Application of Multiple Regressions on the Impact of Building Information Modelling Adoption Drivers on Sustainable Construction in Nigeria
International Journal of Innovation and Sustainability, 1 (2017) 22- 31
10 Pages Posted: 1 Aug 2017
Date Written: July 30, 2017
Abstract
This study aims at determining the influence of BIM adoption drivers on attaining sustainable construction in Nigeria, with a view to fostering the adoption of BIM through the use of these drivers by the necessary authorities. Exploratory and survey research design approach was used for the study. 191 copies of structured questionnaire were administered on the respondents using random sampling method on the construction professionals in Akwa Ibom State, South-South, Nigeria. The research instrument’s validity test was done by experts in the department of building, University of Uyo; and a reliability test was carried out on the collected data using Cronbach’s alpha. The perceptions of the professionals on the adoption strategies were analysed using relative importance index (R.I.I) method; while the test on the impact of the strategies on sustainable buildings was done using multiple regression analysis. The professionals agreed that the most important strategies that will enhance the adoption of BIM for sustainable building projects in the study area, are organising professional workshops and training for stakeholders, the availability of well-trained professionals, and making the software packages affordable; from the multiple regression analysis, it was found that the strategies have a positive impact on attaining sustainable construction. The coefficient of determination (R2) was 0.995 while the adjusted R2 was 0.995 showing that 99.5% of the variation in achieving sustainable building projects in the study area was explained by combined changes in the predicting variables (Advanced Man-Power and Public Sector Led Strategies). The analysis also showed that the overall fit of the regression model was good given the ANOVA F-value of 13869.627 and significant at 0.05 critical level. The Durbin Watson showed 1.766, which was an indication that there was an autocorrelation among the successive values of the variables in the model since the value was greater than one. The study therefore establishes that in order to implement BIM for sustainable building projects, the use of advanced man-power training and the role of the public sector must be strongly adhered to.
Keywords: Building information modelling, Information technology, Sustainable buildings, and Building projects
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