University of Oulu

Mansoori, S., Haapasalo, H., & Harkonen, J. (2022). Potential of building information modeling in the project lifecycle – reflection against iceberg model. International Journal of Management, Knowledge and Learning, 11. https://doi.org/10.53615/2232-5697.11.85-104

Potential of building information modeling in the project lifecycle : reflection against iceberg model

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Author: Mansoori, Solmaz1; Haapasalo, Harri1; Härkönen, Janne1
Organizations: 1Industrial Engineering and Management (IEM), University of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 3.2 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022102763562
Language: English
Published: ToKnowPress, 2022
Publish Date: 2022-10-27
Description:

Abstract

Purpose: The implementation of building information modeling (BIM) has been previously approached from various perspectives, but confusion regarding BIM’s full potential and on how to apply it remains. The whole is viewed from distinct perspectives to reflect the full potential and explain the tentatively unused potential.

Study design/methodology/approach: The study follows a conceptual research approach in conjunction with a single case study. The BIM iceberg model is utilized as an explanatory synthesis frame to reflect perspectives describing BIM utilization.

Findings: A BIM implementation status framework is developed to describe the BIM utilization maturity in a typical case company. The framework is tested, and indications of support for the logic of the BIM iceberg model are gained. To date, BIM has been used successfully in the early construction project stages (tip of the iceberg, primary BIM). The below-sea-level parts, the collaborative BIM and integrative BIM — the full potential — are rarely recognized.

Originality/value: The presented BIM implementation status shows that there is a gap between the full potential of BIM and the level of BIM utilization in practice.

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Series: International journal of management, knowledge and learning
ISSN: 2232-5107
ISSN-E: 2232-5697
ISSN-L: 2232-5107
Volume: 11
Pages: 85 - 104
DOI: 10.53615/2232-5697.11.85-104
OADOI: https://oadoi.org/10.53615/2232-5697.11.85-104
Type of Publication: A1 Journal article – refereed
Field of Science: 222 Other engineering and technologies
Subjects:
Copyright information: © 2022 Solmaz Mansoori, Harri Haapasalo, Janne Harkonen. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
  https://creativecommons.org/licenses/by-sa/4.0/