Abstract
Adapting innovations in construction project management can proliferate the production of high-quality projects which are known as vital contributors to the socio-economic development of a country. This study was conducted to provide a new approach to cost estimation that would help prevent cost overrun problem during project implementation. Preliminary data collection through literature review and interview led to the determination of qualitative information pertaining to the most frequently encountered cost-influencing conditions and issues, which were adopted to develop the Cost-influencing Factor Assessment Questionnaire, following an Exploratory Factor Analysis through Principal Axis Factoring Method and Oblique Promax Rotation Method to uncover the latent underlying cost-influencing factors for building projects. The survey data were validated through the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO>0.5) and the Bartlett test of sphericity (p<0.05), which indicate the suitability of the data for Factor Analysis. Scree Plot Analysis and Parallel Analysis suggested that 9 factors should be extracted, which were then named according to the shared concepts of the items clustered under each factor. After extensive data screening and analysis, the validity and reliability requirements for scale construction were met, and a new set of items categorized into 9 cost-influencing factors were obtained, establishing the Project Cost Assessment Instrument. A mathematical model was developed through multiple linear regression analysis which showed that 4 out of 9 factors were significant predictors for residential project cost, and these were Project Scale, Equipment Management, Site Condition, and Client Collaboration. The validity of the model was ascertained by means of graphical and mathematical validation, proving the mathematical model’s good prediction accuracy.
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Cabuñas, J. T., & Silva, D. L. (2019). Exploratory factor-item analytic approach for construction project cost overrun using oblique promax rotation for predictors determination. International Journal of Innovative Technology and Exploring Engineering, 8(6), 47–54.
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