Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/24676
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dc.contributor.advisorAbbod, M-
dc.contributor.advisorSwash, M. R.-
dc.contributor.authorAlrashedi, Ahmed-
dc.date.accessioned2022-06-09T13:31:43Z-
dc.date.available2022-06-09T13:31:43Z-
dc.date.issued2021-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/24676-
dc.descriptionThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University Londonen_US
dc.description.abstractCurrent organisations face many challenges and changes that have resulted from human and technological developments in modern society. Human capital is an active component of an organization's economic value. To benefit from this resource, an effective performance appraisal system must be designed. Such a system should provide job descriptions for all the employees. Additionally, it should contain comprehensive data about all employees in the past and present and determine their capabilities, skills, experience, and level of competence to identify the extent of their contribution to achieving business goals. Knowing the employee’s performance level enables management to identify deficiencies in their performance and work. That can help the management to improve performance by identifying appropriate training courses so they can perform their tasks efficiently and effectively. It is important for the organisation to obtain a comprehensive and clear picture of the duties and responsibilities of all its employees by having job descriptions for all its functions and having all data related to employees, their abilities, qualifications, and previous experience. This research focuses on the urgent need for human resources management systems to take advantage of technological developments using artificial intelligence as a means to achieve the goals of human resource management in accordance with the vision and mission of the organisation and, more specifically, in a fast, accurate, and more objective way. The study has been organised into six phases with regard to developing a performance appraisal system. The study began by providing job descriptions for all organisational jobs, followed by using computer programmes to enter all data related to the employees in all roles they previously held and departments they worked in within the organization. Subsequently, a questionnaire was designed and distributed to employees in many universities and companies to understand the employees' opinions about (1) the importance of job descriptions and the performance evaluation form, and (2) the importance of using Artificial intelligence in the appraisal system. The researcher inserted the artificial neural network into the applicable performance appraisal system in order to develop it. The new system has been implemented in the College of Business Administration in Jeddah. The researcher then conducted personal interviews to explore the views and experiences of managers after using the advanced system. Most of the opinions, about 80%, were in favour of using the newly developed human resources management system instead of the previous system because it showed many added benefits, such as speed, accuracy, and comprehensiveness of objective information about the employee, in addition to the ease of making the right decisions.en_US
dc.publisherBrunel University Londonen_US
dc.relation.urihttp://bura.brunel.ac.uk/handle/2438/24676-
dc.subjectPerformance appraisalen_US
dc.subjectLiner regressionen_US
dc.subjectJob descriptionen_US
dc.subjectAnalysis of varianceen_US
dc.subjectPerformance Appraisal Systemen_US
dc.titleArtificial intelligence based system for human resources appraisalen_US
dc.typeThesisen_US
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Electrical Engineering Theses

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