Chapter
Mar 29, 2018

Predicting BIM Maturity Based on Learning Curve Model at Firm Level

Publication: Construction Research Congress 2018

Abstract

The benefits of building information modeling (BIM) have been recognized by many construction companies over past years. Due to daily advancement in BIM, users need to improve their BIM skills and learn its recent developments and changes to earn more benefits for their companies. Currently, BIM-based research mainly focuses on how to improve the short-term benefits at a project level and their majorities are concerned on measuring the benefits of BIM through making a comparison between projects implemented with BIM and those without BIM implementation. However, such research has not well discussed the appropriate investment and training strategy of BIM implementation at firm’s perspectives. In response, this paper develops a BIM maturity prediction (BMP) model that predicts the learning trend of a BIM model for a specific organization based on the current resources and training strategies of the organization. The results of implementing of the developed model on a case study show the effectiveness of the model to predict the learning trend. This model benefits the BIM domain by helping managers understand the current and future BIM maturity level of their teams.

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Go to Construction Research Congress 2018
Construction Research Congress 2018
Pages: 273 - 284

History

Published online: Mar 29, 2018

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Ph.D. Student, Durham School of Architectural Engineering and Construction, Univ. of Nebraska-Lincoln, PKI 104A, Omaha, NE 68182; Project Engineer, Jacobs Engineering Group, 4041 N 72nd St., Omaha, NE 68134. E-mail: [email protected]; [email protected]
Stuart Bernstein [email protected]
Associate Professor, Durham School of Architectural Engineering and Construction, Univ. of Nebraska-Lincoln, PKI 104A, Omaha, NE 68182. E-mail: [email protected]
Zhexiong Shang [email protected]
Ph.D. Candidate, Durham School of Architectural Engineering and Construction, Univ. of Nebraska-Lincoln, NH 122, Lincoln, NE 68588. E-mail: [email protected]
Hamed Nabizadeh Rafsanjani, S.M.ASCE [email protected]
Ph.D. Candidate, Durham School of Architectural Engineering and Construction, Univ. of Nebraska-Lincoln, NH 113, Lincoln, NE 68588. E-mail: [email protected]

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