Dynamic Pricing When Customers Have Time-Inconsistent Preferences

37 Pages Posted: 23 Nov 2021 Last revised: 16 Nov 2022

See all articles by Xiangyu Gao

Xiangyu Gao

The Chinese University of Hong Kong (CUHK) - Department of Decision Sciences & Managerial Economics

Xin Chen

Georgia Institute of Technology - H. Milton Stewart School of Industrial and Systems Engineering

Ying-Ju Chen

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management

Date Written: November 21, 2021

Abstract

This paper examines the dynamic pricing decisions of a monopolist seller when customers have time-inconsistent preferences, which is modeled by quasi-hyperbolic discounting. By considering the cases where customers can be sophisticated, naive, or partially naive about their time-inconsistent preferences, we characterize the subgame perfect equilibrium for the full spectrum of customers' naivete. Our results show that cream-skimming pricing strategies emerge as a robust pattern across different scenarios. The firm's profits can be improved when customers have time-inconsistent preferences. However, the firm does not benefit from customers' naivete about their time-inconsistent preferences. Our numerical experiments show that the pricing tactics are non-trivial as we vary the degrees of customers' time inconsistency and naivete, and the seller's ignorance of customers' time-inconsistent behaviors can lead to significant profit loss.

Keywords: dynamic pricing, time-inconsistent preference, quasi-hyperbolic discounting, strategic customers

Suggested Citation

Gao, Xiangyu and Chen, Xin and Chen, Ying-Ju, Dynamic Pricing When Customers Have Time-Inconsistent Preferences (November 21, 2021). HKUST Business School Research Paper No. 2021-040, Available at SSRN: https://ssrn.com/abstract=3968335 or http://dx.doi.org/10.2139/ssrn.3968335

Xiangyu Gao (Contact Author)

The Chinese University of Hong Kong (CUHK) - Department of Decision Sciences & Managerial Economics ( email )

Shatin, N.T.
Hong Kong

Xin Chen

Georgia Institute of Technology - H. Milton Stewart School of Industrial and Systems Engineering ( email )

Ying-Ju Chen

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management ( email )

Clear Water Bay
Kowloon
Hong Kong

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