Share:


Building information modeling acceptance and readiness assessment in Taiwanese architectural firms

    Yi-Kai Juan Affiliation
    ; Wan-Ying Lai Affiliation
    ; Shen-Guan Shih Affiliation

Abstract

Building information modeling (BIM) has received considerable recognition in the architecture, engineering, and construction (AEC) industry because it can potentially reduce costs and delivery time and improve quality. Conscious of the benefits derived by adopting BIM, the Taiwanese government is planning to enact a policy that would incorporate BIM-based e-submission into the Taiwanese building permit review process, revolutionizing the local AEC industry. Nevertheless, the effects of BIM application are unpredictable. The aim of this study was to investigate the current status of BIM adoption in 224 Taiwanese architectural firms, assess how accepting and ready the firms were to implement BIM, and create a predictive model that can be used by decision makers who are considering adopting BIM. The results revealed that approximately one-third of the firms surveyed had already adopted BIM-based tools. More than half of the firms were willing to use BIM-based tools to streamline the building permit review process; however, their willingness was strongly influenced by governmental policies, competitor motivation, financial incentives, and technological support. The challenges, problems, and opportunities related to adopting BIM were discussed. Lessons learned from the experiences of the Taiwanese firms may be useful to firms facing similar situations and challenges in other countries.


First published online: 27 Jun 2016

Keyword : building information modeling (BIM), building permit review process, architectural firms, organizational readiness, technology acceptance, artificial neural network (ANN)

How to Cite
Juan, Y.-K., Lai, W.-Y., & Shih, S.-G. (2017). Building information modeling acceptance and readiness assessment in Taiwanese architectural firms. Journal of Civil Engineering and Management, 23(3), 356-367. https://doi.org/10.3846/13923730.2015.1128480
Published in Issue
Mar 2, 2017
Abstract Views
1641
PDF Downloads
2201
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.