A framework to design a green supply chain for the steel industry with a strategic approach (The case of Guilan province)
محورهای موضوعی : Supply Chain ManagementSirous Balaeia 1 , Nabiollah Mohammadi 2 , Homa Doroudi 3
1 - Department of Industrial management, Zanjan Branch, Islamic Azad University, Zanjan, Iran
2 - Department of Industrial Management, Zanjan branch, Islamic Azad University, Zanjan, Iran.
3 - Department of Industrial Management, Zanjan branch, Islamic Azad University, Zanjan, Iran.
کلید واژه: Supply Chain, Fuzzy DEMATEL, Fuzzy Network Analysis Process, Green Supply Chain, fuzzy multi-attribute decision-making,
چکیده مقاله :
The present research aims to identify the factors affecting the green supply chain in the steel industry with a combined approach. The research is an applied study in type, an exploratory study in goal, a quantitative and qualitative study in data type, and a field study in procedure, in which questionnaire and interview were used as the research instrument. The statistical population was composed of the experts of the steel industry, out of whom 25 experts were selected as the statistical sample by the purposive technique. Data were analyzed by the fuzzy DEMATEL and fuzzy network process analysis in the SPSS21 and MS-Excel software packages. Then, the fuzzy Delphi technique was used, resulting in the identification of five criteria and 25 subcriteria. Then, the fuzzy DEMATEL was employed to determine the influence and dependence of the factors according to which among the main factors, the environment factor was the most influential with an influence value of 0.792 and the financial factor was the most dependent factor with a net dependence value of -0.996. Also, the identified factors were ranked by the fuzzy analytical network process. The results show that the financial factor has the highest weight. Also, the other factors are in the order of environmental, quality, environment, and technology in terms of importance.
The present research aims to identify the factors affecting the green supply chain in the steel industry with a combined approach. The research is an applied study in type, an exploratory study in goal, a quantitative and qualitative study in data type, and a field study in procedure, in which questionnaire and interview were used as the research instrument. The statistical population was composed of the experts of the steel industry, out of whom 25 experts were selected as the statistical sample by the purposive technique. Data were analyzed by the fuzzy DEMATEL and fuzzy network process analysis in the SPSS21 and MS-Excel software packages. Then, the fuzzy Delphi technique was used, resulting in the identification of five criteria and 25 subcriteria. Then, the fuzzy DEMATEL was employed to determine the influence and dependence of the factors according to which among the main factors, the environment factor was the most influential with an influence value of 0.792 and the financial factor was the most dependent factor with a net dependence value of -0.996. Also, the identified factors were ranked by the fuzzy analytical network process. The results show that the financial factor has the highest weight. Also, the other factors are in the order of environmental, quality, environment, and technology in terms of importance.
Agi, M.A.N., Yan, X., (2020). Greening products in a supply chain under market segmentation and different channel power structures. Int. J. Prod. Econ. 223.
Ahmadi, S., Akbari, S., Afshari, M., & Shekari, H. (2013).A model for evaluating the success of green supply chain management with green supplier approach (Case STudy: Iran Alloy Steel). Iranian Journal of Trade Studies, 17(66), 95-127. (In Persian with an English Abstract)
Ansari, I., & Sadeghi Moghaddam, M. (2021). Identification and determination of the relations and categorization of green supply chain management incentives with a structural-interpretive modeling approach. Industrial Management Studies, 12(35), 123-150. (In Persian)
Azad, S., & Modiri, M. (2017). The application of structural interpretive modeling to empower green supply chain management: The case of Iran Khodro. Proceeding of 8th International Conference of Management and Accounting and 5th Conference of Entrepreneurship and Open Innovations (pp. 1-18). Tehran: Tehran University Press. (In Persian)
Babaei Meybodi, H., & Delshad, Z. (2018). Dynamic modeling of systems to evaluate the factors affecting green supply chain management. Biannual Journal of Value Chain Management, 2(6), 51-62. (In Persian)
Bhatia, M.S., Gangwani, K.K., (2020). Green supply chain management: scientometric review and analysis of empirical research. J. Clean. Prod. https://doi.org/10.1016/j.jclepro.2020.124722
Bolanos, R., Fontela, E., Nenclares, A., Paster, P., (2005), Using interpretive structural modeling in strategic decision making groups. Management Decision, vol. 43, vol6, pp.877−895.
Centobelli, P., Cerchione, R., Esposito, E., (2020). Pursuing supply chain sustainable development goals through the adoption of green practices and enabling technologies: a cross-country analysis of LSPs. Technol. Forecast. Soc. Change 153. https://doi.org/10.1016/j.techfore.2020.119920.
Govindan, K. Kaliyan, M. Kannan, D. Haq, A. (2014).Barriers analysis for green supply chain management implementation in Indian industries using analytic hierarchy process.Int.J.Prod.Econ.147, 555–568 (B).
Guido, J.L. Micheli, Enrico, Cagno, Gianluca, Mustillo, Andrea, Trianni, (2020). Green supply chain management drivers, practices and performance: a comprehensive study on the moderators. J. Clean. Prod. 259. https://doi.org/10.1016/j. jclepro.2020.121024.
Kamble, S.S., Gunasekaran, A., Gawankar, S.A., (2020). Achieving sustainable performance in a data-driven agriculture supply chain: a review for research and applications. Int. J. Prod. Econ. 219, 179–194. https://doi.org/10.1016/j. ijpe.2019.05.022.
Kannan, D. Govindan, D. Rajendran, S. (2014), Fuzzy Axiomatic Design approach based green.
Karimi Shirazi, H., Modiri, M., Pourhabibi, Z., Rafiei Gilevaee, A (2017), Improving the Quality of Clinical Dental Services Using the Importance-Performance Analysis (IPA) approach and Interpretive-Structural Modeling (ISM), Journal of Dentomaxillofacial Radiology, Pathology and Surgery, Vol 6, No 1, PP: 14-26.
Khan, S.A.R., Yu, Z., Golpira, H., Sharif, A., Mardani, A., (2021). A state-of-the-art review and meta-analysis on sustainable supply chain management: future research directions. J. Clean. Prod. 278 https://doi.org/10.1016/j.jclepro.2020.123357, 123357.
Kumar Rakesh Malviya Ravi Kant. (2015)."Modeling the enablers of green supply chain management: an integrated ISM -fuzzy MICMAC approach benchmarking: An International Journal, Vol. 24 Iss 2 pp. -Permanent link to this document: 10.1108/BIJ-08-2015-74-82.
Kumar, V., Jabarzadeh, Y., Jeihouni, P., Garza-Reyes, J.A., (2020). Learning orientation and innovation performance: the mediating role of operations strategy and supply chain integration. Supply Chain Manag.: An Int. J. 25 (4), 457–474. https://doi.org/10.1108/SCM-05-2019-0209.
Lari, K-h., Cheng, T.C.E. and Tang, A.K.Y. (2015), “Green retailing: factors for success”, California Management Review, Vol. 52No. 2, pp. 6-31.
Mahesh Chand, Neha Bhatia, Rajesh Kumar Singh, (2018) "ANP-MOORA-based approach for the analysis of selected issues of green supply chain management", Benchmarking: An International Journal, Vol. 25 Issue: 2, pp.642-659, https://doi.org/10.1108/BIJ-11-2016-0177.
Micheli, G.J.L., Cagno, E., Mustillo, G., Trianni, A., (2020). Green supply chain management drivers, practices and performance: a comprehensive study on the moderators. J. Clean. Prod. 259 https://doi.org/10.1016/j.jclepro.2020.121024, 121024.
Omidvar, R., Sardari, A., & Yazdani, N. (2015). Ranking barriers to green supply chain management using DIMATEL. New Marketing Research Journal, 5(2), 1-14. (In Persian with an English Abstract)
Saaty, T. L. (2002), "Fundamentals of the Analytic Network Process", Proceedings of ISAHP 1999, Kobe, Japan.126-142.
Srivastava, S., Singh, R.K., (2020). Exploring integrated supply chain performance in healthcare: a service provider perspective. Benchmarking. https://doi.org/10.1108/BIJ-03-2020-0125 a-head-of-print.
Tseng, M. L. Tan, K. H. Lim, M. Lin, R. J. & Geng, Y. (2014). Benchmarking eco-efficiency in green supply chain practices in uncertainty. Production Planning & Control, 25(13-14), 61-79.
Venkatesa Narayanan, P.T., Thirunavukkarasu, R., SundarM, V., (2021). Indispensable link between green supply chain practices, performance and learning: an ISM approach. J. Clean. Prod. 279 https://doi.org/10.1016/j.jclepro.2020.123387, 123387.
Wang, Z. Subramanian, N. Gunasekaran, A. Abdulrahman, M.D. and Liu, C. (2015), “Composite sustainable manufacturing practice and performance framework: Chinese auto parts suppliers’ perspective”, International Journal of Production Economics, Vol. 170 Part A, pp. 219-233.
Zaeri, M., & Ramazani, E. (2011). Assessment and selection of suppliers in green supply chain with a multi-criteria decision-making approach. Proceedings of 2nd Internation Conference and 4th National Conference of Logistics and Supply Chain (pp. 1-17). Tehran: Industry Conference Institution. (In Persian)