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Abstract
This study estimates the efficiency of employees’ performances under profit
sharing system using data envelopment analysis (DEA). This method is one of the
most common methods used in efficiency measurement analysis. However, a
robust approach is used to deal with the complexity of the traditional DEA
estimators. Robust Data Envelopment Analysis (RDEA) is very useful when
outliers contaminate the data. The sample includes five divisions which cover as
many as 102 employees of a shipping company in Malaysia are analyzed by using
R program. The results reveal that the initial DEA efficiency is an over-estimate of
the true efficiency. RDEA provides better accuracy of the results. Further, the
robust approach is appropriate to be used in the measurement of the efficiency of
company divisions under profit sharing program.
Keywords
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References
- Banker, R.D., Charnes A., & Cooper W.W., (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 3 (9), 1078-1092.
- Bertsimas, D., & Sim, M. (2003). Robust discrete optimization and network flows. MathematicalProgramming, 98(1), 49-71
- Bhargava, S., & Jenkinson, T. (1995). Explicit versus implicit profit-sharing and the determination of wages: microeconomic evidence from the U.K. Labour, 9, 73-95.
- Blasi, J. (2013). The evidence on employee stock ownership and profit sharing: The citizen’s share. Forthcoming from Yale University Press in August of 2013.
- Cahuc, P., & Dormont, B. (1997). Profit Sharing: Does It Increase Productivity and Employment? A theoretical model and empirical evidence on French micro data. Labour Economics, 4, 293-319.
- Charnes A., Cooper W.W., & Rhodes E., (1978). Measuring the inefficiency of decision making units. European Journal of Operational Research, 2, 429-444.
- Coelli, T., Rao, D., & Battese, G. (1994). an introduction to efficiency and productivity analysis. Kluwer Academic Publishers.
- Cooper, W.W., Z.M. Huang, V. Lelas, S. Xi & O.B. Olesen .(1998). Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA. Journal of Productivity Analysis 9 (1), 53-79.
- Efron, B., & Tibshirani, R. (1993). An Introduction to the Bootstrap. Boca Raton, FL: Chapman & Hall/CRC.
- Estrin, S., Perotin, V., Robinson, A., & Wilson, N. (1997). Profit sharing in OECD countries: a review and some evidence. Business Strategy Review, 8, 27-32.
- Farrell, M.J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society Series, 120(3), 253-290.
- Gharakhan, M., Kazemi, I., & Haji, H.A. (2011). A robust DEA model for measuring the relative efficiency of Iranian high schools. Management Science Letters, 1, 389-404.
- Golec, A., & Kahya, E. (2007). A Fuzzy model for competency-based employee evaluation and selection. Computers & Industrial Engineering, 52, 143-161.
- Gstach, D. (1998). Another Approach to Data Envelopment Analysis in Noisy Environments: DEA+. Journal of Productivity Analysis 9 (2), 161-176.
- Hainaut, D. (2009). Profit sharing: A stochastic control approach. ESC Rennes 35065 Rennes, Frances.
- Jerger, J., & Michaelis, J. (2007). To share or not to share? why profit sharing is so hard to implement?. Economic Letters, 110(2), 104-106.
- Koskela, E., & J. König .(2010). Can profit sharing lower flexible outsourcing?. HECER Discussion Paper No. 310.
- Kraft, K., & Ugarkovic, M. (2005). Profit sharing and the financial performance of firms: Evidence from Germany. Economic Letters, 92, 333-338.
- Kruse, D. (1992). Profit Sharing and productivity: Microeconomic evidence from the United States. The Economic Journal, 102 (410), 24-36.
- OECD. (1995). Profit sharing in OECD countries. Employment Outlook, 139-169.
- Perotin, V., & Robinson, A. (2002). Employee participation in profit and ownership: a review of the issues and evidence. Paper prepared for the European Parliament. Leeds University Business School, UK.
- Shirouyehzad, H., Lotfi, F.H., Aryanezhad, M.B., Reza, D. (2012). A Data Envelopment Analysis approach for measuring efficiency of employees: a case study. South African Journal of Industrial Engineering, 23(1), 191-210.
- Simar, L., Wilson, P.W. (1998). Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models. Management Science, 44, 49-61.
- Simar, L., Wilson, P.W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136, 31-64.
- Tao, G. (2012). Multi-department employee performance evaluation based on DEA cross efficiency. Journal of emerging Trends in Economics and Management Sciences, 3(5), 553-558.
- Testi, A., Fareed, N., Ozcan, Y., & Tanfani, E. . (2013). Assessment of Physician Performance Diabetes: a Bias-corrected Data envelopment Analysis Model. Quality in Primary Care, 21, 345-257.
- Thanassoulis E., Dyson, R.G., & Foster, M.J. (1987). Relative efficiency assessments using data envelopment analysis: an application to data on rates departments. Journal of Operational Research, 38, 397-412.
- Wadhwani, S., & Wall, M. (1990). The effects of profit sharing on employment, wages, stock returns and productivity: Evidence from UK micro-data. Economic Journal, 100(399), 1-17.
- Wilson, P. (1995). Detecting Influential Observations in Data Envelopment Analysis. Journal of Productivity Analysis 6, 27 – 45.
- Wu, Y.-J., & Hou, J.-L. (2010). An employee performance estimation model for the logistic industry. Decision Support Systems, 48, 568-581.
- Zbranek, P. (2013). Data Envelopment Analysis as a tool for evaluation of employees’ performance. Acta Economica et Informatica, 26(1), 12-21
References
Banker, R.D., Charnes A., & Cooper W.W., (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 3 (9), 1078-1092.
Bertsimas, D., & Sim, M. (2003). Robust discrete optimization and network flows. MathematicalProgramming, 98(1), 49-71
Bhargava, S., & Jenkinson, T. (1995). Explicit versus implicit profit-sharing and the determination of wages: microeconomic evidence from the U.K. Labour, 9, 73-95.
Blasi, J. (2013). The evidence on employee stock ownership and profit sharing: The citizen’s share. Forthcoming from Yale University Press in August of 2013.
Cahuc, P., & Dormont, B. (1997). Profit Sharing: Does It Increase Productivity and Employment? A theoretical model and empirical evidence on French micro data. Labour Economics, 4, 293-319.
Charnes A., Cooper W.W., & Rhodes E., (1978). Measuring the inefficiency of decision making units. European Journal of Operational Research, 2, 429-444.
Coelli, T., Rao, D., & Battese, G. (1994). an introduction to efficiency and productivity analysis. Kluwer Academic Publishers.
Cooper, W.W., Z.M. Huang, V. Lelas, S. Xi & O.B. Olesen .(1998). Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA. Journal of Productivity Analysis 9 (1), 53-79.
Efron, B., & Tibshirani, R. (1993). An Introduction to the Bootstrap. Boca Raton, FL: Chapman & Hall/CRC.
Estrin, S., Perotin, V., Robinson, A., & Wilson, N. (1997). Profit sharing in OECD countries: a review and some evidence. Business Strategy Review, 8, 27-32.
Farrell, M.J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society Series, 120(3), 253-290.
Gharakhan, M., Kazemi, I., & Haji, H.A. (2011). A robust DEA model for measuring the relative efficiency of Iranian high schools. Management Science Letters, 1, 389-404.
Golec, A., & Kahya, E. (2007). A Fuzzy model for competency-based employee evaluation and selection. Computers & Industrial Engineering, 52, 143-161.
Gstach, D. (1998). Another Approach to Data Envelopment Analysis in Noisy Environments: DEA+. Journal of Productivity Analysis 9 (2), 161-176.
Hainaut, D. (2009). Profit sharing: A stochastic control approach. ESC Rennes 35065 Rennes, Frances.
Jerger, J., & Michaelis, J. (2007). To share or not to share? why profit sharing is so hard to implement?. Economic Letters, 110(2), 104-106.
Koskela, E., & J. König .(2010). Can profit sharing lower flexible outsourcing?. HECER Discussion Paper No. 310.
Kraft, K., & Ugarkovic, M. (2005). Profit sharing and the financial performance of firms: Evidence from Germany. Economic Letters, 92, 333-338.
Kruse, D. (1992). Profit Sharing and productivity: Microeconomic evidence from the United States. The Economic Journal, 102 (410), 24-36.
OECD. (1995). Profit sharing in OECD countries. Employment Outlook, 139-169.
Perotin, V., & Robinson, A. (2002). Employee participation in profit and ownership: a review of the issues and evidence. Paper prepared for the European Parliament. Leeds University Business School, UK.
Shirouyehzad, H., Lotfi, F.H., Aryanezhad, M.B., Reza, D. (2012). A Data Envelopment Analysis approach for measuring efficiency of employees: a case study. South African Journal of Industrial Engineering, 23(1), 191-210.
Simar, L., Wilson, P.W. (1998). Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models. Management Science, 44, 49-61.
Simar, L., Wilson, P.W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136, 31-64.
Tao, G. (2012). Multi-department employee performance evaluation based on DEA cross efficiency. Journal of emerging Trends in Economics and Management Sciences, 3(5), 553-558.
Testi, A., Fareed, N., Ozcan, Y., & Tanfani, E. . (2013). Assessment of Physician Performance Diabetes: a Bias-corrected Data envelopment Analysis Model. Quality in Primary Care, 21, 345-257.
Thanassoulis E., Dyson, R.G., & Foster, M.J. (1987). Relative efficiency assessments using data envelopment analysis: an application to data on rates departments. Journal of Operational Research, 38, 397-412.
Wadhwani, S., & Wall, M. (1990). The effects of profit sharing on employment, wages, stock returns and productivity: Evidence from UK micro-data. Economic Journal, 100(399), 1-17.
Wilson, P. (1995). Detecting Influential Observations in Data Envelopment Analysis. Journal of Productivity Analysis 6, 27 – 45.
Wu, Y.-J., & Hou, J.-L. (2010). An employee performance estimation model for the logistic industry. Decision Support Systems, 48, 568-581.
Zbranek, P. (2013). Data Envelopment Analysis as a tool for evaluation of employees’ performance. Acta Economica et Informatica, 26(1), 12-21