A new framework to evaluate and optimize digital transformation policies in the construction industry: A China case study. (1st July 2023)

• Record Type: Journal Article
• Authors: Zhang, Jingxiao; Chen, Mengting; Ballesteros-Pérez, Pablo; Ke, Yongjian; Gong, Zhiguo; Ni, Qichang
• Is Part Of: Journal of building engineering. Volume 70(2023)
• Publication Date: 2023-07-01
• Subjects: Digital transformation -- Policy optimization -- Construction industry -- Policy instrument -- PMC-AE index model -- Quantitative evaluation; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2023.106388
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Issuing effective policies to promote the digital transformation of the construction industry in the current digital context is an ongoing concern for many countries. This study aims to explore the policies' focus of digital transformation in the construction industry, identify which policy tools are being used, and what results are being obtained. Then, some optimization paths to improve the policy system for digital transformation in the construction industry are proposed. Based on the theory of policy tools, a theme-instrument-evaluation analysis framework is built. Then, a latent Dirichlet allocation (LDA) theme model, and a policy modeling consistency model with auto encoder (PMC-AE) are used to empirically analyze 82 policies issued between 2017 and 2022. Policy themes include the integration of assembled buildings, digital technology system construction, enterprise transformation and upgrading, and smart platform construction. Regarding instruments, it is found that there is a need for a more demand-based policy instruments, whereas supply-based dominate current policy tools. In terms of policy evaluation, the average rating of 25 policy samples is good, but common problems remain as their short timeliness, unclear needs and single incentives and safeguards. This study expands the analysis framework and index systems of current research on the digital transformation policies aimed at the construction industry. Namely, it improves a theoretically-informed system for the quantitative evaluation of policies which provides concrete suggestions for policy adjustment and optimization. With the latter, governments will be able to formulate more effective digital transformation strategies for the construction industry. Highlights: Propose a new "theme-instrument-evaluation"framework for digital transformation policies. Build a co-occurrence network of high-frequency words for digital transformation policies in the construction industry. Propose specific optimization paths for 4 different levels of policy ratings (excellent, good medium, pass). Common policy problems are short timeliness, unclear needs and single incentives. The Chinese case study indicates that policies improvement must focus on policy instruments, nature and incentives.