Comparative analysis of the barriers to smart sustainable practices adoption in the construction industry between Hong Kong and Nigeria

Chan, Daniel W.M.; Olawumi, Timothy O.; Saka, Abdullahi B.; Ekundayo, Damilola

Abstract

The deployment of digital systems has facilitated process improvement in building construction, including for green practices implementation. However, it has encountered several challenges that have limited its use and hindered the diffusion of sustainable practices. Hence, this study aims to identify and assess the major barriers to smart-sustainable practices (SSP) adoption and evaluate its likely impact. A quantitative research method using empirical questionnaire surveys to solicit stakeholders' perceptions in Hong Kong and Nigeria to understand whether there is a commonality in the identified barriers between the two contexts. The collated data were analysed using descriptive statistics such as mean and inferential statistics (factor analysis), while fuzzy synthetic evaluation was used to develop the predictive models. Using non-probability sampling techniques, 97 and 69 responses were gotten from respondents in Hong Kong and Nigeria, respectively. The results revealed that workforce expertise, hesitancy to change from working practices, technical know-how, and inadequate understanding of the SSP process as the most critical barriers to SSP diffusion in Hong Kong and Nigeria. Also, impact evaluation models were developed as a predictive tool to evaluate and respond to the impact of these barriers. It is recommended for industry practitioners and policymakers to collaborate to create local context-based guidelines for facilitating SSP diffusion and monitor its implementation.

Citation

Chan, D. W., Olawumi, T. O., Saka, A. B., & Ekundayo, D. (in press). Comparative analysis of the barriers to smart sustainable practices adoption in the construction industry between Hong Kong and Nigeria. International journal of construction management, https://doi.org/10.1080/15623599.2022.2108973

• Journal Article Type: Article
• Acceptance Date: Jul 29, 2022
• Online Publication Date: Aug 17, 2022
• Deposit Date: Aug 24, 2022
• Publicly Available Date: Aug 24, 2022
• Journal: International journal of construction management
• Print ISSN: 1562-3599
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1080/15623599.2022.2108973
• Keywords: barrier, BIM, construction industry, digital system, predictive tool, sustainability practices, fuzzy synthetic evaluation
• Public URL: http://researchrepository.napier.ac.uk/Output/2894660