JOURNAL ARTICLE

Retailing Strategies of Imperfect Produce and the Battle Against Food Waste.

  • Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2025, v. 27, n. 4. P. 1146 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Kazaz, Burak; Xu, Fasheng; Yu, Haoran 3 of 3

Abstract

This article investigates optimal retailing strategies for imperfect produce—fruits and vegetables that are edible but cosmetically flawed—and their implications for food waste reduction. It analyzes three common retailer approaches: discarding imperfect produce, bunching imperfect with perfect produce in a single package, and differentiating by selling them separately at different prices. Using analytical models that incorporate consumer preferences and quality perceptions, the study identifies market conditions favoring each strategy and reveals that widely advocated policy interventions, such as consumer education and relaxing tolerance limits on imperfect produce, may unintentionally increase food waste due to effects like sales cannibalization and shifting waste from farms to retailers. Extensions considering upcycling imperfect produce, mixed retailing strategies, and full-shelf ordering policies confirm the robustness of these findings. The research offers actionable insights for retailers and policymakers, emphasizing the complexity of managing imperfect produce and cautioning against simplistic solutions to food waste.

Additional Information

  • Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2025/07, Vol. 27, Issue 4, p1146
  • Document Type:Article
  • Subject Area:Nutrition and Dietetics
  • Publication Date:2025
  • ISSN:1523-4614
  • DOI:10.1287/msom.2023.0167
  • Accession Number:187706280
  • Copyright Statement:Copyright of Manufacturing & Service Operations Management (M&SOM) (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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