Development of a Predictive Model Based on the Alignment Tool in the Early Stages of Projects: The Case of Saudi Arabia Infrastructure Projects

Abdulrahman Bin Mahmoud (), Abdullah Alrashdi, Salman Akhtar, Ayman Altuwaim and Abdulmohsen Almohsen
Additional contact information
Abdulrahman Bin Mahmoud: Civil Engineering Department, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia
Abdullah Alrashdi: Civil Engineering Department, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia
Salman Akhtar: Civil Engineering Department, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia
Ayman Altuwaim: Civil Engineering Department, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia
Abdulmohsen Almohsen: Civil Engineering Department, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia

Sustainability, 2024, vol. 16, issue 18, 1-18

Abstract: The construction industry plays a substantial role in shaping the economies of many countries. Construction management faces various challenges that can lead to project failures, particularly in infrastructure projects struggling to meet cost and time requirements. Inadequate project planning and the intricate nature of construction projects can cause participants’ project goals to not align. It is crucial to address these challenges early in the planning stages to ensure project success. This research involved investigating previous studies to understand current practices for improving infrastructure project planning and selecting the best pre-project planning tool. Infrastructure projects in the Saudi construction industry are used as a case study. A questionnaire was prepared based on essential alignment issues affecting team alignment during pre-project planning. Participants rated the level of agreement with alignment issues and the overall success of a project they worked on. The study utilized descriptive and inferential analysis techniques to assess infrastructure project success rates and develop a predictive model driven by the alignment tool. Multiple linear regression techniques were used during the model’s development, and validation and reliability outputs were obtained. By evaluating all relevant stakeholders, the model generates a score to facilitate the pre-project planning process, increasing the likelihood of project success. The study found that the model’s predictive accuracy was 94%. This research is significant in creating a predictive model applicable to infrastructure projects, enhancing project management practices by enabling project teams to evaluate project progress, identify projects in need of corrective action, and ultimately improve project performance, leading to cost and time savings.

Keywords: predictive model; project alignment tool; early stages; infrastructure projects (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/18/8122/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/18/8122/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:18:p:8122-:d:1479941

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().