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Optimal markdown policy of perishable food under the consumer price fairness perception

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  • Xiaohuan Wang
  • Zhi-Ping Fan
  • Zheng Liu

Abstract

Markdown policies are widely used by retailers to sell perishable food. Consumers purchase food at different prices during different sales periods. Some consumers may compare their experience with others who purchase the same items. Price unfairness or inequity is perceived when different prices are quoted without reasonable explanations. This study develops an optimal markdown model for perishable food pricing to optimise the food retailer revenue and enable a maximum aggregated consumer utility considering individuals’ price fairness perception. The model serves as the first step in evaluating trade-offs between food retailer revenue and consumer utility. In addition, it enables consumer utility to be depicted through perceived price fairness by including the effects of food perishability and scarcity. Another innovative feature is the equalisation of the consumer average aggregated utility during different sales periods as a condition of intertemporal price fairness perception. The proposed model is compared with two benchmark models to justify the effectiveness and advantages in the example. Finally, a sensitive analysis based on the food deterioration rate, consumer food desire rate and consumer average reservation price is conducted to justify the manner in which these factors influence the optimal pricing policy, and managerial insights are suggested for food retailers.

Suggested Citation

  • Xiaohuan Wang & Zhi-Ping Fan & Zheng Liu, 2016. "Optimal markdown policy of perishable food under the consumer price fairness perception," International Journal of Production Research, Taylor & Francis Journals, vol. 54(19), pages 5811-5828, October.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:19:p:5811-5828
    DOI: 10.1080/00207543.2016.1179810
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    Cited by:

    1. Ilkyeong Moon & Yoon Jea Jeong & Subrata Saha, 2020. "Investment and coordination decisions in a supply chain of fresh agricultural products," Operational Research, Springer, vol. 20(4), pages 2307-2331, December.
    2. Xiaohuan Wang & Zhi-Ping Fan & Haibin Li & Yujie Li, 2023. "Discriminatory Pricing Strategy for Sustainable Tourism in Theme Parks considering Visitors’ Price Fairness and Service Value Perceptions," Sustainability, MDPI, vol. 15(19), pages 1-19, September.
    3. Hongyong Fu & Kok Loy Teo & Yujie Li & Lei Wang, 2018. "Weather Risk–Reward Contract for Sustainable Agri-Food Supply Chain with Loss-Averse Farmer," Sustainability, MDPI, vol. 10(12), pages 1-25, December.
    4. Yixian Chen & Prakhar Mehrotra & Nitin Kishore Sai Samala & Kamilia Ahmadi & Viresh Jivane & Linsey Pang & Monika Shrivastav & Nate Lyman & Scott Pleiman, 2021. "A Multiobjective Optimization for Clearance in Walmart Brick-and-Mortar Stores," Interfaces, INFORMS, vol. 51(1), pages 76-89, February.
    5. Mitra, Subrata, 2018. "Newsvendor problem with clearance pricing," European Journal of Operational Research, Elsevier, vol. 268(1), pages 193-202.
    6. Vincent C. Li & Yat-wah Wan & Chi-Leung Chu & Yi-Cheng Lin, 2020. "A Dynamic Programming-Based Heuristic for Markdown Pricing and Inventory Allocation of a Seasonal Product in a Retail Chain," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 37(01), pages 1-30, January.
    7. Guangxing Wei & Linrong Zhou & Binta Bary, 2022. "Operational Decision and Sustainability of Green Agricultural Supply Chain with Consumer-Oriented Altruism," Sustainability, MDPI, vol. 14(19), pages 1-25, September.

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