نوع مقاله : مقاله پژوهشی
نویسندگان
1 مدیریت صنعتی - گروه مدیریت سیستم، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
2 مدیریت صنعتی، گروه مدیریت سیستم، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
3 گروه مدیریت صنعتی دانشکده مدیریت دانشگاه تهران
چکیده
هدف: هدف این پژوهش ارائه مدلی دینامیکی برای اندازهگیری عملکرد یک زنجیره تامین لارج با رویکرد کارت امتیازی متوازن میباشد.
روششناسی: در این پژوهش، از شبیهسازی پویا به منظور ارزیابی عملکرد یک زنجیره تامین استفاده شده است. برای این منظور ابتدا یک نقشه استراتژی طراحی شده و برای هر یک از اهداف استراتژیک، شاخصهایی با توجه به زنجیره تامین لارج شناسایی گردید. سپس یک مدل کمی برای تعیین روابط ریاضی بین آنها طراحی شده است.
یافتهها: مدل پیشنهاد شده برای یک شرکت فعال در صنعت قطعهسازی در یک زنجیره دو سطحی به اجرا درآمده است. براساس اهداف استراتژیک شرکت، سناریوهایی جهت بهبود عملکرد تعریف شده و اثر آن بر هریک از عناصر لارج تبیین شده است.
نوآوری: هر یک از عناصر لارج در بعضی از سنجهها دو به دو ناسازگار هستند. طراحی یک مدل ارزیابی عملکرد متوازن این امکان را میدهد تا اثر هر تصمیم استراتژیک و اجرای هریک از رویکردهای لارج را بر عملکرد نهایی شرکت که غالبا در حوزه مالی و مشتری تبلور مییابد مشخص گردد و با این تحلیل و تعریف سناریوهای مختلف بهترین تصمیمات را اتخاذ کرد.
نتیجه گیری: مدل دینامیکی این امکان را به مدیران میدهد تا عوامل موثر بر عملکرد زنجیره تامین را شناسایی کرده و با بررسی سناریوهای محتمل قبل از وقوع، زمینه برای تصمیمگیریهای لازم را فراهم نمایند. پیاده سازی هریک از عناصر لارج میتواند بر عملکرد شرکت تاثیر بگذارد. بسته به اینکه کدام استراتژی از میان چهار گزینه لارج به کارگرفته شود اثر آنها را بر سودآوری شرکت میتوان ارزیابی کرد.
کلیدواژهها
موضوعات
عنوان مقاله [English]
Developing a Balanced Scorecard Model for LARG Supply Chain Evaluation: A Dynamic Approach
نویسندگان [English]
- Mohammad Reza Atefi 1
- Reza Radfar 2
- Ezzatollah Asgharizadeh 3
1 Industerial Management Department, Management and Economy Faculty, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Department of Industrial Management, Science and Research branch, Islamic Azad University, Tehran, Iran.
3 Department of Industrial Management, Faculty of Manangement, University of Tehran
چکیده [English]
Purpose – Organization managers tend to use an optimal and precise method to evaluate the performance of their organization by understanding the organization dynamics. The immediate research goal was to propose a dynamic model for the performance evaluation of a LARG supply chain with the balanced scorecard (BSC) approach.
Design/methodology/approach – In this study, dynamic simulations are carried out for the performance evaluation of a supply chain. At first, a strategy map was designed, and measures are identified for each strategic objective considering the LARG supply chain measures. Afterward, a quantitative dynamic model was designed to identify the mathematical relationships among them.
Findings – The proposed model is implemented in a company operating in the automotive industry. Based on the company’s strategic objectives, scenarios were designed and analyzed to evaluate the performance of the LARG supply chain with the balanced scorecard approach.
Research limitations/implications – The BSC- based LARG supply chain evaluation has been studied for the auto part manufacturer sector. The different industry may lead to different results as the model designed important in each sector may differ as well as how each model is designed.
Originality/value – The dynamic model enables managers to identify the determinants of the supply chain performance and set the scene for the necessary decisions by analyzing the possible scenarios in advance.
کلیدواژهها [English]
- System dynamics
- LARG supply chain
- Balanced scorecard
- Performance evaluation
management. International Journal of Production Research, 50(17), pp.4830-4845. Campuzano, F., & Mula, J. (2011). Supply chain simulation: A system dynamics approach for improving performance. Springer Science & Business Media. 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.
Carvalho, H., Azevedo, S.G. and Cruz-Machado, V. (2013), “An innovative agile and resilient index for the automotive supply chain”, International Journal of Agile Systems and Management, Vol. 6 No. 3, pp. 259-283. 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. Carvalho, H., Duarte, S. and Cruz Machado, V., (2011). Lean, agile, resilient and green: divergencies and synergies. International Journal of Lean Six Sigma, 2(2), pp.151-179. 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. 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. El-Garaihy, W. H. (2021). Analysis of supply chain operations reference (SCOR) and balanced scorecard (BSC) in measuring supply chains efficiency using DEMATEL and DEA techniques. Journal of Global Operations and Strategic Sourcing, Vol. 14 No. 4, pp. 680-700. Elzarka, S. (2020). A study on using lean, agile, resilient and green index to assess the sustainability of Egyptian FMCGs supply chains. International Journal of Logistics Systems and Management, 37(2), 285-298. Foxon, F. (2021). Evaluating modern system dynamics software for use in astrophysical simulations. Astronomy and Computing, 36, 100486. 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.
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. Ka, Jagan Mohan Reddy, Neelakanteswara Rao Ab, and Krishnanand Lb. (2019). A review on supply chain performance measurement systems. Procedia Manufacturing, 30, 40-47. Katsaliaki, K., Galetsi, P., & Kumar, S. (2021). Supply chain disruptions and resilience: a major review and future research agenda. Annals of Operations Research, 1-38.
Kaplan, R.S. and Norton, D.P. (1992) ‘The balanced scorecard – measures that drive performance’,
Kaplan, R.S. and Norton, D.P. (2004) Strategy Maps, Harvard Business School Press, Boston, Kaplan, R.S. and Norton, D.P. (1996) “The balanced scorecard: translating strategy into action. Harvard Business Press. Espejo, R., Khakbaz, S. B., & Hajiheydari, N. (2015). Proposing a basic methodology for developing balanced scorecard by system dynamics approach. Kybernetes, Vol. 44 No. 6/7, pp. 1049-1066. 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. Mendoza, J. 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, Vol. 34 No. 8, pp. 1055-1079. Mittal, V. K., Sindhwani, R., Kalsariya, V., Salroo, F., Sangwan, K. S., & Singh, P. L. (2017). Adoption of integrated lean-green-agile strategies for modern manufacturing systems. Procedia Cirp, 61, 463-468. Mohammadzadeh, M., Sobhanallahi, M., & Khamseh, A. A. (2020). Closed loop supply chain mathematical modeling considering lean agile resilient and green strategies. Croatian Operational Research Review, 11(2), 177-197. Moubed, M., Boroumandzad, Y., & Nadizadeh, A. (2021). A dynamic model for deteriorating products in a closed-loop supply chain. Simulation Modelling Practice and Theory, 108, 102269. Mutanov, G., Ziyadin, S., & Serikbekuly, A. (2020). Application of System-Dynamic Modeling to Improve Distribution Logistics Processes in the Supply Chain. Communications-Scientific letters of the University of Zilina, 22(3), 29-39.
Nadimi, N., & Eshlaghi, A. T. (2021). Hybrid of System Dynamics-Agent Based Analysis of Mobile Operators Revenue The Case: Digital Service Entry of MCCI Company. Journal of Industrial Management Studies, 19(60), 51-84. (In Persian) Nielsen, E.H., Nielsen, S., Jacobsen, A. and 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), pp.31-44. Nielsen, S. and Nielsen, E.H. (2008). System Dynamic Modelling for a Balanced Scorecard: With a Special Emphasis on Skills, Customer Base, and WIP. Management Research News, Vol. 31, No. 3, April, pp. 169-188 Nielsen, S. and Nielsen, E.H. (2012). Discussing feedback system thinking in relation to scenario evaluation in a balanced scorecard setup. Production Planning & Control, 23(6), pp.436-451. Nielsen, S. and Nielsen, E.H. (2013). Transcribing the balanced scorecard into system dynamics: from idea to design. International Journal of Business and Systems Research, 7(1), pp.25-50. Özbayrak, M., Papadopoulou, T. C., & Akgun, M. (2007). Systems dynamics modelling of a manufacturing supply chain system. Simulation Modelling Practice and Theory, 15(10), 1338-1355. 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. Raut, R. D., Mangla, S. K., Narwane, V. S., Dora, M., & Liu, M. (2021). Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains. Transportation Research Part E: Logistics and Transportation Review, 145, 102170. Rebs, T., Brandenburg, M., & Seuring, S. (2019). System dynamics modeling for sustainable supply chain management: A literature review and systems thinking approach. Journal of cleaner production, 208, 1265-1280. Reddy, K. J. M., Rao, A. N., & Krishnanand, L. (2019). A Survey on Application of a System Dynamic Approach in Supply Chain Performance Modeling. Mechanical Engineering for Sustainable Development, 283-295. 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.
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 2006 Winter Simulation Conference (pp. 1422-1430). IEEE. 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. Sangari, M.S. and 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), pp.356-380. 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. Singh, A.K. and Vinodh, S. (2017). Modeling and performance evaluation of agility coupled with sustainability for business planning. Journal of Management Development, 36(1), pp.109-128. Sterman, John D. (2000). Business Dynamics: Systems Thinking and Modelling for a Complex World. McGraw-Hill Higher Education ed. New York, USA. Suifan, T., Alazab, M., & Alhyari, S. (2019). Trade-off among lean, agile, resilient and green paradigms: an empirical study on pharmaceutical industry in Jordan using a TOPSIS-entropy method. International Journal of Advanced Operations Management, 11(1-2), 69-101. Supino, E., Barnabè, F., Giorgino, M. C., & Busco, C. (2019). Strategic scenario analysis combining dynamic balanced scorecards and statistics. International Journal of Productivity and Performance Management, 69(9), 1881-1902. Sayyadi Tooranloo, H., Alavi, M., & Saghafi, S. (2018). Evaluating indicators of the agility of the green supply chain. Competitiveness Review: An International Business Journal incorporating Journal of Global Competitiveness, 28(5), 541-563. Udokporo, C. K., Anosike, A., Lim, M., Nadeem, S. P., Garza-Reyes, J. A., & Ogbuka, C. P. (2020). Impact of Lean, Agile and Green (LAG) on business competitiveness: An empirical study of fast moving consumer goods businesses. Resources, Conservation and Recycling, 156, 104714. 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 (pp. 1880-1884). IEEE. Zandieh, M., Shariat, S. Y., & Tootooni, M. (2020). A new framework for dynamic sustainability balanced scorecard in order to strategic decision making in a turbulent environment. Journal of Industrial and Systems Engineering, 12(4), 107-135.