بررسی عوامل مؤثر بر بهره وری سبز در صنایع خودروسازی ایران با رویکرد دی متل خاکستری
محورهای موضوعی :
مدیریت صنعتی
Adel Azar
1
,
Reza Esmaeilpour
2
,
ATENA Mahdavi
3
1 - Humanities, Management, Tarbiat Modarres University
2 - Associate Professor, Department of Management, University of Guilan, Rasht
3 - Rahbord Shomal University
تاریخ دریافت : 1396/12/05
تاریخ پذیرش : 1397/10/10
تاریخ انتشار : 1398/03/08
کلید واژه:
کیفیت,
بهره وری سبز,
محیط زیست,
صنایع خودروسازی,
دی متل خاکستری,
چکیده مقاله :
هدف تمامی تولیدات، ارائه ی محصولاتی است که به نوعی دوستدار محیط زیست باشد. از طرف دیگر در این راستا سازمان ها به دنبال رسیدن به محصولات دوستدار محیط زیست در کنار بهره وری هستند. با توجه به این امر می توان گفت که هدف اصلی بهره وری سبز افزایش حفاظت محیط زیست است به نحوی که موجب افزایش سودآوری تجاری گردد، به طرف موضوع اصلی محیط، کیفیت و سودآوری تأکید دارد و در سطوح مختلف منطقه ای، فرا منطقه ای، ملی و سازمانی قابل به کارگیری است و رویکرد اصلی آن ارتقای کیفیت زندگی است. با توجه به این موضوع یافتن عوامل مؤثر در بهره وری سبز می تواند بسیار حائز اهمیت باشد. از اینرو در این پژوهش به بررسی عوامل مؤثر بر بهره وری سبز در صنایع خودروسازی با رویکرد دی متل خاکستری پرداخته می شود. جامعه آماری تحقیق 40 فر از خبرگان صنایع خودروسازی می باشد. ابتدا 23 عامل مؤثر در بهره وری سبز و در قالب 6 گروه اصلی فرهنگی، سازمانی، فنی و تکنولوژیک، مدیرینی، برنامه ریزی و فرآیند تقسیم بندی شدند. سپس با استفاده از روش دی متل خاکستری اثرات متقایل عوامل با هم سنجده شد. نتایج یافته ها نشان داد که مهم ترین عامل های علی در بهره وری سبز، عامل های فنی و تکنولوژیک، فرهنگی و مدیریتی می باشند. در این راستا پیشنهاد می شود که با در نظر گرفتن روابط علی و معلولی موجود در این تحقیق برنامه ریزی های آتی جهت مدیریت بهتر زمان و هزینه در صنایع خودروسازی انحام شود.
چکیده انگلیسی:
The goal of products is to providing to products that are environmentally friendly. On the other hand, organizations are seeking to achieve eco-friendly products along with productivity. Regarding this, it can be said that the main goal of green productivity is to increase environmental protection in a way that increases commercial profit, emphasizes the main issue of environment, quality and profitability and at different levels of regional, transregional, National and institutional, and its main approach is to improve the quality of life. Considering this, finding of effective factors in green productivity can be very important. Therefore, in this research, are considered factors of affecting green productivity in automobile industry with a grey dematel approach. First, the statistical population of the study is 40 ovens of automotive industry experts 23 factors influencing of green productivity were categorized into 6 main cultural, organizational, technical and technological groups, managers, planning and process. In the sequel, the effects of the interlocking factors were measured using the grey dematel method. The results of the findings showed that the most important causal factors in green productivity are technical and technological, cultural and managerial factors. It is suggested that green productivity planning be in line with these factors. In this regard, it is suggested that taking into account the causal relationships existing in this research, future plans are planned for the automotive industry in order to save time and cost management.
منابع و مأخذ:
Aksoy, A., Küçükolu, Ene, S., & Öztürk, N. (2014). Integrated Emission and Fuel Consumption Calculation Model for Green Supply Chain Management. Procedia-Social and Behavioral Sciences, 109, 1106-1109.
Ashrafi, M. (2014). Green Marketing in Hospitality Industry. Journal of Applied Environmental and Biological Sciences, 4(4), 42-46.
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Darmawan, Marimin, Muhammad Arif; Putra, Machfud Muhammad PanjiIslam Fajar; Wiguna, Bangkit. (2014). Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study. Journal of Cleaner Production, 85, 201-211.
Deylami Moezzi. S; Chini Foroosh. H; Saeidi. H; Rastegar. L; Kouhi Janaghrad. S. (2013). Investigate the relationship between greenhouse gas supply functions and operational functions through the Green Supply Chain Management Model, First National Conference on Industrial Engineering and Systems, 2013, 1-9. [in Persian].
Fallah. S; Razavi. S.H; Imani. A; Imamgholizade. S. (2016). Identification and ranking of green productivity strategy components by FAHP (Tehran metro organization), Public Administration Research, 8 (28), 167-191. [in Persian].
Govindan Kannan., Diabat Ali., K. Madan Shankar K. (2014). Analyzing the drivers of green manufacturing with fuzzy approach. Journal of Cleaner Production, XXX.1-12.
Gandhi, M, Selladurai, V & Santhi, P. (2006). Green productivity indexing a practical step towards integrating environmental protection into corporate performance. International Journal of Productivity and Performance Management, 55(7).
Govindan, Kanan, Khodaverdi, Roohollah, Vafadarnikjoo, Amin (2016). A grey DEMATEL approach to develop third-party logistics provider selection criteria. Industrial Management & Data Systems, 1-28.
Hsu C. W., Hu A. H. (2008). Green supply chain management in the electronic industry. International Journal Environ Science Technology, 5 (2), 205-216.
Li, Ke; Lin, Boqiang. (2016). Impact of energy conservation policies on the green productivity in China’s manufacturing sector: Evidence from a three-stage DEA model. Applied Energy, 168, 351-363.
Luthra, S., Kumar, V., Kumar, S., & Haleem, A. (2011). Barriers to implement green supply chain management in automobile industry using interpretive structural modeling technique-An Indian perspective. Journal of Industrial Engineering and Management, 4(2), 231-257.
Oliver, J. D. (2013). Promoting sustainability by marketing green products to non-adopters. Gestion 2000, 30(3), 77-86.
Siegel, D. S. (2009). Green management matters only if it yields more green: An economic/strategic perspective. The Academy of Management Perspectives.
Sriram, K., Ganesh, L & Madhumathi, R. (2013). Inferring principles for sustainable development of business through analogies from ecological systems. IIMB Management Review, 25, 36-48.
Tao, Feng; Zhang, Huiqin; Hu, Jun; Xia, X.H. (2017). Dynamics of green productivity growth for major Chinese urban agglomerations. Applied Energy 196, 170-179.
Wu, John, Dunn, Steve, Forman, Howard. (2012). A Study on Green Supply Chain Management Practices among Large Global Corporations. Journal of Supply Chain and Operations Management, 10(1).
Xie, Rong-hui; Yuan, Yi-jun; Huang, Jing-jing. (2017). Different Types of Environmental Regulations and Heterogeneous Influence on “Green” Productivity: Evidence from China. Ecological Economics, 132, 104-112.
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Aksoy, A., Küçükolu, Ene, S., & Öztürk, N. (2014). Integrated Emission and Fuel Consumption Calculation Model for Green Supply Chain Management. Procedia-Social and Behavioral Sciences, 109, 1106-1109.
Ashrafi, M. (2014). Green Marketing in Hospitality Industry. Journal of Applied Environmental and Biological Sciences, 4(4), 42-46.
Chen, Y and Chang, C. (2013). The Determinants of Green Product Development Performance: Green Dynamic Capabilities, Green Transformational Leadership, and Green Creativity, J Bus Ethics, 116,107–119.
Darmawan, Marimin, Muhammad Arif; Putra, Machfud Muhammad PanjiIslam Fajar; Wiguna, Bangkit. (2014). Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study. Journal of Cleaner Production, 85, 201-211.
Deylami Moezzi. S; Chini Foroosh. H; Saeidi. H; Rastegar. L; Kouhi Janaghrad. S. (2013). Investigate the relationship between greenhouse gas supply functions and operational functions through the Green Supply Chain Management Model, First National Conference on Industrial Engineering and Systems, 2013, 1-9. [in Persian].
Fallah. S; Razavi. S.H; Imani. A; Imamgholizade. S. (2016). Identification and ranking of green productivity strategy components by FAHP (Tehran metro organization), Public Administration Research, 8 (28), 167-191. [in Persian].
Govindan Kannan., Diabat Ali., K. Madan Shankar K. (2014). Analyzing the drivers of green manufacturing with fuzzy approach. Journal of Cleaner Production, XXX.1-12.
Gandhi, M, Selladurai, V & Santhi, P. (2006). Green productivity indexing a practical step towards integrating environmental protection into corporate performance. International Journal of Productivity and Performance Management, 55(7).
Govindan, Kanan, Khodaverdi, Roohollah, Vafadarnikjoo, Amin (2016). A grey DEMATEL approach to develop third-party logistics provider selection criteria. Industrial Management & Data Systems, 1-28.
Hsu C. W., Hu A. H. (2008). Green supply chain management in the electronic industry. International Journal Environ Science Technology, 5 (2), 205-216.
Li, Ke; Lin, Boqiang. (2016). Impact of energy conservation policies on the green productivity in China’s manufacturing sector: Evidence from a three-stage DEA model. Applied Energy, 168, 351-363.
Luthra, S., Kumar, V., Kumar, S., & Haleem, A. (2011). Barriers to implement green supply chain management in automobile industry using interpretive structural modeling technique-An Indian perspective. Journal of Industrial Engineering and Management, 4(2), 231-257.
Oliver, J. D. (2013). Promoting sustainability by marketing green products to non-adopters. Gestion 2000, 30(3), 77-86.
Siegel, D. S. (2009). Green management matters only if it yields more green: An economic/strategic perspective. The Academy of Management Perspectives.
Sriram, K., Ganesh, L & Madhumathi, R. (2013). Inferring principles for sustainable development of business through analogies from ecological systems. IIMB Management Review, 25, 36-48.
Tao, Feng; Zhang, Huiqin; Hu, Jun; Xia, X.H. (2017). Dynamics of green productivity growth for major Chinese urban agglomerations. Applied Energy 196, 170-179.
Wu, John, Dunn, Steve, Forman, Howard. (2012). A Study on Green Supply Chain Management Practices among Large Global Corporations. Journal of Supply Chain and Operations Management, 10(1).
Xie, Rong-hui; Yuan, Yi-jun; Huang, Jing-jing. (2017). Different Types of Environmental Regulations and Heterogeneous Influence on “Green” Productivity: Evidence from China. Ecological Economics, 132, 104-112.