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A multi-objective mean–variance mathematical programming approach to combined phase-out and clearance pricing strategy for seasonal products: case study of a Jeans retailer

Author

Listed:
  • Mahmoud Dehghan Nayeri

    (Tarbiat Modares University)

  • Amir-Nader Haghbin

    (Tarbiat Modares University)

  • Abdolkarim Mohammadi-Balani

    (Tarbiat Modares University)

  • Karim Bayat

    (Tarbiat Modares University)

Abstract

This paper presents a novel multi-objective mean–variance mathematical programming approach to the dynamic pricing problem for seasonal products. The basic pricing scheme is a combination of phase-out pricing that gradually lowers the price over time and clearance pricing in which the end-of-season inventory is sold altogether at a lower price to a wholesaler in order to make room for the next season’s products. The model is then applied to a real-world case of a Jeans retailer in three different risk attitudes. Results show that the retailer should follow an almost fixed non-dynamic pricing strategy in the risk-taking attitudes, and a more flexible dynamic pricing strategy in risk-averse attitudes.

Suggested Citation

  • Mahmoud Dehghan Nayeri & Amir-Nader Haghbin & Abdolkarim Mohammadi-Balani & Karim Bayat, 2020. "A multi-objective mean–variance mathematical programming approach to combined phase-out and clearance pricing strategy for seasonal products: case study of a Jeans retailer," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(3), pages 210-217, June.
    • Handle: RePEc:pal:jorapm:v:19:y:2020:i:3:d:10.1057_s41272-019-00219-0
    DOI: 10.1057/s41272-019-00219-0
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