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Optimal decisions and comparison of VMI and CPFR under price-sensitive uncertain demand

Journal Name:

  • Journal of Industrial Engineering and Management

Publication Year:

  • 2013

Key Words:

Author NameUniversity of Author
Abstract (2. Language): 
Purpose: The purpose of this study is to make optimal decisions on retail price and order quantity for two advanced supply chain coordination mechanisms, Vendor Managed Inventory (VMI) and Collaborative Planning Forecasting and Replenishment (CPFR), under a pricesensitive uncertain demand environment, and to compare the performance of VMI and CPFR. Sensitivity analysis is also conducted to gain managerial insight. Design/methodology/approach: Analytical models are first applied to formulate a profit maximization problem; furthermore, by applying simulation optimization solution procedures, the optimal decisions and performance comparisons are accomplished. Sensitivity analysis is also conducted to show how production cost and inventory holding cost affect optimal decisions and the total profits in VMI and CPFR. Findings: The optimal decisions and expected total profits are impacted by the demand patterns, production cost, inventory holding cost, and internal transfer price. In addition, the results of the case study reveal that CPFR outperforms VMI in terms of higher expected total profit and lower retail price. Research limitations/implications: This study only considers a single vendor and a single retailer in the supply chain structure. Practical implications: Knowledge obtained from this study about the performance of each coordination mechanism and decision making under uncertainty are critical to managers and industry practitioners who may apply the coordination mechanisms considered. Originality/value: This study includes the production cost in the mathematical model and combines it with price-sensitive demand under stochastic settings to maximize the total profit. Many studies have worked on information sharing within the supply chain; however, determining the optimal retail price and order quantity and comparing the performance of VMI and CPFR when the demand is price-sensitive and stochastic were not reported by the past literature.
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  • 2
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  • English

REFERENCES

References: 

Attaran, M., & Attaran, S. (2007). Collaborative supply chain management: The most
promising practice for building efficient and sustainable supply chains. Business Process
Management Journal, 13(3), 390-404. http://dx.doi.org/10.1108/14637150710752308
Aviv, Y. (2001). The effect of collaborative forecasting on supply chain performance.
Management Science, 47(10), 1326-1343. http://dx.doi.org/10.1287/mnsc.47.10.1326.10260
Aviv, Y. (2002). Gaining benefits from joint forecasting and replenishment processes: The case
of auto-correlated demand. Manufacturing & Service Operations Management, 4(1), 55-74.
http://dx.doi.org/10.1287/msom.4.1.55.285
Aviv, Y. (2004). Collaborative Forecasting and Inventory Management: Capacity
Considerations. St. Louis, MO, 34.
Baganha, M.P., & Cohen, M.A. (1998). The stabilizing effect of inventory in supply chains.
Operations Research, 46(3), 72-83. http://dx.doi.org/10.1287/opre.46.3.S72
Bamford, D.R., & Forrester, P.L. (2003). Managing planned and emergent change within an
operations management environment. International Journal of Operations & Production
Management, 23(5), 546-564. http://dx.doi.org/10.1108/01443570310471857
Cachon, G.P., & Fisher, M. (2000). Supply chain inventory management and the value of shared
information. Management Science, 46(8), 1032-1048.
http://dx.doi.org/10.1287/mnsc.46.8.1032.12029
Chen, F. (1998). Echelon reorder points, installation reorder points, and the value of
centralized demand information. Management Science, 44(12), 221-234.
http://dx.doi.org/10.1287/mnsc.44.12.S221
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. http://dx.doi.org/10.1287/mnsc.46.3.436.12069
Cooke, J.A. (1998). VMI: very mixed impact? Logistics Management and Distribution.
Dana Jr, J.D., & Petruzzi, N.C. (2001). Note: The newsvendor model with endogenous demand.
Management Science, 47(11), 1488-1497. http://dx.doi.org/10.1287/mnsc.47.11.1488.10252
Disney, S.M., & Towill, D.R. (2003). Vendor-managed inventory and bullwhip reduction in a
two-level supply chain. International Journal of Operations & Production Management, 23(6),
625-651. http://dx.doi.org/10.1108/01443570310476654
Emerson, D., Zhou, W., & Piramuthu, S. (2009). Goodwill, inventory penalty, and adaptive
supply chain management. European Journal of Operational Research, 199(1), 130-138.
http://dx.doi.org/10.1016/j.ejor.2008.11.007
Fliedner, G. (2003). CPFR: an emerging supply chain tool. Industrial Management & Data
Systems, 103(1), 14-21. http://dx.doi.org/10.1108/02635570310456850
Forrester, J.W. (1958). Industrial dynamics: a major breakthrough for decision makers.
Harvard business review, 36(4), 37-66.
Ganeshan, R., Boone, T., & Stenger, A.J. (2001). The impact of inventory and flow planning
parameters on supply chain performance: An exploratory study. International Journal of
Production Economics, 71(1-3), 111-118. http://dx.doi.org/10.1016/S0925-5273(00)00109-2
Gaur, V., Giloni, A., & Seshadri, S. (2005). Information sharing in a supply chain under ARMA
demand. Management Science, 51(6), 961-969. http://dx.doi.org/10.1287/mnsc.1050.0385
Gavirneni, S., Kapuscinski, R., & Tayur, S. (1999). Value of information in capacitated supply
chains. Management Science, 45(1), 16-24. http://dx.doi.org/10.1287/mnsc.45.1.16
Goodwin, J.S., & Franklin, S.G. (1994). The beer distribution game: using simulation to teach
systems thinking. Journal of Management Development, 13(8), 7-15.
http://dx.doi.org/10.1108/02621719410071937
Gronalt, M., & Rauch, P. (2008). SILVA FENNICA. Silva Fennica, 42, 1.
Holmström, J., Främling, K., Kaipia, R., & Saranen, J. (2002). Collaborative planning
forecasting and replenishment: new solutions needed for mass collaboration. Supply Chain
Management: An International Journal, 7(3), 136-145.
http://dx.doi.org/10.1108/13598540210436595
Holt, C.C. (1960). Planning production, inventories, and work force: Prentice Hall.
Kahn, J.A. (1987). Inventories and the Volatility of Production. The American Economic Review,
77, 667-679.
Ketzenberg, M.E., Laan, E., & Teunter, R.H. (2006). Value of information in closed loop supply
chains. Production and Operations Management, 15(3), 393-406.
http://dx.doi.org/10.1111/j.1937-5956.2006.tb00253.x
Kuk, G. (2004). Effectiveness of vendor-managed inventory in the electronics industry:
determinants and outcomes. Information & management, 41(5), 645-654.
http://dx.doi.org/10.1016/j.im.2003.08.002
Lau, J.S.K., Huang, G.Q., & Mak, K. (2004). Impact of information sharing on inventory
replenishment in divergent supply chains. International Journal of Production Research,
42(5), 919-941. http://dx.doi.org/10.1080/00207540310001628911
Lee, H.L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: the
bullwhip effect. Management Science, 43(4), 546-558. http://dx.doi.org/10.1287/mnsc.43.4.546
Lee, H.L., So, K.C., & Tang, C.S. (2000). The value of information sharing in a two-level supply
chain. Management Science, 46(5), 626-643. http://dx.doi.org/10.1287/mnsc.46.5.626.12047
Magee, J.F., & Boodman, D.M. (1967). Production planning and inventory control. Vol. 131.
New York: McGraw-Hill.
Mohtadi, H., & Kinsey, J.D. (2005). Information Exchange and Strategic Behavior in Supply Chains:
Application to the Food Sector. American Journal of Agricultural Economics, 87(3), 582-599.
http://dx.doi.org/10.1111/j.1467-8276.2005.00749.x
Naish, H.F. (1994). Production smoothing in the linear quadratic inventory model. The
Economic, 104(425), 864-875. http://dx.doi.org/10.2307/2234980
Ouyang, Y. (2007). The effect of information sharing on supply chain stability and the bullwhip
effect. European Journal of Operational Research, 182(3), 1107-1121.
http://dx.doi.org/10.1016/j.ejor.2006.09.037
Raghunathan, S. (1999). Interorganizational collaborative forecasting and replenishment
systems and supply chain implications. Decision Sciences, 30(4), 1053-1071.
http://dx.doi.org/10.1111/j.1540-5915.1999.tb00918.x
Ramey, G., & Ramey, V.A. (1991). Technology commitment and the cost of economic
fluctuations. National Bureau of Economic Research.
Sajadieh, M.S., & Akbari Jokar, M.R. (2009). Optimizing shipment, ordering and pricing policies
in a two-stage supply chain with price-sensitive demand. Transportation Research Part E:
Logistics and Transportation Review, 45(4), 564-571. http://dx.doi.org/10.1016/j.tre.2008.12.002
Sari, K. (2008). On the benefits of CPFR and VMI: A comparative simulation study.
International Journal of Production Economics, 113(2), 575-586.
http://dx.doi.org/10.1016/j.ijpe.2007.10.021
Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2003). Designing and managing the supply
chain: concepts, strategies, and case studies. Irwin/McGraw-Hill.
Småros, J., & Holmström, J. (2000). Viewpoint: reaching the consumer through e-grocery VMI.
International Journal of Retail & Distribution Management, 28(2), 55-61.
http://dx.doi.org/10.1108/09590550010315098
Southard, P.B., & Swenseth, S.R. (2008). Evaluating vendor-managed inventory (VMI) in
non-traditional environments using simulation. International Journal of Production Economics,
116(2), 275-287. http://dx.doi.org/10.1016/j.ijpe.2008.09.007
Sterman, J.D. (1989). Modeling managerial behavior: Misperceptions of feedback in a dynamic
decision making experiment. Management Science, 321-339.
http://dx.doi.org/10.1287/mnsc.35.3.321
Waller, M., Johnson, M.E., & Davis, T. (1999). Vendor-managed inventory in the retail supply
chain. Journal of Business Logistics, 20, 183-204.
Zhang, C. (2007). Design and simulation of demand information sharing in a supply chain.
Simulation Modelling Practice and Theory, 15(1), 32-46.
http://dx.doi.org/10.1016/j.simpat.2006.09.011
Zhao, X., Xie, J., & Leung, J. (2002). The impact of forecasting model selection on the value of
information sharing in a supply chain. European Journal of Operational Research, 142(2),
321-344. http://dx.doi.org/10.1016/S0377-2217(01)00300-9
Zhao, Y., & Simchi-Levi, D. (2006). Performance analysis and evaluation of assemble-to-order
systems with stochastic sequential lead times. Operations Research-Baltimore Then
Linthicum, 54(4), 706. http://dx.doi.org/10.1287/opre.1060.0302

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