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The main goal of any organization is to achieve the best quality of work through employees, and managers play a very important role in this field. Managers and leaders of organizations often face with paradoxes that make decision-making difficult. The purpose of this paper is to develop a competency model for human resource managers considering the importance of the role of paradoxes for organizations.

The research methodology is of a mixed type and with an approach based on paradox theory and using theme analysis and fuzzy Delphi, it seeks to provide a model of paradoxical managers’ competence. The statistical sample included 11 experts working in the information and communication technology industry, who were selected using the snowball and judgmental sampling method.

The results of this research show that the competency model of human resource managers has three managerial, organizational and individual levels and has 15 themes including strategic partner, organizational knowledge, awareness of the industry environment, awareness of the external environment, paradoxical thinking, managerial knowledge, relationship management, resource management , leadership, human resources analyzer, information technology (IT) knowledge, personality traits, development, multitasking and cognitive competence. The most important theme identified is paradoxical thinking and familiarity with IT knowledge, and it is suggested that human resource managers working in this field should preferably study technical and engineering fields at the undergraduate level and shift to human resource management fields at the graduate level.

The distinguishing feature of this paper is the presentation of a competency model based on paradox theory. Paradoxes are part of organizational life. Therefore, there should be a paradoxical view in all organizational analysis.

The purpose of this paper is to present a new technique for the determination of effective criteria weight on satisfaction using genetic algorithm and fuzzy synthetic evaluation.

The weight values express the relative importance of criteria. In most of research works, weight values depend heavily on expert knowledge, and customer’s perspective have not been considered. The proposed approach determines the criteria weight on satisfaction using genetic algorithm and fuzzy synthetic evaluation considering Euclidean distance between the computed overall satisfaction evaluation and the surveyed overall satisfaction evaluation.

The research findings show that different segments of customer have various needs and explain causes of various needs in customers using genetic algorithm and fuzzy synthetic evaluation.

The value of the paper is in it using a new approach in order to determine the weight of criteria. The main advantage of proposed approach is that it will help managers and researchers to determine the weight of criteria on satisfaction, and this process will no longer just rely on expert knowledge.