Sustainable food supply chain screening and relationship analysis with unknown criteria weight information
Abstract
Sustainable food supply chain management (SFSC) can control food loss and waste by reducing resource consumption and environmental pollution, thereby ensuring sustainable food consumption and production patterns. Scholars have investigated specific aspects or links in SFSC but rarely studied the sustainability evaluation and selection of a whole supply chain to provide management suggestions under uncertain decision-making environments. This paper presents a comprehensive multiple criteria decision-making method called the SMAA-ORESTE method for SFSC selection. To reduce experts’ efforts, the holistic acceptability index in the SMAA-2 method is used to screen inferior SFSCs from a large number of alternatives. Then, the ORESTE method is combined with the SMAA method to evaluate SFSCs under uncertain information. The ORESTE method can specifically analyze the relationship between alternatives, and the SMAA method can analyze alternatives with unknown criteria weights by Monte Carlo simulation. The proposed method ensures the robustness and credibility of obtained ranking results. An illustrative example validates the applicability and robustness of the proposed method in selecting SFSCs with unknown criteria weights.
Keyword : sustainable food supply chain;, multiple criteria group decision-making, SMAA, ORESTE, food loss
How to Cite
Liao, H., Liu, F., Long, Y., Zhang, Z., & Zavadskas, E. K. (2024). Sustainable food supply chain screening and relationship analysis with unknown criteria weight information. Technological and Economic Development of Economy, 30(6), 1732–1768. https://doi.org/10.3846/tede.2024.22127
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Golini, R., Moretto, A., Caniato, F., Caridi, M., Kalchschmidt, M. (2017). Developing sustainability in the Italian meat supply chain: An empirical investigation. International Journal of Production Research, 55(4), 1183–1209. https://doi.org/10.1080/00207543.2016.1234724
Govindan, K., Kadziński, M., & Sivakumar, R. (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega, 71, 129–145. https://doi.org/10.1016/j.omega.2016.10.004
Greco, S., Ishizaka, A., Tasiou, M., & Torrisi, G. (2020). The ordinal input for cardinal output approach of non-compensatory composite indicators: The PROMETHEE scoring method. European Journal of Operational Research, 288(1), 225–246. https://doi.org/10.1016/j.ejor.2020.05.036
Grunert, K. G. (2005). Food quality and safety: Consumer perception and demand. European Review of Agricultural Economics, 32(3), 369–391. https://doi.org/10.1093/eurrag/jbi011
Gupta, R., & Shankar, R. (2016). Ranking of collusive behaviour in Indian agro-supply chain using interval 2-tuple linguistic TOPSIS method. Journal of Modelling in Management, 11(4), 949–966. https://doi.org/10.1108/JM2-03-2015-0006
Izadikhah, M., Saen, R. F., Ahmadi, K., Shamsi, M. (2020). How to use fuzzy screening system and data envelopment analysis for clustering sustainable suppliers? A case study in Iran. Journal of Enterprise Information Management, 34(1), 199–229. https://doi.org/10.1108/JEIM-09-2019-0262
Khan, S. A. R., Mathew, M., Dominic, P. D. D., & Umar, M. (2022). Evaluation and selection strategy for green supply chain using interval-valued q-rung orthopair fuzzy combinative distance-based assessment. Environment, Development and Sustainability, 24, 10633–10665. https://doi.org/10.1007/s10668-021-01876-1
Kumar, A., Mangla, S. K., Kumar, P. (2022). An integrated literature review on sustainable food supply chains: Exploring research themes and future directions. Science of The Total Environment, 821, Article 153411. https://doi.org/10.1016/j.scitotenv.2022.153411
Lahdelma, R., Hokkanen, J., & Salminen, P. (1998). SMAA – Stochastic multiobjective acceptability analysis. European Journal of Operational Research, 106(1), 137–143. https://doi.org/10.1016/S0377-2217(97)00163-X
Lahdelma, R., & Salminen, P. (2001). SMAA-2: Stochastic multicriteria acceptability analysis for group decision making. Operations Research, 49(3), 444–454. https://doi.org/10.1287/opre.49.3.444.11220
Lahdelma, R., & Salminen, P. (2002). Pseudo-criteria versus linear utility function in stochastic multi-criteria acceptability analysis. European Journal of Operational Research, 141(2), 454–469. https://doi.org/10.1016/S0377-2217(01)00276-4
Li, D., Wang, X. J., Chan, H. K., & Manzini, R. (2014). Sustainable food supply chain management. International Journal of Production Economics, 152, 1–8. https://doi.org/10.1016/j.ijpe.2014.04.003
Liao, H., Wu, X., Liang, X., Xu, J., & Francisco, H. (2018). A new hesitant fuzzy linguistic ORESTE method for hybrid multicriteria decision making. IEEE Transactions on Fuzzy Systems, 26(6), 3793–807. https://doi.org/10.1109/TFUZZ.2018.2849368
Long, Y. L., & Liao, H. C. (2021). A social participatory allocation network method with partial relations of alternatives and its application in sustainable food supply chain selection. Applied Soft Computing, 109, Article 107550. https://doi.org/10.1016/j.asoc.2021.107550
Long, Y., Liao, H., & Lev, B. (2023). Sustainable supply chain management: Definition, bibliometrics, applications, and future directions. In F. P. García Márquez & B. Lev (Eds.), Sustainability: Vol. 333. International Series in Operations Research & Management Science (pp. 27–52). Springer. https://doi.org/10.1007/978-3-031-16620-4_3
Manzini, R., & Accorsi, R. (2013). The new conceptual framework for food supply chain assessment. Journal of Food Engineering, 115(2), 251–263. https://doi.org/10.1016/j.jfoodeng.2012.10.026
Miranda-Ackerman, M. A., Azzaro-Pantel, C., & Aguilar-Lasserre, A. A. (2017). A green supply chain network design framework for the processed food industry: Application to the orange juice agrofood cluster. Computers & Industrial Engineering, 109, 369–389. https://doi.org/10.1016/j.cie.2017.04.031
Mohseni, S., Baghizadeh, K., & Pahl, J. (2022). Evaluating barriers and drivers to sustainable food supply chains. Mathematical Problems in Engineering. https://doi.org/10.1155/2022/4486132
Oglethorpe, D. (2010). Optimising economic, environmental, and social objectives: A goal-programming approach in the food sector. Environment and Planning A: Economy and Space, 42(5), 1239–1254. https://doi.org/10.1068/a42292
Pastijn, H., & Leysen, J. (1989). Constructing an outranking relation with ORESTE. Mathematical & Computer Modelling, 12(10–11), 1255–1268. https://doi.org/10.1016/0895-7177(89)90367-1
Patidar, S., Shukla, A. C., & Sukhwani, V. K. (2021). Food supply chain management (FSCM): A structured literature review and future research agenda. Journal of Advances in Management Research, 19(2), 272–299. https://doi.org/10.1108/JAMR-04-2021-0143
Pelissari, R., Oliveira, M. C., Amor, S. B., Kandakoglu, A., & Helleno, A. L. (2020). SMAA methods and their applications: A literature review and future research directions. Annals of Operations Research, 293(2), 433–493. https://doi.org/10.1007/s10479-019-03151-z
Pullman, M. E., Maloni, M. J., Carter, C. R. (2009). Food for thought: Social versus environmental sustainability practices and performance outcomes. Journal of Supply Chain Management, 45(4), 38–54. https://doi.org/10.1111/j.1745-493X.2009.03175.x
Raut, R., Kharat, M., Kamble, S., & Kumar, C. S. (2018). Sustainable evaluation and selection of potential third-party logistics (3PL) providers: An integrated MCDM approach. Benchmarking, 25(1), 76–97. https://doi.org/10.1108/BIJ-05-2016-0065
Rezaei, J., Nispeling, T., Sarkis, J., & Tavasszy, L. (2016). A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method. Journal of Cleaner Production, 135, 577–588. https://doi.org/10.1016/j.jclepro.2016.06.125
Rezaei, J., Papakonstantinou, A., Tavasszy, L., Pesch, U., & Kana, A. (2019). Sustainable product-package design in a food supply chain: A multi-criteria life cycle approach. Packaging Technology and Science, 32(2), 85–101. https://doi.org/10.1002/pts.2418
Roubens, M. (1982). Preference relations on actions and criteria in multicriteria decision making. European Journal of Operational Research, 10(1), 51–55. https://doi.org/10.1016/0377-2217(82)90131-X
Roy, B. (1971). Problems and methods with multiple objective functions. Mathematical Programming, 1(1), 239–266. https://doi.org/10.1007/BF01584088
Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & Industrial Engineering, 140, Article 106231. https://doi.org/10.1016/j.cie.2019.106231
Sufiyan, M., Haleem, A., Khan, S., & Khan, M. I. (2019). Evaluating food supply chain performance using hybrid fuzzy MCDM technique. Sustainable Production and Consumption, 20, 40–57. https://doi.org/10.1016/j.spc.2019.03.004
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