Reducing Bias and Strengthening Objectivity in Performance Appraisal: A Thematic Analysis
Volume 1, Issue 1, Article Number: 251008 (2025)
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Mohammad Shakeel Akhtar1,* | Dr. Vimlesh Tanwar2 | Dr. Nishtha Pareek3
1Research Scholar, Department of Commerce and Management, Banasthali Vidyapith, Tonk 304022, Rajasthan, India
2Assistant Professor, Department of Commerce and Management, Banasthali Vidyapith, Tonk 304022, Rajasthan, India
3Associate Professor, Department of Commerce and Management, Banasthali Vidyapith, Tonk 304022, Rajasthan, India
*Corresponding Author: md.shakeel.akhtar@gmail.com
Received: 12 May 2025 | Revised: 18 May 2025
Accepted: 19 May 2025 | Published Online: 21 May 2025
DOI: https://doi.org/10.5281/zenodo.15472775
© 2025 The Authors, under a Creative Commons license, Published by Scholarly Publication
Abstract
Appraisals are fundamental to the management of human resources since they affect the development of an employee, the organizational fairness, and the advancement in one’s career. However, performance appraisal systems tend to lack precision due to biases that adversely impact trust, fairness, accuracy, and objectivity. This thesis aims to analyze reasons for biases in performance appraisal and determine practical methods to improve objectivity using action-oriented thematic analysis. Following qualitative literature synthesis, three overarching themes were identified: biases associated with raters, alterations proposed to enhance structures and processes, and use of technology. Findings highlight biases such as halo bias, age, ethnicity and gender biases, and leniency bias are steeped in cultural and organizational deep cognitive frameworks. An increase in measurement precision is essential in overcoming biases using Z-ethically acceptable design, CPM systems, automated feedback BARS, AI, and analytics. It is emphasized that technological frameworks must be approached from the standpoint of fairness, devoid of historical inequity perpetuation. Ultimately, the argument presented in the text underscores the complexity of the intervention using systems approach combining governance by ethical machine systems with human retraining, organizational strategy redesign, and allegiance to bounding policies for structural fairness, openness, inclusion, and objectivity.
Keywords
Performance Appraisal, Bias Mitigation, Objectivity, Rater Training, Behaviorally Anchored Rating Scales (BARS), 360-Degree Feedback, Continuous Performance Management (CPM), Organizational Fairness, Systemic Discrimination
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Cite This Article
M. S. Akhtar, V. Tanwar, and N. Pareek, “Reducing Bias and Strengthening Objectivity in Performance Appraisal: A Thematic Analysis,” Commercia 1(1) (2025) 251008. https://doi.org/10.5281/zenodo.15472775
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