Evolutionary Game Analysis of Construction Workers' Unsafe Behaviors Based on Incentive and Punishment Mechanisms

Abstract

Construction is one of the most dangerous industries because of its open working environment and risky construction conditions. In the process of construction, risk events cause great losses for owners and workers. Most of the risk events are closely related to unsafe behaviors of workers. Therefore, it is of great significance for contractors to establish management measures, e.g., incentive and punishment mechanism, to induce workers to reduce unsafe behaviors. This paper aims to take the incentive and punishment mechanism into consideration and develop an evolutionary game model to improve the effectiveness of safety management. The evolutionary stability strategies which can help reduce unsafe behaviors are obtained and analyzed. Results show that there are 12 equilibrium strategies under the condition of different parameters. Specifically, the incentive and punishment mechanism has played an important role for the evolution direction. A balanced incentive and punishment mechanism for the investment and positive stimulus for workers can effectively promote both sides to take positive behaviors, and then realize good evolutionary stable situations. In addition, the initial perceptions of both sides have a decisive impact on the evolution direction. Strengthening communication with the mutual trust between both sides can improve safety performance of both sides. This study is valuable for contractors to design appropriate incentive and punishment measures and establish relevant strategies to promote safe behaviors of construction workers.

Keywords: construction workers; evolutionary game; incentive and penalty; mechanism design; unsafe behavior.

Figure 1

The dynamic evolutionary path of the game in category 1, including low safety costs to workers (A), high safety costs to workers (C), and medium safety costs to workers (B).

Figure 2

The dynamic evolutionary path of the game in category 2, including low safety costs to workers (A), high safety costs to workers (C), and medium safety costs to workers (B).

Figure 3

The dynamic evolutionary path of the game in sub-category 3-1, including low safety costs to workers (A), high safety costs to workers (C), and medium safety costs to workers (B).

Figure 4

The dynamic evolutionary path of the game in sub-category 3-2, including low safety costs to workers (A), high safety costs to workers (C), and medium safety costs to workers (B).

Figure 5

The evolutionary trajectories of (0.1,0.1) (A), (0.2,0.6) (B), and (0.7,0.3) (C) in scenario 1.

Figure 6

The evolutionary trajectories of (0.1,0.1) (A), (0.2,0.6) (B) and (0.7,0.3) (C) in scenario 2.

Figure 7

The evolutionary trajectories influenced by F.

Figure 8

The evolutionary trajectories influenced by R.

Figure 9

The evolutionary trajectories influenced by G.