Price Optimization for a Multi-Stage Choice Model

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Price Optimization for a Multi-Stage Choice Model 47 Pages Posted: 24 Oct 2022 See all articles by Jiaqi ShiJiaqi ShiColumbia University - Department of Industrial Engineering and Operations ResearchGinger KeMemorial UniversityZizhuo WangThe Chinese University of Hong Kong, ShenzhenLianmin ZhangShenzhen Research Institute of Big Data; Nanjing University Date Written: October 22, 2022 Abstract Considering the real-world situations where past purchases could influence future prices, this research examines the multi-product price optimization problem under a multi-stage choice model. Particularly, the seller commits to a multi-stage pricing policy and determines product prices based on the customer's purchase history, and the customer makes purchase decisions such that the expected utility is maximized. We show that the pricing problem has a unique optimal solution under some mild conditions and the optimal solution satisfies a modified equal adjusted markup property. Based on the property, the problem can be solved efficiently by reducing it to a single-dimensional search problem. Moreover, the optimal pricing policy has an important property, namely, the product with a higher adjusted markup in earlier stages should always lead to lower prices in subsequent stages. We also show that compared to customers that are myopic, the seller should offer higher first-stage prices and lower second-stage prices to forward-looking customers, which will lead to a higher profit. Numerical analyses are also conducted to demonstrate the above results. Keywords: Price optimization; Multi-stage choice model; Sequential decision making Suggested Citation: Suggested Citation Shi, Jiaqi and Ke, Ginger and Wang, Zizhuo and Zhang, Lianmin, Price Optimization for a Multi-Stage Choice Model (October 22, 2022). Available at SSRN: https://ssrn.com/abstract=4255327 Jiaqi Shi (Contact Author) Columbia University - Department of Industrial Engineering and Operations Research ( email ) 500 W. 120th Street #315New York, NY 10027United States Ginger Ke Memorial University ( email ) 230 Elizabeth AveSt John's, NL NL A1B 3X9Canada7098643469 (Phone) HOME PAGE: http://www.business.mun.ca/why-us/meet-our-people/faculty-instructor-profiles/ginger-ke.php Zizhuo Wang The Chinese University of Hong Kong, Shenzhen ( email ) 2001 Longxiang RoadLonggang DistrictShenzhen, Guangdong 517182China Lianmin Zhang Shenzhen Research Institute of Big Data ( email ) Nanjing University ( email ) Nanjing, Jiangsu 210093China Download This Paper Open PDF in Browser Do you have a job opening that you would like to promote on SSRN? Place Job Opening Paper statistics Downloads 6 Abstract Views 31 PlumX Metrics Related eJournals IO: Theory eJournal Follow IO: Theory eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 928 PAPERS 15,024 Microeconomics: Production, Market Structure & Pricing eJournal Follow Microeconomics: Production, Market Structure & Pricing eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 762 PAPERS 16,486 Feedback Feedback to SSRN Feedback (required) Email (required) Submit If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday. Submit a Paper Section 508 Text Only Pages SSRN Quick Links SSRN Solutions Research Paper Series Conference Papers Partners in Publishing Jobs & Announcements Newsletter Sign Up SSRN Rankings Top Papers Top Authors Top Organizations About SSRN SSRN Objectives Network Directors Presidential Letter Announcements Contact us FAQs Copyright Terms and Conditions Privacy Policy We use cookies to help provide and enhance our service and tailor content. To learn more, visit Cookie Settings. This page was processed by aws-apollo-5dc in 0.234 seconds