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.

Over the last 40 years, the Kingdom of Saudi Arabia (KSA) has experienced economic growth that has driven urbanization and infrastructure improvements. However, this has also led to high resource use and poor planning, exacerbating climate challenges and underscoring the need for international cooperation. Given the substantial energy use associated with buildings, sustainable global building standards have been developed. Saudi Vision 2030 encourages sustainable practices in energy, housing, and water by adopting green building standards to guide environmentally friendly initiatives. This study provides an overview of the current status of green building rating systems in KSA and examines the principal obstacles faced during their implementation. Utilizing importance-performance analysis (IPA), the study identifies and evaluates strategies to advance green building ratings, drawing upon survey data from diverse stakeholders. Major barriers include low awareness across the public and private sectors and technical challenges such as a shortage of qualified professionals, limited information, and unreliable resources. The strategies proposed aim to establish clear standards for sustainable construction and promote targeted awareness campaigns with industry leaders and government, highlighting the long-term environmental and financial advantages of green buildings. Identifying these barriers and evaluating interventions will help to advance green building rating systems and sustainability in KSA and worldwide.

The lifespan of site drilling machines is a critical factor influencing construction projects’ cost, efficiency, and safety. While previous research has identified various factors affecting machine longevity, a significant knowledge gap exists in quantifying the relative importance of these factors and their combined impact, particularly across diverse geographical regions like Saudi Arabia and India. This study addresses this gap by providing a comprehensive risk assessment of the lifespan. The research aims to identify and prioritize the most critical factors impacting lifespan and quantify their contributions to lifespan reduction using correspondence analysis (CA) and the matrix assessment method. A systematic literature review identified 30 risk factors: operational factors, environmental conditions, equipment design and quality, maintenance practices, and operator skill and training. A survey of construction professionals in Saudi Arabia and India, alongside a global perspective, provided data on the probability and impact of each factor. CA and matrix assessment methods were employed to analyze the data, revealing regional variations and commonalities. The results demonstrate that “Operator Training” is consistently a high-impact, high-probability risk across all regions. However, the relative importance of other factors, such as soil conditions and overloading, varies significantly between Saudi Arabia and India. This study introduces the integration of CA and the matrix assessment method to offer a systematic, data-driven approach to the problem. The findings provide actionable insights for construction companies, engineers, and project managers, enabling targeted risk mitigation strategies, optimized maintenance planning, and improved operator training programs. Ultimately, this research contributes to more sustainable, efficient, and cost-effective construction practices by extending the operational life of vital drilling equipment.