Strategic Positioning of the Push-Pull Boundary within a Supply Chain: An Ordering Policy Co-ordination Perspective

The rapid advancement in IT communication enables the availability of demand data in a seamless manner. One manifestation of this technological advancement within the supply chain (SC) domain has been the emergence of a push-pull boundary (PPB). Push-pull boundary is a virtual demarcation point separating the portion of the SC under decentralized from that operating under centralized information sharing. However, the impact of key issues like adoption of inventory ordering policy characterized by the various echelons of a SC network structure while positioning the push-pull boundary need to be investigated comprehensively (Ahn and Kaminsky, 2005). This paper is concerned with the ‘Average Fill Rate’ and ‘Average Total Inventory Cost’ performance behaviour of a SC network structure. These performances typically results from different parameters that involves: (i) inventory ordering policy, (ii) push-pull boundary under the influence of information sharing, (iii) forecasting error, and (iv) lead time and their standard deviations. The study is accomplished via Taguchi experimental design framework and simulation analysis. The results suggest the effect of various factors on SC network system wide performance and identify the appropriate combinations of these factors for optimal performance concerned.

[1]  Remko I. van Hoek,et al.  The thesis of leagility revisited , 2000 .

[2]  Charu Chandra,et al.  Simulation Modeling for Information Management in a Supply Chain , 2001 .

[3]  N. D. Burns,et al.  Implications of postponement for the supply chain , 2003 .

[4]  Ingegneria Meccanica.  Cost performance and bullwhip effect in a hybrid manufacturing and remanufacturing system with different control policies , 2006 .

[5]  J. W. Patterson,et al.  Comparison of push and pull control strategies for supply network management in a make-to-stock environment , 2004 .

[6]  T. F. Burgess,et al.  Modelling a complex supply chain: understanding the effect of simplified assumptions , 2005 .

[7]  Jan Olhager,et al.  Simulating production and inventory control systems: a learning approach to operational excellence , 2006 .

[8]  Hau L. Lee,et al.  Material Management in Decentralized Supply Chains , 1993, Oper. Res..

[9]  Alan Harrison,et al.  Implications of form postponement to manufacturing a customized product , 2006 .

[10]  Henry Aigbedo,et al.  An assessment of the effect of mass customization on suppliers' inventory levels in a JIT supply chain , 2007, Eur. J. Oper. Res..

[11]  Chandrasekharan Rajendran,et al.  A Simulation Study of Dynamic Order-up-to Policies in a Supply Chain with Non-Stationary Customer Demand and Information Sharing , 2005 .

[12]  Philip M. Kaminsky,et al.  Designing and managing the supply chain : concepts, strategies, and case studies , 2007 .

[13]  Victoria C. P. Chen,et al.  Performance analysis of conjoined supply chains , 2001 .

[14]  Ricardo Ernst,et al.  Evaluation of supply chain structures through modularization and postponement , 2000, Eur. J. Oper. Res..

[15]  Danny Berry,et al.  Leagility: Integrating the lean and agile manufacturing paradigms in the total supply chain , 1999 .

[16]  Marek Pawlak,et al.  A local collaboration as the most successful co-ordination scenario in the supply chain , 2008, Ind. Manag. Data Syst..

[17]  Hyun-Soo Ahn,et al.  Production and distribution policy in a two-stage stochastic push-pull supply chain , 2005 .

[18]  Y. A. Hidayat,et al.  Partner Selection in Supplier-Buyer Relationship with Integration of Leadtime Decisions under Demand Uncertainty Situation , 2014 .

[19]  Werner Jammernegg,et al.  Performance improvement of supply chain processes by coordinated inventory and capacity management , 2007 .

[20]  Marshall L. Fisher,et al.  Supply Chain Inventory Management and the Value of Shared Information , 2000 .

[21]  Ming Dong.  Process Modeling, Performance Analysis and Configuration Simulation in Integrated Supply Chain Network Design , 2001 .

[22]  Randall P. Sadowski,et al.  Simulation with Arena , 1998 .

[23]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .