PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
August 10, 2013Journal of Management in Engineering275 citations

BIM Acceptance Model in Construction Organizations

View Full Paper
SLSeulki LeeJYJung-Ho YuHJH. David Jeong

Key Points

Key points are not available for this paper at this time.

Abstract

Substantial research has been performed on the data standards and exchanges in the Architectural, Engineering, Construction/Facility Management (AEC/FM) industry over the past several years. The growing popularity of building information modeling (BIM) technology is based heavily upon the perception that it can facilitate the sharing and reuse of information during a project life cycle. Although many researchers and practitioners are in agreement about the potential applicability and benefit of BIM in construction, it is still unclear why BIM is adopted, and what factors enhance implementation of BIM. Thus, BIM acceptance and use remains a central concern of BIM research and practice. Therefore, we propose an acceptance model for BIM in construction organizations using structural equation modeling (SEM). The key components, including the BIM acceptance model (BAM), are identified through a literature review about technology acceptance-behavior related theories, and was then consolidated by interviews and pilot studies with professionals in the construction industry. Based on the components, a questionnaire was designed and sent out to workers in construction organizations (such as contractors, architects, construction managers, and engineers) in South Korea. A total of 114 completed questionnaires were retrieved. We used SEM for hypothesis testing. The validated BAM can serve as a foundation for positioning and comparing BIM acceptance research and provides users with a framework for evaluating BIM acceptance.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Lee et al. (2013) studied this question.

synapsesocial.com/papers/69d917e2ccb0bba5a56840fdhttps://doi.org/10.1061/(asce)me.1943-5479.0000252
Ask AI
Helpful
Bookmark
Share
View Full Paper