Exploring Data-Driven Culture in The Construction Industry: Insights from Industry Practitioners.

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Title: Exploring Data-Driven Culture in The Construction Industry: Insights from Industry Practitioners.
Authors: Hashim, Muhammad Adib1 adib.hashim95@gmail.com, Che Ibrahim, Che Khairil Izam1, Kordi, Nurul Elma1
Source: Online Journal for TVET Practitioners (OJ-TP). 2025, Vol. 10 Issue 3, p32-44. 13p.
Subject Terms: *Corporate culture, Construction industry, Industry 4.0, Businesspeople, Construction management, Thematic analysis, Statistical measurement
Abstract: In previous studies, attributes, sub-attributes and indicators of data driven culture has been studied within the organizations specifically for the construction industry. Nevertheless, there has been no further study conducted on the perspective of construction industry personnels about their viewpoint on the indicators associated with a data-driven culture. Thus, the aim of this research is to cover the gap of data by identifying "perspectives" of industry practitioners on data driven culture in the construction industry. The study started by using Systematic Literature Review (SLR) as a method of literature study, then obtaining validation from 18 practitioners from construction industry analysed by using thematic analysis, and Relative Importance Index (RII). The highest RII value recorded based on each subattributes listed are: D1 - knowledge and expertise, ID3 - availability of fund, C4 - competency, U7 - building model exploration, P1 - register based statistics, P3 - information extraction and P8 - control strategy. The finding of this study benefit construction industry stakeholders to become more skilled, cooperative and dynamic through the documented acknowledgment of their perspective as practitioners in digital construction as emphasized in Malaysian Digital Construction and Industry 4.0 Roadmap 2020-2025. [ABSTRACT FROM AUTHOR]
Copyright of Online Journal for TVET Practitioners (OJ-TP) is the property of Universiti Tun Hussein Onn Malaysia and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Exploring Data-Driven Culture in The Construction Industry: Insights from Industry Practitioners.
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  Data: <searchLink fieldCode="AR" term="%22Hashim%2C+Muhammad+Adib%22">Hashim, Muhammad Adib</searchLink><relatesTo>1</relatesTo><i> adib.hashim95@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Che+Ibrahim%2C+Che+Khairil+Izam%22">Che Ibrahim, Che Khairil Izam</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kordi%2C+Nurul+Elma%22">Kordi, Nurul Elma</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Online+Journal+for+TVET+Practitioners+%28OJ-TP%29%22">Online Journal for TVET Practitioners (OJ-TP)</searchLink>. 2025, Vol. 10 Issue 3, p32-44. 13p.
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  Data: *<searchLink fieldCode="DE" term="%22Corporate+culture%22">Corporate culture</searchLink><br /><searchLink fieldCode="DE" term="%22Construction+industry%22">Construction industry</searchLink><br /><searchLink fieldCode="DE" term="%22Industry+4%2E0%22">Industry 4.0</searchLink><br /><searchLink fieldCode="DE" term="%22Businesspeople%22">Businesspeople</searchLink><br /><searchLink fieldCode="DE" term="%22Construction+management%22">Construction management</searchLink><br /><searchLink fieldCode="DE" term="%22Thematic+analysis%22">Thematic analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+measurement%22">Statistical measurement</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In previous studies, attributes, sub-attributes and indicators of data driven culture has been studied within the organizations specifically for the construction industry. Nevertheless, there has been no further study conducted on the perspective of construction industry personnels about their viewpoint on the indicators associated with a data-driven culture. Thus, the aim of this research is to cover the gap of data by identifying "perspectives" of industry practitioners on data driven culture in the construction industry. The study started by using Systematic Literature Review (SLR) as a method of literature study, then obtaining validation from 18 practitioners from construction industry analysed by using thematic analysis, and Relative Importance Index (RII). The highest RII value recorded based on each subattributes listed are: D1 - knowledge and expertise, ID3 - availability of fund, C4 - competency, U7 - building model exploration, P1 - register based statistics, P3 - information extraction and P8 - control strategy. The finding of this study benefit construction industry stakeholders to become more skilled, cooperative and dynamic through the documented acknowledgment of their perspective as practitioners in digital construction as emphasized in Malaysian Digital Construction and Industry 4.0 Roadmap 2020-2025. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Online Journal for TVET Practitioners (OJ-TP) is the property of Universiti Tun Hussein Onn Malaysia and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.30880/ojtp.2025.10.03.004
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Construction industry
        Type: general
      – SubjectFull: Industry 4.0
        Type: general
      – SubjectFull: Businesspeople
        Type: general
      – SubjectFull: Construction management
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      – SubjectFull: Thematic analysis
        Type: general
      – SubjectFull: Statistical measurement
        Type: general
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              M: 09
              Text: 2025
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