An intelligent decision support model for staff selection based on the application of the Fuzzy Delphi Method and the Fuzzy Analytical Hierarchical Process

Abstract

Businesses today are required to operate in an ever-changing business environment characterized by complexity and uncertainty, in which the ability to make effective decisions is of particular importance. Furthermore, it is now indisputable that in the modern work environment, the difference between successful and unsuccessful organizations is determined by people, the so-called human resources. In this light, the proper selection of staff by the management of an organization is a critical parameter of competitiveness, productivity, and efficiency. Because of the above, the present work presents a comprehensive methodological approach to the issue that focuses on the multi-criteria nature of the problem. The proposed conceptual framework is based on the Fuzzy Analytical Hierarchical Process (FAHP), which uses the theory of fuzzy Logic and is considered appropriate in terms of the high degree of uncertainty about decision-making. The paper aims to define and analyze the criteria related to the modern administrative skills required by managers for the successful fulfillment of administrative practices. To this end, our methodology extends the Fuzzy Analytical Hierarchical Process by introducing the Fuzzy Delphi Method (FDM) technique. In this way, we can take into account the significance of each decision-maker and their particular preferences through the relative importance of decision-makers per evaluation criterion. As a case study, it was chosen to apply our method to a real institution and specifically at the Neapolis University Pafos, Cyprus, in a real case of the selection of academic staff. By using the Fuzzy Analytical Hierarchical Process, the candidates to fill the vacancy are ranked in order of priority, thus providing an appropriate tool at the institution’s disposal (and possibly a company or organization) to obtain the most appropriate decision for the problem under study.