بهینه‌سازی جریانات فیزیکی و مالی زنجیره‌های تأمین با استفاده از شبیه‌سازی مبتنی بر عامل

نوع مقاله : مقاله پژوهشی

نویسندگان

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

2 استاد، گروه مهندسی صنایع، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران.

3 دانشیار، گروه مدیریت صنعتی، دانشکده مدیریت، دانشگاه آزاد اسلامی، واحد تهران مرکزی، تهران، ایران.

چکیده

در پژوهش حاضر، جریانات موجودی و مالی در زنجیره‌های تأمین بررسی می‌­شود. هدف این پژوهش، ارائه روشی برای بهینه‌سازی این دو جریان در زنجیره‌ها است. درصد بازگشت سرمایه به‌عنوان متغیر وابسته و سه جزء تشکیل‌دهنده چرخه تبدیل نقدینگی که نمایانگر جریانات مالی و فیزیکی به­‌شمار می‌روند، به‌عنوان متغیرهای مستقل هستند. داده‌های اعضای زنجیره شش صنعت شامل خودرو و قطعات، دارو، غذایی، پتروشیمی، فلزی و معدنی استخراج و با دو سناریوی «بازنگری در روزهای متغیرهای وابسته بدون تغییر در چرخه تبدیل نقدینگی در کل زنجیره» و «کاهش در روزهای متغیرهای وابسته به همراه کاهش در چرخه تبدیل نقدینگی» صورت‌مسئله پژوهش تعریف‌ شده و با استفاده از مدل‌سازی مبتنی بر عامل و نرم‌افزار نت لگو شبیه‌سازی شده است. بر اساس نتایج سناریوی اول درصورتی‌که روزهای نگهداری موجودی در پایین‌دست زنجیره کاهش و به بالادست زنجیره انتقال یابد و در مقابل دوره پرداخت به بالادست کوتاه‌تر شود، دوره بازگشت سرمایه برای کل زنجیره بهبود می­یابد؛ همچنین بر اساس نتایج سناریوی دوم، به نسبت میزان کاهش چرخه تبدیل نقدینگی از طریق بهره­‌وری در سایه همکاری اعضای زنجیره، بهبود عملکرد شاخص بازگشت سرمایه قابل‌ملاحظه است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Optimizing Physical and Financial Flows of Supply Chains Using Agent-Based Simulation

نویسندگان [English]

  • Reza Zavarikia 1
  • Ahmad Makui 2
  • Mohammad Ali Keramati 3
1 Ph.D Candidate, Department of Industrial Management, Faculty of Management and Economics, Science & Research Branch, Islamic Azad University, Tehran, Iran.
2 Professor, Department of Industrial Engineering, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
3 Associate Professor Department of Industrial Management, Faculty of Management, Islamic Azad University, Tehran Central Branch, Tehran, Iran.
چکیده [English]

This paper has investigated the inventory and financial flows in supply chains. Its purpose is to provide a method to optimize these two flows for chain members, where Return on Capital (ROC) is defined as the dependent variable, and cash conversion cycle (CCC) equation components, which show financial and physical flows, are formulated as independent variables. The data of chain members from six selected industries, including auto & parts, pharmacy, food, petrochemical, metal, and mining, have been extracted. Two scenarios, 1) revision of independent variables without a change in the cash conversion cycle of the entire supply chain, and 2) reducing the days of independent variables along with reducing the cash conversion cycle, have been defined. The problem is simulated using Agent-Based Modeling and NetLego software. Results of the first scenario indicate that if Days Inventory Outstanding (DIO) is reduced in downstream and transferred to upstream of the chain, and Days Payment Outstanding (DPO) in the upstream is shortened, ROC is improved for the entire chain. Also, the results of the second scenario show that, in proportion to the reduction of the cash conversion cycle through productivity under collaboration of chain members, the performance improvement of ROC is remarkable.

کلیدواژه‌ها [English]

  • Supply Chian
  • Physical Flow
  • Financial Flow
  • Optimizing
  • Agent Based Simulation

مراجع

  1. Badakhshan, E., Ball P&. Badakhshan A. (2022). Using Digital Twins for Inventory and Cash management in supply chains. IFAC PapersOnline, 55-10, 1980-1985
  2. Brandenburg, M. (2015). Supply Chain, Value Creation and the Economic Crisis-An empirical assessment of the European Automotive Industry (2002-2010). International Journal of Production Economics, 171, 321-335.
  3. Blackman, I., Holland, C., & Wescott, T. (2014). Motorola’s Global Financial Supply Chain Strategy. Supply Chain Management: An International Journal, 18(2), 132-147.
  4. Caniato, F., Henke, M., & Zsidisin, G.A. (2019). Supply chain Fiance: Historical Foundation, Current Research, Future Development. Purchasing and Supply Management, 19, 1-20
  5. Cullen, J. (2021). Supply Chain Accounting, Canada. Society of Management Accountants of Canada.
  6. Farahbakhsh, M., Modiri, M., Firozabadi, S.M. &Ebrahimi, A.P. (2023). Power Industry’s Life Cycle Simulation Using Agent Based Modeling. The Journal of Industrial Management Perspective, 12(48), 9-35 (In Persion).
  7. Farris, M. T., & Hutchison, P.D. (2003). Measuring Cash-to-Cash Performance. International Journal of Logistics Management, 14(2), 83–92.
  8. Farris, M.T., & Randall, W. (2009). Supply Chain Financing: Using Cash-to-Cash Variables to Strengthen the Supply Chain. International Journal of Physical Distribution & Logistics Management, 39(8), 669-689.
  9. Rahchomai, S.M., Hydariyeh, S., & Zargar, S.M. (2022).Deigning a Model for Intelligent Service Supply Chain Based on Grounded Theory .Case Study: Omid Enterpreneurship Fund. The Journal of Industrial Management Perspective, 12(46), 89-111. (In Persion).
  10. Rokneddini, S.A., Ardakani, D.A., & Ahmadabadi, H.Z. (2023). Modeling The Enablers of Industry 4.0in the implementation of a Sustainable Supply Chain with Fuzzy Dematel-ANP. The Journal of Industrial Management Perspective, 13(49), 141-172. (In Persion)
  11. Rosse, T., Ruyken, S., Wagner, M. & Jokem, R. (2011). What is the right Cash Conversion Cycle for Your Supply Chain. J.Services and operations Management, 10(1(, 13-29.
  12. Grimm, C., Knemeyer, M., Polyviou, M. & Ren, X. (2015). Supply Chain Research in management Journals. A review of recent Literatur (2004-2013). International Journal of Physical Distribution &Logistics Management, 45(5), 404-458.
  13. Hofmann, E. & Kotzab, H. (2010). A Supply Chain-Oriented Approach of Working Capital Management. Journal of Business Logistics, 31(2), 305-329
  14. Iraine, P. & Pontiff, J. (2009). Idiosyncratic Return Volatility, Cash Flows, and product Market Competitions. The Review of Financial Studies, 22(3), 1149-1177.
  15. Jin, J., Wei, Z., & Liu, G. (2015). Comparative Research of Financial Model in Supply Chain. Switzerland Springer International Publishing.
  16. Lind, L. (2019). Mapping Working Capital Models in the Automotive Industry. published by Elsevier, 1-20.
  17. Lind, L. (2018). Identifying Working Capital Models In Value Chains:Toward Ageneric Framework, PhD, LUT University, Lappeenranta.
  18. Lind,L.,Pirttila,M.,Viskari,S.,Schupp,F.&Karri,T. (2012).Working Capital Management in the Automotive Industry:Financial Value Chain Analysis. Journal of Purchasing & Supply Management, 18, 92-100.
  19. Li, Jian., He, Zhou. & Wang Shouyang. (2022). A survey of chain operation and finance with Fintech: Research framework and managerial insights. J.Production Economics, 247, 108131, 1-9.
  20. Luis, S., Lozano, P., & Farzipoor, M. (2016). Watch the working Capital of tier- tow suppliers: a finanacial perspective of supply chain collaboration in the automotive industry. Supply Chain Management: An International Journal, 21, 1-26.
  21. Monto, S., Lind, L., & Karri, T. (2013).Working Capital Models: Avenues for Financial Innovation. ISPIIM Conference On 16-19.
  22. Monto, S. (2013). Towards Inter-organizational WCM. (PhD), Thesis for the degree of Doctor of Science (Technology), Lappeenranta University of Technology, Lappeenranta, Finland.
  23. Moretto, A., Grassi, I., Caniato, F., Giorgino, M., & Ronchi, S. (2018). Supply Chain Finance: From Traditional to Supply Chain Credit Rating. Journal of Purchasing and Supply Management, 24, 1478-4092.
  24. Pfohl, H. Ch., & Gomm, M. (2009). Supply Chain Finance: Optimizing Financial Flows in Supply Chain. Res1, 149-161.
  25. Pirttila, M., Virolainen, V. M., Lind, L., Karri, T. (2019). Working Capital Management in the Russian Automotive Industry Supply Chain. International Journal of Production Economics,221,107474, 1-24.
  26. Richards, V.D., & Laughlin, E.J. (1980). A CCC Approach to Liquidity Analysis. Financial Management, 9(1), 32-38.
  27. Sieke, M.P. &Seifert, R.W. (2017). Benefits of Working Capital Sharing in Supply Chain. Journal of the Operation Research Society, 68, 521-532.
  28. Shi, M., & Yu, W. (2013). Supply Chain Management and Financial Performance: Literature Review and Future Directions. International Journal of Operation & Production Management, 33(10), 1283-1317.
  29. Talonpoika, A., Monto, S., & Pirttilä, M. (2014). Modifying the CCC: Revealing concealed advance payments. International Journal of Productivity and Performance Management, 63(3), 341-353.
  30. Viskari, S., Lind, L., & Karri, T. (2012). Using Working Capital Management to Improve Profitability in the Value Chain of Automotive Industry. J. Services and Operation Management, 13(1), 42-64.
  31. Virolainen, V., Pirttilia, M., Lind, L., T., & Karri, T. (2019). Scenario Development for Collaborative Financial Supply Chain Management. In the Automotive Industry 25th International Conference on Production Research Manufacturing Innovation.
  32. Wuttke, ,Blome,C&Henke,M.(2013). Focusing the Financial Flow of Supply Chains: An Empirical Investigation of Financial Flow of Supply Chain Management. International Journal of Production Economics,145.773-789.
  33. Yan, N& Sun, (2013).Coordinating Loan Strategies for Supply Chain Financing With Limited Credit. OR Spectrum, 35.1039-1058
  34. Zhang, L & Yan, (2009). The Complex Economic System of Supply Chain Financeing, Jzhou (Ed).Complex,Part1,Lnicst4,763-772.
  35. Zenkevich, (2018). Working Capital Optimization in Supply Chain.Journal of Coporate Finance Research,12.29-42.

فایل ها

هم رسانی

ارجاع به این مقاله

آمار