Probing the Effect of Business Intelligence on the Performance of Construction Projects Through the Mediating Variable of Project Quality Management

Golestanizadeh, Mahboobeh and Sarvari, Hadi and Parishani, Amirhossein and Akindele, Nelson and Edwards, David J. (2025) Probing the Effect of Business Intelligence on the Performance of Construction Projects Through the Mediating Variable of Project Quality Management. Buildings, 15 (4). p. 621. ISSN 2075-5309

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Abstract

Business intelligence is a new approach to helping project managers and personnel to make correct, informed decisions through preparing a series of analytical reports in a management dashboard by analysing and mining all of the related project data. This study aimed to investigate the effect of business intelligence on the performance of construction projects in Iran through the mediating variable of project quality management. In contrast to prior research that has evaluated the aforementioned variables in isolation, the current study introduced a comprehensive structural model to investigate the interrelationships among business intelligence, quality management, and construction project performance. This study employed a descriptive–correlational methodology utilising structural equation modelling, involving a sample of 102 Iranian construction industry specialists recruited by convenience sampling. Data were gathered using standardised questionnaires and analysed with structural equation modelling (SEM) in Smart-PLS and regression analysis in the SPSS software. The SEM indicated that business intelligence significantly enhances construction project performance (β = 0.534, p < 0.01) and influences project quality management (β = 0.743, p < 0.01) and that project quality management positively affects construction project performance (β = 0.396, p < 0.01). Furthermore, project quality management exerts a slight mediating influence in this relationship, with the indirect effect calculated at 0.295 and the direct effect assessed at 0.534. The regression analysis revealed that the business intelligence variable’s dimensions (technical and managerial, financial and economic, and data and information management) can predict construction project performance, while the technical and managerial and financial and economic dimensions can predict project quality management. Implementing business intelligence technologies in construction project management enhances decision-making for managers and elevates project performance. This study’s findings suggest that managers and specialists should employ data analysis technologies and business intelligence systems to enhance project quality and performance.

Item Type:	Article
Identification Number:	10.3390/buildings15040621
Dates:	Date Event 13 February 2025 Accepted 17 February 2025 Published Online
Uncontrolled Keywords:	business intelligence, project performance, project quality management, construction industry
Subjects:	CAH13 - architecture, building and planning > CAH13-01 - architecture, building and planning > CAH13-01-02 - building
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Built Environment
Depositing User:	Gemma Tonks
Date Deposited:	21 Mar 2025 14:40
Last Modified:	21 Mar 2025 14:40
URI:	https://www.open-access.bcu.ac.uk/id/eprint/16245

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