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https://hdl.handle.net/10356/159622
Title: | New model for identifying critical success factors influencing BIM adoption from precast concrete manufacturers' view | Authors: | Phang, Thomas C. H. Chen, Chen Tiong, Robert Lee Kong |
Keywords: | Engineering::Civil engineering | Issue Date: | 2020 | Source: | Phang, T. C. H., Chen, C. & Tiong, R. L. K. (2020). New model for identifying critical success factors influencing BIM adoption from precast concrete manufacturers' view. Journal of Construction Engineering and Management, 146(4), 04020014-. https://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0001773 | Journal: | Journal of Construction Engineering and Management | Abstract: | The construction industry is embracing the digital transformation to streamline the process from design to build. However, compared with design companies, precast concrete (PC) companies seem to be slow in the adoption of building information modeling (BIM). The paper thus intends to (1) understand the current BIM maturity levels in these companies via a survey among the PC companies; (2) develop a model for identifying critical success factors (CSFs) influencing BIM adoption from PC companies' view; and (3) give recommendations to the PC companies as well as policymakers. From the survey responses of 53 respondents from the PC industry in various countries including Association of Southeast Asian Nations (ASEAN) countries, China, Korea, Taiwan, the Middle East, and Finland, the study successfully identified a total of eight CSFs, which are regarded as the main contributions this research makes to the body of knowledge. Based on these CSFs, recommendations are provided to assist PC companies to become industry innovators. Some additional contributions are (1) a new BIM adoption model, which is a mix of a BIM maturity model and a BIM adopters' model and acted on by driving forces; (2) a new framework (called "PCBIM Hexagon" by the authors) consisting of driving forces from six areas: The government, ecosystem, company, team, process, and BIM software tool; and (3) a new approach for ranking the importance of the factors. | URI: | https://hdl.handle.net/10356/159622 | ISSN: | 0733-9364 | DOI: | 10.1061/(ASCE)CO.1943-7862.0001773 | Schools: | School of Civil and Environmental Engineering | Rights: | © 2020 American Society of Civil Engineers. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | CEE Journal Articles |
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