ارائه مدلی دینامیکی برای ارزیابی میزان لارج‌بودن عملکرد متوازن یک زنجیره تأمین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مدیریت صنعتی،‌ مدیریت سیستم، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

2 استاد، گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ‌ایران.

3 دانشیار، گروه مدیریت صنعتی، دانشکده مدیریت، دانشگاه تهران، تهران، ‌ایران.

چکیده

هدف این پژوهش ارزیابی میزان لارج­‌بودن فعالیت‌­های یک شرکت موجود در یک زنجیره تأمین در چارچوب کارت امتیازی متوازن و با کمک­‌گرفتن از روش مدل­‌سازی دینامیکی است. در این پژوهش برای ارزیابی میزان لارج‌بودن عملکرد شرکت از روش ادغامی مفاهیم لارج و کارت امتیازی متوازن استفاده گردید؛ بدین ترتیب که ابتدا اهداف استراتژیک تدوین و در چارچوب روش کارت امتیازی متوازن، شاخص­هایی انتخاب گردید که لارج‌بودن عملکرد شرکت را نشان دهد و سپس این شاخص‌­ها به همراه متغیرهای کمکی وارد مدل دینامیکی شده است. مدل دینامیکی طراحی‌شده که شامل سنجه‌های کارت امتیازی متوازن است برای یک شرکت فعال در صنعت قطعه‌سازی اجرا شده است. بر اساس اهداف استراتژیک شرکت، سناریوهایی تعریف و اثرات آن بر عملکرد شرکت و میزان لارج­بودن زنجیره تأمین ارزیابی شده است. با تحلیل سناریوها مشخص شد که با تغییر هر پارامتر در مدل دینامیکی بعضی از عناصر لارج افزایش و به‌طور هم‌زمان بعضی دیگر از عناصر کاهش می‌یابد. برای مثال، با افزایش بهره‌وری آموزش میزان ناب و تاب‌آوری افزایش می‌‌یابد؛ اما بر محیط‌زیست بدون تأثیر است. با استفاده از مدل دینامیکی طراحی‌شده می‌توان اثر هر اقدام و تصمیم مدیریتی را بر رویکردهای چهارگانه لارج تعیین کرده و میزان تحقق اهداف استراتژیک را مشخص کرد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A System Dynamics Model for Balanced Performance Evaluation of A LARG Supply Chain

نویسندگان [English]

  • Mohammad Reza Atefi 1
  • Reza Radfar 2
  • Ezatollah Asgharizade 3
1 Ph.D student, Department of Systems Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 Professor, Department of Industrial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3 Associate Professor, Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran.
چکیده [English]

The purpose of this research is to evaluate the level to which a company’s activities in a supply chain are LARG. In this study, an integrated method is used to evaluate the LARG supply chain performance of a company resulting from the integration of LARG concepts and Balanced Scorecard approach. The BSC measures are selected based on the LARG concepts, and then the indicators entered into the dynamic model. Variables are changed in different scenarios to analyze changes in the company’s performance. Scenarios are designed to evaluate the supply chain performance using the strategic objectives. The results show that simultaneous implementation of LARG elements is not possible due to the trade off relationship. By analyzing the scenarios, it was found that by changing each parameter in the dynamic model, some LARG elements increase and at the same time, some other elements decrease. For example, by increasing the productivity of education, the level of leanness and resilience increases, but it has no effect on the environment. Using the designed dynamic model, the effect of each managerial action and decision on LARG can be determined and the extent to which strategic goals can be achieved.

کلیدواژه‌ها [English]

  • System Dynamics
  • LARG Supply Chain Management
  • Performance Evaluation
  • Scenario Planning
  • Balanced Scorecard

مراجع

  1. Abdoli Bidhandi, R. & Valmohammadi, C., (2017). Effects of supply chain agility on profitability. Business Process Management Journal, 23(5), 1064-1082.
  2. Adamides, D., Karacapilidis, N., Pylarinou, H. & Koumanakos, D. (2008). “Supporting collaboration in the development and management of lean supply networks. Production Planning & Control, 19(1), 35-52.
  3. Afonso, H., & do Rosário Cabrita, M. (2015). Developing a lean supply chain performance framework in a SME: a perspective based on the balanced scorecard. Procedia engineering, 131, 270-279.
  4. Agarwal, A., Shankar, R. & Tiwari, M.K. (2007). Modeling agility of supply chain. Industrial Marketing Management, 36, 443-57.
  5. Akkermans, H. & Dellaert, N. (2005). The rediscovery of industrial dynamics: the contribution of system dynamics to supply chain management in a dynamic and fragmented world. System Dynamics Review: The Journal of the System Dynamics Society, 21(3), 173-186.
  6. Arif-Uz-Zaman, K. & Nazmul Ahsan, A.M.M. (2014). Lean supply chain performance measurement. International Journal of Productivity and Performance Management, 63(5), 588-612.
  7. Azevedo, S.G., Carvalho, H. & Cruz-Machado, V. (2016). LARG index: A benchmarking tool for improving the leanness, agility, resilience and greenness of the automotive supply chain. Benchmarking: An International Journal, 23(6), 1472-1499.
  8. Azevedo, S.G., Carvalho, H. & Machado, V.C. (2011). The influence of green practices on supply chain performance: a case study approach. Transportation research part E: logistics and transportation review, 47(6), 850-871.
  9. Azevedo, S.G., Carvalho, H., Duarte, S. & Cruz-Machado, V. (2012a). Influence of green and lean upstream supply chain management practices on business sustainability. IEEE Transactions on Engineering Management, 59(4), 753-765.
  10. Azevedo, S.G., Machado, V.H., Barroso, A.P. & Cruz-Machado, V. (2008). Supply chain vulnerability: environment changes and dependencies. International Journal of Logistics and Transport, 2, 41-55.
  11. Barnabè, F. (2011). A “system dynamics‐based Balanced Scorecard” to support strategic decision making.International Journal of Productivity and Performance Management, 60(5), 446-473.
  12. Bargshady, G., Chegeni, A., Kamranvand, S. & Zahraee, S.M. (2016). A relational study of supply chain agility and firms’ performance in the services providers. International Review of Management and Marketing, 6(4S), 38-42.
  13. Cabral, I., Grilo, A. & Cruz-Machado, V. (2012). A decision-making model for lean, agile, resilient and green supply chain management. International Journal of Production Research, 50(17), 4830-4845.
  14. Campuzano, F. and Mula, J., 2011. Supply chain simulation: A system dynamics approach for improving performance. Springer Science & Business Media.
  15. Capelo, C. & Dias, J.F. (2009). A system dynamics‐based simulation experiment for testing mental model and performance effects of using the balanced scorecard.System Dynamics Review: The Journal of the System Dynamics Society, 25(1), 1-34.
  16. Carter, C.R. & Rogers, D.S. (2008). A framework of sustainable supply chain management: moving toward new theory. International journal of physical distribution & logistics management, 38(5), 360-387.
  17. Carvalho, H., Azevedo, S.G. & Cruz-Machado, V. (2013). An innovative agile and resilient index for the automotive supply chain. International Journal of Agile Systems and Management, 6(3), 259-283.
  18. Carvalho, H., Azevedo, S.G. & Cruz-Machado, V. (2010). Supply chain performance management: lean and green paradigms. International Journal of Business Performance and Supply Chain Modelling, 2(3-4), 304-333.
  19. Carvalho, H., Duarte, S. & Cruz Machado, V. (2011). Lean, agile, resilient and green: divergencies and synergies. International Journal of Lean Six Sigma, 2(2), 151-179.
  20. Carvalho, H., Govindan, K., Azevedo, S.G. & Cruz-Machado, V. (2017). Modelling green and lean supply chains: An eco-efficiency perspective. Resources, Conservation and Recycling, 120, 75-87.
  21. Chavez, R., Gimenez, C., Fynes, B., Wiengarten, F. & Yu, W. (2013). Internal lean practices and operational performance: The contingency perspective of industry clockspeed. International Journal of Operations & Production Management, 33(5), 562-588.
  22. Chen, F., Drezner, Z., Ryan, J.K. & Simchi-Levi, D. (2000). Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management science, 46(3), 436-443.
  23. Christopher, M. & Towill, D.R. (2000). Supply chain migration from lean and functional to agile and customized. Supply Chain Management: An International Journal, 5(4), 206-13.
  24. Cox, A., & Chicksand, D. (2005). The limits of lean management thinking: multiple retailers and food and farming supply chains. European Management Journal, 23(6), 648-62.
  25. do Rosário Cabrita, M., Duarte, S., Carvalho, H. & Cruz-Machado, V. (2016). Integration of Lean, Agile, Resilient and Green Paradigms in a Business Model Perspective: Theoretical Foundations. IFAC-PapersOnLine, 49(12), 1306-1311.
  26. Dües, C.M., Tan, K.H. & Lim, M. (2013). Green as the new Lean: how to use Lean practices as a catalyst to greening your supply chain. Journal of cleaner production, 40, 93-100.
  27. Eckstein, D., Goellner, M., Blome, C. & Henke, M. (2015). The performance impact of supply chain agility and supply chain adaptability: the moderating effect of product complexity. International Journal of Production Research, 53(10), 3028-3046.
  28. Faghih, N., Ranaei Kordshooli, H., Mohammadi, A., Samadi, A. H., Moosavi Haghighi, M. H., & Ghafournian, M. (2013). Assessment of Services Supply Chain of Iran Fixed Communications by SystemDynamics Approach. Journal of Industrial Management Perspective, 3(3), 111-137. (In Persian)
  29. Frazzon, E.M., Albrecht, A., Pires, M., Israel, E., Kück, M. & Freitag, M. (2017). Hybrid approach for the integrated scheduling of production and transport processes along supply chains. International Journal of Production Research, 56(5), 2019-2035.
  30. Gottberg, A., Morris, J., Pollard, S., Mark-Herbert, C. & Cook, M. (2006). Producer responsibility, waste minimisation and the WEEE directive: case studies in eco-design from the European lighting sector. Science of the Total Environment, 359, 38-56.
  31. Haimes, Y.Y. (2006). On the definition of vulnerabilities in measuring risks to infrastructures. Risk Analysis, 26(2), 293-296.
  32. Hallgren, M. & Olhager, J. (2009). Lean and agile manufacturing: external and internal drivers and performance outcomes. International Journal of Operations & Production Management, 29(10), 976-999.
  33. Hu, B., Leopold-Wildburger, U. & Strohhecker, J. (2017). Strategy map concepts in a balanced scorecard cockpit improve performance. European Journal of Operational Research, 258(2), 664-676.
  34. Izadyar, M., Toloie Eshlaghy, A., & Mehri, Z. (2021). Developing a Model for Sustainability Assessment in LARG Supply Chains using System‎ Dynamics‎‎‎. International Journal of Industrial Mathematics, 13(2), 181-198.
  35. Izadyar, M., Toloie-Eshlaghy, A., & Seyed Hosseini, S. M. (2020). A Model of Sustainability Performance Assessment of LARG Supply Chain Management Practices in Automotive Supply Chain Using System Dynamics. Industrial Management Journal, 12(1), 111-142.
  36. Kaplan, R.S. and Norton, D.P. (2004) Strategy Maps, Harvard Business School Press, Boston.
  37. Khakbaz, S.B. & Hajiheydari, N. (2015). Proposing a basic methodology for developing balanced scorecard by system dynamics approach. Kybernetes, 44(6/7), 1049-1066.
  38. Lambert, D.M., Cooper, M.C. & Pagh, J.D. (1998). Supply chain management: implementation issues and research opportunities. The international journal of logistics management, 9(2), 1-20.
  39. Langroodi, R.R.P. & Amiri, M. (2016). A system dynamics modeling approach for a multi-level, multi-product, multi-region supply chain under demand uncertainty. Expert Systems with Applications, 51, 231-244.
  40. Li, Y., & Zobel, C. W. (2020). Exploring supply chain network resilience in the presence of the ripple effect. International Journal of Production Economics, 228, 107693.
  41. Lin, C.T., Chiu, H. & Tseng, Y.H. (2006). Agility evaluation using fuzzy logic. International Journal of Production Economics, 101(2), 353-368.
  42. Manzouri, M., Nizam Ab Rahman, M., Saibani, N. & Rosmawati Che Mohd Zain, C., 2013. Lean supply chain practices in the Halal food. International Journal of Lean Six Sigma, 4(4), 389-408.
  43. Melton, T. (2005). The benefits of lean manufacturing what lean thinking has to offer the process industries”, Chemical Engineering Research and Design, 83(A6), 662-73.
  44. Mendoza, Juan D., Mula, J., & Campuzano-Bolarin, F. (2014). Using systems dynamics to evaluate the tradeoff among supply chain aggregate production planning policies. International Journal of Operations & Production Management, 34(8), 1055-1079.
  45. Moosavi Haghighi, M. H., Ranaei Kordshooli, H., & Ghafournian, M. (2013). The Analysis of Iran Cell Phone Market by Using System Dynamics Approach. Journal of Industrial Management Perspective, 3(1), 135-158. (In Persian)
  46. Nazari-Ghanbarloo, V. (2020). A dynamic performance measurement system for supply chain management. International Journal of Productivity and Performance Management. Vol. ahead-of-printNo. ahead-of-print. Https://doi.org/10.1108/IJPPM-01-2020-0023
  47. Nielsen, E.H. & Nielsen, S. (2018). System Dynamics Modeling, its concept of causality and particular relevance for providing the Balanced Scorecard thinking with a dynamic analytical framework. Working paper, Institut for Økonomi, Aarhus Universitet.
  48. Nielsen, E.H., Nielsen, S., Jacobsen, A. & Pedersen, L.B. (2014). Management Accounting and Business Analytics: An example of System Dynamics Modelling's use in the design of a Balanced Scorecard. Danish Journal of Management and Business, 78(3 & 4), 31-44.
  49. Nielsen, S. & Nielsen, E.H. (2012). Discussing feedback system thinking in relation to scenario evaluation in a balanced scorecard setup. Production Planning & Control, 23(6), 436-451.
  50. Nielsen, S. & Nielsen, E.H. (2013). Transcribing the balanced scorecard into system dynamics: from idea to design. International Journal of Business and Systems Research, 7(1), 25-50.
  51. Paulraj, A. (2009). Environmental motivations: a classification scheme and its impact on environmental strategies and practices. Business Strategy and the Environment, 18(7), 453-468.
  52. Peck, H. (2005). Drivers of supply chain vulnerability: an integrated framework. International Journal of Physical Distribution & Logistics Management, 35(4), 210-32.
  53. Prasanna, M. & Vinodh, S., 2013. Lean Six Sigma in SMEs: an exploration through literature review. Journal of Engineering, Design and Technology, 11(3), 224-250.
  54. Rao, P. & Holt, D. (2005). Do green supply chains lead to competitiveness and economic performance? International journal of operations & production management, 25(9), 898-916.
  55. Reichhart, A., & Holweg, M. (2007). Lean distribution: concepts, contributions, conflict.International Journal of Production Research, 45(16), 3699-722.
  56. Reiner, G. (2005). Customer-oriented improvement and evaluation of supply chain processes supported by simulation models. International journal of production economics, 96(3), 381-395.
  57. Reis, L.V., Kipper, L.M., Velásquez, F.D.G., Hofmann, N., Frozza, R., Ocampo, S.A. & Hernandez, C.A.T. (2018). A model for Lean and Green integration and monitoring for the coffee sector. Computers and Electronics in Agriculture, 150, 62-73.
  58. Ren, C., Dong, J., Ding, H. & Wang, W. (2006). December. Linking strategic objectives to operations: towards a more effective supply chain decision making. In Proceedings of the 38th conference on Winter simulation(1422-1430). Winter Simulation Conference.
  59. Rice, B.F. & Caniato, F. (2003). Building a secure and resilient supply network. Supply Chain Management Review, 7, 22-30.
  60. Ruiz-Benitez, R., López, C. & Real, J.C. (2017). Environmental benefits of lean, green and resilient supply chain management: The case of the aerospace sector. Journal of Cleaner Production, 167, 850-862.
  61. Rydzak, F., Magnuszewski, P., Pietruszewski, P., Sendzimir, J. & Chlebus, E. (2004). July. Teaching the dynamic balanced scorecard. In Proceedings of the 22nd International Conference of the System Dynamics Society.
  62. Sahu, A.K., Datta, S. & Mahapatra, S.S. (2017). Evaluation of performance index in resilient supply chain: a fuzzy-based approach. Benchmarking: An International Journal, 24(1), 118-142.
  63. Sangari, M.S. & Razmi, J. (2015). Business intelligence competence, agile capabilities, and agile performance in supply chain: An empirical study. The International Journal of Logistics Management, 26(2), 356-380.
  64. Sayyadi, Tooranloo, H., Saghafi, S. & Alavi, M. (2018). Evaluating indicators of the agility of the green supply chain. Competitiveness Review: An International Business Journal, (just-accepted), pp.00-00.
  65. Senge, P. (1990). The art and practice of the learning organization. The new paradigm in business: Emerging strategies for leadership and organizational change, 126-138.
  66. Shah, R. & Ward, P.T. (2003). Lean manufacturing: context, practice bundles, and performance. Journal of operations management, 21(2), 129-149.
  67. Sharma, V., Raut, R. D., Mangla, S. K., Narkhede, B. E., Luthra, S., & Gokhale, R. (2021). A systematic literature review to integrate lean, agile, resilient, green and sustainable paradigms in the supply chain management. Business Strategy and the Environment, 30(2), 1191-1212.
  68. Singh, A.K. & Vinodh, S. (2017). Modeling and performance evaluation of agility coupled with sustainability for business planning. Journal of Management Development, 36(1), 109-128.
  69. Soltanian Telkabadi, H., Mohaghar, A., & Sadeghi Moghadam, M. R. (2016). Pricing-Policy Analysis of Petrochemical Feed-Stock through Dynamic Systems Approach. Journal of Industrial Management Perspective, 5(4), 59-78. (In Persian)
  70. Srivastava, S.K. (2007). Green supply-chain management: a state-of the-art literature review. International Journal of Management Reviews, 9(1), 53-80.
  71. Sterman, J.D. (2000). Business dynamics: systems thinking and modeling for a complex world(No. HD30. 2 S7835 2000).
  72. Tang, C.S. (2006). Robust strategies for mitigating supply chain disruptions. International Journal of Logistics: Research and Applications, 9(1), 33-45.
  73. Thanki, S. & Thakkar, J. (2018). A quantitative framework for lean and green assessment of supply chain performance. International Journal of Productivity and Performance Management, 67(2), 366-400.
  74. Towill, D.R. (1996). Industrial dynamics modelling of supply chains. International Journal of Physical distribution & logistics management, 26(2), 23-42.
  75. Tseng, Y.H. & Lin, C.T. (2011). Enhancing enterprise agility by deploying agile drivers, capabilities and providers. Information Sciences, 181(17), 3693-3708.
  76. Ugarte, G.M., Golden, J.S. & Dooley, K.J. (2016). Lean versus green: The impact of lean logistics on greenhouse gas emissions in consumer goods supply chains. Journal of Purchasing and Supply Management, 22(2), 98-109.
  77. Wittstruck, D., & Teuteberg, F. (2011). Development and Simulation of a Balanced Scorecard for Sustainable Supply Chain Management – A System Dynamics Approach. Wirtschaftinformatik Proceedings. Paper 86.
  78. Womack, J., Jones, D. & Roos, D. (1991). The Machine that Change the World. HarperCollins, New York, NY.
  79. Yaakub, S. & Mustafa, H.K. (2015). Supply chain risk management for the SME’s. Academic Journal of Interdisciplinary Studies, 4(1 S2), 151-158.
  80. Ying, Y. (2010). December. Modeling and simulation of operational decisions in manufacturing enterprises based on SD and BSC. In Industrial Engineering and Engineering Management (IEEM), 2010 IEEE International Conference on (pp. 1880-1884). IEEE.
  81. Zhu, Q., Sarkis, J. & Lai, K. (2008). Confirmation of a measurement model for green supply chain management practices implementation. International Journal of Production Economics, 111, 261-73.

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