Moral hazard problem and collaborative coordination in supply chain with capacity reservation contract

Abstract

This paper has considered collaborative coordination in supply chains with capacity reservation contracts using the game theory. In some traditional papers, the capacity reservation contracts have contained a capacity quantity, a reservation quantity and a reservation fee as a decision variable. Each decision variable is determined separately based on individual profit functions of a supplier and a manufacturer under the noncooperative game theory. Those papers have assumed that the supplier is always forced to build sufficient capacity to cover the reservation amount of the manufacturer. However, the supplier might not always comply with the reservation amount of the manufacturer since the capacity quantity is a private decision in the supplier and not released to external companies in practice. For instance, the supplier may choose to under-build knowingly to ensure high utilisation of his capacity. This is a kind of moral hazard problems. This paper has investigated such a strategy that the supplier and manufacturer voluntarily comply with the contract for the purpose of solving the moral hazard problem in the capacity reservation contract. Consequently, we have proposed a method of determining the decision variables collaboratively in the contract such that a consensus of the supplier and manufacturer is built.

Keywords:

• forced and voluntary compliance regimes
• incentive compatible condition
• moral hazard problem
• Nash bargaining approach
• penalty strategy

Acknowledgments

The authors would like to thank the Editor and referees very much for their helpful, useful, and constructive comments and suggestions regarding this article. The authors would like to appreciate the grant for our research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI [grant number 17K01266]: ‘The investigation of data visualisation and its application to production and operation management’.