Building information modeling (BIM) adoption for enhanced legal and contractual management in construction projects

The Internet of Things is a comprehensive system of connected computing devices and sensors that provide extensive data sharing capability for any specific purpose. For the construction industry, the applications of the Internet of Things have been increasing over the past few years, and it is because technology can provide full support to construction projects in attaining significant efficiency. The most critical part of construction products where the internet of things can be adopted is safety management because hundreds of accidents happen every year that result in significant injuries to construction workers and even death in some cases. For small construction projects, the situation is much worse, as there are never enough resources to adopt the latest technology, such as the Internet of Things. This study is structured with the aim of identifying the critical implementation barriers of the internet of things that affect small construction projects in Malaysia specifically. A mixed methodology study design is followed in which, after identifying the implementation barriers of the internet of things from existing literature, they are filtered with expert opinion. A pilot survey was conducted on which exploratory factor analysis was applied to further identify the significant barriers relating to the Internet of Things in small construction projects in Malaysia. A main survey was conducted afterwards, on which the structural equation modelling was done to develop the model involving the final 16 barriers divided into 5 formative constructs. The most critical barriers are found to be related to databases and technology, while the least impact is created by management barriers. Positive theoretical and managerial implications are indicated for future researchers and construction workers, respectively, by which they can improve the implementation of internet of things in small construction projects in Malaysia.

Oil and gas construction projects are critical for meeting global demand for fossil fuels, but they also present unique risks and challenges that require innovative construction approaches. Artificial Intelligence (AI) has emerged as a promising technology for tackling these challenges, and this study examines its applications for sustainable development in the oil and gas industry. Using a systematic literature review (SLR), this research evaluates research trends from 2011 to 2022. It provides a detailed analysis of how AI suits oil and gas construction. A total of 115 research articles were reviewed to identify original contributions, and the findings indicate a positive trend in AI research related to oil and gas construction projects, especially after 2016. The originality of this study lies in its comprehensive analysis of the latest research on AI applications in the oil and gas industry and its contribution to developing recommendations for improving the sustainability of oil and gas projects. This research’s originality is in providing insight into the most promising AI applications and methodologies that can help drive sustainable development in the oil and gas industry.

Building information modeling (BIM) application in construction projects is considered beneficial for effective decision making throughout the project lifecycle, as it maximizes benefits without compromising practicality. The Malaysian construction industry is also keen on the adoption of BIM culture. However, various identified and unidentified barriers are hindering its practical implementation. In light of this, this study identified and analyzed critical obstacles to using BIM in Malaysian small construction projects. Through the use of semi-structured interviews and a pilot study using the exploratory factor analysis (EFA) method, the critical BIM barriers (CBBs) have been identified. Based on the findings of the EFA, CBBs were classified into five categories, i.e., technical adoption barrier, behavioral barrier, implementation barrier, management barrier, and digital education barrier. Following the questionnaire survey, feedback of 235 professionals was collected with vested interests in the Malaysian construction business, and the CBBs model was created using analysis of moment structures (AMOS). The findings revealed that although Malaysian experts with little experience in practice were fairly educated about BIM, technical adoption barriers, behavioral barriers, management barriers, and implementation hurdles were critical for adopting BIM. The study’s findings will help policymakers eliminate CBBs and use BIM in Malaysia’s modest construction projects to save costs, save time, boost productivity, and improve quality and sustainability.