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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Abdulrahman Bin Mahmoud & Abdullah Alrashdi & Salman Akhtar & Ayman Altuwaim & Abdulmohsen Almohsen, 2024. "Development of a Predictive Model Based on the Alignment Tool in the Early Stages of Projects: The Case of Saudi Arabia Infrastructure Projects," Sustainability, MDPI, vol. 16(18), pages 1-18, September.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8122-:d:1479941
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    References listed on IDEAS

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    1. Kwabena Asomanin Anaman & Charity Osei-Amponsah, 2007. "Analysis of the causality links between the growth of the construction industry and the growth of the macro-economy in Ghana," Construction Management and Economics, Taylor & Francis Journals, vol. 25(9), pages 951-961.
    2. Arshi Shakeel Faridi & Sameh Monir El-Sayegh, 2006. "Significant factors causing delay in the UAE construction industry," Construction Management and Economics, Taylor & Francis Journals, vol. 24(11), pages 1167-1176.
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