Performance: Differences in measuring performance


  • Daniel Philipp Schettler University of Latvia



An important issue in human resources is the procedure of the employees’ performance evaluation. The appraisal is essential in the sense of employee appreciation and motivation. Most employers use a subjective performance evaluation of a single superior or a group of persons involved in the employee’s working processes. The subjective evaluation of a group or one person is often questioned about being appropriate. An often-named solution for a more objective criteria could be data driven performance measures. Professional sport provides a unique opportunity to compare objective and subjective performance evaluation measures. A data set of the German Bundesliga was used to test if the two different performance measure come to equal results. It is shown that differences in means exist but equivalence tests support the hypothesis that both measures could be treated as equal. In toto, it seems that in an environment where performance is relatively good to measure objective and subjective performance evaluations lead to equivalent results.


Albright, M. D., Levy, P. E. (1995). The Effects of Source Credibility and Perfromance Discrepancy on Reactions to Multiple Raters. Journal of Applied Social Psychology, 25 (7), 577–600.

Berry, W. D. (1993). Understanding Regression Assumptions. Thousand Oaks: SAGE Publications.

Bortz, J., Döring, N. (2006). Forschungsmethoden und Evaluation für Human- und Sozialwissenschaftler. 4th ed. Heidelberg: Springer Medizin Verlag.

Cappelli, P., Conyon, M. J. (2018). What Do Performance Appraisals Do? ILR Review, 71 (1), 88–116.

Choon, L. K., Embi, M. A. (2012). Subjectivity, Organizational Justice and Performance Appraisal: Understanding the Concept of Subjectivity in Leading Towards Employees’ Perception of Fairness in the Performance Appraisal. Procedia – Social and Behavioral Sciences 62, 189–193.

Colquitt, J. A. (2001). On the Dimensionality of Organizational Justice: A Construct Validation of a Measure. Journal of Applied Psychology, 86 (3), 386–400.

Danaher, J. (2016). The Threat of Algocracy – Reality, Resistance and Accommodation. Philosophy and Technology, 29 (3), 245–268.

Delfgaauw, J., Souverijn, M. (2016). Biased supervision. Journal of Economic Behavior & Organization, 130 (1), 107–125.

Della Torre, E., Giangreco, A., Legeais, W., Vakkayil, J. (2018). Do Italians Really Do It Better? Evidence of Migrant Pay Disparities in the Top Italian Football League. European Management Review 15 (1), 121–136.

Della Torre, E., Giangreco, A., Maes, J. (2014). Show Me the Money! Pay Structure and Individual Performance in Golden Teams. European Management Review, 11 (1), 85–100.

Espinilla, M., Andrés, R. de, Martínez, F. J., Martínez, L. (2013). A 360-degree performance appraisal model dealing with heterogeneous information and dependent criteria. Information Sciences, 222 (1), 459–471.

Filiz, I., Judek, J. R., Lorenz, M., Spiwoks, M. (2021). Reducing algorithm aversion through experience. Journal of Behavioral and Experimental Finance, 31 (100524), 1–8.

Frederiksen, A., Lange, F., Kriechel, B. (2017). Subjective performance evaluations and employee careers. Journal of Economic Behavior & Organization, 134 (2–3), 408–429.

Frey, B. B. (2018). The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation.

Frick, B. (2011). Performance, Salaries, and Contract Length: Empirical Evidence from German Soccer. International Journal of Sport Finance, (6), 87–118.

Judge, T. A., Ferris, G. R. (1993). Social Context of Performance Evaluation Decisions. The Academy of Management Journal, 36 (1), 80–105.

Kahn, L. M. (2000). The Sports Business as a Labor Market Laboratory. The Journal of Economic Perspectives, 14 (3), 75–94.

Kim, T. K. (2015). T test as a parametric statistic. Korean Journal of Anesthesiology, 68 (6), 540–546.

Köbis, N., Mossink, L. D. (2021). Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry. Computers in Human Behavior, 114 (2), 1–13.

Lakens, D., Scheel, A. M., Isager, P. M. (2018). Equivalence Testing for Psychological Research: A Tutorial. Advances in Methods and Practices in Psychological Science, 1 (2), 259–269.

Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5 (1), 1–16.

LigaInsider: Deutschlands fairste Fussballnote. Available online at:, checked on 2/11/2021.

McCarthy, A. M., Garavan, T. N. (2007). Understanding acceptance of multisource feedback for management development. Personnel Review, 36 (6), 903–917.

Nagtegaal, R. (2021). The impact of using algorithms for managerial decisions on public employees' procedural justice. Government Information Quarterly, 38 (1), 1–10.

Roberson, Q. M., Stewart, M. M. (2006). Understanding the motivational effects of procedural and informational justice in feedback processes. British Journal of Psychology (London, England: 1953), 97 (Pt 3), 281–298.

Selvarajan, T. T., Cloninger, P. A. (2012). Can performance appraisals motivate employees to improve performance? A Mexican study. The International Journal of Human Resource Management, 23 (15), 3063–3084.

Strohmeier, S., Piazza, F. (2013). Domain driven data mining in human resource management: A review of current research. Expert Systems with Applications, 40, 2410–2420.

Taylor, S. M., Tracy, K. B., Renard, M. K., Harrison, K., Carroll, S. J. (1995). Due Process in Performance Appraisal: A Quasi-Experiment in Procedural Justice. Administrative Science Quarterly, 40 (3), 495–523.

Wesche, J. S., Sonderegger, A. (2019). When computers take the lead – The automation of leadership. Computers in Human Behavior, 101, 197–209.

Wolfe, R. A., Weick, K. E., Usher, J. M., Terborg, J. R.; Poppo, L., Murrel, A. J. et al. (2005). Sport and Organizational Studies. Exploring Synergy. Journal of Management Inquiry, 14 (2), 182–210.




How to Cite

Schettler, D. P. (2023). Performance: Differences in measuring performance. Humanities and Social Sciences Latvia, 31(1), 65–79.