Assessing Relationships in Industry and Optimizing Related Decisions with the Help of Fuzzy Properties
Subject Areas : Fuzzy Optimization and Modeling Journal
1 -
Keywords: Optimization, Fuzzy theory, Pareto analysis, Sustainability barriers, Industrial engineering,
Abstract :
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.
References:
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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.
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