on multi-sourcing and inventory control. He is the recipient of the Finalist in George Nicholson Student Paper Competition, 2nd Place in POMS Student Paper Competition, and 2nd Place in POMS-HK Best Student Paper Competition. Zhe received his PhD in Operations Management from Columbia Business School and BS in Industrial Engineering from Tsinghua University.