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Pricing decisions with reference price effect and risk preference customers
Author(s) -
Zhao Nenggui,
Wang Qiang,
Cao Ping,
Wu Jie
Publication year - 2021
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12673
Subject(s) - multinomial logistic regression , preference , microeconomics , reference price , product (mathematics) , economics , loss aversion , risk neutral , prospect theory , price discrimination , business , computer science , geometry , mathematics , machine learning
We consider a seller selling a single product in a short period and taking reference price effect into account in the presence of risk preference customers. Customers' demand for the product is closely related to their purchase probability, which is determined by their purchase utility that is contingent on the reference price, selling price, and risk coefficients, through a multinomial logit model. Customers in the market are categorized as three types according to their asymmetry perceptions anchoring on the difference between the reference price and selling price: loss‐averse, gain‐seeking, and loss‐neutral. We first theoretically explore the influences of the reference price, risk coefficients, as well as the numbers of three types of customers on the seller's pricing decisions and profits. Then, we introduce model misspecification and use a computational study to further illustrate the significance of the seller's correct cognition on the customers' risk preference behaviors. We find that customers with higher reference price or lower risk coefficients would urge the seller to increase the optimal price. When there are more loss‐averse customers in the market, markdown is optimal for the seller; whereas markup is optimal for the seller when there are more gain‐seeking customers in the market. In addition, we find that customers' risk preference behaviors are nonnegligible for the seller in making pricing decisions, especially when gain‐seeking customers' risk coefficient is small enough or loss‐averse customers' risk coefficient is large enough.