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

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  • Kabadurmus, Ozgur
  • Kayikci, Yaşanur
  • Demir, Sercan
  • Koc, Basar

Abstract

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.

Suggested Citation

  • Kabadurmus, Ozgur & Kayikci, Yaşanur & Demir, Sercan & Koc, Basar, 2023. "A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    • Handle: RePEc:eee:soceps:v:85:y:2023:i:c:s003801212200218x
    DOI: 10.1016/j.seps.2022.101417
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    1. Meherishi, Lavanya & Narayana, Sushmita A. & Ranjani, K.S., 2021. "Integrated product and packaging decisions with secondary packaging returns and protective packaging management," European Journal of Operational Research, Elsevier, vol. 292(3), pages 930-952.
    2. Tiwari, Sunil & Jaggi, Chandra K. & Gupta, Mamta & Cárdenas-Barrón, Leopoldo Eduardo, 2018. "Optimal pricing and lot-sizing policy for supply chain system with deteriorating items under limited storage capacity," International Journal of Production Economics, Elsevier, vol. 200(C), pages 278-290.
    3. Bo Yan & Xiaoxu Chen & Qin Yuan & Xiaotai Zhou, 2020. "Sustainability in fresh agricultural product supply chain based on radio frequency identification under an emergency," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(4), pages 1343-1361, December.
    4. Dong Li & Xiaojun Wang, 2017. "Dynamic supply chain decisions based on networked sensor data: an application in the chilled food retail chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5127-5141, September.
    5. Frishammar, Johan & Richtnér, Anders & Brattström, Anna & Magnusson, Mats & Björk, Jennie, 2019. "Opportunities and challenges in the new innovation landscape: Implications for innovation auditing and innovation management," European Management Journal, Elsevier, vol. 37(2), pages 151-164.
    6. Seyed Mohammad Gholami-Zanjani & Mohammad Saeed Jabalameli & Walid Klibi & Mir Saman Pishvaee, 2021. "A robust location-inventory model for food supply chains operating under disruptions with ripple effects," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 301-324, January.
    7. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.
    8. Lee, Deishin & Tongarlak, Mustafa Hayri, 2017. "Converting retail food waste into by-product," European Journal of Operational Research, Elsevier, vol. 257(3), pages 944-956.
    9. Sven Winkelhaus & Eric H. Grosse, 2020. "Logistics 4.0: a systematic review towards a new logistics system," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 18-43, January.
    10. Wang, Xiaojun & Li, Dong, 2012. "A dynamic product quality evaluation based pricing model for perishable food supply chains," Omega, Elsevier, vol. 40(6), pages 906-917.
    11. Herbon, Avi & Levner, Eugene & Cheng, T.C.E., 2014. "Perishable inventory management with dynamic pricing using time–temperature indicators linked to automatic detecting devices," International Journal of Production Economics, Elsevier, vol. 147(PC), pages 605-613.
    12. Cenamor, J. & Rönnberg Sjödin, D. & Parida, V., 2017. "Adopting a platform approach in servitization: Leveraging the value of digitalization," International Journal of Production Economics, Elsevier, vol. 192(C), pages 54-65.
    13. Luiz Philipi Calegari & Marianne Costa Avalone & Diego Castro Fettermann, 2020. "Barriers and enablers to food mass customization," Journal of Agribusiness in Developing and Emerging Economies, Emerald Group Publishing Limited, vol. 10(4), pages 403-428, April.
    14. Cicatiello, Clara & Franco, Silvio & Pancino, Barbara & Blasi, Emanuele & Falasconi, Luca, 2017. "The dark side of retail food waste: Evidences from in-store data," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 273-281.
    15. Vazquez-Martinez, Gerardo A. & Gonzalez-Compean, J.L. & Sosa-Sosa, Victor J. & Morales-Sandoval, Miguel & Perez, Jesus Carretero, 2018. "CloudChain: A novel distribution model for digital products based on supply chain principles," International Journal of Information Management, Elsevier, vol. 39(C), pages 90-103.
    16. Ahmed Zainul Abideen & Veera Pandiyan Kaliani Sundram & Jaafar Pyeman & Abdul Kadir Othman & Shahryar Sorooshian, 2021. "Digital Twin Integrated Reinforced Learning in Supply Chain and Logistics," Logistics, MDPI, vol. 5(4), pages 1-22, November.
    17. Winkelhaus, S. & Grosse, E. H., 2020. "Logistics 4.0: a systematic review towards a new logistics system," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 118539, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    18. Dye, Chung-Yuan, 2020. "Optimal joint dynamic pricing, advertising and inventory control model for perishable items with psychic stock effect," European Journal of Operational Research, Elsevier, vol. 283(2), pages 576-587.
    19. Mohamed Ben-Daya & Elkafi Hassini & Zied Bahroun, 2019. "Internet of things and supply chain management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4719-4742, August.
    20. Buisman, M.E. & Haijema, R. & Bloemhof-Ruwaard, J.M., 2019. "Discounting and dynamic shelf life to reduce fresh food waste at retailers," International Journal of Production Economics, Elsevier, vol. 209(C), pages 274-284.
    21. Rymaszewska, Anna & Helo, Petri & Gunasekaran, Angappa, 2017. "IoT powered servitization of manufacturing – an exploratory case study," International Journal of Production Economics, Elsevier, vol. 192(C), pages 92-105.
    22. Bernhard Wohner & Erik Pauer & Victoria Heinrich & Manfred Tacker, 2019. "Packaging-Related Food Losses and Waste: An Overview of Drivers and Issues," Sustainability, MDPI, vol. 11(1), pages 1-15, January.
    23. Rubi Das & Abhijit Barman & Pijus Kanti De, 2022. "Integration of pricing and inventory decisions of deteriorating item in a decentralized supply chain: a Stackelberg-game approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 479-493, February.
    24. Awan, Usama & Shamim, Saqib & Khan, Zaheer & Zia, Najam Ul & Shariq, Syed Muhammad & Khan, Muhammad Naveed, 2021. "Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    25. Chen, Jing & Dong, Ming & Rong, Ying & Yang, Liang, 2018. "Dynamic pricing for deteriorating products with menu cost," Omega, Elsevier, vol. 75(C), pages 13-26.
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