Performance analysis of conjoined supply chains

This research is concerned with the performance behaviour of conjoined supply chains, which typically arise in web-based retail. In particular, five performance measures belonging to three performance measure classes were used to study the performance effects of various operational factors on conjoined supply chains. The study is accomplished via experimental design and simulation analysis, and the results suggest the effects of the various factors on supply chain performance and identify the nature of the relationships among these factors and overall supply chain performance.

[1]  Mahesh Gupta,et al.  Comparative analysis of lot-sizing models for multi-stage systems: a simulation study , 1992 .

[2]  Jeremy F. Shapiro,et al.  Optimizing the Value Chain , 1993 .

[3]  Alan J. Stenger.  Reducing inventories in a multi-echelon manufacturing firm A case study , 1996 .

[4]  S. Newell,et al.  Winner Takes all , 1996 .

[5]  Örjan Ekeberg,et al.  Cortex-basal ganglia interaction and attractor states , 2001, Neurocomputing.

[6]  Surendra M. Gupta,et al.  Lead time uncertainty with back-ordering in multi-level product structures , 1994 .

[7]  S. Hestrin,et al.  Spike Transmission and Synchrony Detection in Networks of GABAergic Interneurons , 2001, Science.

[8]  A. Grace,et al.  Alterations in electrophysiological activity and dye coupling of striatal spiny and aspiny neurons in dopamine‐denervated rat striatum recorded in vivo , 1999, Synapse.

[9]  Holly Moore,et al.  A Role for Electrotonic Coupling in the Striatum in the Expression of Dopamine Receptor-mediated Stereotypies , 2002, Neuropsychopharmacology.

[10]  E. Fernandez,et al.  On the validity of the two-cells model in the analysis of passive electrical properties of gap-junction connected cells , 2001, European Biophysics Journal.

[11]  J. O. Spalding,et al.  TRANSPORTATION INDUSTRY TAKES THE RIGHT-OF-WAY IN THE SUPPLY CHAIN , 1998 .

[12]  Denis Royston Towill,et al.  Conceptual modelling of industrial production-distribution systems via standard forms , 1990 .

[13]  R. Westbrook,et al.  New Strategic Tools for Supply Chain Management , 1991 .

[14]  L. LeeHau,et al.  Information Distortion in a Supply Chain , 1997 .

[15]  Douglas J. Thomas,et al.  Coordinated supply chain management , 1996 .

[16]  Peter McCullen,et al.  The Impact of Agile Manufacturing on Supply Chain Dynamics , 1999 .

[17]  Denis Royston Towill,et al.  The seamless supply chain - the predator's strategic advantage , 1997 .

[18]  S. Hestrin,et al.  Electrical and chemical synapses among parvalbumin fast-spiking GABAergic interneurons in adult mouse neocortex , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[19]  L. Zurich,et al.  Operations Research in Production Planning, Scheduling, and Inventory Control , 1974 .

[20]  A. McMullan.  Supply chain management practices in Asia Pacific today , 1996 .

[21]  Mohamed Mohamed Naim,et al.  Smoothing Supply Chain Dynamics , 1991 .

[22]  Carlos D. Brody,et al.  Correlations Without Synchrony , 1999, Neural Computation.

[23]  Francis J. Vasko,et al.  Consolidating Product Sizes to Minimize Inventory Levels for a Multi-Stage Production and Distribution System , 1993 .

[24]  Jim Freeman,et al.  Inventory Control and Management , 1992 .

[25]  George E. P. Box,et al.  Empirical Model‐Building and Response Surfaces , 1988 .

[26]  M. Amin,et al.  Control policies for multi-product multi-stage manufacturing systems: An experimental approach , 1997 .

[27]  Radivoj Petrovic,et al.  Modelling and simulation of a supply chain in an uncertain environment , 1998, Eur. J. Oper. Res..

[28]  Paul van Beek,et al.  Modelling and simulating multi-echelon food systems , 2000, Eur. J. Oper. Res..

[29]  Erik Johnsen,et al.  Jay W. Forrester: Industrial Dynamics. The M. I. T. Pres. Massachusetts Intistute of Technology and John Wiley & Sons Inc. New York, 1961, 464 sider. , 1962 .

[30]  S. Hestrin,et al.  Electrical synapses between Gaba-Releasing interneurons , 2001, Nature Reviews Neuroscience.

[31]  G. Box,et al.  Some New Three Level Designs for the Study of Quantitative Variables , 1960 .

[32]  M. Naim,et al.  Supply chain dynamics , 1991 .

[33]  Arthur M. Geoffrion,et al.  Twenty Years of Strategic Distribution System Design: An Evolutionary Perspective , 1995 .

[34]  Arianna Alfieri,et al.  Object-oriented modeling and simulation of integrated production/distribution systems , 1997 .

[35]  Derek J. Pike,et al.  Empirical Model‐building and Response Surfaces. , 1988 .

[36]  J. Forrester.  Industrial Dynamics , 1997 .

[37]  Avijit Banerjee,et al.  Heuristic production triggering mechanisms under discrete unequal inventory withdrawals , 1996 .

[38]  James R. Evans,et al.  Blending OR/MS, Judgment, and GIS: Restructuring P&G's Supply Chain , 1997 .

[39]  Charles J. Wilson,et al.  Surround inhibition among projection neurons is weak or nonexistent in the rat neostriatum. , 1994, Journal of neurophysiology.

[40]  M. Naim,et al.  Industrial Dynamics Simulation Models in the Design of Supply Chains , 1992 .