راهبرد‌های اثر شلاقی در زنجیره‌های تأمین حلقه بسته

نوع مقاله : پژوهشی

نویسندگان

1 مسئول پژوهش و فناوری دانشگاه جامع علمی کاربردی یزد

2 دانشجوی دکتری رشته مدیریت صنعتی، دانشکده اقتصاد، مدیریت و حسابداری، دانشگاه یزد، آدرس پستی: یزد-صفائیه- دانشگاه یزد- دانشکده اقتصاد،

3 کارشناس ارشد رشته مدیریت صنعتی، دانشکده مدیریت، اقتصاد و حسابداری، دانشگاه شهید اشرفی اصفهانی،

چکیده

توجه همزمان به زنجیره‌های تأمین رو به جلو و رو به عقب باعث ایجاد مفهومی جدید در ادبیات زنجیره تأمین به عنوان زنجیره‌های تأمین حلقه بسته شده است. یکی از عواملی که می‌تواند منجر به اختلال در روند حرکتی زنجیره‌های تأمین و کاهش سطح سودآوری و عملکرد سازمان‌‌ها گردد، اثر شلاقی است. هدف از این پژوهش طراحی مدل مفهومی استراتژی‌های اثرگذار بر کاهش اثر شلاقی در زنجیره تأمین حلقه بسته است. این پژوهش از لحاظ هدف کاربردی و از جنبه نوع و نحوه گردآوری داده‌ها توصیفی- پیمایشی است. جامعه آماری پژوهش را 75 تن از خبرگان صنعتی و دانشگاهی حوزه تولیدات روغن خودرو در کشور تشکیل داده‌اند. در این پژوهش با مطالعه پیشینه پژوهش، 8 استراتژی اثرگذار بر کاهش اثر شلاقی در زنجیره تأمین حلقه بسته شناسایی و با جمع‌بندی نظرات 5 تن از خبرگان دانشگاهی تعدیل یافت. ابزار مورد استفاده در این پژوهش را پرسشنامه مقایسات زوجی حاوی 8 استراتژی شناسایی شده تشکیل داده است. در ادامه با استفاده از تکنیک مدل‌سازی ساختاری تفسیری، 8 استراتژی بدست آمده در 5 سطح کلی ساختاربندی گردید. یافته‌های پژوهش حاکی از قرارگیری استراتژی‌های "ایجاد سیاست‌های بررسی دوره‌ای کنترل موجودی و برنامه‌ریزی تولید" و " در دسترس بودن اطلاعات در مورد پارامترهای محصولات بازیافتی" در سطح آغازین مدل است. همچنین یافته‌های پژوهش نشان از قرارگیری استراتژی‌های "افزایش دید در روند بازیابی محصولات در فرآیند زنجیره تأمین رو به عقب با استفاده از سیاست تبادل محصول با مشتری" و "کاهش زمان تحویل محصول" در سطح پایانی مدل دارد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Model of bullwhip effect strategies in closed loop supply chains

نویسندگان [English]

  • Ali Saffari Darberazi 1
  • Pooria Malekinejad 2
  • Mehran Ziaeian 3
1 Head of Research and Technology, Yazd University of Applied Science and Technology
2 PhD student in Industrial Management, Faculty of Economics, Management and Accounting, Yazd University
3 Master of Industrial Management, Faculty of Management, Economics and Accounting, Shahid Ashrafi University of Isfahan
چکیده [English]

Aim and introduction: Simultaneous attention to forward and backward supply chains has created a new concept in the supply chain literature as closed-loop supply chains. The use of closed-loop supply chains leads to profitability and improved organizational performance, which can help reduce the environmental damage caused by the activities of organizations. One of the factors that can lead to disruption in the movement of supply chains and reduce the level of profitability and performance of organizations is the bullwhip effect. This phenomenon can cause irreparable damage to the supply chain structure and cause problems with the efficiency and effectiveness of a supply chain. The automobile oil production industry in the country has been able to meet the needs of a large number of customers in this field due to various international sanctions. But changes in customer behavior can lead to a bullwhip effect in the supply chain of the industry and the companies involved. The purpose of this study is to design a conceptual model of effective strategies to reduce the bullwhip effect in the closed-loop supply chains in the country's automobile oil industry so that it can provide the ability to deal with bullwhip effects in the supply chain while responding appropriately to environmental requirements.
Methodology: This research is descriptive in terms of applied purpose and in terms of type and method of data collection and has been done in a survey. The statistical population of the study consists of 75 industrial and academic experts in the field of automobile oil production in the country. Among these experts, 9 academic experts and 66 industrial experts answered the questions. In this study, by studying the research background, 8 effective strategies on reducing the bullwhip effect in the closed-loop supply chain were identified and adjusted by summarizing the opinions of 5 academic experts. The instrument used in this study is a pairwise comparison questionnaire containing 8 identified strategies. Then, using interpretive structural modeling technique, 8 obtained strategies were leveled. Then, using Mick Mac analysis, a structural analysis of the dimensions and type of behavior of each strategy was performed according to the opinions of experts.
Finding: Findings indicate the identification of 8 strategies to reduce the bullwhip effect in the supply chain. These strategies include "strategies to reduce the bullwhip effect in the closed loop supply chain", "application of control and monitoring strategies and coordination of nodes in the closed loop supply chain", "reduction of product delivery time", "creation of inventory control process using From order setting and information sharing "," Creating a new compensation policy, providing a seamless ordering model for inventory and production planning "," Creating policies for reviewing inventory control periods and production planning "," Providing forecasting algorithm to adjust The variables of order and production control are "availability of information about the parameters of recycled products" and "increasing visibility in the process of product recovery in the process of supply chain reversal using the product exchange policy with the customer". Among these strategies, two strategies are updated at the initial level of their model. The strategies of "creating policies to review inventory control periods and production planning" and "availability of information on recycled product parameters" are at the initial level of the model. The research findings also indicate the strategies of "increasing visibility in the process of product recovery in the process of backward supply chain using product exchange policy with the customer" and "reducing product delivery time" at the final level of the model. These findings indicate that if the strategic conditions in the automobile oil production environment are improved, the bullwhip effect in the closed-loop supply chain can be properly addressed and reduced. Other findings of the research in the Mick Mac analysis section show that the strategies identified in this study are divided into three parts: dependent region, transplanted region and independent region.
Discussion and conclusion: The placement of the strategy "Availability of information on the parameters of recycled products" at the initial level of the model shows that one of the requirements in order to deal with the bullwhip effect within the supply chain is to provide information related to this area. Another appropriate classification of this information can improve the use of information. In this regard, managers working in the automobile oil production sector of the country are advised to use a suitable structure to classify and improve the situation in the field of information and its maintenance. On the other hand, placing the strategy of "creating policies for reviewing inventory control periods and production planning" at the initial level of the model shows that addressing inventory control policies for a period can be a good ground to reduce the bullwhip effect in a Provide supply chain structure. Therefore, in this section, it is recommended to the managers of the automobile oil industry in Iran to continuously monitor the necessary requirements for inventory by creating an instantaneous platform in control.

کلیدواژه‌ها [English]

  • Closed-loop supply chain
  • Strategy
  • bullwhip effect
  • Automotive oil industry
  1. Adenso-Díaz, B., Moreno, P., Gutiérrez, E., & Lozano, S. (2012). An analysis of the main factors affecting bullwhip in reverse supply chains. International Journal of Production Economics, 135(2), 917–928.
  2. Braz, A. C., De Mello, A. M., de Vasconcelos Gomes, L. A., & de Souza Nascimento, P. T. (2018). The bullwhip effect in closed-loop supply chains: A systematic literature review. Journal of Cleaner Production, 202, 376–389.
  3. Cannella, S., Bruccoleri, M., & Framinan, J. M. (2016). Closed-loop supply chains: What reverse logistics factors influence performance? International Journal of Production Economics, 175, 35–49.
  4. 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.
  5. Chen, L., & Lee, H. L. (2017). Modeling and measuring the bullwhip effect. In Handbook of Information Exchange in Supply Chain Management (pp. 3–25). Springer.
  6. Das, D., & Dutta, P. (2016). Performance analysis of a closed-loop supply chain with incentive-dependent demand and return. The International Journal of Advanced Manufacturing Technology, 86(1–4), 621–639.
  7. Dev, N. K., Shankar, R., & Choudhary, A. (2017). Strategic design for inventory and production planning in closed-loop hybrid systems. International Journal of Production Economics, 183, 345–353.
  8. Forrester, J. W. (1961). Industrial Dynamics. MITPress. Cambridge, MA.

 

  1. Govindan, K., Soleimani, H., & Kannan, D. (2015). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operational Research, 240(3), 603–626.
  2. Green, K., Morton, B., & New, S. (1996). Purchasing and environmental management: interactions, policies and opportunities. Business Strategy and the Environment, 5(3), 188–197.
  3. Guide, V. D. R., Harrison, T. P., & Van Wassenhove, L. N. (2003). The challenge of closed-loop supply chains. Interfaces, 33(6), 3–6.
  4. Guo, H. (2017). Model predictive control algorithm of closed-loop supply chain networks dynamic system and its bullwhip effect. 2017 36th Chinese Control Conference (CCC), 7511–7515. IEEE.
  5. He, S., Yuan, X., & Zhang, X. (2016). The Government’s environment policy index impact on recycler behavior in electronic products closed-loop supply chain. Discrete Dynamics in Nature and Society, 2016.
  6. Hofmann, E. (2017). Big data and supply chain decisions: the impact of volume, variety and velocity properties on the bullwhip effect. International Journal of Production Research, 55(17), 5108–5126.
  7. Hong, Z., Zhang, Y., Yu, Y., & Chu, C. (2020). Dynamic pricing for remanufacturing within socially environmental incentives. International Journal of Production Research, 58(13), 3976–3997.
  8. Hosoda, T., & Disney, S. M. (2018). A unified theory of the dynamics of closed-loop supply chains. European Journal of Operational Research, 269(1), 313–326.
  9. Hosoda, T., Disney, S. M., & Gavirneni, S. (2015). The impact of information sharing, random yield, correlation, and lead times in closed loop supply chains. European Journal of Operational Research, 246(3), 827–836.
  10. Hosseini Bamkan, S M., Malikinejad, P., & Ziaian, M. (2019). Investigation and analysis of urban service supply chain (Case study: Isfahan Municipality). Urban and Rural Management, (56), 92-73. (In Persian).
  11. Hosseini, S M., Mohammadi, A S., & Pishvaei, M. (2010). Supply chain strategy and production system selection. Strategic Management Studies, (2), 89-112. (In Persian).
  12. Hosseini, S M., & Sheikhi, 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, (10), 60-35. (In Persian).
  13. Ignaciuk, P. (2014). Discrete-time control of production-inventory systems with deteriorating stock and unreliable supplies. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 45(2), 338–348.
  14. Jiang, Q., & Ke, G. (2019). Information sharing and bullwhip effect in smart destination network system. Ad Hoc Networks, 87, 17–25.
  15. Khan, M. H., Ahmed, S., & Hussain, D. (2019). Analysis of bullwhip effect: a behavioral approach. Supply Chain Forum: An International Journal, 20(4), 310–331. Taylor & Francis.
  16. Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546–558.
  17. Li, C. (2013). Controlling the bullwhip effect in a supply chain system with constrained information flows. Applied Mathematical Modelling, 37(4), 1897–1909.
  18. Li, K., Li, Y., Gu, Q., & Ingersoll, A. (2019). Joint effects of remanufacturing channel design and after-sales service pricing: an analytical study. International Journal of Production Research, 57(4), 1066–1081.
  19. Li, Q.-K., Li, Y.-G., & Lin, H. (2017). $ H_ {infty} $ Control of Two-Time-Scale Markovian Switching Production-Inventory Systems. IEEE Transactions on Control Systems Technology, 26(3), 1065–1073.
  20. Ma, L., Chai, Y., Zhang, Y. Y., & Zheng, L. (2014). Modeling and Analysis of the Bullwhip Effect in Remanufacturing Closed-loop Supply Chain. Applied Mechanics and Materials, 541, 1556–1561. Trans Tech Publ.
  21. Madaan, J., & Wadhwa, S. (2010). Decision and information synergy for improving product recovery performance. Global Journal of Flexible Systems Management, 11(1–2), 89–96.
  22. Maina, J., & Mwangangi, P. (2020). A Critical Review of Simulation Applications in Supply Chain Management. Journal of Logistics Management, 9(1), 1–6.
  23. Murray, A., Skene, K., & Haynes, K. (2017). The circular economy: an interdisciplinary exploration of the concept and application in a global context. Journal of Business Ethics, 140(3), 369–380.
  24. Nadery Bani, M., Ebrahimzadeh Pezeshki, R., Abolghasemi, M., & Malikinejad, P. (2017). Designing a conceptual model for achieving organizational entrepreneurship with an integrated approach of mikhailov fuzzy hierarchical analysis and interpretive structural modeling (Case Study: Yazd Sports and Youth Organization). Applied Research in Sports Management, (6), 127–139. (In Persian).
  25. Online Economy. (2020). Energy. https://www.eghtesadonline.com.
  26. Oswaldo, M. M., Mauricio, F. C., Ricardo, T. P., Isaías, B. P., & Ignacio, C. M. (2011). Fractal characterization of an after-sales spare parts supply chain in telecom industry. International Journal of Physical Sciences, 2462–2469.
  27. Özceylan, E., & Paksoy, T. (2013). A mixed integer programming model for a closed-loop supply-chain network. International Journal of Production Research, 51(3), 718–734.
  28. Paksoy, T., Bektaş, T., & Özceylan, E. (2011). Operational and environmental performance measures in a multi-product closed-loop supply chain. Transportation Research Part E: Logistics and Transportation Review, 47(4), 532–546.
  29. Pati, R. K., Vrat, P., & Kumar, P. (2010). Quantifying bullwhip effect in a closed loop supply chain. Opsearch, 47(4), 231–253.
  30. Quariguasi Frota Neto, J., Walther, G., Bloemhof, J., Van Nunen, J., & Spengler, T. (2010). From closed-loop to sustainable supply chains: the WEEE case. International Journal of Production Research, 48(15), 4463–4481.
  31. Sawik, B. (2020). Selected Multiple Criteria Supply Chain Optimization Problems. In Applications of Management Science. Emerald Publishing Limited, 20, 31-58.
  32. Thierry, M., Salomon, M., Van Nunen, J., & Van Wassenhove, L. (1995). Strategic issues in product recovery management. California Management Review, 37(2), 114–136.
  33. Warfield, J. N. (1974). Developing interconnection matrices in structural modeling. IEEE Transactions on Systems, Man, and Cybernetics, (1), 81–87.
  34. Wei, J., Chen, W., & Liu, G. (2020). How manufacturer’s integration strategies affect closed-loop supply chain performance. International Journal of Production Research, 1–19.
  35. Zhang, S., Li, X., & Zhang, C. (2016). A fuzzy control model for restraint of bullwhip effect in uncertain closed-loop supply chain with hybrid recycling channels. IEEE Transactions on Fuzzy Systems, 25(2), 475–482.
  36. Zhang, S., & Zhang, M. (2020). Mitigation of bullwhip effect in closed-loop supply chain based on fuzzy robust control approach. Complexity, 2020.
  37. Zhao, Y., Cao, Y., Li, H., Wang, S., Liu, Y., Li, Y., & Zhang, Y. (2018). Bullwhip effect mitigation of green supply chain optimization in electronics industry. Journal of Cleaner Production, 180, 888–912.
  38. Zhao, S., & Zhu, Q. (2018). A risk-averse marketing strategy and its effect on coordination activities in a remanufacturing supply chain under market fluctuation. Journal of Cleaner Production, 171, 1290–1299.
  39. Yang, T., Fu, C., Liu, X., Pei, J., Liu, L., & Pardalos, P. M. (2018). Closed-loop supply chain inventory management with recovery information of reusable containers. Journal of Combinatorial Optimization, 35(1), 266–292.