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Purpose

Urban public safety is increasingly important and engineering safety risk monitoring is a key link in this area, where information asymmetry exists. Given the technological advantages of blockchain, it is of great significance for engineering safety supervision. This study aims to reveal the behavioral evolution patterns of multiple entities in the process of engineering safety risk monitoring under blockchain technology and to discuss the mechanism of action of blockchain technology on engineering safety risk monitoring.

Design/methodology/approach

By integrating prospect theory and mental accounting, a game model involving construction companies, third-party monitoring units and government regulatory departments under blockchain technology is established. With numerical analysis, a comparative analysis is conducted before and after the introduction of blockchain technology.

Findings

The results show that under the influence of complexity factors, blockchain technology effectively resolves the problem of information asymmetry and creates a stricter regulatory environment. The introduction of blockchain technology changes the strategic preferences and decision-making speed of the game participants, thereby enhancing the effectiveness and efficiency of engineering safety risk monitoring. In addition, countermeasure suggestions, marginal contributions and future prospects are also presented.

Originality/value

The possible marginal contributions of this paper are mainly in three aspects: First, it expands previous studies on decision-making behavior in engineering safety risk monitoring, constructs an evolutionary game model among construction enterprises, third-party monitoring institutions and government regulatory departments under blockchain technology and analyzes the stability of different strategies. Second, it uses prospect theory and mental accounting to depict the psychological motivations and subjective emotions behind the decision-making behavior of construction enterprises, third-party monitoring institutions and government regulatory departments, profoundly showing the evolutionary trends of multi-agent decision-making behavior under blockchain. Third, it establishes game analysis models, compares the differences in multi-agent decision-making behavior before and after the introduction of blockchain and further proposes countermeasure suggestions.

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