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Construction process is complex and traditionally fragmented; thus, it is almost impossible to have a project completed without changes to the original plan or the construction process. The purpose of this study is to identify and examine the causes of variation orders, ascertain their effects and establish the cost and time performance implication as a result of variation orders.

This study obtained information from 90 construction stakeholders on 30 completed educational building projects to ascertain the causes and effects of variation orders on project delivery using questionnaire survey. In addition to this, a pro forma document was designed to obtain the project characteristics, cost and time data from these 30 completed educational building projects. Factor analysis was used to categorise the causes of variation orders, while severity index was used to examine their effects on project delivery. The hypothesised statement was tested using paired t-statistics to examine whether a statistically significant difference existed between variation orders, cost and time performance of the projects.

The study identified 13 main factors as causes of variation orders and the results revealed that the most frequent effects of variations were increase in construction costs, time, client dissatisfaction, increase construction project rework and demolition and project abandonment. The results also showed that variation orders had significant effects on both cost and scheduled performance of the educational building projects with average cost and time escalation of 33.95 and 29.45 per cent of the original project cost and time, respectively, for the entire projects studied, while average cost implication of variation orders is 23.79 per cent.

The findings in this study will be of assistance to government agencies and management of public works in higher institutions of learning in managing variations in construction projects. The study will also add to the current literature on the impact of variation orders on educational building projects in developing countries. Finally, it will create the much-needed awareness on the severity and implication of change or variation orders on project delivery.

The study identified and examined the causes of variation orders, ascertained their effects and established the cost and time effects of the causes of variation order on project performance. This will assist project initiators, contractors, consultants and other stakeholders to fully appreciate and understand the significant effects of variation orders on project performance.

This paper evaluates the benefits of harnessing artificial intelligence (AI) tools for safety compliance on construction projects in Nigeria.

This study employed a specialised approach by combining qualitative and quantitative approach. The study carried out a brief systematic literature review (SLR) to identify the variables of the study. These variables were prepared in a questionnaire which was distributed among professionals within the Nigerian construction sector using purposive sampling. A total of 140 questionnaires were retrieved. The collected data were analysed using Relative Importance Index (RII), Ginni’s Mean (GM) and exploratory factor analysis (EFA).

The analysis revealed that all the identified benefits hold considerable importance, with an average RII of 0.86, with real-time monitoring as the most prominent advantage. However, using the GM which was 0.861, the study identified “mitigation of hazards on worksites” as the stationary benefit of AI in safety compliance.

The study was conducted exclusively within Nigeria’s Federal Capital Territory, using a cross-sectional survey approach.

The results will be valuable for professionals and practitioners in the Nigerian construction sector, as they will acquire insights into the potential advantages of utilising AI tools for monitoring of safety compliance on construction projects.

The study adopted a robust approach by identifying the stationary benefit using the GM in combination with RII and EFA.