Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC Industry
The construction industry is considered as one of the least productive, highest energy consuming, and least digitized industries. The Lean Management (LM) philosophy became a significant way for eliminating non-value-added activities and wastes during a building’s lifecycle. However, studies have sh...
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doaj-a76c582349b2411fb2e71949c689ebd52021-09-26T01:27:49ZengMDPI AGSustainability2071-10502021-09-0113100291002910.3390/su131810029Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC IndustryGökhan Demirdöğen0Nihan Sena Diren1Hande Aladağ2Zeynep Işık3Department of Civil Engineering, Yildiz Technical University, Davutpaşa Caddesi, 34220 İstanbul, TurkeyDepartment of Civil Systems Engineering, Technical University Berlin, 13355 Berlin, GermanyDepartment of Civil Engineering, Yildiz Technical University, Davutpaşa Caddesi, 34220 İstanbul, TurkeyDepartment of Civil Engineering, Yildiz Technical University, Davutpaşa Caddesi, 34220 İstanbul, TurkeyThe construction industry is considered as one of the least productive, highest energy consuming, and least digitized industries. The Lean Management (LM) philosophy became a significant way for eliminating non-value-added activities and wastes during a building’s lifecycle. However, studies have shown that philosophies are not efficient by themselves to solve the issues of the construction industry. They need to be supported with the appropriate technologies and tools. Therefore, the integrated use of Building Information Modelling (BIM) with LM or Value Engineering (VE) were proposed in the literature. Nonetheless, it was also seen that BIM can provide more insights and improvements when BIM is integrated with data analysis tools to analyze BIM data. In the literature, the synergies between these concepts are generally addressed pairwise, and there is no comprehensive framework which identifies their relationships. Therefore, this study aims to develop a maturity framework that facilitates the adoption of LM, VE, BIM, and Big Data Analytic (BDA) concepts to address long-standing productivity and digitalization issues in the Architecture, Engineering, and Construction (AEC) industry. Design Science Research (DSR) methodology and its three-cycle view (relevance, rigor, and design cycle) were applied to build the proposed maturity framework. Two interviews were performed to identify and observe research problem in relevance cycle. In the rigor cycle, a comprehensive literature review was performed to create a base for the development of the maturity framework. In addition to the developed base of the framework, lean processes were added to this cycle. In the design cycle, the developed framework was evaluated and validated by five experts through face-to-face interviews. The importance of employer’s requirements to adopt the proposed methodologies, the negative impact of change orders, the importance of pre-construction phases to facilitate value creation and waste elimination, and the usage of common data environment with BIM were identified as the prominent application and adaptation issues.https://www.mdpi.com/2071-1050/13/18/10029lean managementvalue engineeringbuilding information modelingbig data analytic |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gökhan Demirdöğen Nihan Sena Diren Hande Aladağ Zeynep Işık |
spellingShingle |
Gökhan Demirdöğen Nihan Sena Diren Hande Aladağ Zeynep Işık Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC Industry Sustainability lean management value engineering building information modeling big data analytic |
author_facet |
Gökhan Demirdöğen Nihan Sena Diren Hande Aladağ Zeynep Işık |
author_sort |
Gökhan Demirdöğen |
title |
Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC Industry |
title_short |
Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC Industry |
title_full |
Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC Industry |
title_fullStr |
Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC Industry |
title_full_unstemmed |
Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC Industry |
title_sort |
lean based maturity framework integrating value, bim and big data analytics: evidence from aec industry |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2021-09-01 |
description |
The construction industry is considered as one of the least productive, highest energy consuming, and least digitized industries. The Lean Management (LM) philosophy became a significant way for eliminating non-value-added activities and wastes during a building’s lifecycle. However, studies have shown that philosophies are not efficient by themselves to solve the issues of the construction industry. They need to be supported with the appropriate technologies and tools. Therefore, the integrated use of Building Information Modelling (BIM) with LM or Value Engineering (VE) were proposed in the literature. Nonetheless, it was also seen that BIM can provide more insights and improvements when BIM is integrated with data analysis tools to analyze BIM data. In the literature, the synergies between these concepts are generally addressed pairwise, and there is no comprehensive framework which identifies their relationships. Therefore, this study aims to develop a maturity framework that facilitates the adoption of LM, VE, BIM, and Big Data Analytic (BDA) concepts to address long-standing productivity and digitalization issues in the Architecture, Engineering, and Construction (AEC) industry. Design Science Research (DSR) methodology and its three-cycle view (relevance, rigor, and design cycle) were applied to build the proposed maturity framework. Two interviews were performed to identify and observe research problem in relevance cycle. In the rigor cycle, a comprehensive literature review was performed to create a base for the development of the maturity framework. In addition to the developed base of the framework, lean processes were added to this cycle. In the design cycle, the developed framework was evaluated and validated by five experts through face-to-face interviews. The importance of employer’s requirements to adopt the proposed methodologies, the negative impact of change orders, the importance of pre-construction phases to facilitate value creation and waste elimination, and the usage of common data environment with BIM were identified as the prominent application and adaptation issues. |
topic |
lean management value engineering building information modeling big data analytic |
url |
https://www.mdpi.com/2071-1050/13/18/10029 |
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