Analysis of the Causal Relationship between Factors Affecting the Management of a Sustainable Supply Chain of Chicken Meat

Document Type : Research Paper

Authors

1 Ph.d. student of Agricultural Economics, Islamic Azad University, Marvdasht Branch, Shiraz, Iran

2 Associate professor of Agricultural Economics, Islamic Azad University, Marvdasht Branch, Shiraz, Iran.

3 Assistant Professor, Faculty of Fars Research Centre for Agriculture, Shiraz, Iran.

4 Assistant Professor, Department of Economics, Islamic Azad University, Yazd Branch, Yazd, Iran.

Abstract

 In this study, using the fuzzy DEMATEL approach, causal relationships between factors and criteria for sustainable chicken meat supply chain management were evaluated from three perspectives: optimistic, pessimistic and moderate. For this purpose, a group of experts was considered for mental responses to these effects in the form of paired comparison questionnaires. In this regard, 16 factors or criteria affecting the sustainable supply chain of chicken meat were extracted by reviewing the literature in this field as well as the opinions of experts. These factors were divided into four categories: critical, effective, dependent and elimination. The results of causal evaluation showed that in the optimistic view most of these factors are critical and in the pessimistic view most of the factors are elimination type. The results showed that the growth of profits from the implementation of sustainable supply chain, the cost of material recycling in the process of sustainable supply chain and investment of environmental protection in the process of sustainable supply chain are three factors that are critical in all three perspectives: optimistic, pessimistic and moderate. Recycling of resources used in the sustainable supply chain process is also one of the variables affecting other factors. Accordingly, government support for the development of new technologies, the development of logistics infrastructure and increasing energy and water productivity along the chicken supply chain not only can increase profits, but also reduce recycling costs and expand environmental investment.

Keywords

References

Ali, S. M., Moktadir, M. A., Kabir, G., Chakma, J., Rumi, M. J. U., & Islam, M. T. (2019). Framework for evaluating risks in food supply chain: Implications in food wastage reduction. Journal of Cleaner Production, 228, 786-800.
Amani, M., Ashrafi, A., & Dehghanan, H. (2017). Assessing the barriers to green supply chain adoption using fuzzy DEMATEL technique. Journal of Business Intelligence Management Studies, 5, 147-179.
An, D., Yang, Y., Chai, X., Xi, B., Dong, L., & Ren, J. (2015). Mitigating pollution of hazardous materials from WEEE of China: portfolio selection for a sustainable future based on multi-criteria decision making. Resources, Conservation & Recycling, 105, 198-210.
Asan, U., Kadaifci, C., Bozdag, E., Soyer, A., & Serdarasan, S. (2018). A new approach to DEMATEL based on interval-valued hesitant fuzzy sets. Applied Soft Computing, 66, 34-49.
Ashfaq, M., Hassan, S., Abbas, A., Razzaq, A., Mehdi, M., Ariyawardana, A., & Anwar, M. (2019). Critical issues at the upstream level in sustainable supply chain management of agri-food industries: Evidence from Pakistan’s citrus industry. Sustainability, 11(5), 1326.
Azizi, S. (2018). Identify and prioritize the factors affecting the performance of the sustainable supply chain. 2nd International Conference on New Developments in Management, Economics and Accounting, Tehran, Iran.
Behdani, B., Adhitya, A., Lukszo, Z., & Srinivasan, R. (2012). Mitigating supply disruption for a global chemical supply chain-Application of agent-based modeling. In Computer Aided Chemical Engineering, 31, 1070-1074.
Benis, K., & Ferrão, P. (2017). Potential mitigation of the environmental impacts of food systems through urban and peri-urban agriculture (UPA) - a life cycle assessment approach. Journal of Cleaner Production, 140, 784-795.
Bloemhof, J. M., van der Vorst, J. G. A. J., Bastl, M., & Allaoui, H. (2015). Sustainability assessment of food chain logistics. International Journal of Logistics Research and Applications, 18(2), 101-117.
Chiffoleau, Y., Millet-Amrani, S., & Canard, A. (2016). From short food supply chains to sustainable agriculture in urban food systems: food democracy as a vector of transition. Agriculture, 6(4), 1-18.
Chopra, S., & Meindl, P. (2007). Supply chain management. Strategy, planning & operation. In Das summa summarum des management (pp. 265-275). Gabler.‏
Country Livestock Support Company. (2016). from http://www.iranslal.com (In Farsi)
Dunne, J. B., Chambers, K. J., Giombolini, K. J., & Schlegel, S. A. (2011). What does 'Local' mean in the Grocery Store? Multiplicity in food retailers' perspectives on sourcing and marketing local foods. Renewable Agriculture and Food Systems, 26(1), 46-59.
Erfanifar, S., Bakhshoodeh, M., & Zibaei, M. (2020). Valuing the Quality of Chicken Meat from Consumers' Viewpoint in Shiraz City of Iran. Agricultural Economics and Development, 28(1), 143-169. (In Farsi)
Gabus, A., & Fontela, E. (1973). Perceptions of the world problematique: communication procedure. Communicating with Those Bearing Collective Responsibility, 1.‏
Jeng, D. J. F. (2015). Generating a causal model of supply chain collaboration using the fuzzy DEMATEL technique. Computers & Industrial Engineering, 87, 283-295.
Kuo, R. J., Wang, Y. C., & Tien, F. C. (2010). Integration of artificial neural network and MADA methods for green supplier selection. Journal of Cleaner Production, 18(12), 1161-1170.
Lin, C. J., & Wu, W. W. (2004). A fuzzy extension of the DEMATEL method for group decision-making. In Proceedings of the 1st operations research society of Taiwan annual conference, 843-852.
Lin, K. P., Tseng, M. L., & Pai, P. F. (2018). Sustainable supply chain management using approximate fuzzy DEMATEL method. Resources, Conservation and Recycling, 128, 134-142.
Mardani Najafabadi, M., Mirzaei, A., Abdeshahi, A., & Azarm, H. (2020). Determining the efficiency of broiler chicken units in Sistan region, using interval data envelopment analysis and Mont Carlo simulation approach. Iranian Journal of Agricultural Economics and Development Research, 2, 179-194. (In Farsi)
Maye, D., & Kirwan, J. (2010). Alternative food networks. Sociology of Agriculture and Food, 20(3), 383-389.
Mirzaei, A., Azarm, H., Noshad, M., & Behbahani, B. A. (2021). Identifying Barriers and Problems in the Sustainable Supply Chain of the Chicken Meat Industry Using Grounded Theory. Iranian Journal of Biosystems Engineering, 52(2), 271-285.
Nsamzinshuti, A., Janjevic, M., Rigo, N., & Ndiaye, A. B. (2017). Logistics collaboration solutions to improve short food supply chain solution performance. In Proceedings of the World Conference on Supply Chain Management, 2(1), 57-69.
Paciarotti, C., & Torregiani, F. (2021). The logistics of the short food supply chain: A literature review. Sustainable Production and Consumption, 26, 428-442.
Rizou, M., Galanakis, I. M., Aldawoud, T. M., & Galanakis, C. M. (2020). Safety of foods, food supply chain and environment within the COVID-19 pandemic. Trends in Food Science & Technology, 102, 293-299.
Seuring, S., & Müller, M. (2008). Core issues in sustainable supply chain management–a Delphi study. Business strategy and the environment, 17(8), 455-466.
Simatupang, T. M., & Sridharan, R. (2008). Design for supply chain collaboration. Business Process Management Journal, 14(3), 401-418
Srivastava, S. K. (2007). Green supply‐chain management: a state‐of‐the‐art literature review. International Journal of Management Reviews, 9(1), 53-80.
Su, C. M., Horng, D. J., Tseng, M. L., Chiu, A. S. F., Wu, K. J., & Chen, H. P. (2016). Improving sustainable supply chain management using a novel hierarchical grey-DEMATEL approach. Journal of Cleaner Production, 134, 469–481.
Todorovic, V., Maslaric, M., Bojic, S., Jokic, M., Mircetic, D., & Nikolicic, S. (2018). Solutions for more sustainable distribution in the short food supply chains. Sustainability, 10(10), 1-27.
Torra, V., & Narukawa, Y. (2009, August). On hesitant fuzzy sets and decision. In 2009 IEEE International Conference on Fuzzy Systems (pp. 1378-1382). IEEE.‏
Tseng, M. L., Lin, Y. H., Tan, K., Chen, R. H., & Chen, Y. H. (2014). Using TODIM to evaluate green supply chain practices under uncertainty. Applied Mathematical Modelling, 38, 2983-2995.
Wei, P. L., Huang, J. H., Tzeng, G. H., & Wu, S. I. (2010). Causal modeling of web advertising effects by improving SEM based on DEMATEL technique. International Journal of Information Technology & Decision Making, 9(5), 799-829.
Wu, K. J., Liao, C. J., Tseng, M. L., & Chiu, A. S. F. (2015). Exploring decisive factors in green supply chain practices under uncertainty. International Journal of Production Economics, 159, 147-157.
Yang, J., Liu, H., Xiao, F., & Wang, J. (2021). Identification of Key Drivers for Sustainable Supply-Chain Management of Fresh Food Based on Rough DEMATEL. International Journal of Information Systems and Supply Chain Management (IJISSCM), 14(2), 1-29.
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information Science, 8(3), 199-249.
Iranian Journal of Biosystems Engineering
Volume 53, Issue 3
October 2022
Pages 231-248

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History

  • Receive Date: 21 December 2021
  • Revise Date: 01 May 2022
  • Accept Date: 19 September 2022

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