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Green Manufacturing: An Assessment of Enablers’ Framework Using ISM-MICMAC Analysis

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Manufacturing is one of the biggest drivers of a country's economic growth. Nevertheless, due to globalization and flourishing consumer markets, the technological influx in manufacturing evolution poses a significant threat to climate change. To deal with the situation, green manufacturing came forward to play a vital role in lowering the impact of mass production on the global environment. The qualitative research based on expert opinion is used to have viewpoints for the implementation of green manufacturing based on green supply chain manufacturing (GSCMEs) enablers. The study, in this regard, focuses on exploring the key enablers adopted by the manufacturers to embrace green practices by using framework based on Interpretative Structural Modelling and Cross-Impact Multiplication Applied to Classification (MICMAC) analysis. Results indicate that economic constraints and the regulatory framework have high driving power and less dependency power. Researchers provide managers with a new outlook on the future towards building an eco-friendly supply chain and gaining a competitive edge over their competitors.
Słowa kluczowe
Rocznik
Strony
271--290
Opis fizyczny
Bibliogr. 34 poz., tab., rys.
Twórcy
  • Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Bibliografia
  • [1] Akabar, M., & Irohara, T. (2018). Scheduling for sustainable manufacturing: A review. Journal of Cleaner Production, 205, 866–883. https://doi.org/10.1016/j.jclepro.2018.09.100.
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  • [3] Ali, S.S., Kaur, R. & Khan, S. (2022) Evaluating sustainability initiatives in warehouse for measuring sustainability performance: an emerging economy perspective. Ann Oper Res . https://doi.org/10.1007/s10479-021-04454-w.
  • [4] Ali, S. S.; and Kaur. R. (2021) Effectiveness of corporate social responsibility (CSR) in implementation of social sustainability in warehousing of developing countries: A hybrid approach, Journal of Cleaner Production, 324,129154. https://doi.org/10.1016/j.jclepro.2021.129154.
  • [5] Ali, S. S., Paksoy, T., Torgŭl, B., & Kaur, R. (2020a). Reverse logistics optimization of an industrial air conditioner manufacturing company for designing sustainable supply chain: A fuzzy hybrid multi criteria decision-making approach. Wireless Network, 26, 5759–5782. https://doi.org/10.1007/s11276-019-022, 46-6.
  • [6] Ali, S. S., Kaur, R., Ersoz, F., Altaf, B., Basu, A., & Weber, G.-W. (2020b). Measuring carbon performance for sustainable green supply chain practices. Central Journal of European Research, 28(4), 1389–1416. https://doi.org/10.1007/s10100-020-00673-x.
  • [7] Ali, Sadia Samar, Kaur, R., Persis, D. J., Saha, R., Pattusamy, M. & Sreedharan, V. R. (2020c), Developing a hybrid evaluation approach for the low carbon performance on sustainable manufacturing environment, Annals of Operations Research, DOI: 10.1007/s10479-020-03877-1.
  • [8] Ali, S. S., Kaur, R., & Ersöz, F. (2019a). Evaluation of the effectiveness of green practices in manufacturing sector using CHAID analysis. Journal of Remanufacturing, 9, 3–27. https://doi.org/10.1007/s13243-01 8-0053-y.
  • [9] Ali, S. S., Kaur, R., & Marmolejo, J. A. (2019b). Best practices of green supply chain management: A developing countries perspectives. Emerald Global Publications ISBN: 9781787562165, pp. 10, 30, 51.
  • [10] Ali, S. S., Kaur, R., & Jarmillo, L. A. B. (2018). An assessment of green supply chain framework in Indian automobile industry using interpretive structural modelling and its validation using MICMAC analysis. International Journal of Service and Operations Management, 30(3), 318–356. https://doi.org/10.1504/ IJSOM.2018.092607.
  • [11] Allevi, E., Gnudi, A., Konnov, I. V., & Oggioni, G. (2018). Evaluating the effects of environmental regulations on a closed-loop supply chain network: A variational inequality approach. Annals of Operations Research, 261(1), 1–43.
  • [12] Altaf, B. Ali, S. S. and G. W. Weber (2020) Modelling the relationship between organizational performance and green supply chain practices using Canonical correlation analysis, Wireless Networks (S.I Intelligent Resource Management using analytical methods), 26, 5835–5853, http://doi.org/10.1007/s11276-020-02313-3.
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  • [32] Thamsatitdej, P., S. Boon-itt, P. Samaranayake, M. Wannakarn, and T. Laosirihongthong. (2017) Eco-design Practices Towards Sustainable Supply Chain Management: Interpretive Structural Modelling (ISM) Approach. International Journal of Sustainable Engineering 10 (6): 326–338.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c3b25d4e-fcda-4743-9071-5773e0a9b1fe
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