An Empirical Study of the Impact of Organizational, Social, and Psychological Factors on the Performance of Employees

Krishna Kumar Singh (), Charvi Vats () and M. P. Singh ()
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Krishna Kumar Singh: Symbiosis Centre for Information Technology
Charvi Vats: Symbiosis Centre for Information Technology
M. P. Singh: Graphic Era University

Chapter Chapter 39 in Digital Economy Post COVID-19 Era, 2023, pp 621-636 from Springer

Abstract: Abstract Human Resource is the most valuable asset for any organization that drives the firm’s overall growth. Hence, performance evaluation becomes essential to ensure that the right talent has been allocated to the right job at the right time. Human Resource (HR) analytics plays an essential role in performance evaluation. While evaluating performance, most organizations consider only organizational factors and overlook the social and psychological factors. This paper attempts to study the impact of organizational, social, and psychological factors on employees’ performance by using data mining and machine tools for intelligent automated decisions. The machine learning models are developed using the employees’ databases via which predictions of employees’ performance are being made. This study provides a forecasting model for employee performance that allows Human Resource professionals to forecast employee performance and emphasize human capability criteria to improve the quality of life and human capital’s performance appraisal process. The study helps optimize HRM in organizations for the betterment in the long run.

Keywords: Data mining; Machine learning; Human resource management (HRM); K-nearest neighbor; Logistic regression; Random forest (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-981-99-0197-5_39

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DOI: 10.1007/978-981-99-0197-5_39

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