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Soft Computing

, Volume 22, Issue 17, pp 5593–5602 | Cite as

Project duration contract design problem under uncertain information

Focus

Abstract

A suitable and attractive contract may bring large profits and lower the risk caused by uncertain information in project management; thus, how to design incentive contracts under uncertainty has been the most pressing demand for the owner. This paper investigates the project incentive contract design problem with random asymmetric information, in which a risk-neutral owner (he) engages a risk-averse contractor (she) to complete a project. The contractor’s construction capacity is private information and characterized as a random variable. Furthermore, two incentive contracts, duration-based contract and deadline-based contract, are designed, where the owner offers a fixed payment and a penalty or bonus factor based on the real project duration and a predetermined deadline for the contractor in these two different contracts. Then, a project duration contract and a deadline-based contract model are developed with the purpose of maximizing the owner’s expected payoff, respectively. The optimal contracts are investigated, and the values of the contractor’s construction capacity information for the owner under these two contracts are quantified. The results show that the owner benefits better from getting more construction capacity information and should commit an information rent to the contractor due to asymmetric information, which distorts the penalty factor under both contracts. Moreover, regardless of contract type, the deadline has no effects on the owner’s incentive term and only affects the fixed payments. Further, the contractor is more likely to keep information private, while the owner benefits more from knowing the contractor’s construction capacity when the deadline-based contract is used.

Keywords

Project duration Incentive contract Asymmetric information Deadline Random variable 

Notes

Compliance with ethical standards

Conflict of interest

All authors have no conflict of interest.

Human participants

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.School of Economics and ManagementBeijing Jiaotong UniversityBeijingChina

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