Assessment of preconstruction factors in sustainable project management performance
Autor(en): |
Khalid Naji
Murat Gunduz Fatema Salat |
---|---|
Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Engineering, Construction and Architectural Management, Februar 2021, n. 10, v. 28 |
Seite(n): | 3060-3077 |
DOI: | 10.1108/ecam-05-2020-0333 |
Abstrakt: |
PurposeThe construction sector has a global reach, and construction professionals worldwide often encounter challenges in delivering a project on time and within the assigned budget. Hence, this paper aims to investigate the preproject factors that most affect the performance of construction projects. Design/methodology/approachA literature review was conducted to identify these factors from previous research, after which a questionnaire was developed and distributed to construction industry professionals worldwide. The response data were collected and analyzed using several methods, including Cronbach’s alpha, Relative Importance Index (RII), Kruskal–Wallis test, and Spearman’s and Pearson correlations. FindingsThe results highlight four categories of significance, namely design, stakeholder, engineering, and procurement, with 31 factors being assigned to these categories. The relationships between each factor based on the categories established in the survey are then presented. With the help of data analysis, focusing on these significant preproject factors will help management teams to evaluate and improve the preconstruction process to achieve a higher project success rate. Originality/valueThis study differs from other studies in the literature by gathering all relevant preconstruction success factors by an extensive literature review. Finally, highly ranked factors are studied in detail for a better understanding of the impact of preconstruction factors on project performance. This study is supported by powerful tests such as Kruskal–Wallis test and Spearman’s correlation to study the perception of different groups on preconstruction factors. Furthermore, the data analysis will help in identifying and avoiding the failure part of the previous projects and will improve the planning and/or forecasting of the new projects. |
- Über diese
Datenseite - Reference-ID
10577098 - Veröffentlicht am:
26.02.2021 - Geändert am:
29.11.2021