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Title: The Effect of Using Artificial Intelligence on Performance of Appraisal System: A Case Study for University of Jeddah Staff in Saudi Arabia
Authors: Alrashedi, A
Abbod, M
Keywords: Artificial intelligence;Performance appraisal;Software benefit;Technology adoption
Issue Date: 25-Aug-2020
Publisher: Springer
Citation: Advances in Intelligent Systems and Computing, 2021, 1250 AISC pp. 145 - 154
Abstract: © 2021, Springer Nature Switzerland AG. Despite the interest of developed countries in relying on artificial intelligence in the performance of their work, developing countries are at the beginning of this path. The researcher has noted that the use of modern technologies, especially artificial intelligence, did not give the necessary attention in government business and many private sector companies, so it was necessary to draw attention to the importance of using it to develop all businesses. This study focuses on clarifying the importance of using artificial intelligence (AI) technology in the process of evaluating the employee’s performance to increase the effectiveness of performance appraisal for all organisational levels to make strategic decisions which affect the objectives of the organisation. This study has used a questionnaire that looked at participants’ views and attitudes towards technology and its usefulness in the appraisal process. Knowing the opinions of employees and their supervisors will enable to demonstrate the need to use AI to raise the efficiency of the performance appraisal system and develop its processes for the employee’s benefits and the general interest at the organisation. Most of the answers were between agree and strongly agree, and on the other side, there was a very small percentage that did not believe the importance of using artificial intelligence in works, and this may be due to their feeling of resisting change and the desire to work a way they used to. This paper begins by providing demographic details and background information on the participants, followed by an examination of the reliability of the extracted factors/metrics. The extracted factors will then be described individually using general descriptive statistics (such as repetition percentages) to look at their respective elements and see the level of the agreement created by the participant. Following this descriptive part of the analysis, this paper seeks to conduct an in-depth analysis of the results using various inferential statistics to test group differences using demographic and background details of the participants (e.g. age, gender, education). This study investigates the impact of the use of AI on the performance appraisal model, and to examine the effect of AI on the technology adoption.
Description: The final authenticated version is available online at
ISBN: 9783030551797
ISSN: 2194-5357
Appears in Collections:Dept of Electronic and Computer Engineering Embargoed Research Papers

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