NEXT-GENERATION PERFORMANCE APPRAISAL: BALANCING TECHNOLOGY AND HUMAN-CENTRIC FAIRNESS

In the digital era, performance appraisal systems are undergoing significant transformation driven by artificial intelligence (AI), analytics, and continuous feedback platforms. Traditional appraisal methods are often criticized for bias, subjectivity, and inefficiency, while digital systems promise real-time evaluations, predictive insights, and improved fairness. However, ethical concerns, employee acceptance, and cultural adaptability remain major challenges. This paper critically reviews contemporary literature (2023–2025) and leading practices of global firms such as Adobe, Microsoft, and Infosys to assess the effectiveness of digital appraisal systems. It identifies research gaps, articulates the problem of balancing technological efficiency with employee trust, and proposes a reimagined framework for performance appraisal. The study contributes to advancing HRM scholarship and offers actionable strategies for organizations seeking sustainable, transparent, and equitable appraisal systems in the digital age. Keywords: Performance Appraisal, Artificial Intelligence, Digital HRM, Employee Perception, Organizational Performance.

Authors

Institutions

Publication Details

Journal
EPRA International Journal of Economics Business and Management Studies
Published
2025-09-13
DOI
https://doi.org/10.36713/epra24028
Primary Topic
Human Resource Development and Performance Evaluation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

NEXT-GENERATION PERFORMANCE APPRAISAL: BALANCING TECHNOLOGY AND HUMAN-CENTRIC FAIRNESS

Basavaraj M Naik, Trupti G Appugol
EPRA International Journal of Economics Business and Management Studies
Human Resource Development and Performance Evaluation
article

NEXT-GENERATION PERFORMANCE APPRAISAL: BALANCING TECHNOLOGY AND HUMAN-CENTRIC FAIRNESS

Basavaraj M Naik, Trupti G Appugol
article en

Abstract

In the digital era, performance appraisal systems are undergoing significant transformation driven by artificial intelligence (AI), analytics, and continuous feedback platforms. Traditional appraisal methods are often criticized for bias, subjectivity, and inefficiency, while digital systems promise real-time evaluations, predictive insights, and improved fairness. However, ethical concerns, employee acceptance, and cultural adaptability remain major challenges. This paper critically reviews contemporary literature (2023–2025) and leading practices of global firms such as Adobe, Microsoft, and Infosys to assess the effectiveness of digital appraisal systems. It identifies research gaps, articulates the problem of balancing technological efficiency with employee trust, and proposes a reimagined framework for performance appraisal. The study contributes to advancing HRM scholarship and offers actionable strategies for organizations seeking sustainable, transparent, and equitable appraisal systems in the digital age. Keywords: Performance Appraisal, Artificial Intelligence, Digital HRM, Employee Perception, Organizational Performance.

EPRA International Journal of Economics Business and Management Studies
KLE Academy of Higher Education and Research (IN)
Openalex Percentile: Top 73%
Human Resource Development and Performance Evaluation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

NEXT-GENERATION PERFORMANCE APPRAISAL: BALANCING TECHNOLOGY AND HUMAN-CENTRIC FAIRNESS — Basavaraj M Naik, Trupti G Appugol · EPRA International Journal of Economics Business and Management Studies (2025) | TGRS Research Map | TGRS