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Mining logistics data to assure the quality in a sustainable food supply chain: A case in the red wine industry

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  • Ting, S.L.
  • Tse, Y.K.
  • Ho, G.T.S.
  • Chung, S.H.
  • Pang, G.

Abstract

In recent years, food supply chains have faced increased quality risk, caused by the extended global supply chain and increased consumer demands on quality and safety. Given the concern regarding quality sustainability in the food supply chain, much attention is being paid to continuous planning and monitoring of quality assurance practices in the supply chain network. In this research, we propose a supply chain quality sustainability decision support system (QSDSS), adopting association rule mining and Dempster's rule of combination techniques. The aim of QSDSS is to support managers in food manufacturing firms to define good logistics plans in order to maintain the quality and safety of food products. We conduct a case study of a Hong Kong red wine company in order to illustrate the applicability and effectiveness of QSDSS. Implications of the proposed approach are discussed, and suggestions for future work are outlined.

Suggested Citation

  • Ting, S.L. & Tse, Y.K. & Ho, G.T.S. & Chung, S.H. & Pang, G., 2014. "Mining logistics data to assure the quality in a sustainable food supply chain: A case in the red wine industry," International Journal of Production Economics, Elsevier, vol. 152(C), pages 200-209.
    • Handle: RePEc:eee:proeco:v:152:y:2014:i:c:p:200-209
    DOI: 10.1016/j.ijpe.2013.12.010
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    References listed on IDEAS

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    Cited by:

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    8. Kamble, Sachin S. & Gunasekaran, Angappa & Gawankar, Shradha A., 2020. "Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications," International Journal of Production Economics, Elsevier, vol. 219(C), pages 179-194.
    9. Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Maxim Kotsemir & Alina Lavrynenko, 2018. "Mapping the Radical Innovations in Food Industry: A Text Mining Study," HSE Working papers WP BRP 80/STI/2018, National Research University Higher School of Economics.
    10. Naoum Tsolakis & Roman Schumacher & Manoj Dora & Mukesh Kumar, 2023. "Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?," Annals of Operations Research, Springer, vol. 327(1), pages 157-210, August.
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    12. Rodrigues, Daniel & Teixeira, Rafael & Shockley, Jeff, 2019. "Inspection agency monitoring of food safety in an emerging economy: A multilevel analysis of Brazil's beef production industry," International Journal of Production Economics, Elsevier, vol. 214(C), pages 1-16.
    13. Anup Kumar & Santosh Kumar Shrivastav & Avinash K. Shrivastava & Rashmi Ranjan Panigrahi & Abbas Mardani & Fausto Cavallaro, 2023. "Sustainable Supply Chain Management, Performance Measurement, and Management: A Review," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    14. Miao Su & Su‐Han Woo & Xiaochun Chen & Keun‐sik Park, 2023. "Identifying critical success factors for the agri‐food cold chain's sustainable development: When the strategy system comes into play," Business Strategy and the Environment, Wiley Blackwell, vol. 32(1), pages 444-461, January.
    15. Mauricio Varas & Franco Basso & Armin Lüer-Villagra & Alejandro Mac Cawley & Sergio Maturana, 2019. "Managing premium wines using an $$(s - 1,s)$$ ( s - 1 , s ) inventory policy: a heuristic solution approach," Annals of Operations Research, Springer, vol. 280(1), pages 351-376, September.
    16. Van Nguyen, Truong & Zhang, Jie & Zhou, Li & Meng, Meng & He, Yong, 2020. "A data-driven optimization of large-scale dry port location using the hybrid approach of data mining and complex network theory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    17. Franco Basso & Juan Pablo Contreras & Raúl Pezoa & Alejandro Troncozo & Mauricio Varas, 2023. "Optimizing the wine transportation process from bottling plants to ports," Operational Research, Springer, vol. 23(2), pages 1-28, June.
    18. Tobias Rebs & Marcus Brandenburg & Stefan Seuring & Margarita Stohler, 2018. "Stakeholder influences and risks in sustainable supply chain management: a comparison of qualitative and quantitative studies," Business Research, Springer;German Academic Association for Business Research, vol. 11(2), pages 197-237, September.
    19. Simonetto, Marco & Sgarbossa, Fabio & Battini, Daria & Govindan, Kannan, 2022. "Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda," International Journal of Production Economics, Elsevier, vol. 253(C).
    20. Dutta, Debprotim & Bose, Indranil, 2015. "Managing a Big Data project: The case of Ramco Cements Limited," International Journal of Production Economics, Elsevier, vol. 165(C), pages 293-306.
    21. Ahmed Zainul Abideen & Veera Pandiyan Kaliani Sundram & Jaafar Pyeman & Abdul Kadir Othman & Shahryar Sorooshian, 2021. "Food Supply Chain Transformation through Technology and Future Research Directions—A Systematic Review," Logistics, MDPI, vol. 5(4), pages 1-24, November.
    22. Wang, Haiyan & Zhan, Sha-lei & Ng, Chi To & Cheng, T.C.E., 2020. "Coordinating quality, time, and carbon emissions in perishable food production: A new technology integrating GERT and the Bayesian approach," International Journal of Production Economics, Elsevier, vol. 225(C).

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