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  • طراحی مدل مفهومی تولید سبز با رویکرد مدل سازی ساختاری تفسیری

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کد مقاله : JEST-2106-5411 (R4) بازدید : 69 صفحه: 1 - 16

10.30495/jest.2022.61223.5411

نوع مقاله: پژوهشی

طراحی مدل مفهومی تولید سبز با رویکرد مدل سازی ساختاری تفسیری

محورهای موضوعی : طراحی محیط زیست

آفرین رضایی 1 (دانشجوی دکتری، گروه مدیریت صنعتی، واحد یزد، دانشگاه آزاد اسلامی، یزد، ایران.)
حسن دهقان دهنوی 2 (دانشیار، گروه مدیریت صنعتی، واحد یزد، دانشگاه آزاد اسلامی، یزد، ایران.)
حمید بابائی میبدی 3 (استادیار، گروه مدیریت، دانشگاه میبد، میبد، ایران. *(مسوول مکاتبات))
علیرضا انوری 4 (استادیار، گروه مدیریت و مهندسی صنایع، واحد گچساران، دانشگاه آزاد اسلامی، گچساران، ایران.)

تاریخ دریافت : 1400/03/17 تاریخ پذیرش : 1400/05/09 تاریخ انتشار : 1400/12/01

کلید واژه: شرکت‌های دانش بنیان, تولید سبز, مدل سازی ساختاری تفسیری,

چکیده مقاله :

زمینه و هدف: با توجه به این امر که در دنیای کنونی عواملی همچون افزایش جمعیت، تلاش روزافزون جهت دستیابی به رشد اقتصادی و تلاش سیستم‌های تولیدی برای افزایش تولید و دستیابی به مزیت رقابتی منجر به از بین رفتن منابع طبیعی، گرمایش زمین، تغییرات آب و هوایی، ایجاد بلایای طبیعی و درنهایت تخریب محیط‌زیست شده است و تولید سبز به عنوان عاملی تأثیرگذار بر کاهش آلودگی‌های زیست‌محیطی و مخاطرات انسانی و همچنین افزایش مزیت رقابتی و کسب سود برای سازمان ها مطرح شده است، این پژوهش با هدف طراحی مدل مفهومی تولید سبز با رویکرد مدل سازی ساختاری تفسیری صورت گرفته است. روش بررسی: در این پژوهش که از نظر شیوه‌ی جمع‌آوری داده ها، ترکیبی و استقرائی-قیاسی است و در سال 1400 صورت گرفته است، ۱۲ نفر از متخصصان مدیریت صنعتی در سطح دانشگاهی به عنوان اعضای پانل در بخش کیفی مشارکت داشتند. در واقع در بخش کیفی که از تحلیل‌های فراترکیب و دلفی استفاده شد، هدف براین بود تا مضامینِ تولید سبز شناسایی گردد و سپس در بخش کمی با مشارکت ۱۶ نفر از مدیران شرکت‌های دانش بنیان در بخش تولید سبز، گزاره‌های شناسایی شده در قالبِ مدلِ تحلیل تفسیری ساختاری براساس اولویت تاثیرگذاری سطح‌بندی شوند. لذا با اتکا به تحلیل فراترکیب ابتدا ۱۲ پژوهش به عنوان مبنای ارزیابی جهت تعیین مضامینِ تولید سبز براساسِ ارزیابی انتقادی بررسی شدند که براساس آن ۸ مضمون انتخاب و به شیوه چک لیستی وارد تحلیل دلفی جهت تعیین حدِ کفایت نظری شدند. طی دو مرحله تحلیل دلفی هر ۸ مضمونِ شناسایی شده ی تولید سبز وارد بخش تحلیل کمی یعنی تحلیل تفسیری ساختاری شدند. یافته‌ها: نتایج نشان داد، تاثیرگذارترین مولفه‌های تولیدِ سبز شرکت‌های دانش بنیان، پنج مولفه ی آب ؛ انرژی ؛ منابع طبیعی ؛ سرمایه و نیروی کار بودند که در سطح سوم مدل ارائه شده قرار گرفته است. بحث و نتیجه‌گیری: نتایج کسب شده نشان می‌دهد، عوامل مصرف انرژی، مصرف آب، نیروی کار، سرمایه و مواد اولیه عواملی مهم هست که هرگونه تغییر در آن‌ها باعث ایجاد تغییر در سایر متغیرها نیز می‌شود و از سوی دیگر تولید ناخالص داخلی دارای نفوذ کم و گازهای گلخانه‌ای و تکنولوژی نفوذپذیرترین متغیر است.

چکیده انگلیسی:

Background and Objective: Given that in today's world, factors such as population growth, increasing efforts to achieve economic growth and production systems to increase production and achieve competitive advantage lead to the loss of natural resources, global warming, climate change, Natural disasters and ultimately environmental degradation and green production has been proposed as an effective factor in reducing environmental pollution and human risks as well as increasing competitive advantage and profitability for organizations. This study aims to design a conceptual model of green production with a modeling approach. An interpretive structure has been developed. Material and Methodology: In this study, which is synthetic and inductive-deductive in terms of data collection method, and was conducted in 1400, and 12 industrial management specialists at the university level participated as panel members in the quality department. In fact, in the qualitative section, which used meta-synthesis and Delphi analysis, the aim was to identify the themes of green production and then in the quantitative section, with the participation of 16 managers of knowledge-based companies in the green production section, the propositions identified in ISM templates should be graded based on influential priority. Therefore, relying on meta-synthesis analysis, the first 12 studies were reviewed as a basis for evaluation to determine the themes of green production based on critical evaluation, based on which eight themes were selected and entered into Delphi analysis in a checklist manner to determine theoretical adequacy. During the two stages of Delphi analysis, all eight identified themes of green production entered the quantitative analysis section, i.e., structural interpretive analysis. Findings: The results showed that the most influential components of green production of knowledge-based companies are the five components of water (C1), energy (C2), natural resources (C3), capital (C5), and labor (C6), which is at the third level of the proposed model. Also, a Mick Mac analysis as a complementary interpretive structural analysis was performed to better understand the research topic. Discussion and Conclusion: The results showed that the factors of energy consumption, water consumption, labor, capital, and raw materials are important factors that any change in them will cause changes in other variables and on the other hand, GDP is with the low impression, and greenhouse gases and technology is the most impression variable.

منابع و مأخذ:


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_||_

  1. Baylan, E. B. (2014). Facility layout: as a tool for clean production and eco efficiency.
    2.
  2. Li, G., Zheng, H., Sethi, S. P., & Guan, X. (2018). Inducing Downstream Information Sharing via Manufacturer Information Acquisition and Retailer Subsidy. Decision Sciences. https://doi.org/10.1111/ deci.12340.
    3.
  3. Paul, I. D., Bhole, G. P., & Chaudhari, J. R. (2014). A review on green manufacturing: it's important, methodology and its application. Procedia Materials Science, 6, 1644-1649.
    4.
  4. Zameer, H., Wang, Y., & Yasmeen, H. (2020). Reinforcing green competitive advantage through green production, creativity and green brand image: implications for cleaner production in China. Journal of Cleaner Production, 247, 119119.
    5.
  5. Li, G., Lim, M. K., & Wang, Z. (2019). Stakeholders, green manufacturing, and practice performance: empirical evidence from Chinese fashion businesses. Annals of Operations Research, 1-22.
    6.
  6. Mendoza-Fong, J. R., García-Alcaraz, J. L., Díaz-Reza, J. R., Jiménez-Macías, E., & Blanco-Fernández, J. 2019. The role of green attributes in production processes as well as their impact on operational, Commercial, and Economic Benefits.  Sustainability, 11(5), 1294.‏ https://doi.org/10.3390/su11051294.
    7.
  7. Przychodzen, J., & Przychodzen, W. (2015). Relationships between eco-innovation and financial performance–evidence from publicly traded companies in Poland and Hungary. Journal of Cleaner Production, 90, 253-263.
    8.
  8. Charmondusit, K., Gheewala, S. H., & Mungcharoen, T. 2016. Green and sustainable innovation for cleaner production in the Asia-Pacific region. Journal of Cleaner Production, 134, 443-446.‏ https://doi.org/10.1016/j.jclepro.2016.06.160.
    9.
  9. Woo, C., Kim, M. G., Chung, Y., & Rho, J. J. (2016). Suppliers' communication capability and external green integration for green and financial performance in Korean construction industry. Journal of Cleaner Production, 112, 483-493.‏
    10.
  10. Gayduk, E., Matyugina, E., Pogharnitskaya, O., & Bolsunovskaya, L. (2020). National security: green production to ensure quality of labor force. In E3S Web of Conferences (Vol. 164, p. 11034). EDP Sciences.
    11.
  11. Pang, R., & Zhang, X. (2019). Achieving environmental sustainability in manufacture: A 28-year bibliometric cartography of green manufacturing research. Journal of Cleaner Production.
    12.
  12. Dornfeld, D., Cea, Y.(2013). Green Manufacturing: Fundamentals and Applications. Springer Science, New York.
    13.
  13. Hou, C., Chen, H., & Long, R. (2022). Coupling and coordination of China's economy, ecological environment and health from a green production perspective. International Journal of Environmental Science and Technology, 19(5), 4087-4106.
    14.
  14. Glavič, P., & Lukman, R. (2007). Review of sustainability terms and their definitions, Journal of Cleaner Production, 15(18), 1875-1885.
    15.
  15. Baah, C., Opoku-Agyeman, D., Acquah, I. S. K., Agyabeng-Mensah, Y., Afum, E., Faibil, D., & Abdoulaye, F. A. M. (2021). Examining the correlations between stakeholder pressures, green production practices, firm reputation, environmental and financial performance: evidence from manufacturing SMEs. Sustainable Production and Consumption, 27, 100-114.
    16.
  16. Cervera-Ferri, J. L., & Luz Ureña, M. (2017). Green production indicators, a guide for moving towards sustainable development.
    17.
  17. Singh, M. D., & Kant, R. (2011). Knowledge management barriers: An interpretive structural modeling approach. International Journal of Management Science and Engineering Management, 3(2), 10.
    18.
  18. Malone, D. W. (2014). An introduction to the application of interpretive structural modeling. Proceedings of the IEEE, 63(3), 397-404.
    19.
  19. Ramesh, A., Banwet, D.K., Shankar, R. (2010). “Modeling the Barriers of Supply Chain Collaboration”, Journal of Modelling in Management, 5(2): 176–193.
    20.
  20. Attri, r., Dev, n., & Sharma, v. (2013). Interpretive Structural Modelling (ISM) approach: An Overview. Research Journal of Management Sciences, 2(2), 6.
    21.
  21. Chen, Y, Sh., Lin, Sh, H., Lin, Ch, Y., Huang, Sh, T., Chang, Ch, W., Huang, Ch, W. (2019). Improving green product development performance from green vision and organizational culture perspectives, Corporate Social Responsibility and Environmental Management, 27(1): 222-231. https://doi.org/10.1002/csr.1794
    22.
  22. Dabbagh, R., Aghapour Esbaq, S. (2020). Presenting an appropriate decision-making model for selecting an effective green production strategy in Bonab Sanat Steel Complex, Journal of Industrial Engineering Research in Production Systems, 8 (16): 57-75.
    23.
  23. Duber-Smith, D. C. (2005). The green imperative. SPC. Soap, perfumery and cosmetics, 78(8), 24-26.
    24.
  24. Goyal, S., Routroy, S. and Singhal, A. (2019). Analyzing environment sustainability enablers using fuzzy DEMATEL for an Indian steel manufacturing company, Journal of Engineering, Design and Technology, 17(2): 300-329. https://doi.org/10.1108/JEDT-02-2018-0033
    25.
  25. Melnyk, S. A., & Smith, R. T. (1996). Green Manufacturing, Society for Manufacturing Engineering. Dearborn, MI.
    26.
  26. Ning, S., & Li, X. (2019, August). A Scientometric Review of Emerging Trends in Green Manufacturing. In International Conference on Management Science and Engineering Management (pp. 234-247). Springer, Cham.
    27.
  27. O'Neill, S., Ghadimi, P., Wang, C. and Sutherland, J.W. (2021). Analysis of enablers on the successful implementation of green manufacturing for Irish SMEs, Journal of Manufacturing Technology Management, 32(1): 85-109. https://doi.org/10.1108/JMTM-10-2019-0382
    28.
  28. Pampanelli, A.B.; Found, P.; Bernardes, A.M. A lean & green model for a production cell. J. Clean. Prod.2014, 85, 19–30. [CrossRef].
    29.
  29. Raharjo, K. (2019). The role of green management in creating sustainability performance on the small and medium enterprises, Management of Environmental Quality, 30(3): 557-577. https://doi.org/10.1108/MEQ-03-2018-0053
    30.
  30. Rahimi Al-Waqareh, M., Davoodi, M R. (2020). Designing a Green Workshop Production Model, by Balancing Completion Time and Energy Consumption (Case Study: Padideh Machinery Company of the West), Industrial Management Quarterly, 15 (53): 26-52.
    31.
  31. Saufi, N. A. A., Daud, S., & Hassan, H. (2016). Green growth and corporate sustainability performance. Procedia Economics and Finance, 35(1), 374-378.‏
    32.
  32. Schleich, J. (2007). The economics of energy efficiency: barriers to profitable investments. EIB papers, 12(2), 82-109.‏
    33.
  33. Singh, C., Singh, D. and Khamba, J.S. (2021). In quest of green practices in manufacturing industries through literature review, World Journal of Entrepreneurship, Management and Sustainable Development, 17(1): 30-50. https://doi.org/10.1108/WJEMSD-02-2019-0014.
    34.
  34. Song, W., Wang, G, Zh., Ma, X. (2019). Environmental innovation practices and green product innovation performance: A perspective from organizational climate, Sustainable Development, 28(1): 224-234. https://doi.org/10.1002/sd.1990.
    35.
  35. Sun, L. Y., Miao, C. L., & Yang, L. 2017. Ecological-economic efficiency evaluation of green technology innovation in strategic emerging industries based on entropy weighted TOPSIS method. Ecological indicators, 73, 554-558.‏ https://doi.org/10.1016/j.ecolind.2016.10.018.
    36.
  36. Thanki, S. and Thakkar, J.J. (2020). An investigation on lean–green performance of Indian manufacturing SMEs, International Journal of Productivity and Performance Management, 69(3): 489-517. https://doi.org/10.1108/IJPPM-11-2018-0424
    37.
  37. Tizhosh, M., Philly A. (2020). Identifying and ranking green production ideals in the automotive  industry with a hierarchical analysis approach (AHP), Quarterly Journal of New Research Approaches in Management and Accounting, 4 (30): 1-16.
    38.
  38. Zhang, J., Ouyamg, Y., Philbin, S, P., Zhao, X., Ballesteros-Perez, P., Li, H. (2020). Green dynamic capability of construction enterprises: Role of the business model and green production, Corporate Social Responsibility and Environmental Management, 27(6): 2920-2940. https://doi.org/10.1002/csr.2012
    39.
  39. Zhu, Q., Li, X. and Zhao, S. (2018). Cost-sharing models for green product production and marketing in a food supply chain, Industrial Management & Data Systems, 118(4): 654-682. https://doi.org/10.1108/IMDS-05-2017-0181.
    40.

 




 

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