BIM performance assessment system using a K-means clustering algorithm

Currently, various guidelines regarding building information modelling (BIM) technology policy are being developed in different countries. However, for many companies, the cost-effectiveness of BIM investment remains unclear. Some studies suggest a return on investment (ROI) as the result of cost-ef...

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Bibliographic Details
Published in:Journal of Asian architecture and building engineering 2021-01, Vol.20 (1), p.78-87
Main Authors: Kim, Hyeon-Seung, Kim, Sung-Keun, Kang, Leen-Seok
Format: Article
Language:English
Subjects:
BIM
BIM performance assessment
K-means clustering
ROI
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Summary:Currently, various guidelines regarding building information modelling (BIM) technology policy are being developed in different countries. However, for many companies, the cost-effectiveness of BIM investment remains unclear. Some studies suggest a return on investment (ROI) as the result of cost-effective analysis calculations, which can be obtained by the introduction of BIM. However, a lack of research has led to inconsistent metrics being applied to the calculation of BIM-ROI for various types of projects. The purpose of this study is to develop a system to evaluate the performance of BIM using a K-means clustering algorithm and ROI analysis to reflect the cost-effectiveness of BIM investment. The proposed system also includes methods for determining best-case projects with high similarities from existing case projects and benchmarking their evaluation know-how, and its usability was verified through experienced BIM users.
ISSN:1346-7581
1347-2852
DOI:10.1080/13467581.2020.1800471