Liu, R; Du, J; Issa, R R A and Giel, B (2017) BIM cloud score: Building information model and modeling performance benchmarking. Journal of Construction Engineering and Management, 143(4): 04016109, ISSN 0733-9364
Abstract
The rapid adoption of building information modeling (BIM) in the architecture, engineering, construction, and operations (AECO) industry in recent years has resulted in large differences in the level of BIM adoption and application among organizations. AECO stakeholders, including owners, general contractors, and designers, do not have a benchmark system for them to understand their own performance and know how to improve themselves. A cloud-based BIM performance benchmarking application, BIM Cloud Score (BIMCS), has been proposed to collect BIM performance data from BIM users nationwide in order to allow them to compare their BIM performance with the results collected from their industry peers. This research aims to develop and validate an initial list of metrics that are suitable for the proposed BIM benchmarking application. A survey was conducted in the AECO industry and included BIM authors (architects) and users (contractors) to validate the proposed initial list of metrics. The responses from the survey were used for initializing the metric weights for the benchmarking system. In addition, an analysis of the differences in perception among different groups of respondents showed that out of 26 variables used, the perceived importance of 6 variables was statistically different between BIM authors and BIM users. This result indicates that the surveyed architects and contractors were in agreement with the importance level for most of the variables proposed including model usefulness, model economy, and model productivity. Future adjustments of the metric weights might be needed in the implementation based on the different intended purposes for the BIM models.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | benchmarking; building information modeling; information technologies; performance evaluation; productivity |
| Index terms: | general contractor, survey, performance evaluation, benchmarking, information technology, building information modelling, productivity, owner, designer, architect, implementation, modelling |
| Subjects: | practitioner, computing systems, profession, data collection methods, analytical methods, contractual arrangements, performance measurement, management, information systems, sociology |
| Topics: | Procurement, Stakeholder Management, Roles and Professions, Research Practice, Engineering Principles, Business Strategy, Quality Management, Digital Applications |
| Descriptive scope: | 3 PCE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here