A Bargaining Model for a First-Time Interaction Under Asymmetric Beliefs of Supply Reliability

We consider the case of a first-time interaction between a buyer and a supplier who is unreliable in delivery. The supplier declares her estimate of the ability to meet the order obligations, but the buyer may have a different estimate, which may be higher or lower than the suppliers estimate. We derive the Nash bargaining solution and discuss the role of using a down-payment or nondelivery penalty in the contract. For the case of buyer overtrust, the down-payment contract maximizes channel profits when the suppliers estimate is public information. If the suppliers estimate is private information, a nonsymmetric contract is shown to be efficient and incentive compatible. For the case of buyer undertrust, the contract structure is quite different as both players choose not to include down-payments in the contract. When delivery estimates are public information, a nondelivery penalty contract is able to maximize channel profits if the buyer uses the suppliers estimate in making the ordering decision. If estimates are private information, channel profits are maximized only if the true estimates of both players are not far part. We also discuss the effect of different risk profiles on the nature of the bargaining solution. In three extensions of the model, we consider the following variants of the basic problem. First, we analyze the effect of early versus late negotiation on the bargaining solution. Then, we study the case of endogenous supply reliability, and finally, for the case of repeated interactions, we discuss the impact of updating delivery estimates on the order quantity and negotiated prices of future orders.

[1]  Scott A. Neslin,et al.  The Ability of Nash's Theory of Cooperative Games to Predict the Outcomes of Buyer-Seller Negotiations: A Dyad-Level Test , 1986 .

[2]  J. Nash Two-Person Cooperative Games , 1953 .

[3]  Scott A. Neslin,et al.  Nash's Theory of Cooperative Games as a Predictor of the Outcomes of Buyer-Seller Negotiations: An Experiment in Media Purchasing , 1983 .

[4]  Louis W. Stern,et al.  Assessing the Predictive Accuracy of Two Utility-Based Theories in a Marketing Channel Negotiation Context , 1986 .

[5]  J. Lehoczky,et al.  Optimal order policies in assembly systems with random demand and random supplier delivery , 1996 .

[6]  P. Kollock The Production of Trust in Online Markets , 1999 .

[7]  Paul Resnick,et al.  Reputation systems , 2000, CACM.

[8]  Tuomas Sandholm,et al.  Contracting With Uncertain Level Of Trust , 2002, Comput. Intell..

[9]  Hau L. Lee,et al.  Lot Sizing with Random Yields: A Review , 1995, Oper. Res..

[10]  A. Roth Axiomatic models of bargaining , 1979 .

[11]  Ram Akella,et al.  Supply management in assembly systems with random yield and random demand , 2000 .

[12]  F. Webster Industrial Marketing Strategy , 1991 .

[13]  Paul Slovic,et al.  Risk Perception And Trust , 1996 .

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

[15]  A. Muthoo Bargaining Theory with Applications , 1999 .

[16]  R. Kohli,et al.  A cooperative game theory model of quantity discounts , 1989 .

[17]  R. Aumann Agreeing to disagree. , 1976, Nature cell biology.

[18]  Paul Resnick,et al.  Reputation Systems: Facilitating Trust in Internet Interactions , 2000 .

[19]  Yigal Gerchak,et al.  The Structure of Periodic Review Policies in the Presence of Random Yield , 1990, Oper. Res..

[20]  J. Nash THE BARGAINING PROBLEM , 1950, Classics in Game Theory.

[21]  Hector Garcia-Molina,et al.  Making trust explicit in distributed commerce transactions , 1996, Proceedings of 16th International Conference on Distributed Computing Systems.