A study on incentive mechanism of the large-scale construction performance audit based on the computational experiment

Abstract

The characteristics of large-scale constructions, such as multi-agent, multi-stage and multi-target have brought great difficulties to improve the construction's performance.This paper builds a computational experiment model of the incentive mechanism, and simulates the behavioral strategies of all participants by using computational experiment artificial system. The experiment results show that: the incentive mechanism of performance audit can optimize the project's performance to a certain extend; in the single-period audit, the subcontractors are more sensitive to the incentive level, and show a strong risk aversion characteristic; while in the multi period audit, the incentive level lose effectiveness on improving the constructions' performance, it's more critical to take the individual's equity preference into consideration.