مدل‌سازی پویای بهینگی زنجیره تأمین صنعت برق کشور

نوع مقاله : پژوهشی

نویسندگان

1 دانشجوی دکتری مدیریت بازرگانی، دانشکده علوم انسانی، گروه مدیریت، واحد سمنان، دانشگاه آزاداسلامی، سمنان، ایران

2 استادیار و رئیس مرکز تحقیقات کارآفرینی، ایده پردازی و تجاری سازی، واحد سمنان، دانشگاه آزاد اسلامی، سمنان، ایران.

3 استادیار گروه مدیریت، واحد سمنان، دانشگاه آزاداسلامی، سمنان، ایران

چکیده

هدف از این مطالعه مدل سازی عوامل موثر بر بهینگی زنجیره تامین مبتنی بر تکنیک پویایی های سیستم در صنعت برق می باشد.مطالعه حاضر با استفاده از روش ترکیبی،یک رهیافت کیفی-کمی را برای تدوین و اعتباریابی مدل عوامل موثر بر بهینگی زنجیره تامین از دیدگاه نخبگان صنعت برق ارائه می نماید.در راستای تدوین و شناسایی عوامل بهینگی،از تحلیل مضمون و شبکه مضمونها با استفاده از نرم افزار نویو برای تشکیل شبکه مضامین،الگوی کیفی عوامل موثر بر بهینگی زنجیره تامین طراحی شد.برای تدوین الگوی اولیه عوامل موثر بر بهینگی زنجیره تامین،تعداد 23 نفر از خبرگان و متخصصان صنعت برق با روش نمونه گیری هدفمند انتخاب شدند.در بخش کمی نیز برای مدلسازی از روش پویایی سیستم استفاده شد و سپس داده‌های جمع آوری شده توسط نرم افزار ونسیم مورد تجزیه و تحلیل قرار گرفت. این شبیه سازی طی یک دوره یک ساله انجام شده است و نشان دهنده‌ی یک افق دید طولانی مدت می‌باشد. سپس نتایج بدست آمده از این شبیه سازی بر روی متغیر‌های مورد مطاله ارائه و تفسیر شد. تعیین روابط بین متغیرها و نوع متغیرها می تواند به درک بهتر موضوع و اتخاذ تصمیمات مناسبی در مساله بهینگی زنجیره تامین منجر شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Dynamic modeling of power supply chain optimization

نویسندگان [English]

  • Mojtaba Omidiyan 1
  • Younos Vakil Alroaia 2
  • Seyyed Abdolla heydariyeh 3
1 PhD Student in Business Management, Department of Management, Semnan Branch, Islamic Azad University, Semnan, Iran.
2 Assistant Prof. and Chairman, Entrepreneurship and Commercialization Research Center, Semnan Branch, Islamic Azad University, Semnan, Iran
3 Assistant Prof., Department of Management, Semnan Branch, Islamic Azad University, Semnan, Iran
چکیده [English]

The purpose of this study is to modeling the factors affecting supply chain optimality based on the system dynamics technique in the power industry. The present study uses a hybrid approach to develop a qualitative-quantitative approach to formulate and validate the factors influencing the supply chain optimality. To elaborate and identify the optimal factors, from content analysis and thematic analysis using Novio software to construct themes, a qualitative model of factors influencing supply chain optimality was designed. On the optimality of the supply chain, 23 experts and experts in the electricity industry with purposive sampling method were selected. In the quantitative part, the system dynamics method was used for modeling, and then the data collected was analyzed by Venice software. This simulation was carried out over a one year period and represents a long-term horizon. Then the results of this simulation were presented and interpreted on the variables studied. Determining the relationships between variables and the types of variables can lead to a better understanding of the issue and to making appropriate decisions on the supply chain optimality problem.

کلیدواژه‌ها [English]

  • "Optimization"
  • "Supply Chain"
  • "Content analysis"
  • "System Dynamics"
  • "Electricity Industry"
  1. Abidi, H., Klumpp, M., & De Leeuw, S. (2015). Modelling impact of key success factors in humanitarian logistics. In logistics management, 427-443. Springer, Cham.
  2. Ahire, S.L., Golhar, D.Y., & Waller, M.A. (1996). Development and validation of TQM implementation constructs. Decision sciences, 27(1), 23-56.
  3. Akhavan, P., Ghidar Khaljani, J., & Khairkhah, M. (2017). Model for evaluating organizational business strategies. Strategic Management Studies Quarterly, 8(29), 161-143. .[In Persian]
  4. Amiri, M.,  Mansouri Mohammad Abadi, S., Shaabani, A., & Mohammadi, K. (2016). An analysis of factors affecting supply chain performance using an integrated approach of confirmatory factor analysis and fuzzy TOPSIS in food industry companies of Shiraz Industrial City, Supply Chain Science Quarterly, 18, 54, 15-4.[In Persian]
  5. Anand, N., & Grover, N. (2015). Measuring retail supply chain performance: Theoretical model using key performance indicators (KPIs). Benchmarking: An International Journal, 22(1), 135-166.
  6. Arshinder, K., & Arun, S.G. (2008). Supply chain coordination: perspectives, empirical studies and research directions. International journal of production Economics. 115, 316 – 335.
  7. Azadeh, S., &  Yavarzadeh, M.R. (2015). Factors affecting supply chain management in industries, 2nd International Conference on Modern Research in Industrial Management and Engineering.[In Persian]
  8. Bawer Sad, B., Nili Ahmad Abadi, M., & Biranvand, T. (2018). Offering sustainable supply chain management in the marine industry (Case Study: Marine Industry Organization,Journal of Marine Science Education, 12, 37-48.[In Persian]
  9. Cao, M., & Zhang, Q. (2011). Supply chain collaboration: impact on collaborative Advantage and firm performance. Journal of Operations Management. 29, 163–180.
  10. Colin, M., Galindo, R., & Hernández, O. (2015). Information and communication technology as a key strategy for efficient supply chain management in manufacturing SMEs. Procedia Computer Science, 55, 833 - 842.
  11. Cooper, M.C., Lambert, D.M., & Pagh, J.D. (1997). Supply chain management: more than a new name for logistics. The international journal of logistics management, 8(1), 1-14.
  12. Dow Jones Sustaiablity indices. (DJSI) (2014). http://www.sustainabilityindices.com.
  13. Emami Namivandi, S., Moradnejadi, H., & Sayi Mohammadi, S. (2019). Evaluation of Dairy Product Supply Chain Performance in Rural Areas of Kermanshah, Rural Research Quarterly, Drouh 10(3), 437-427. [In Persian]
  14. Fakkorsahiyeh, A.M. (2015). Measuring supply chain flexibility using gray systems theory, management research in Iran, 19(4), 177-117.[In Persian]
  15. Fekri.R., Ahmadi, M,. &  Babaian, M. (2015). Conceptual model of service chain agility supply chain using fuzzy conceptual mapping, Tomorrow's Management & Science Journal, Thirteenth Year, 42. [In Persian]
  16. Fekri, R., &  Mirzadzare, S.H. (2016). Supply chain evaluation framework based on supply chain management model (SCOR Model) reference model, MSc thesis, Payam Noor University, Rey Branch.[In Persian]
  17. Fischer, M., Law, K., & Lee, H. (2010). Real-Time supply chain management (SCM) using virtual design and construction (VDC) and Lean., S.l. : CIFE, Stanford University.
  18. Govindaraju, V.G.R.C., Kaliani Sundram, V.P., Muhammad, A.B., Gunasekaran, A. (2016). Supply chain practices and performance: the indirect effects of supply chain integration, Benchmarking International Journal, 23(6).
  19. Ghorbanpour, A., & Rasouli, E. (2018). Structural-interpretive model of supply chain resilience: A Case Study of Bushehr Power Distribution Company, Journal of Energy Policy and Planning Research, 11, 169-200.[In Persian]
  20. Ghosh, M. (2013). Lean manufacturing performance in Indian manufacturing plants. Journal of Manufacturing Technology Management.
  21. Hassini, E., Surti, C., & Searcy, C. (2012). A literature review and a case study of sustainable supply chains with a focus on metrics. International Journal of Production Economics, 140(1), 69-82.
  22. Hodge, G.L., Goforth Ross, K., Joines, J.A., & Thoney, K. (2011). Adapting lean manufacturing principles to the textile industry. Production Planning & Control, 22(3), 237-247.
  23. Hosseini, S.M., & Sheikh, N. (2012). Explaining the strategic role of supply chain management operations in improving company performance: A Study of the Iranian Food Industry, Strategic Management Studies Journal, 10, 60-35.[In Persian]
  24. Hosseini, S.M., Mohammadi, A.S., & Pishavi, M. (2010). Supply chain strategy and production system selection, Strategic Management Studies Journal, 2, 112-189.[In Persian]
  25. Industrial and Commercial Bank of China (ICBC Bank).(2013). Corporate Social Responsibility Report.
  26. Javadian, N.B., Khani, M., & Mahdavi, E. (2012). Identifymd factors affecting supply chain performance and improving it using the case studysystem dynamics technique at darugar company, Management Research in Iran,16(3), 49-58. [In Persian]
  27. Kabra, G., Ramesh, A., & Arshinder, K. (2015). Identification and prioritization of coordination barriers in humanitarian supply chain management. International Journal of Disaster Risk Reduction, 13, 128-138.
  28. Kanji, G.K., & Wong, A. (1999). Business excellence model for supply chain management. Total quality management, 10(8), 1147-1168.
  29. Katiyar, R., Barua, M.K., & Meena, P.L. (2015). Modelling the measures of supply chain performance in the Indian automotive industry. Benchmarking: An International Journal, 22(4), 665-696.
  30. Kaynak, H., & Hartley, J.L. (2008). A replication and extension of quality management into the supply chain. Journal of Operations Management, 26(4), 468-489.
  31. Kuei, C.H., & Madu, C.N. (2001). Identifying critical success factors for supply chain quality management (SCQM). Asia Pacific Management Review, 6(4), 409-423.
  32. Kundu, G.K., & MuraliManohar, B. (2012). A unified model for implementing lean and CMMI for Services (CMMI-SVC v1. 3) best practices. Asian Journal on Quality, 13(2), 138-162.
  33. Kuruppalil, Z. (2007). Leanness and agility in job shops: A framework for a survey instrument developed using the Delphi method. Indiana State University.
  34. Machado, M.C., Fernandes, A.C., Sampaio P., Sameiro M.C., Nóvoa H., & Silva, S.D. (2016). Supply chain quality management: a theoretical framework for integration measurement.
  35. Mahmoudzadeh, M., & Laleh, A. (2014). Evaluating supply network efficiency by using social networks analysis (Case Study: Tractor Motor Manufacturing Company), Productivity Management, autumn 8, 3(30), 135-152.[In Persian]
  36. Mary, J., & N.L.C. (2012). Organization theory. Translated by H. Danaei Fard, Tehran: Ketab Nashr.
  37. Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix, N.W., Smith, C.D., & Zacharia, Z.G. (2001). Defining supply chain management, Journal of Business Logistics. 22(2), 1–25.
  38. Mirghafouri, S., MarvatiSharifabadi, A., & KarimiTakav, S. (2017). Application of cognitive mapping method in designing sustainable supply Chain Model of Hospitals in Type 2 Fuzzy Environment, Health and Treatment Management, 8(3), 64-51.[In Persian]
  39. Nazeri, A., Nosratpour, M., & Asakereh, S. (2017). Investigating the impact of supply chain quality management measures on performance in the iranian automotive industry considering the mediating role of innovation, Business Research Journal, 85, 103-59.[In Persian]
  40. Omidian, M., & Heydarieh, S. (2018). Prioritizing supply chain strategy in power generation using fuzzy hierarchical analysis, 2nd International Conference on Business Management, University of Tabriz. [In Persian]
  41. Otto, P. (2008). A system dynamics model as a decision aid in evaluating and communicating complex market entry strategies, Journal of Business Research, 61, 1173-1181.
  42. Panizzolo, R., Garengo, P., Sharma, M. K., & Gore, A. (2012). Lean manufacturing in developing countries: evidence from Indian SMEs. Production Planning & Control, 23(10-11), 769-788.
  43. RezaeiPendari, A., & Azar, A. (2018). Designing a supply chain management model with a data theory approach, Public Management Research, Eleventh Year, 39, 5–32.[In Persian]
  44. RezaeiPenderi, A., Azar, A., Taghavi, A., & MoghbelBarz, A. (2014). Presentation of service chain performance evaluation model with fuzzy cognitive mapping approach (Case Study: Insurance Industry), Journal of Industrial Vision Management, 16, 93-75.[In Persian]
  45. Royal Bank of Scatland. (2013). Sustainability review report.
  46. SadeghiMoghaddam, M.R., Safari, H., & AhmadiNozari, M. (2016). Supply chain stability measurement using multi-step / multi-fuzzy inference system (Case Study: Parsian Bank), Industrial Management, 7(3), 562-533.[In Persian]
  47. SaeediKia, M., & JafarMarzafariFard, M. (2000). Supply chain management, Method, Tenth Year, 61.[In Persian]
  48. Sah, M.A.M., Habidin, N.F., Latip, N.A.M., & Salleh, M.I. (2014). A review of structural relationship between supply chain management and organizational performance in Malaysian automotive industry.
  49. SalehiTadadi, E., BorumandJazi Shahzad., & Khani, N. (2017). Identifying and prioritizing the factors influencing the success of the humanitarian supply chain , Journal of Rescue and Relief, Eighth Year, 3.[In Persian]
  50. SeifiShojaei, H. (2016). Evaluating factors affecting supply chain management performance improvement using hierarchical analysis in food industry, Value Chain Management, 1(2).[In Persian]
  51. Shafi'i, M., & Tarmest, P. (2014). The impact of supply chain management processes on competitive advantage and organizational performance (Sappco Company Case Study), Quarterly Journal of Management Studies, 5(2), 104-105.[In Persian]
  52. Shah, R ., & Ward, P. (2013). Toyota production system and kanban system. Journal of Operations Management, 129-149.
  53. Shahroudi, K., & BabaeiQasemAbadi, F. (2014). Competitive forces and the application to improve supply chain performance, Strategic Management Studies Journal, 17, 194-167.[In Persian]
  54. Sharma, V. K., Chandna, P., & Bhardwaj, A. (2017). Green supply chain management related performance indicators in agro industry: A review. Journal of Cleaner Production, 141, 1194-1208.
  55. Shetty, D., Ali, A., & Cummings, R. (2010). Survey-based spreadsheet model on lean implementation. International Journal of Lean Six Sigma, 1(4), 310-334.
  56. Standard Bank Group. (2013). Sustainability report.
  57. Torbati, A., Arsanjani, M. A., & Firouzahi, M. (2015). Developing a supply chain management strategy map by integrating the cause chart and balanced scorecard, Journal of Modeling in Engineering, 13, 42, 165-151.[In Persian]
  58. Vanichchinchai, A., & Igel, B. (2009). Total quality management and supply chain management: similarities and differences. The TQM Journal, 21(3), 249-260.
  59. Vinodh, S., & Aravindraj, S. (2012). Axiomatic modeling of lean manufacturing system. Journal of Engineering, Design and Technology, 10(2), 199-216.
  60. Yahya Zadehfar, M., Azar, A., Aghajani, H., & Farhadian, A. (2016). Identifying strategic risks in iran's automotive supply chain, Strategic Management Studies Journal, 32, 56-37.[In Persian]
  61. Zhang, X., Song, H., & Huang, G. Q. (2009). Tourism supply chain management: A new research agenda. Tourism management, 30(3), 345-358.