Organizational Factors, Construction Risk Management and Government Regulations in Nigerian Construction Companies: Data Screening and Preliminary Analysis

The aim of this paper is to investigate the accumulated data pertaining to the organizational factors, construction risk management and government regulations in Nigerian construction companies. A total sample of 238 were selected from the total population of 338 contractors operating...

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Bibliographic Details
Main Authors: Adeleke, A. Q., Windapo, Abimbola Olukemi, Bamgbaded, J. A., Salimon, Maruf Gbadebo, Afolabi, Yakibi Ayodele
Format: Article
Language:English
Published: Penerbit Universiti Malaysia Pahang 2018
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Online Access:http://umpir.ump.edu.my/id/eprint/22605/1/Organizational%20Factors%2C%20Construction%20Risk%20Management%20and%20Government.pdf
http://umpir.ump.edu.my/id/eprint/22605/
http://jgi.ump.edu.my/index.php/en/current-issue/71-organizational-factors-construction-risk-management-and-government-regulations-in-nigerian-construction-companies-data-screening-and-premilinary-analysis/file
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Institution: Universiti Malaysia Pahang
Language: English
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Summary:The aim of this paper is to investigate the accumulated data pertaining to the organizational factors, construction risk management and government regulations in Nigerian construction companies. A total sample of 238 were selected from the total population of 338 contractors operating in Abuja and Lagos State construction companies in Nigeria. Therefore, a proportionate stratified random sampling approach was employed for this study to further divide the companies into different strata, and they were all picked randomly from each stratum. Furthermore, data cleaning and screening were conducted with the intent to fulfil the multivariate analysis assumptions. Hence, this study carried out various tests like missing data analysis, outliers, normality, Multicollinearity, non-response bias and common method variance with the use of Statistical Package for Social Science (SPSS) v21. Lastly, it was discovered that the data fulfil all the requirements for multivariate analysis.