The Use of Binary Logistic Regression on the Awareness Level of Building Information Modelling in Nigeria

Abstract

The study examined the awareness level of BIM in the Nigerian construction industry, with a view to achieving sustainable building projects through effective collaboration among building professionals. A survey was carried out, using 191 copies of structured questionnaire, self-administered through random sampling technique on the construction professionals in Akwa Ibom State, South-South, Nigeria; to examine the respondents’ awareness level of BIM. The responses from the professionals were analysed using binary logistic regression; while the hypothesis was tested using the Kruskal-Wallis test. The findings revealed that the professionals were probably aware of BIM in the study area with 65.7% awareness probability against 45.1% unawareness probability level. The overall classification accuracy of the model was 55.3% which showed a perfect fit to model in the data; it also revealed that there is a significant variation in the professionals’ awareness level of BIM. Most of the variables were with p-values less than 0.05, which by indication means they are significant. This means that the null hypothesis was rejected, while the alternative hypothesis was accepted for the variables. However, there were three variables with p-values greater than 0.05; this means that for those three variables, the null hypothesis was accepted, while the alternative hypothesis is rejected. Hence, due to the significant variation of eleven variables, a post hoc test was carried out on these variables using Mann-Whitney U test to determine the variations’ contributing respondents. The study concluded that there is a high level of awareness of BIM, and its concepts in Nigeria’s construction industry. Hence, the study recommended that there is still a need for an increased awareness of the benefits of BIM, and how it can be used particularly in the Nigerian construction industry.

Keywords: Building information modelling, Information technology, Sustainable buildings, and Building projects.