Review of Previous Research Methods in Evaluating BIM Investments in the AEC Industry

Building Information Modeling (BIM) provides many recognized benefits and becomes the most promising technology in the AEC industry. However, many construction companies are still hesitant to invest in this technology. The lack of information about the financial benefits of BIM implementation against the high cost of investment incurred is one of the obstacles in BIM practice. Therefore, stakeholders need to be encouraged by empirical evidence regarding the financial benefits that BIM presents. Over the last ten years (2010–2020) identified there were 16 studies on the topic of BIM investment. This study using the literature review method aims to review and map the methods used in the studies. The results of this study show that quantitative research with secondary data, case studies, and Return on Investment (ROI) is the most widely used method. However, ROI is still considered incapable of capturing the overall costs and benefits. Therefore, Cost benefit analysis (CBA) becomes the solution to the gap because it can measure intangible benefits and indirect costs as well as a combination with systems dynamic that can be modeling the financial implications arising from BIM investment. The confidentiality of construction cost data and the lack of ability to track BIM project data are among the obstacles when conducting CBA. Therefore, to address the problem two recent studies published in 2020 propose predictive methods using artificial intelligence (AI) approaches to predict the net costs and benefits of BIM implementation. The findings of this study can be used as a guideline for further research methodologies in evaluating and justifying BIM investment to encourage greater adoption of technology in the AEC industry.