Intl. Trans. in Op. Res. 24 (2017) 907–924 DOI: 10.1111/itor.12371 INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH The influence of reference effect on pricing strategies in revenue management settings Hui Yang a , Ding Zhang b and Chen Zhang a a School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China b School of Business, State University of New York at Oswego, Oswego, NY, USA E-mail: yanghui@njust.edu.cn [Yang]; ding.zhang@oswego.edu [D. Zhang]; zcrg8578@126.com [C. Zhang] Received 28 December 2015; received in revised form 8 September 2016; accepted 26 October 2016 Abstract This paper studies the reference effect on dynamic pricing in revenue management for cases with limited capacity and stochastic demand. We first present a single-period fixed pricing (FP) model in finite horizon with fixed capacity and stochastic demand, and show that there is a unique optimal solution. The model is then extended to a discrete-time dynamic pricing (DP) model as a benchmark case. We subsequently propose a DP model with reference effect (DPR), investigate the properties of the revenue function, and present a computational scheme to compute the dynamic optimal price. Numerical experiments are conducted to exhibit how the reference effect may influence the initial price, pricing trend, price dispersion, and expected revenue, with the FP, DP, and DPR policies in the same environment of a fixed capacity facing stochastic demand. We also present, through numerical examples, a comparison between deterministic demand and stochastic demand scenarios under reference effect, and with a fixed initial price versus a variable initial price. Keywords: revenue management; pricing; reference effect; dynamic programming 1. Introduction Revenue management (RM), the use of dynamic pricing to set different prices at different times to maximize revenue, is a highly successful Operations Research technique with direct real-world applications. American Airlines, for instance, used revenue management strategies to create over 500 million dollars in additional annual revenue in the 1990s (Anderson and Wilson, 2003). In the retail industry, gross-margin increases of from 5% to 15% can be achieved through optimal pricing and assortment using RM (Friend and Walker, 2001). From the theoretical perspective, RM pricing problems typically share three common characteristics: (1) A finite selling season: Airlines start to sell seats several months before the departure date, but fashion apparel retailers may have a selling season of only weeks. (2) A fixed stock of products or fixed capacity for service with no replenishment option during the selling horizon: Airlines have a certain number of seats available on a given flight C  2017 The Authors. International Transactions in Operational Research C  2017 International Federation of Operational Research Societies Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main St, Malden, MA02148, USA.