Mean-variance analysis of Quick Response Program ☆

Abstract Quick Response Program (QRP) has been well established in fashion supply chains. It is known that QRP may not be equally good to all channel members and some measures have to be taken in order to achieve a win–win situation. However, little is known about the corresponding level of risk associated with QRP and some proposed measures. In light of this, we study QRP via a mean-variance (MV) approach. We illustrate how the measures such as price commitment policy, service-level commitment policy, and buy-back policy can be adjusted to achieve the MV win–win situation in which the channel members can be better off with considerations of both expected profit and risk. Numerical analyses are included and the analytical conditions for achieving both the supply chain channel coordination and the MV win–win situation are derived. Managerial insights are generated.

[1]  Amrik S. Sohal,et al.  Quick Response supply chain alliances in the Australian textiles, clothing and footwear industry , 1999 .

[2]  Dimitrios Vlachos,et al.  An inventory system with two supply modes and capacity constraints , 2001 .

[3]  Li Yao,et al.  A newsvendor pricing game , 2004, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[4]  Amy Hing-Ling Lau,et al.  Reordering strategies for a newsboy-type product , 1997 .

[5]  Katy S. Azoury,et al.  A Comparison of the Optimal Ordering Levels of Bayesian and Non-Bayesian Inventory Models , 1984 .

[6]  Katy S. Azoury Bayes Solution to Dynamic Inventory Models Under Unknown Demand Distribution , 1985 .

[7]  Hon-Shiang Lau The Newsboy Problem under Alternative Optimization Objectives , 1980 .

[8]  Tsan-Ming Choi,et al.  Quick response in fashion supply chains with dual information updating , 2006 .

[9]  D. Lambert,et al.  Fundamentals of Logistics Management , 1998 .

[10]  Tsan-Ming Choi,et al.  Optimal two-stage ordering policy with Bayesian information updating , 2003, J. Oper. Res. Soc..

[11]  Ananth V. Iyer,et al.  Improved Fashion Buying with Bayesian Updates , 1997, Oper. Res..

[12]  J. Spengler Vertical Integration and Antitrust Policy , 1950, Journal of Political Economy.

[13]  Tsan-Ming Choi,et al.  Optimal single ordering policy with multiple delivery modes and Bayesian information updates , 2004, Comput. Oper. Res..

[14]  David F. Pyke,et al.  Exploiting timely demand information to reduce inventories , 1996 .

[15]  H. Scarf Bayes Solutions of the Statistical Inventory Problem , 1959 .

[16]  Young-Jun Son,et al.  Effect of information update frequency on the stability of production–inventory control systems , 2007 .

[17]  Tsan-Ming Choi,et al.  Mean–Variance Analysis for the Newsvendor Problem , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[18]  Kumar Rajaram,et al.  The Benefits of Advance Booking Discount Programs: Model and Analysis , 2004, Manag. Sci..

[19]  Jian Chen,et al.  A coordination mechanism for a supply chain with demand information updating , 2006 .

[20]  J. Kiefer,et al.  The Inventory Problem: II. Case of Unknown Distributions of Demand , 1952 .

[21]  Jen Tang,et al.  Determination of burn‐in parameters and residual life for highly reliable products , 2003 .

[22]  T. C. Edwin Cheng,et al.  The impact of information sharing in a two-level supply chain with multiple retailers , 2005, J. Oper. Res. Soc..

[23]  Houmin Yan,et al.  Optimal returns policy for supply chain with e-marketplace , 2004 .

[24]  Suresh P. Sethi,et al.  Information Updated Supply Chain with Service-Level Constraints , 2005 .

[25]  Kumar Rajaram,et al.  Optimizing Inventory Replenishment of Retail Fashion Products , 2001, Manuf. Serv. Oper. Manag..

[26]  Ananth V. Iyer,et al.  Backup agreements in fashion buying—the value of upstream flexibility , 1997 .

[27]  Ananth V. Iyer,et al.  Quick Response in Manufacturer-Retailer Channels , 1997 .

[28]  Sifeng Liu,et al.  Supply-Chain Coordination With Combined Contract for a Short-Life-Cycle Product , 2006, IEEE Trans. Syst. Man Cybern. Part A.

[29]  Kumar Rajaram,et al.  Advance Booking Discount Programs Under Retail Competition , 2004, Manag. Sci..

[30]  R. Posner Vertical Restraints and Antitrust Policy , 2005 .

[31]  E. Silver,et al.  A Bayesian Analysis of the Style Goods Inventory Problem , 1966 .

[32]  Tsan-Ming Choi,et al.  Production , Manufacturing and Logistics Quick response policy with Bayesian information updates , 2005 .

[33]  Marshall L. Fisher,et al.  Reducing the Cost of Demand Uncertainty Through Accurate Response to Early Sales , 1996, Oper. Res..

[34]  Tong Heng Lee,et al.  HinftyOutput Tracking Control for Nonlinear Systems via T-S Fuzzy Model Approach , 2006, IEEE Trans. Syst. Man Cybern. Part B.

[35]  K. Donohue Efficient Supply Contracts for Fashion Goods with Forecast Updating and Two Production Modes , 2000 .

[36]  Özalp Özer,et al.  Integrating Replenishment Decisions with Advance Demand Information , 2001, Manag. Sci..

[37]  Christopher S. Tang,et al.  Optimal Ordering Decisions with Uncertain Cost and Demand Forecast Updating , 1999 .

[38]  Hag‐Soo Kim A Bayesian analysis on the effect of multiple supply options in a quick response environment , 2003 .

[39]  T. Choi Pre-season stocking and pricing decisions for fashion retailers with multiple information updating , 2007 .

[40]  Tsan-Ming Choi,et al.  Mean-variance analysis of a single supplier and retailer supply chain under a returns policy , 2008, Eur. J. Oper. Res..

[41]  W. Lovejoy Myopic policies for some inventory models with uncertain demand distributions , 1990 .