عوامل کلیدی مؤثر بر بهره وری در زنجیره تأمین صنعت فولاد
عوامل کلیدی مؤثر بر بهره وری در زنجیره تأمین صنعت فولاد
الموضوعات :
رضا بشارتی زاده 1 , رضا رادفر 2 , عباس طلوعی اشلقی 3 , محمدرضا معتدل 4
1 - دانشجوی دکتری گروه مدیریت صنعتی، واحد امارات، دانشگاه آزاد اسلامی، امارات متحده عربی، دبی
2 - استاد گروه مدیریت صنعتی، واحدعلوم‌و‌تحقیقات،دانشگاه آزاد اسلامی، تهران، ایران
3 - استاد گروه مدیریت صنعتی، واحدعلوم‌و‌تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
4 - استادیار گروه مدیریت صنعتی، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران
الکلمات المفتاحية: مدیریت زنجیره تامین, بهره وری, زنجیره تامین, صنعت فولاد, مدل اسکور,
ملخص المقالة :
زنجیره تامین کارآمد و نیز مدیریت صحیح مولفه های آن نقش بسزایی در بهره وری زنجیره تامین ایفا می نماید. صنعت فولاد جزء صنایع مادر بوده و نیازمند آن است تا بهره وری زنجیره خود را هر چه بیشتر ارتقاء دهد. هدف پژوهش حاضر شناسایی عوامل کلیدی موثر بر بهره وری زنجیره تامین فولاد کشورمی باشد. به منظور شناسایی عوامل موثر بر بهره وری زنجیره تامین فولاد، از مدل اسکور بهره گیری شده است و شاخص های مدل با فرم های CVR وCVI و نیز با نظر خبرگان صنعت فولاد مورد تایید قرارگرفته و بر اساس آن پرسشنامه طراحی شده بین مدیران و کارشناسان صنعت فولاد توزیع و جمع آوری گردید. در نهایت تجزیه و تحلیل داده‌ها با استفاده از تحلیل عاملی تأییدی با معادلات ساختاری و نرم افزار PLS انجام شد و عوامل تاثیرگذار بر بهره وری زنجیره تامین، با 30 شاخص و در 6 عامل مورد تایید واقع گردید. نتایج پژوهش حاکی از آن است که هر 6 عامل بر بهره وری زنجیره تامین فولاد تاثیر گذار می باشند اما در بین آنها عامل توانمندسازها دارای بیشترین تاثیر بر بهره وری زنجیره تامین فولاد است.
Abstract
Efficient supply chain as well as the proper management of its components play an important role in supply chain productivity. The steel industry is one of the mother industries and needs to further enhance its chain productivity. The purpose of the present study is to identify key factors affecting the productivity of national steel supply chain. In order to identify the factors affecting steel supply chain productivity, the SCOR model has been used and its indices have been validated by CVR and CVI forms as well as by steel industry experts, based on which the designed questionnaire was distributed among the managers and experts of the steel industry and the data were collected. Finally, the data analysis was performed using confirmatory factor analysis with structural equations and PLS software. The factors affecting supply chain productivity were confirmed by 30 indices and 6 factors.The results revealed that all 6 factors influence steel supply chain efficiency, however, among these factors, the enabler’s factor
Key Words: supply chain, supply chain management, productivity, steel industry, SCOR model
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Cagliano, R., Worley, C. G., & Caniato, F. F. (2016). The Challenge of Sustainable Innovation in Agri-Food Supply Chains. In Organizing Supply Chain Processes for Sustainable Innovation in the Agri-Food Industry (pp. 1-30).Emerald Group Publishing Limited. doi:10.1108/S2045-060520160000005009
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Fornell, C. &Larcker, D.(1981). Evaluating Structural Equation Modeling with Unobserved ariables and Measurement Error, Journal of Marking Research, 18(1):39-50. doi:10.2307/3151312
Gefen, D. & Straub, D.W.(2005). A Practical Guide to Factorial Validity Using PLS-Graph: Tutorial and Annotated Example. Communications of AIS, 16 (1): 91-109. doi:10.17705/1CAIS.01605
Güner, H. M., Çemberci, M., & Civelek, M. E. (2018). The Effect of Supply Chain Agility on Firm Performance, 4(2), 25-34.
Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. & Tatham, R.(2006). Multivariate Analysis (6th ed.), New Jersey: Pearson Education In, 1-761.
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Khamseh, A; Ghodarzi, M; Asghari, M.(2019), “Identification of key success factors of R&D collaborations with an approach to future in MAPNA Group Supply Chain Management, journal of future studies management, 30(3), 81-92.[In Persian]. https://jmfr.srbiau.ac.ir/article_15294.html
Lii, P., Kau, F. (2016). Innovation-oriented supply chain integration for combined competitiveness and firm performance. Intern. Journal of Production Economics, 174, 142-155. doi:10.1016/j.ijpe.2016.01.018
Kumar, V., Chibuzo, E., Reyes, J., Kumari, A., Lona, L., Torres, G., (2017). The Impact of Supply Chain Integration on Performance: Evidence from the UK Food Sector. Procedia Manufacturing 11 (2017)814–82. doi:10. 1016/j.promfg.2017.07.183
Rimienė, Kristina. 2011. “Supply Chain Agility Concept Evolution(1990- 2010)”, Journal of Economics and Management, 892-899.
Sabegh, M. H. Z., Caliskan, A., Ozturkoglu, Y., & Cetiner, B. (2019). Testing the Effects of Agile and Flexible Supply Chain on the Firm Performance Through SEM. In System Performance and Management Analytics (pp. 35-46). Springer, Singapore. doi:10.1007/978-981-10-7323-6_3
SCC(2004), Supply-Chain Operations Reference-model: Supply-chain.org, Overview Version 7.0.
Sarkis,J.,Zhu,Q.and Laai,KH.(2011) An organizational theoretic review of green supply chain management literature, International journal of Production Economics,Vol.130,No.1,pp.1-15.doi:10.1016/j.ijpe.2010.11. 010
Srvulaki, E., & Davis, M. (2010). "Aligning product with supply chain processes and strategy". The international journal of logistic management, 21, 127- 151. doi:10.1108/09574091011042214
Tarofder, A. K., Haque, A., Hashim, N., Azam, S. M., & Sherief, S. R. (2019). Impact of Ecological Factors on Nationwide Supply Chain Performance. Ekoloji Dergisi, 28(107):695-704.
Van, N., Vikas, K., Archana, K., Arturo, G., Supalak, A., (2016). The role of supply chain integration in achieving competitive advantage: A study of UK automobile manufacturers. Proceedings of the 26th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM), Seoul, Republic of Korea, 1-8.
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Azar, A; GholamReza, R; Ghanavati, M.(2012) “Route structural modeling in management: application of Smart PLS Software”, Tehran:Negah Danesh Publication, 1-280.[In Persian].
Cagliano, R., Worley, C. G., & Caniato, F. F. (2016). The Challenge of Sustainable Innovation in Agri-Food Supply Chains. In Organizing Supply Chain Processes for Sustainable Innovation in the Agri-Food Industry (pp. 1-30).Emerald Group Publishing Limited. doi:10.1108/S2045-060520160000005009
Espadinha-Cruz, P., Grilo, A., Puga-Leal, R., & Cruz-Machado, V. (2011). A model for evaluating Lean, Agile, Resilient and Green practices interoperability in supply chains. Industrial Engineering and Engineering Management, IEEM 2011(pp.1209-1213), Singapore. doi:10.1109/IEEM. 2011.6118107.
Fornell, C. &Larcker, D.(1981). Evaluating Structural Equation Modeling with Unobserved ariables and Measurement Error, Journal of Marking Research, 18(1):39-50. doi:10.2307/3151312
Gefen, D. & Straub, D.W.(2005). A Practical Guide to Factorial Validity Using PLS-Graph: Tutorial and Annotated Example. Communications of AIS, 16 (1): 91-109. doi:10.17705/1CAIS.01605
Güner, H. M., Çemberci, M., & Civelek, M. E. (2018). The Effect of Supply Chain Agility on Firm Performance, 4(2), 25-34.
Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. & Tatham, R.(2006). Multivariate Analysis (6th ed.), New Jersey: Pearson Education In, 1-761.
Hair, J.F., Ringle, C.M. & Sarstedt, M.(2011). PLS-SEM: indeed a silver bullet, Journal of Marketing heory and Practice, 19 (2): 139-151. doi:10.2753/MTP1069-6679190202
Henseler, J., & Fassott, G.(2011). Testing moderating effects in PLS path models: An illustration of available procedures. In Handbook of partial least squares. Pp. 713-735, Springer Berlin Heidelberg. doi:10.1007/978-3-540-32827-8_31
Handfield, R., Nichols, E. L. (1999) “Introduction to Supply Chain Management”. New Jersey, N. J.: Upper Saddle River: Prentice Hall.
Khamseh, A; Ghodarzi, M; Asghari, M.(2019), “Identification of key success factors of R&D collaborations with an approach to future in MAPNA Group Supply Chain Management, journal of future studies management, 30(3), 81-92.[In Persian]. https://jmfr.srbiau.ac.ir/article_15294.html
Lii, P., Kau, F. (2016). Innovation-oriented supply chain integration for combined competitiveness and firm performance. Intern. Journal of Production Economics, 174, 142-155. doi:10.1016/j.ijpe.2016.01.018
Kumar, V., Chibuzo, E., Reyes, J., Kumari, A., Lona, L., Torres, G., (2017). The Impact of Supply Chain Integration on Performance: Evidence from the UK Food Sector. Procedia Manufacturing 11 (2017)814–82. doi:10. 1016/j.promfg.2017.07.183
Rimienė, Kristina. 2011. “Supply Chain Agility Concept Evolution(1990- 2010)”, Journal of Economics and Management, 892-899.
Sabegh, M. H. Z., Caliskan, A., Ozturkoglu, Y., & Cetiner, B. (2019). Testing the Effects of Agile and Flexible Supply Chain on the Firm Performance Through SEM. In System Performance and Management Analytics (pp. 35-46). Springer, Singapore. doi:10.1007/978-981-10-7323-6_3
SCC(2004), Supply-Chain Operations Reference-model: Supply-chain.org, Overview Version 7.0.
Sarkis,J.,Zhu,Q.and Laai,KH.(2011) An organizational theoretic review of green supply chain management literature, International journal of Production Economics,Vol.130,No.1,pp.1-15.doi:10.1016/j.ijpe.2010.11. 010
Srvulaki, E., & Davis, M. (2010). "Aligning product with supply chain processes and strategy". The international journal of logistic management, 21, 127- 151. doi:10.1108/09574091011042214
Tarofder, A. K., Haque, A., Hashim, N., Azam, S. M., & Sherief, S. R. (2019). Impact of Ecological Factors on Nationwide Supply Chain Performance. Ekoloji Dergisi, 28(107):695-704.
Van, N., Vikas, K., Archana, K., Arturo, G., Supalak, A., (2016). The role of supply chain integration in achieving competitive advantage: A study of UK automobile manufacturers. Proceedings of the 26th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM), Seoul, Republic of Korea, 1-8.
