A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks

KABADURMUS, Ozgur, KAYIKCI, Yasanur, DEMIR, Sercan and KOC, Basar (2023). A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks. Socio-Economic Planning Sciences, 85: 101417.

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Link to published version:: https://doi.org/10.1016/j.seps.2022.101417


The unexpected emergence of the COVID-19 pandemic has changed how grocery shopping is done. The grocery retail stores need to ensure hygiene, quality, and safety concerns in-store shopping by providing “no-touch” smart packaging solutions for agri-food products. The benefit of smart packaging is to inform consumers about the freshness level of a packaged product without having direct contact. This paper proposes a data-driven decision support system that uses smart packaging as a smart product-service system to manage the sustainable grocery store supply chain during outbreaks to prevent food waste. The proposed model dynamically updates the price of a packaged perishable product depending on freshness level while reducing food waste and the number of rejected customers and maximising profit by increasing the inventory turnover rate of grocery stores. The model was tested on a hypothetical but realistic case study of a single product. The results of this study showed that stock capacities, freshness discount rate, freshness period, and quantity discounts significantly affect the performance of a grocery store supply chain during outbreaks.

Item Type: Article
Uncontrolled Keywords: Operations Research; 0102 Applied Mathematics; 1205 Urban and Regional Planning
Identification Number: https://doi.org/10.1016/j.seps.2022.101417
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 09 Aug 2022 09:47
Last Modified: 11 Oct 2023 17:47
URI: https://shura.shu.ac.uk/id/eprint/30569

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