Frequent ambiguities in contract terms often lead to costly legal disputes and project delays in the construction industry. Large Language Models (LLMs) offer a promising solution, enhancing accuracy and reducing misinterpretations. As studies pointed out, many professionals use LLMs, such as ChatGPT, to assist with their professional tasks at a minor level, such as information retrieval from the Internet and content editing. With access to a construction regulation database, LLMs can automate contract interpretation. However, the lack of Artificial Intelligence tools tailored to industry regulations hinders their adoption in the construction sector. This research addresses the gap by developing and deploying a publicly available specialised chatbot using the ChatGPT language model. The development process includes architectural design, data preparation, vector embeddings, and model integration. The study uses qualitative and quantitative methodologies to evaluate the chatbot’s role in resolving contract-related issues through standardised tests. The specialised chatbot, trained on construction-specific legal information, achieved an average score of 88%, significantly outperforming ChatGPT’s 36%. The integration of a domain-specific language model promises to revolutionise construction practices through increased precision, efficiency, and innovation. These findings demonstrate the potential of optimised language models to transform construction practices.

The Construction Industry (CI) faces disputes that cause several negative impacts such as project delays and cost overruns. Alternative Dispute Resolution (ADR) methods are often recommended in resolving disputes due to their time and cost efficiency. However, with the technological advancements of the CI, it is necessary to incorporate Digital Technologies (DT) for effective dispute resolution. Thus, the study aims to explore the applications of DT in ADR in the CI to address the challenges in the Sri Lankan context. The research aim was accomplished through a quantitative approach by conducting a questionnaire survey with the participation of 37 respondents. Collected data was analysed through descriptive analysis. The findings identified three major causes of construction disputes in the Sri Lankan context contract-related factors, financial and economic factors, and task factors. Further, negotiation was found the most commonly used ADR method in Sri Lanka followed by arbitration and adjudication. Findings indicated that DT such as MS Office Packages, Virtual Online Dispute Resolution (ODR), Building Information Modelling (BIM), and Artificial Intelligence (AI) have high levels of effectiveness in enhancing ADR processes. BIM and Virtual ODR were highly valued for their ability to facilitate visualisation and remote dispute resolution respectively. The study suggests that DT applications can significantly improve ADR processes, enhancing efficiency and decision-making in dispute resolution, and calls for further research on global applicability and ethical implications.

Digital twin technology holds immense potential for the construction industry in developing countries, while providing numerous benefits. Yet, financial, cultural, infrastructural and technological barriers hinder the implementation of digital twin. Researchers have emphasised the importance of considering both visible and invisible barriers of digital twin implementation. ‘Lean Iceberg Model’ (LIM) emphasises that most of the underlying barriers and problems in a project are invisible and unaddressed, and it is critical to solve these underlying issues to achieve effective implementation. The study aims to develop a LIM to minimise barriers for successful digital twin implementation in the Sri Lankan construction industry. This study adopts an interpretivism stance and employs a qualitative research approach. Semi-structured interviews were conducted with 15 experts chosen through purposive sampling. VBA script was employed to analyse the data. LIM highlights the unseen aspects such as leadership, commitment, employee engagement, and organisational strategy as crucial to the successful digital twin implementation. Thus, a comprehensive approach is required to contemplates the technical aspects with the organisation's overall strategy, employee engagement, and leadership commitment. Moreover, cultural values, norms, leadership, and social networks are also examined to determine their impact on digital twin implementation. A framework for minimising the barriers to the implementation of digital twins in the Sri Lankan construction industry using the LIM has been developed incorporating the findings, which will offer valuable insights for construction industry professionals and policymakers interested in implementing digital twin to improve construction project management.

The digital twin (DT) presents an opportunity for the integration of the physical world into the digital world. DT technology has the potential to transform the construction industry and respond to some of its challenges. In conventional construction projects, progress is largely monitored by direct observation and measurement which suffers from numerous challenges, including low productivity, blunders, and poor technology advancements. Concerns are now being raised about integrating technology for autonomously monitoring building activity. In other sectors, DT technology has been responsible for saving product development time and costs by up to 50%. However, DT is still lagging the adoption of new technologies in the construction industry. The overarching aim of this study was to explore the adaptability of DT in construction site progress monitoring. This study comprehensively reviews and analyses DT concepts, technologies, and applications in the construction industry, parameters of applications of DT in construction site progress monitoring, how DT could be used for site progress monitoring in construction, common challenges in the implementation of DT in site progress monitoring, and strategies such as barriers related to DT in site progress monitoring, using literature findings while incorporating qualitative analysis of semi-structured interviews. This research shows that DT has a high potential to solve the numerous challenges in construction site progress monitoring, rather than other current technologies in use. Thus, this study raises awareness and the need for the application of DT in construction site progress monitoring

The Sri Lankan construction industry is facing significant challenges in building construction projects due to the negative impacts of using traditional building materials. Consequently, there has been a surge of interest in sustainable materials, and among them, bioplastics have emerged as a promising alternative. The aim of this study is to investigate the potential of bioplastics as a sustainable building material specifically for the Sri Lankan construction industry. To achieve this, the study applied a qualitative research approach to collect data through semi-structured interviews. The research objectives are to identify alternative sustainable materials used in construction and identify how bioplastics could contribute to the construction industry as ta sustainable material. In addition to that, the study also identifies the motivators and challenges to the use of polymer building materials in Sri Lanka and subsequently develop a framework including potential strategies to use bioplastic as a sustainable construction material. The study's findings have identified significant factors that establish bioplastics as a sustainable material suitable for the Sri Lankan construction sector. Moreover, the research offers valuable recommendations to address challenges related to the adoption of polymer building materials. Furthermore, the study would contribute to the formulation of policies and regulations that promote the use of bioplastics as a sustainable building material.