A strategic roadmap to overcome blockchain technology barriers for sustainable construction: A deep learning-based dual-stage SEM-ANN approach

Abstract

The adoption of blockchain technology in the sustainable construction industry in India is slow. Existing literature in this area has primarily focused on the potential applications of blockchain technology in construction but little attention is given to the barriers, impeding its adoption. This study fills this research gap by identifying the most significant barriers to adopting blockchain technology for India's sustainable construction industry. The collected data were analyzed via a two-stage PLS-SEM-artificial-neural-network (ANN) predictive analytical approach. In total, 722 construction stakeholder surveys were conducted, and the final model of barriers to adopting blockchain technology for sustainable construction was statistically validated. This study's findings suggest that significant organizational, technological, cultural, legal, security and government barriers limit the adoption of blockchain technology for sustainable construction in India. These findings also imply that effective legislative processes and economic incentives are crucial for ensuring blockchain technology integration into sustainable construction and for efficient implementation of practices. As a further step, a roadmap is developed to support decision-makers in overcoming these barriers in the short, medium, and long terms. Finally, multitiered strategies that construction mapping, sustainability, and integration should be adopted to ensure the successful integration of BT into sustainable construction practices in India.