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Managerial Opportunities In Application of Business Intelligence In Construction Companies

Author(s): ORCID
ORCID
ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Journal of Civil Engineering and Management, , n. 6, v. 29
Page(s): 487-500
DOI: 10.3846/jcem.2023.19533
Abstract:

In construction projects, managers make multiple decisions every day. Most of these decisions are relatively unimportant; some of them are critical and could lead to the success or failure of a construction project. To ensure construction companies make effective managerial decisions, decision making requires performing an initial technical and economic analysis, comparing different decision-making solutions, using a planning system, and ensuring project implementation based on the provided plans. Therefore, the use of powerful systems such as business intelligence (BI), which play a central role in management and decision-making, is essential in project-based companies. The current study aims to determine and evaluate the main managerial opportunities in the application of BI in project-based construction companies using a descriptive survey approach. An empirical research questionnaire consisting of 60 factors and 7 categories was adopted. The questionnaire, after confirming its validity and reliability, was distributed to 100 experts engaged in 5 active project-based construction companies who were familiar with BI topics. To analyse the data, a one-sample t-test and the Friedman test were performed using the SPSS software. The findings indicated that the importance of the identified opportunities for the use of BI in project-based construction companies is above average and that, in the case of using BI in such companies, these opportunities can be used to improve project performance. The results of the current study can help managers and other stakeholders as an effective decision-making tool to better implement BI in project-based companies.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3846/jcem.2023.19533.
  • About this
    data sheet
  • Reference-ID
    10737799
  • Published on:
    03/09/2023
  • Last updated on:
    03/09/2023
 
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