Structural equation modelling of risk factors influencing the success of building projects

Abstract

Purpose Despite several research efforts tackling construction project risks globally, tertiary education building projects are not devoid of experiencing risks with cascading effects on projects. In the past decades, there has been increasing application of linear assessments of risks in construction risk management practices. However, this study aims to assess the influence of risk factors on the success of tertiary education building projects using a structural equation modelling approach. This study will further reinforce the risk factors that require attention because risk factors are not linear but interdependent. Design/methodology/approach A quantitative research method was undertaken in this study, where data collection was achieved via a structured questionnaire survey. In total, 452 questionnaires were administered to client representatives, consultants and contractors involved in executing tertiary education building projects across five public tertiary education institutions in Ondo State, Nigeria. Of 452 questionnaires, 279 were found usable for the analysis, implying a response rate of 61.73%. The Cronbach α test, average variances extracted and composite reliabilities values show high reliability and internal consistency of the instrument used for data gathering. Furthermore, the study adopted percentile, mean, correlation, regression analysis and structural equation modelling for analyzing the data collected upon which the study’s inferences were based. Findings The study found that three out of six criteria for measuring the success of tertiary education building projects were significantly affected by risk factors while using the structural equation modelling technique. With this non-linear method of assessment, completion to time was significantly impacted by environmental risk factors. In addition, safety performance was also significantly influenced by logistic, environmental and legal risk factors; furthermore, logistics, design and environmental risks significantly affected profit. However, completion to cost, standard/quality and end-user satisfaction was not significantly affected by the risk factors in tertiary education building projects. Research limitations/implications The quantitative data used for the analysis are limited to the tertiary education building projects from selected five tertiary education institutions in Ondo State; therefore, the results do not indicate all tertiary institutions in Nigeria. In addition, the findings are based on building projects that were procured through a competitive tendering arrangement only and thus considered a limitation for this study. Practical implications Not all the risks significantly influence the tertiary education building projects. Therefore, risk factors with a significant effect on the success indicators of tertiary education building projects should be prioritized for a successful project. While risk factors have not affected the completion to cost per se, the study implies that the resultant effect of risks on other success indicators could have a cascading effect on these projects in terms of cost and time overruns. These results may assist during the project risk management while also addressing complexity and uncertainty to avoid chaos in a tertiary education building projects. Originality/value The study found significant construction risk factors impacting the success of tertiary education building projects using a non-linear methodology, an extension beyond the usual linear method of assessment of risk impacts on the project performance.

Structural Equation Modeling of the Critical Success Factors of Lean Six Sigma Implementation in Nigeria

“…In the context of SEM, multiple latent independent variables are measured by various indicators, and one or more latent dependent variables are assessed using multiple indicators, leading to complex interactions, nonlinearity, measurement errors, and correlated error terms (Adedokun and Egbelakin, 2022). The technique provides several model fit indices, utilizing multiple indices to assess the model's fitness for the data (Adedokun et al, 2022). Structural equation models are formulated based on priori theoretical or logical complex relationships between variables in a linear system of equations.…”

Random forest and path diagram taxonomies of risks influencing higher education construction projects

“…Furthermore, the significant risk factor triggering delay along the stages of construction projects is financial risks which could emanate from the cashflow problems of the contractors (Nguyen et al, 2021;Shehu et al, 2014;Zhang et al, 2021). While the fiftyeight risk factors were clustered into four categories using random forest classification, this is at variance with studies that clustered similar risks into eight groups (Adedokun & Egbelakin, 2022;Adedokun et al, 2021b). This study focused on higher education building projects (HEBP) in a developing economy based on random forest classification of risk factors, unlike other studies like Adedokun and Egbelakin (2022); (Adedokun et al, 2021b), used the structural equation modelling technique for similar building projects.…”

Structural Equation Modeling of The Critical Success Factors of Lean Six Sigma Implementation in Nigeria

“…In the context of SEM, multiple latent independent variables are measured by various indicators, and one or more latent dependent variables are assessed using multiple indicators, leading to complex interactions, nonlinearity, measurement errors, and correlated error terms [28]. The technique provides several model fit indices, utilizing multiple indices to assess the model's fitness for the data [28]. Structural equation models are formulated based on priori theoretical or logical complex relationships between variables in a linear system of equations.…”