Abstract
Increasing globalization, growing product range diversity, and rising consumer awareness are making markets highly competitive, forcing supply chains to adapt constantly to different stimuli. Growing competition between supply chains (as well as players within them) is also warranting a priority for overall supply chain performance over the goals of individual players. It is now well established in the literature that, among the many order winners, both overall supply chain cost and responsiveness (i.e., supply chain lead time) are the most significant determinants of supply chain competitiveness. The literature, however, mostly focuses on supply chain cost minimization with rather simplistic treatment of responsiveness. By introducing the concept of a coefficient of inverse responsiveness (CIR), we facilitate efficient introduction of responsiveness related costs into the scheme of supply chain (SC) performance evaluation and/or optimization. Thus, our model aids supply chain managers in achieving better strategic fit between individual business unit strategies and overall supply chain requirements in terms of cost efficiency and responsiveness. In particular, it aids in strategic placement of safety stocks at different stages in the supply chain. Our model also offers managerial insights that help improve our intuitions into supply chain dynamics. The model is more suited for strategic SC alignment, for example, when dealing with product changeovers or introduction of new product, rather than for operational control.
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References
Axsäter S (1993) Continuous review policies for multi-level inventory systems with stochastic demand. In: Graves S, Rinnooy Kan A, Zipkin P (eds) Logistics of production and inventory. Elsevier Science, North Holland
Axsäter S, Rosling K (1993) Notes: installation vs. Echelon stock policies for multilevel inventory control. Manage Sci 39(10):1274–1280
Ben-Daya M, Raouf A (1994) Inventory models involving lead time as decision variables. J Oper Res Soc 45:579–582
Bookbinder JH, Cakanyildirim M (1999) Random lead times and expedited orders in (Q, r) inventory systems. Eur J Oper Res 115:300–313
Cherukuri SS, Nieman RG, Sirianni NC (1995) Cycle time and the bottom line. Indust Eng 27(3):20–23
Choi JW (1994) Investment in the reduction of uncertainties in just in time purchasing systems. Naval Res Logistics 41:257–272
Chopra S, Meindl P (2004) Supply chain management: strategy, planning and operation, 2nd edn. Pearson Education Inc., Upper Saddle River
Chopra S, Reinhardt G, Dada M (2004) The effect of lead time uncertainty on safety stocks. Decis Sci 35(1):1–24
Clark A, Scarf H (1960) Optimal policies for a multi echelon inventory problem. Manage Sci 6:474–490
Davis D, Buckler J, Mussomeli A, Kinzler D (2005) Inventory transformation: Revlon style. Supply Chain Manage Rev 9(5):53–59
Eppen GD, Martin RK (1988) Determining safety stock in the presence of stochastic lead time and demand. Manage Sci 34(11):1380–1390
Ettl M, Feigin GE, Lin GY, Yao DD (2000) A supply network model with base—stock control and service requirements. Oper Res 48:216–232
Felgate R, Bott S, Harris C (2007) Get your timing right. Supply Manage 12(1):17
Feller W (1960) An introduction to probability theory and its applications, vol I. Wiley, New York
Fisher ML (1997) What is the right supply chain for your product? Harv Bus Rev 75(2):105–116
Gallego G, Zipkin P (1999) Stock positioning and performance estimation in serial production-transportation systems. Manuf Serv Oper Manage 1(1):77–88
Gaur V, Giloni A, Seshadri S (2005) Information sharing in a supply chain Under ARMA demand. Manage Sci 51(6):961–969
Glasserman P, Tayur S (1995) Sensitivity analysis for base stock levels in multi echelon production-inventory system. Manage Sci 41:216–232
Glasserman P, Tayur S (1996) A simple approximation for a multi stage capacitated production inventory systems. Naval Res Logistics 43:41–58
Graves S (1985) Multi echelon inventory model for a repairable item with one for one replenishment. Manage Sci 31:1247–1256
Graves SC (1988) Safety stocks in manufacturing systems. J Manuf Oper Manage 1:67–101
Graves SC, Willems SP (2003) Supply chain design: safety stock placement and supply chain configuration. In: de Kok AG, Graves SC (eds) Handbooks in operations research and management science, supply chain management: design, coordination and operation, Chap 3, vol 11. Elsevier BV, Amsterdam, The Netherlands
Hanssmann F (1959) Optimal inventory location and control in production and distribution networks. Oper Res 7:483–498
Hill T (1993) Manufacturing strategy: text and cases, 2nd edn. IRWIN, Illinois
Kapuscinski R, Tayur S (1999) Optimal policies and simulation based optimization for capacitated production inventory systems. In: Tayur S, Ganeshan R, Magazine MJ (eds) Quantitative models for supply chain management. Kluwer Academic Publishers, Boston
Lee HL, Billington C (1993) Material management in decentralized supply chains. Oper Res 41(5):835–847
Lee HL, Moinzadeh K (1987a) Two parameter approximations for multi echelon repairable inventory models with batch ordering policy. IIE Trans 19:140–149
Lee HL, Moinzadeh K (1987b) Operating characteristics of a two echelon inventory system for repairable and consumable items under batch ordering and shipment policy. Naval Res Logistics Quart 34:365–380
Lee Y, Zipkin P (1992) Tandem queues with planned inventories. Oper Res 40:936–947
Moon I, Choi S (1998) Technical note: a note on lead time and distributional assumptions in continuous review inventory models. Comput Oper Res 25(11):1007–1012
Nazzal D, Mollaghasemi M, Anderson D (2006) A simulation-based evaluation of the cost of cycle time reduction in Agere systems wafer fabrication facility—a case study. Int J Prod Econ 100:300–313
Rosling K (1989) Optimal inventory policies for assembly systems under random demands. Oper Res 37:565–579
Ryu SW, Lee KK (2003) A stochastic inventory model of dual sourced supply chain with lead-time reduction. Int J Prod Econ 81–82:513–524
Simchi-Levi D, Zhao Y (2005) Safety stock positioning in supply chain with stochastic lead times. Manuf Serv Oper Manage 7(4):295–318
Simpson KF (1958) In process inventories. Oper Res 6:863–873
Sourirajan K, Ozsen L, Uzsoy R (2007) A single-product network design model with lead time and safety stock considerations. IIE Trans 39:411–424
Speck C, vander Wal J (1991) The capacitated multi echelon inventory system with serial structure: 1. The “push-ahead” effect. Memorandum COSOR 91-39, Eindhoven University of Technology, Eindhoven, The Netherlands
Upton DM (1997) Process range in manufacturing: an empirical study of flexibility. Manage Sci 43(8):1079–1092
Van Houtum GJ, Inderfurth K, Zijm WHM (1996) Materials coordination in stochastic multi echelon systems. Eur J Oper Res 95:1–23
Vanteddu G, Chinnam RB, Yang, K (2006) A performance Comparison tool for Supply Chain management. Int J Logistics Syst Manage 2(4):342–356
Yang B, Geunes J (2007) Inventory lead time planning with lead-time sensitive demand. IIE Trans 39(5):439
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Vanteddu, G., Chinnam, R.B., Yang, K. et al. Supply chain focus dependent safety stock placement. Int J Flex Manuf Syst 19, 463–485 (2007). https://doi.org/10.1007/s10696-008-9050-z
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DOI: https://doi.org/10.1007/s10696-008-9050-z