Businesses need to analyze labor cost so that they understand what components of businesses affect the amount of resources spent on employees. Interpreting this will help make managerial decisions in adjusting costs of production and develop new strategies regarding investing in workers. Labor cost can vary due to many factors such as employee numbers, assets, liabilities, sales, and debt. In this study, I analyzed labor cost in relation to other firm characteristics, using a large panel data set over thirty years with over 24,000 firm-year observations. I used two different statistical software, R and SPSS and the results are compared. Results show that they both give the same output when running a multivariate regression. Both software are powerful enough to analyze large datasets; however the form of input data and treatment of missing values, matter in determining which one is more efficient. Managers and practitioners can use business analytics with big data to draw conclusions and make important managerial decisions. Future study should include big data analysis using more complex analytical techniques.
International Journal of Business and Applied Social Science (IJBASS)
Bhattacharya, Mousumi, "Big data analytics of labor cost over thirty years" (2018). Business Faculty Publications. 226.
Bhattacharya, M. (2018). Big data analytics of labor cost over thirty years. International Journal of Business and Applied Social Science (IJBASS), 4(12).