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Performance Appraisal on Employees’ Motivation: A Comprehensive Analysis

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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020 (AISI 2020)

Abstract

Several analysis studies have been carried out with a view to providing valuable knowledge into the existing research outline of the performance appraisal and employee motivation. The current study systematically reviews and synthesizes the performance appraisal and employee motivation aiming to provide a comprehensive analysis of 27 articles from 2015 to 2020. The research will aim to establish the impact of performance appraisal fairness on the employees’ motivation in an organization. To achieve its objective, the study will adopt descriptive research. It will be informed of a survey, and there will be a sample selection to make the process economical. This shows that there will be a use of different techniques of information collection since the data to be collected a primary data. There will be interviewing of the sample size, and their responses will be noted down. The presence of the researcher may influence some people, and this necessitates the use of questionnaires for the respondents to fill on their own. In addition, most of the analyzed studies were conducted in Malaysia, China, Pakistan, and India. Besides, most of the analyzed studies were frequently conducted in job satisfaction and performance context, employee motivation followed by organizational effectiveness context. To that end, the findings of this review study provide an insight into the current trend of how performance appraisal affects employee’s motivation.

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Correspondence to Said A. Salloum .

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Alsuwaidi, M., Alshurideh, M., Al Kurdi, B., Salloum, S.A. (2021). Performance Appraisal on Employees’ Motivation: A Comprehensive Analysis. In: Hassanien, A.E., Slowik, A., Snášel, V., El-Deeb, H., Tolba, F.M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020. AISI 2020. Advances in Intelligent Systems and Computing, vol 1261. Springer, Cham. https://doi.org/10.1007/978-3-030-58669-0_61

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