황소채찍효과와 발주크기: 대형할인마트에서의 황소채찍효과

Bullwhip Effect and Lot Size: the Main Cause of BwE is Lot Size

  • 백시현 (중국연변과학기술대학교 경영정보학과)
  • 투고 : 20070700
  • 심사 : 20080100
  • 발행 : 2008.06.30

초록

Normally, suppliers have to decide on what, how much, and when to replenish stocks of goods based on a data flow generated by a vendor managed inventory(VMI) system. But information from supply chain is often misleading. It is common for such data to be distorted by a lack of coordination and synchronization across several business entities managing different supply chain operations. This phenomenon is called the 'bullwhip effect(BwE)'. Many researchers, working over many years, have studied the reasons for the BwE. They have proposed various remedies, but this phenomenon persists. Though overlooked in previous research, this paper reveals that the 'lot size' of a supply chain of distribution is indeed the main cause of the BwE. In addition, some problems in the existing methods of measuring the BwE are identified and a revised much improved method of measurement is suggested.

키워드

참고문헌

  1. Alberto, F. F. T. and Elena, Z. (2005), From a traditional replenishment system to vender -managed inventory : A case study from the household electrical appliances sector, Int.J. Production Economics, 96, 73-79
  2. Baljko, J. L. (1999), Experts warns of Bullwhip effect, Electronic Buyer's News, 1170
  3. Cachon, G. P. (1999), Managing supply chain demand variability with schedules ordering policies, Mgt. Sci., 45(6), 843-856 https://doi.org/10.1287/mnsc.45.6.843
  4. Chen, F. (1998), Echelon reorder points, installation reorder points, and the value of centralized demand information, Mgt. Sci., 44(12), 221-234 https://doi.org/10.1287/mnsc.44.12.S221
  5. Chen, F., Drezner, Z., Ryan, J. K. and Simchi-Levi, D. (2000), Quantifying the Bullwhip effect in a simple supply chain : The impact of forecasting, lead times, and information, Mgt. Sci., 43, 436-443
  6. Dejonckheere, J., Disney, S. M., Lambrecht, M. R. and Towill, D. R. (2003), Measuring and avoiding the Bullwhip effect : A control theoretic approach, Eur. J. of Oper. Res., 147(3), 567-590 https://doi.org/10.1016/S0377-2217(02)00369-7
  7. Forrester, J. W. (1958), Industrial dynamics : a major breakthrough for decision makers, Harvard Business Review, 36, 37-66
  8. Fransoo, J. C. and Wouters, M. J. F. (2000), Measuring the Bullwhip effect in the supply chain, Int.J. Supply Chain Mgt., 5(2), 78-89 https://doi.org/10.1108/13598540010319993
  9. Gavirneni, S. (2005), Price fluctuations, information sharing, and supply chain performance, Euro.J. of Operation Research, 1-13, ARTICLE IN PRESS, from www.elsevier.com/locate/ejor
  10. Holland, W. and Sodhi, M. S. (2003), Quantifying the effect of batch size and order errors on the Bullwhip effect using simulation, Proceedings of the 8$^{th}$ Logistics Research Network Conference, London, 11$^{th}$-12$^{nd}$, 188-195
  11. Lee, H. L. and Billington, C. (1992), Managing supply chain inventory : pitfalls and opportunities, Sloan Mgt. Review, 33(3), 65-73
  12. Lee, H. L., Kut, C. S., and Tang, C. S. (2000), The value of information sharing in a two-level supply chain : The Bullwhip Effect, Mgt. Sci., 46, 626-643 https://doi.org/10.1287/mnsc.46.5.626.12047
  13. Lee, H. L., Padmanabhan, V., and Whang, S. (1997a), The Bullwhip effect in supply chains, Sloan Mgt. Review, 38, 93-102
  14. Lee, H. L., Padmanabhan, V., and Whang, S. (1997b), Information distortion in a supply chain: the Bullwhip effect, Mgt. Sci., 43(43), 546-558 https://doi.org/10.1287/mnsc.43.4.546
  15. Lin, C. and Lin, Y. T. (2006), Mitigating the bullwhip effect by reducing demand variance in the supply chain, Int.J. of Adv. Manuf. Technology, 28, 328-336 https://doi.org/10.1007/s00170-004-2371-5
  16. Miragliotta, G. (2006), Layers and mechanisms: A new taxonomy of the Bullwhip Effect, Int.J. of Production Economics, 104, 365-381 https://doi.org/10.1016/j.ijpe.2005.10.001
  17. Naish, H. F. (1994), Production smoothing in the linear quadratic inventory model, Quarterly Journal of Economics, 104, 864-875 https://doi.org/10.2307/2234980
  18. Nienhaus, J., Ziegenbein, A., and Scheoenslben, P. (2006), How human behaviour amplifies the Bullwhip effect, Production Planning and control, 17 (6), 547-557 https://doi.org/10.1080/09537280600866587
  19. Park, B. I. and Park, M. S. (2001), Measuring the Benefits of Shared Information in Oil Product Supply Chain, J. of the Korean Society of Supply Chain Management, 1(1), 87-96
  20. Paik, S. H., Hong, M. S, and Rim, S. C. (2006), Demand Control Chart, IEEE Int. Conf. Service Operations and Logistics, and Informatics, id 520178
  21. Potter, A. and Disney, S. M. (2006), Bullwhip and batching: An exploration, Int. J. Production Economics, 104, 408-418 https://doi.org/10.1016/j.ijpe.2004.10.018
  22. Pujawan, I. N. (2004), The effect of lot sizing rules on order variability, Eur. J. of Oper. Res., 159(3), 617-635 https://doi.org/10.1016/S0377-2217(03)00419-3
  23. Reddy, A. M. and Rajendran, C. (2004), A Simulation Study of Dynamic Order-up-to Policies in a Supply Chain with Non- Stationary Customer Demand and Information Sharing, Advanced Manufacturing Technology, DOI : 10.1007 /s00170-003-1940-3
  24. Rinks, D. B. (2002), System dynamics in supply chains, Proceedings of the 2002 Euroma Conf, Copenhagen, 443-457
  25. Sahin, F. and Robinson, E. P. (2005), Information sharing and coordination in make-to-order supply chains, J. of Oper. Mgt., 23, 579-598 https://doi.org/10.1016/j.jom.2004.08.007
  26. Simchi-Levi, D., Kaminsky, P., and Simchi-Levi, E. (2000), Designing and managing the Supply Chain Concepts, Strategies, and Case Studies, McGraw-Hill, Boston
  27. Sterman, J. D. (1984), Introduction for running the Beer Distribution Game, sloan School of Mgt., Boston
  28. Sterman, J. D. (1989), Modeling managerial behavior : misperceptions of feedback in a dynamic decision-making experiment, Mgt. Sci., 35(3), 321-339 https://doi.org/10.1287/mnsc.35.3.321
  29. Svensson, G. (2003), The Bullwhip effect in intra-organizational Echelons, Int. J. of Physical Distribution & Logistics Mgt., 33(2), 103-131 https://doi.org/10.1108/09600030310469135
  30. Svensson, G. (2005), The multiple facets of the Bullwhip effect: refined and re-defined, Int. J. Physical Distribution & Logistics Mgt., 35(10), 762-777 https://doi.org/10.1108/09600030510634607
  31. Wang, J., Jia, J. and Takahashi, K. (2005), A study on the impact of uncertain factors on information distortion in supply chains, Production Planning and Control, 16(1), 2-11 https://doi.org/10.1080/09537280412331309235
  32. Zhang, X. (2005), Delayed demand information and dampened bullwhip effect, Operation Research Letters, 33, 289-294 https://doi.org/10.1016/j.orl.2004.05.010
  33. Zhou, L. and Disney, S. M. (2006), Bullwhip and inventory variance in a closed loop supply chain, OR Spectrum, 28, 127-149 https://doi.org/10.1007/s00291-005-0009-0
  34. Ziegenbein, A. and Scheoenslben, P. (2006), How human behaviour amplifies the Bullwhip effect, Production Planning and Control, 17(6), 547-557 https://doi.org/10.1080/09537280600866587