Unsurprisingly, both usage and investment in digital technology, in smaller organizations, indicated higher extent of increase in during and post-pandemic periods when compared to the larger organizations. In addition, a marked difference was observed between the “small” project organizations and the “large” ones. Among the three categories, communication technology indicated higher extent of use as compared to the other two. The results clearly show the increasing level of usage of digital technology in the construction industry from pre-COVID to during COVID and post-COVID periods. The survey included questions on the extent of use and level of investment on the three types of technology in three periods-pre-COVID, during COVID, and post-COVID. The methodology involved conducting a questionnaire survey among the construction professionals in the UAE. For the purpose of this paper, digital technology applications are divided into three groups: data acquisition, processing, and communication. The objective of the study presented in this paper is to investigate how digital technology is making a headway in the construction industry as a consequence of COVID-19. The construction industry has been incorporating digital technology over the last two decades, albeit gradually, as “technology-push” continues to overcome customary and traditional passivity typical in the sector. The developed framework is considered to be a new approach which can automatically estimate the cost of building elements using machine learning-integrated algorithms and MATLAB engine for its effective implementation. This study, therefore, aims to develop an informatics framework to integrate a cost estimation standard with BIM in order to expedite the 5D BIM process and enhance the digital transformation practices in construction projects. As most of the current cost estimation standards are designed and developed based on old-fashioned construction project delivery systems, a lack of compatibility between their classification and BIM-based informatics is observed. Since BIM models are object-based with built-in parametric information, it is easier to capture the quantities of building elements and deliver more accurate estimates with less errors and omissions. However, BIM adoption approaches have attracted significant attention with this respect.
Non-informatics cost estimation is a tedious process and requires substantial amount of time and manual operations. This research provides a clear picture of the leading information and future research trends of the BIM-based coordination, contributing to the body of knowledge theoretically and offering references for related stakeholders practically. Moreover, a framework that presents the existing research gaps and future research directions was proposed. Four emerging research topics were further discussed according to the determined scientific map. To map the representative information in the BIM-based coordination research, the determination and visualization of the most influential scholars, journals, countries/regions, and articles, as well as their importance and relationships, were performed through VOSviewer.
After a comprehensive filtering process, 656 pieces of literature were collected from Scopus. Hence, this study examines the BIM-based coordination literature published from 2006 to 2020 through bibliometric literature searching, scientific mapping, and in-depth critical analysis to fill the research gap.
Recently, there have been numerous studies investigating BIM-based coordination however, no explicit attempt has been made to investigate the current status of relevant research and determine the future directions. Moreover, by conducting a statistical analysis and examining a case study, this paper verifies the accuracy and efficiency of quantity takeoff attained from the proposed BQTCM method and QTCMP.Įnhancing coordination between stakeholders is a critical function of Building Information Modeling (BIM).
This paper proposes a BIM-based quantity takeoff code mapping (BQTCM) method to solve the above issue, and develops a quantity takeoff code mapping plug-in (QTCMP) on a BIM modeling software based on the proposed BQTCM method to obtain an accurate bill of quantities directly and efficiently. Specific construction classification systems embedded in mainstream modeling software for building information modeling (BIM) make it difficult for countries adopting different systems to calculate quantity directly. Theoretically, quantity can be automatically calculated from building information model more quickly and reliably by extracting geometric data and semantic attributes of building elements. Manual quantity takeoff using two-dimensional (2D) drawings and personal knowledge is error-prone and time-consuming.