Product price alignment with seller service rating and consumer satisfaction

Renato Matta () and Timothy J. Lowe ()
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Renato Matta: University of Iowa
Timothy J. Lowe: University of Iowa

Annals of Operations Research, 2023, vol. 320, issue 2, No 7, 695-725

Abstract: Abstract Empirical studies have shown strong evidence that a seller with a better customer feedback score is able to charge a higher price for his/her product or service. We study the problem faced by the seller of setting the price with the objective of maximizing expected revenue over a finite number of periods. Modeling the problem requires building a system of processes that includes: (1) the customer arrival and formation of customer reservation price; (2) the customer feedback collection and aggregation into a Seller Service Rating (SSR); and (3) determining how much to charge customers. Because of the technical difficulty in finding analytical solutions that fully reflect the closed-loop interconnections between these processes, we develop a simulation–optimization approach to solve the problem. We present a computational study and report on results of numerical experiments providing interesting insights on how the retailer could startegically align the price he charges with his service quality performance.

Keywords: Dynamic pricing; Revenue management; Customer satisfaction; Simulation optimization; Stochastic dynamic programming (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-021-04318-3

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