Assessing Relationships in Industry and Optimizing Related Decisions with the Help of Fuzzy Properties
محورهای موضوعی : Fuzzy Optimization and Modeling Journal
1 - Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran
کلید واژه: Optimization, Fuzzy theory, Pareto analysis, Sustainability barriers, Industrial engineering,
چکیده مقاله :
The textile industry supply chains (SC) face numerous risks and disruptions due to the changing dynamics of high demand and limited resources. In this context, the textile sector in these economies must prioritize Sustainable Supply Chain Management ‘(SSCM) to achieve cost reduction, enhance productivity, and improve profitability to sustain their business. Although research has examined several SSCM viewpoints, the barriers that prevent emerging economies from adopting SSCM in the textile sector to meet the Sustainable Development Goals (SDGs) are not sufficiently highlighted in the empirical literature that has already been published. This study analyzes different barriers and investigates how they are interconnected. From the literature research, 17 main barriers were first identified in the process. The barriers were then prioritized in order of significance using a combination of fuzzy theory, Pareto analysis, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) framework. Finally, the cause-and-effect relationships among these barriers were established. A lack of commitment from the supplier’s top management, insufficient financial incentives, and the absence of supportive government standards and regulations were identified as the three topmost significant barriers to SSCM’ adoption. For the textile sector, governments, and policymakers in emerging economies, the study’s results are helpful since they will assist them create mitigation strategies to get rid of these barriers and achieve long-term sustainability.
The textile industry supply chains (SC) face numerous risks and disruptions due to the changing dynamics of high demand and limited resources. In this context, the textile sector in these economies must prioritize Sustainable Supply Chain Management ‘(SSCM) to achieve cost reduction, enhance productivity, and improve profitability to sustain their business. Although research has examined several SSCM viewpoints, the barriers that prevent emerging economies from adopting SSCM in the textile sector to meet the Sustainable Development Goals (SDGs) are not sufficiently highlighted in the empirical literature that has already been published. This study analyzes different barriers and investigates how they are interconnected. From the literature research, 17 main barriers were first identified in the process. The barriers were then prioritized in order of significance using a combination of fuzzy theory, Pareto analysis, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) framework. Finally, the cause-and-effect relationships among these barriers were established. A lack of commitment from the supplier’s top management, insufficient financial incentives, and the absence of supportive government standards and regulations were identified as the three topmost significant barriers to SSCM’ adoption. For the textile sector, governments, and policymakers in emerging economies, the study’s results are helpful since they will assist them create mitigation strategies to get rid of these barriers and achieve long-term sustainability.
1. Abay, K. A., Breisinger, C., Glauber, J., Kurdi, S., Laborde, D., & Siddig, K. (2023). The Russia-Ukraine war: Implications for global and regional food security and potential policy responses. Global Food Security, 36, 100675.
2. Abdelazeem, A. S., & Ibrahim, A. H. (2022). Evaluation of project cost and schedule performance using fuzzy theory-based polynomial function. International Journal of Construction Management, 22(13), 2564-2576.
3. Agrawal, P., & Narain, R. (2023). Analysis of enablers for the digitalization of supply chain using an interpretive structural modelling approach. International Journal of Productivity and Performance Management, 72(2), 410-439.
4. Agrawal, T. K., Kumar, V., Pal, R., Wang, L., & Chen, Y. (2021). Blockchain-based framework for supply chain traceability: A case example of textile and clothing industry. Computers & industrial engineering, 154, 107130.
5. Ali, I., Arslan, A., Chowdhury, M., Khan, Z., & Tarba, S. Y. (2022). Reimagining global food value chains through effective resilience to COVID-19 shocks and similar future events: A dynamic capability perspective. Journal of business research, 141, 1-12.
6. Allen, S. D., Zhu, Q., & Sarkis, J. (2021). Expanding conceptual boundaries of the sustainable supply chain management and circular economy nexus. Cleaner Logistics and Supply Chain, 2, 100011.
7. Almutairi, K., Hosseini Dehshiri, S. J., Hosseini Dehshiri, S. S., Hoa, A. X., Arockia Dhanraj, J., Mostafaeipour, A., . . . Techato, K. (2023). Blockchain technology application challenges in renewable energy supply chain management. Environmental Science and Pollution Research, 30(28), 72041-72058.
8. Amicarelli, V., Lagioia, G., Sampietro, S., & Bux, C. (2022). Has the COVID-19 pandemic changed food waste perception and behavior? Evidence from Italian consumers. Socio-Economic Planning Sciences, 82, 101095.
9. Ayati, S. M., Shekarian, E., Majava, J., & Wæhrens, B. V. (2022). Toward a circular supply chain: Understanding barriers from the perspective of recovery approaches. Journal of Cleaner Production, 359, 131775.
10. Banik, A. (2019). Critical success factors for implementing green supply chain management in electronics industry: A case study.
11. Carmagnac, L. (2021). Expanding the boundaries of SSCM: the role of non-traditional actors. Paper presented at the Supply Chain Forum: An International Journal.
12. Chandra, D., Vipin, B., & Kumar, D. (2023). A fuzzy multi-criteria framework to identify barriers and enablers of the next-generation vaccine supply chain. International Journal of Productivity and Performance Management, 72(3), 827-847.
13. Chien, F., Kamran, H. W., Nawaz, M. A., Thach, N. N., Long, P. D., & Baloch, Z. A. (2021). Assessing the prioritization of barriers toward green innovation: small and medium enterprises Nexus. Environment, development and sustainability, 1-31.
14. Chopra, R., Magazzino, C., Shah, M. I., Sharma, G. D., Rao, A., & Shahzad, U. (2022). The role of renewable energy and natural resources for sustainable agriculture in ASEAN countries: do carbon emissions and deforestation affect agriculture productivity? Resources Policy, 76, 102578.
15. Cui, L., Wu, H., & Dai, J. (2023). Modelling flexible decisions about sustainable supplier selection in multitier sustainable supply chain management. International Journal of Production Research, 61(14), 4603-4624.
16. Devi, S. A., Felix, A., Narayanamoorthy, S., Ahmadian, A., Balaenu, D., & Kang, D. (2022). An intuitionistic fuzzy decision support system for COVID-19 lockdown relaxation protocols in India. Computers and Electrical Engineering, 102, 108166.
17. Dixit, A., Routroy, S., & Dubey, S. K. (2022). Analyzing the operational barriers of government-supported healthcare supply chain. International Journal of Productivity and Performance Management, 71(8), 3766-3791.
18. Dong, J., Ma, R., Cai, P., Liu, P., Yue, H., Zhang, X., . . . Song, X. (2021). Effect of sample number and location on accuracy of land use regression model in NO2 prediction. Atmospheric Environment, 246, 118057.
19. El Korchi, A. (2022). Survivability, resilience and sustainability of supply chains: The COVID-19 pandemic. Journal of Cleaner Production, 377, 134363.
20. Faramarzi-Oghani, S., Dolati Neghabadi, P., Talbi, E.-G., & Tavakkoli-Moghaddam, R. (2023). Meta-heuristics for sustainable supply chain management: A review. International Journal of Production Research, 61(6), 1979-2009.
21. Fernando, Y., Shaharudin, M. S., & Abideen, A. Z. (2022). Circular economy-based reverse logistics: dynamic interplay between sustainable resource commitment and financial performance. European Journal of Management and Business Economics, 32(1), 91-112.
22. Gani, A., Asjad, M., Talib, F., Khan, Z. A., & Siddiquee, A. N. (2021). Identification, ranking and prioritisation of vital environmental sustainability indicators in manufacturing sector using pareto analysis cum best-worst method. International Journal of Sustainable Engineering, 14(3), 226-244.
23. Gao, S., Lim, M. K., Qiao, R., Shen, C., Li, C., & Xia, L. (2022). Identifying critical failure factors of green supply chain management in China’s SMEs with a hierarchical cause–effect model. Environment, development and sustainability, 1-26.
24. Ghosh, S. K., Zoha, N., & Sarwar, F. (2019). A generic MCDM model for supplier selection for multiple decision makers using fuzzy TOPSIS. Paper presented at the Proceedings of the 5th International Conference on Engineering Research, Innovation and Education (ICERIE) Sylhet, Bangladesh.
25. Grover, A. K., & Dresner, M. (2022). A theoretical model on how firms can leverage political resources to align with supply chain strategy for competitive advantage. Journal of Supply Chain Management, 58(2), 48-65.
26. Hina, M., Chauhan, C., Kaur, P., Kraus, S., & Dhir, A. (2022). Drivers and barriers of circular economy business models: Where we are now, and where we are heading. Journal of Cleaner Production, 333, 130049.
27. Islam, M. S., Rubel, M. R. B., Rimi, N. N., Amin, M. B., & Quadir, P. (2024). Attaining sustainable excellence: investigating the impact of sustainable SCM and circular economy on green garment industry in Bangladesh. Sustainable Futures, 8, 100234.
28. Jabber, M. A., Islam, M. T., Hossain, T., & Sultana, R. (2024). Unveiling the power of enablers in enacting sustainable supply chain management practices. Cleaner Logistics and Supply Chain, 13, 100190.
29. Jum’a, L., Ikram, M., Alkalha, Z., & Alaraj, M. (2022). Factors affecting managers’ intention to adopt green supply chain management practices: evidence from manufacturing firms in Jordan. Environmental Science and Pollution Research, 29(4), 5605-5621.
30. Karanikas, N., & Hasan, S. M. T. (2022). Occupational Health & Safety and other worker wellbeing areas: Results from labour inspections in the Bangladesh textile industry. Safety Science, 146, 105533.
31. Karmaker, C. L., & Ahmed, T. (2020). Modeling performance indicators of resilient pharmaceutical supply chain. Modern Supply Chain Research and Applications, 2(3), 179-205.
32. Karmaker, C. L., Ahmed, T., Ahmed, S., Ali, S. M., Moktadir, M. A., & Kabir, G. (2021). Improving supply chain sustainability in the context of COVID-19 pandemic in an emerging economy: Exploring drivers using an integrated model. Sustainable production and consumption, 26, 411-427.
33. Kazancoglu, I., Kazancoglu, Y., Kahraman, A., Yarimoglu, E., & Soni, G. (2022). Investigating barriers to circular supply chain in the textile industry from Stakeholders’ perspective. International Journal of Logistics Research and Applications, 25(4-5), 521-548.
34. Kazancoglu, I., Kazancoglu, Y., Yarimoglu, E., & Kahraman, A. (2020). A conceptual framework for barriers of circular supply chains for sustainability in the textile industry. Sustainable development, 28(5), 1477-1492.
35. Khan, S. A., Mubarik, M. S., Kusi‐Sarpong, S., Gupta, H., Zaman, S. I., & Mubarik, M. (2022). Blockchain technologies as enablers of supply chain mapping for sustainable supply chains. Business strategy and the environment, 31(8), 3742-3756.
36. 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. Journal of Cleaner Production, 278, 123357.
37. Khokhar, M., Zia, S., Islam, T., Sharma, A., Iqbal, W., & Irshad, M. (2022). Going green supply chain management during covid-19, assessing the best supplier selection criteria: a triple bottom line (tbl) approach. Problemy Ekorozwoju, 17(1).
38. Li, J., Fang, H., & Song, W. (2019). Sustainable supplier selection based on SSCM practices: A rough cloud TOPSIS approach. Journal of Cleaner Production, 222, 606-621.
39. Liu, Z., Wan, M.-D., Zheng, X.-X., & Koh, S. L. (2022). Fairness concerns and extended producer responsibility transmission in a circular supply chain. Industrial Marketing Management, 102, 216-228.
40. Manoharan, S., Pulimi, V. S. K., Kabir, G., & Ali, S. M. (2022). Contextual relationships among drivers and barriers to circular economy: An integrated ISM and DEMATEL approach. Sustainable Operations and Computers, 3, 43-53.
41. Mondal, A., & Roy, S. K. (2022). Application of Choquet integral in interval type‐2 Pythagorean fuzzy sustainable supply chain management under risk. International Journal of Intelligent Systems, 37(1), 217-263.
42. Niu, X., Sun, Z., & Kong, X. (2022). A new type of dyad fuzzy β-covering rough set models base on fuzzy information system and its practical application. International Journal of Approximate Reasoning, 142, 13-30.
43. Ogunsanya, O. A., Aigbavboa, C. O., Thwala, D. W., & Edwards, D. J. (2022). Barriers to sustainable procurement in the Nigerian construction industry: an exploratory factor analysis. International Journal of Construction Management, 22(5), 861-872.
44. Pahl, S., Brandi, C., Schwab, J., & Stender, F. (2022). Cling together, swing together: The contagious effects of COVID‐19 on developing countries through global value chains. The World Economy, 45(2), 539-560.
45. Paul, A., Shukla, N., Paul, S. K., & Trianni, A. (2021). Sustainable supply chain management and multi-criteria decision-making methods: A systematic review. Sustainability, 13(13), 7104.
46. Pavan, R. O., Ferreira, M. A., Stefanelli, N. O., & Leal, G. C. L. (2023). Maturity models in SSCM: A systematic review aimed at consolidating models and outlining possibilities for future research. Benchmarking: An International Journal, 30(10), 4076-4099.
47. Pourmehdi, M., Paydar, M. M., Ghadimi, P., & Azadnia, A. H. (2022). Analysis and evaluation of challenges in the integration of Industry 4.0 and sustainable steel reverse logistics network. Computers & industrial engineering, 163, 107808.
48. Reich, J., Kinra, A., Kotzab, H., & Brusset, X. (2021). Strategic global supply chain network design–how decision analysis combining MILP and AHP on a Pareto front can improve decision-making. International Journal of Production Research, 59(5), 1557-1572.
49. Roy, T., Garza-Reyes, J. A., Kumar, V., Kumar, A., & Agrawal, R. (2022). Redesigning traditional linear supply chains into circular supply chains–A study into its challenges. Sustainable production and consumption, 31, 113-126.
50. Sánchez-Flores, R. B., Cruz-Sotelo, S. E., Ojeda-Benitez, S., & Ramírez-Barreto, M. E. (2020). Sustainable supply chain management—A literature review on emerging economies. Sustainability, 12(17), 6972.
51. Sharma, S. K., Routroy, S., Singh, R. K., & Nag, U. (2024). Analysis of supply chain vulnerability factors in manufacturing enterprises: a fuzzy DEMATEL approach. International Journal of Logistics Research and Applications, 27(5), 814-841.
52. Singh, S., Dasgupta, M. S., & Routroy, S. (2022). Analysis of critical success factors to design e-waste collection policy in India: A fuzzy DEMATEL approach. Environmental Science and Pollution Research, 29(7), 10585-10604.
53. Sirisawat, P., Hasachoo, N., & Rodbundith, T. S. (2024). Sustainable supply chain management challenges analysis in local plastic recycling business. Cleaner Logistics and Supply Chain, 13, 100188.
54. Tabbussum, R., & Dar, A. Q. (2021). Performance evaluation of artificial intelligence paradigms—artificial neural networks, fuzzy logic, and adaptive neuro-fuzzy inference system for flood prediction. Environmental Science and Pollution Research, 28(20), 25265-25282.
55. Tsai, F. M., Bui, T.-D., Tseng, M.-L., Ali, M. H., Lim, M. K., & Chiu, A. S. (2021). Sustainable supply chain management trends in world regions: A data-driven analysis. Resources, Conservation and Recycling, 167, 105421.
56. Tseng, M.-L., Ha, H. M., Lim, M. K., Wu, K.-J., & Iranmanesh, M. (2022). Sustainable supply chain management in stakeholders: supporting from sustainable supply and process management in the healthcare industry in Vietnam. International Journal of Logistics Research and Applications, 25(4-5), 364-383.
57. Ullah, F., Sepasgozar, S. M., Thaheem, M. J., Wang, C. C., & Imran, M. (2021). It’s all about perceptions: A DEMATEL approach to exploring user perceptions of real estate online platforms. Ain Shams Engineering Journal, 12(4), 4297-4317.
58. Vishwakarma, A., Dangayach, G., Meena, M., & Gupta, S. (2022). Analysing barriers of sustainable supply chain in apparel & textile sector: A hybrid ISM-MICMAC and DEMATEL approach. Cleaner Logistics and Supply Chain, 5, 100073.
59. Wang, Z., Xiao, F., & Cao, Z. (2022). Uncertainty measurements for Pythagorean fuzzy set and their applications in multiple-criteria decision making. Soft Computing, 26(19), 9937-9952.
60. Warasthe, R., Brandenburg, M., & Seuring, S. (2022). Sustainability, risk and performance in textile and apparel supply chains. Cleaner Logistics and Supply Chain, 5, 100069.
61. Wuni, I. Y. (2022). Mapping the barriers to circular economy adoption in the construction industry: A systematic review, Pareto analysis, and mitigation strategy map. Building and Environment, 223, 109453.
62. Yasmeen, R., Shah, W. U. H., Ivascu, L., Tao, R., & Sarfraz, M. (2022). Energy crisis, firm productivity, political crisis, and sustainable growth of the textile industry: An emerging economy perspective. Sustainability, 14(22), 15112.
63. Yousaf, A., Mishra, A., & Amin, I. (2023). Autonomous/controlled travel motivations and their effect on travel intentions of Indian Millennials: A mixed method approach. Tourism Recreation Research, 48(2), 286-304.
64. Yu, Z., Waqas, M., Tabish, M., Tanveer, M., Haq, I. U., & Khan, S. A. R. (2022). Sustainable supply chain management and green technologies: a bibliometric review of literature. Environmental Science and Pollution Research, 29(39), 58454-58470.
65. Yüksel, S., & Dinçer, H. (2022). Identifying the strategic priorities of nuclear energy investments using hesitant 2-tuple interval-valued Pythagorean fuzzy DEMATEL. Progress in Nuclear Energy, 145, 104103.
66. Zhao, X., Li, X., Liu, T., & Shen, G. (2024). How photovoltaic industry policies foster the development of silicon solar cell manufacturing technology: Based on Self-attention mechanism. Energy, 308, 132866.
67. Zheng, Y., Zhao, H., & He, C. (2022). Robust control design with optimization for uncertain mechanical systems: Fuzzy set theory and cooperative game theory. International Journal of Control, Automation and Systems, 20(4), 1377-1392.
68. Zhu, C., Du, J., Shahzad, F., & Wattoo, M. U. (2022). Environment sustainability is a corporate social responsibility: measuring the nexus between sustainable supply chain management, big data analytics capabilities, and organizational performance. Sustainability, 14(6), 3379.
