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Other literature type . 2025
License: CC BY
Data sources: Datacite
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Other literature type . 2025
License: CC BY
Data sources: Datacite
https://doi.org/10.2139/ssrn.4...
Article . 2023 . Peer-reviewed
Data sources: Crossref
International Journal of Production Research
Article . 2025 . Peer-reviewed
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DBLP
Article . 2025
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Optimal Markdown Policies for Perishable Products with Fixed Shelf Life

Authors: Mohammad S. Moshtagh; Yun Zhou; Manish Verma;

Optimal Markdown Policies for Perishable Products with Fixed Shelf Life

Abstract

The market for perishable products is subject to short selling seasons and volatile demand. Retailers use strategies such as issuing policies, quality disclosure, and markdown pricing to maximise revenue and reduce waste. Among the markdown options, the best policy is not always clear-cut, as there is a trade-off between the complexity of the policy and the revenue generated. To address this, we introduce a joint model that optimises issuing, quality disclosure, production, and markdown pricing for perishable products with fixed shelf lives and freshness-sensitive customers. We make the first attempt to theoretically and numerically evaluate the effectiveness of different markdown policies, including single-stage, multiple-stage, and dynamic markdown policies. Empirical case studies validate the models, showing that hiding product quality is optimal and the best issuing policy depends on customer freshness sensitivity. We prove that the value of markdown policies asymptotically vanishes as the market demand or customers' maximum willingness-to-pay (WTP) increases. Conversely, the benefits of markdown policies increase when per unit expiration, shortage, and production costs rise. Additionally, while multiple-stage and dynamic markdown policies can significantly benefit the system, in most cases, their benefits over the single-stage policies are insignificant and vanish asymptotically.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
Green