Blockchain is an innovative and transformative technology for enabling data collaboration across all stages of smart construction. Despite being inherently aligned with the demands of smart construction, blockchain technology has yet to achieve the anticipated level of practical deployment. This persistent gap, evident even within a supportive policy environment, is largely driven by fragmented coordination across construction phases, pervasive information asymmetries, and enduring deficits of trust among stakeholders. The industry remains cautious of this disruptive technology and, by and large, unprepared to implement it. Previous research has predominantly focused on drivers and barriers in a blockchain within the construction industry, with little attempt made to demonstrate the dynamic interactions of stakeholders’ strategic behaviors in its adoption, and has yet to systematically examine stakeholders’ on-chain adoption behaviors in this industry as well as the data collaboration potential unlocked by going on-chain. Therefore, this study accounts for the unsatisfactory state of blockchain implementation by developing an evolutionary game model of on-chain adoption between the owner and the participant, conducting stability analysis, and assessing how key factors shape adoption strategies, thereby revealing the transformative potential of blockchain for interactor data collaboration. The results show that a higher initial on-chain adoption proportion markedly speeds up the achievement of the evolutionarily stable strategy. Moreover, moderate adjustments to regulatory probabilities and reward–penalty intensity by competent authorities and collaborative organizations, together with changes in revenue-sharing and joint investment among stakeholders, significantly affect the attainment of the desired steady state. Appropriate tuning of the data-collaboration spillover coefficient helps curb free-riding. Overall, the study provides guidance for owners and participants to realize blockchain-enabled data collaboration and offers a theoretical basis for designing effective regulatory and compensation mechanisms.
Li et al. (Tue,) studied this question.