Towards Smarter HR: Soft Computing Solutions for Performance Appraisal and Underperformance Management

DOI

10.2991/978-94-6463-978-0_10How to use a DOI?

Keywords

Soft Computing; HR Decision Support; Performance Appraisal; Underperformance Management; Artificial Intelligence

Abstract

Human Resource Management is shifting towards the use of smart technologies to employee performance appraisal that will improve fairness and accuracy in the digital era. The conventional performance appraisal systems have been criticized since they are subjective, infrequent, and poor in effectively ad-dressing underperformance. This paper discusses how computing methods with soft factors can be used, that is, fuzzy logic, neural networks, and hybrid neuro fuzzy models, with the aim of producing more transparent, objective, and develop-mental appraisals. The design was the mixed-method research design and the data were collected using randomly selected 20 HR managers and 360 employees in 5 ITeS companies in Bengaluru, India. The qualitative data was received regarding the limitations of conventional appraisals, and the quantitative data showed the significant increase of perceived fairness, trust, and motivation because of AI-based processes. Fuzzy and neuro-fuzzy-based computational simulations were found to be highly accurate in underperformance detection and the creation of individual PIPs. Results are therefore confirming the effectiveness of soft computing to make the performance appraisal an actual developmental process. The suggested Human Resource Decision Support System provides a data-driven and ethical model that combines the use of continuous feedback, bi-as reduction, and adaptive learning and promotes fairness, transparency, and long-term performance of the people in the ITes sector.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Prathibha Josephine
AU  - B. Ismail Zabivullah
PY  - 2025
DA  - 2025/12/31
TI  - Towards Smarter HR: Soft Computing Solutions for Performance Appraisal and Underperformance Management
BT  - Proceedings of the 1st Engineering Data Analytics and Management Conference (EAMCON 2025)
PB  - Atlantis Press
SP  - 95
EP  - 107
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-978-0_10
DO  - 10.2991/978-94-6463-978-0_10
ID  - Josephine2025
ER  -