Machine learning-based-HR appraisal system (ML-APS)

Madapuri Rudra Kumar, Vinit Kumar Gunjan and Mohd Dilshad Ansari

International Journal of Applied Management Science, 2023, vol. 15, issue 2, 102-116

Abstract: Appraisal systems hold critical importance in organisational human resource management. The way HR departments have developed over the period to the recent trends of AI-based human resource management systems and practices reflect on the emerging importance of effective HRM. In this present work, one of the key functionalities of the HRM process, the Appraisal system, is focused upon. This work presents a comprehensive model of appraisal system that relies on the machine learning solution for predicting evaluating the appraisal score. The developed model is trained with SVM classifier and is tested with 600+ records for evaluation. The precision and recall values indicated by the test results reflect that the model is potential and if more effectively pursued in terms of training and incorporating more in-depth analysis, the model can be a sustainable solution for human resource appraisal system.

Keywords: machine learning-based appraisal system; ML-APS; 360-degree performance system analysis. (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ids:injams:v:15:y:2023:i:2:p:102-116

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