Evidence map›Paper›PMID 41750934›Full record

ArticleFoods (Basel, Switzerland)2026

IoT-Enabled Quality-Triggered Markdown Pricing for Perishable Food: Equity and Waste Implications.

Elkafi Hassini, Mohamed Ben-Daya, Zied Bahroun

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Elkafi HassiniDeGroote School of Business, McMaster University, Hamilton, ON L8S 4M4, Canada.ORCID 0000-0002-5337-5389
Mohamed Ben-DayaDepartment of Industrial Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates.
Zied BahrounDepartment of Industrial Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates.ORCID 0000-0003-2832-3672

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inequitable access to affordable, nutritious food is partly sustained because markdowns on perishable products are often delayed until quality deterioration becomes visible, through which affordability gains are limited and waste is increased. In this study, the extent to which Internet of Things (IoT) real-time quality monitoring enables quality-triggered markdowns that reduce waste while improving food equity is examined. An analytical pricing and markdown model for perishables with quality-sensitive demand is developed, and optimal decisions under IoT-enabled quality observability and under a baseline setting without IoT are compared. Convexity is established for the retailer's problem, and closed-form solutions are derived for the optimal regular price, markdown timing, and markdown depth. Under continuous quality visibility, earlier markdown initiation within the selling horizon is shown to be optimal while product quality remains acceptable, and a deeper markdown than in the non-IoT setting is shown to be optimal. Through numerical experiments, increased sell-through before products become unsalable is demonstrated, waste reduction is quantified, and an expanded time window is shown in which price-sensitive consumers can purchase acceptable-quality food at a lower price. Overall, improved food equity is supported by proactive, quality-aligned pricing policies without retailer profitability being sacrificed.

Indexed as

dynamic pricing and markdownsfood access equityInternet of Things (IoT)perishable food supply chainsquality-sensitive demand

Identifiers

PMID41750934
PMCPMC12939744

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.