From Industry 4.0 to Construction 4.0: barriers to the digital transformation of engineering and construction sectors

Abstract

Purpose

The purpose of this study is to systematically identify, assess, and categorize the barriers to digital transformation (DT) in the engineering and construction sectors, and thus to better understand the impact and how these sectors might be overcome.

Design/methodology/approach

This study adopted a sequential mixed qualitative and quantitative data collection and analysis approach. DT barriers were first identified from relevant literature and verified by an expert panel. Then, a questionnaire survey assessing the impacts of the identified DT barriers was distributed to construction professionals in China, and 192 valid responses were retrieved. Further, the data obtained were analyzed using ranking analysis, exploratory factor analysis (EFA), and partial least squares-structural equation modeling (PLS-SEM).

Findings

Based on the ranking analysis, the top three barriers are “lack of industry-specific standards and laws,” “lack of clear vision, strategy and direction for DT,” and “lack of support from top management for DT.” EFA enabled the grouping of the 26 barriers into 3 categories: (1) lack of laws and regulations (LLR), (2) lack of support and leadership (LSL), and (3) lack of resources and professionals (LRP). The PLS-SEM analysis revealed that LLR, LSL, and LRP were found to have significant negative impacts on DT.

Originality/value

These findings contribute to the body of knowledge on DT in the construction industry and help construction firms and government bodies improve the understanding of these barriers to DT and put forward relevant policies and incentives, thus seizing the DT benefits as a way to enhance construction project management.

Citation

Wang, K., Guo, F., Zhang, C. and Schaefer, D. (2024), "From Industry 4.0 to Construction 4.0: barriers to the digital transformation of engineering and construction sectors", Engineering, Construction and Architectural Management, Vol. 31 No. 1, pp. 136-158. https://doi.org/10.1108/ECAM-05-2022-0383