Equilibrium strategies and optimal pricing in an online retailing queueing system. (10th February 2020)

• Record Type: Journal Article
• Authors: Wang, Jinting; Wang, Zhongbin; Chen, Yang
• Other Names: Baron Opher guestEditor.
• Is Part Of: Naval research logistics. Volume 68:Number 5(2021)
• Page Start: 556
• Page End: 576
• Publication Date: 2020-02-10
• Subjects: equilibrium strategies -- learning orbit -- online retailing -- optimal pricing -- queueing; Logistics, Naval -- Periodicals; Supplies and stores -- Periodicals; 359.07
• DOI: 10.1002/nav.21890
• Languages: English
• ISSNs: 0894-069X

Abstract

Abstract: This article considers an M/M/1 online retailing queueing model with strategic customers and a monopoly retailer. Customers arrive according to a Poisson process, and upon arrival, they decide whether to purchase the product based on a reward‐cost structure. The valuation of the product is determined by its matching probability with the demand. After receiving the purchased product, each customer enters a "virtual" orbit to update the information about the product and then makes her decision on whether to replace or return the product based on the product's assessed value. Accordingly, a two‐dimensional decision among customers is formulated and we investigate the equilibrium customer strategies and the optimal pricing strategy for the retailer. Interestingly, in equilibrium, we find that the system's throughput can be nonmonotone in the product's matching probability. In addition, under the equilibrium strategy of customers, we reveal the fact that the retailer's optimal price is not necessarily increasing in the matching probability. From the perspective of the social planner, the returning behavior can worsen the social welfare, and therefore those unsatisfied customers are encouraged to replace the product rather than to return it. Finally, some numerical experiments are conducted to verify our results and to examine the sensitivity of several key performance measures of the system.