Competency Assessment Based on Fuzzy Logic and Artificial Intelligence Mechanism: A Study of Competency Assessment Document for the Algerian SEROR Company
Journal: Business Ethics and Leadership (BEL) (Vol.7, No. 4)Publication Date: 2023-12-31
Authors : Mohammed Sahnouni; Riad Benghebrid;
Page : 159-170
Keywords : competence; competency assessment; FisPro; fuzzy logic; artificial intelligence mechanism;
Abstract
Addressing the issue of how automating the quantitative assessment of competencies through a competency assessment document came to remove the assessment process from the descriptive side and an attempt to propose a new model aligned with modern management requirements. Competency assessment is considered one of the most important indicators for managing competencies in organizations, as it offers valuable insights into the strengths and weaknesses of human resources, which is essential for strategic planning. Organizations are actively seeking a cost-effective and accurate system, aiming to minimize the impact of subjective biases in the evaluation process. Additionally, there is a need for a solution that facilitates swift assessment of a large workforce, ultimately reducing overall costs. To meet these requirements, the current study employs Fuzzy Logic and Artificial Intelligence mechanism to develop a contemporary and precise evaluation model. The study, which analyzed competency assessment data from the Algerian SEROR Company, showcased the possibility of creating a sophisticated quantitative model for competency evaluation using Fuzzy Logic and Artificial Intelligence Mechanism. The results imply that the institution has the potential to embrace a cutting-edge and forward-thinking approach, enhancing objectivity, particularly in dealing with complex systems. Developing a quantitative competency evaluation model requires a comprehensive database that includes relevant factors in the evaluation process, encompassing details about each employee's position, skills, knowledge and experience. The research emphasizes that creating a quantitative model through Fuzzy Logic and Artificial Intelligence Mechanism is highly achievable, with the applied study indicating an 85% success rate for the model.
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