Analysis of supply contracts with commitments and flexibility

In this article we address an important class of supply contracts called the Rolling Horizon Flexibility (RHF) contracts. Under such a contract, at the beginning of the horizon a buyer has to commit requirements for components for each period into the future. Usually, a supplier provides limited flexibility to the buyer to adjust the current order and future commitments in a rolling horizon manner. We present a general model for a buyer's procurement decision under RHF contracts. We propose two heuristics and derive a lower bound. Numerically, we demonstrate the effectiveness of the heuristics for both stationary and non-stationary demands. We show that the heuristics are easy to compute, and hence, amenable to practical implementation. We also propose two measures for the order process that allow us to (a) evaluate the effectiveness of RHF contracts in restricting the variability in the orders, and (b) measure the accuracy of advance information vis-a-vis the actual orders. Numerically we demonstrate that the order process variability decreases significantly as flexibility decreases without a dramatic increase in expected costs. Our numer- ical studies provide several other managerial insights for the buyer; for example, we provide insights into how much flexibility is sufficient, the value of additional flexibility, the effect of flexibility on customer satisfaction (as measured by fill rate), etc. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 55: 459-477, 2008

[1]  Ravi Anupindi,et al.  Analysis of supply contracts with total minimum commitment , 1997 .

[2]  Dmitry Krass,et al.  Analysis of supply contracts with minimum total order quantity commitments and non-stationary demands , 2001, Eur. J. Oper. Res..

[3]  Ramesh Srinivasan,et al.  Design of component-supply contract with commitment-revision flexibility , 1997, IBM J. Res. Dev..

[4]  Kamran Moinzadeh,et al.  Adjustment Strategies for a Fixed Delivery Contract , 2000, Oper. Res..

[5]  David Thomas,et al.  The Art in Computer Programming , 2001 .

[6]  R. Tyrrell Rockafellar,et al.  Convex Analysis , 1970, Princeton Landmarks in Mathematics and Physics.

[7]  William S. Lovejoy,et al.  Quantity Flexibility Contracts and Supply Chain Performance , 1999, Manuf. Serv. Oper. Manag..

[8]  S. Nahmias,et al.  Modeling Supply Chain Contracts: A Review , 1999 .

[9]  Ravi Anupindi,et al.  Supply Contracts with Quantity Commitments and Stochastic Demand , 1999 .

[10]  Vineet Padmanabhan,et al.  Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect" , 1997, Manag. Sci..

[11]  D. Simchi-Levi,et al.  The impact of exponential smoothing forecasts on the bullwhip effect , 2000 .

[12]  Boaz Golany,et al.  Supplier-Retailer Flexible Commitments Contracts : A Robust Optimization Approach , 2003 .

[13]  Awi Federgruen,et al.  An Inventory Model with Limited Production Capacity and Uncertain Demands I. The Average-Cost Criterion , 1986, Math. Oper. Res..

[14]  A. Tsay The Quantity Flexibility Contract and Supplier-Customer Incentives , 1999 .

[15]  Awi Federgruen,et al.  An Inventory Model with Limited Production Capacity and Uncertain Demands II. The Discounted-Cost Criterion , 1986, Math. Oper. Res..

[16]  Alan Scheller-Wolf,et al.  Reducing International Risk through Quantity Contracts , 1998 .

[17]  Dimitri P. Bertsekas,et al.  Dynamic Programming: Deterministic and Stochastic Models , 1987 .

[18]  Ravi Anupindi,et al.  Approximations for multiproduct contracts with stochastic demands and business volume discounts: single supplier case , 1998 .

[19]  Yehuda Bassok,et al.  Coordination and Flexibility in Supply Contracts with Options , 2002, Manuf. Serv. Oper. Manag..