A Fuzzy Soft Set-Based MADM Technique for Handling Uncertainty in Recruitment Decisions

Abstract

Since every organization operates smoothly and efficiently through the efforts of its employees, selecting the best person for any organization plays a crucial role in its effective functioning. However, this selection process involves many attributes that must be analyzed carefully. Making a well-informed decision based on several factors requires a multi-attribute decision-making (MADM) technique. To handle uncertainty and ambiguity in this process, a framework integrated with MADM is needed. In this regard, this article presents an advanced MADM technique based on the similarity measures of the complex Fermatean fuzzy soft set. Furthermore, the proposed model is applied to a case study for employee selection in an organization. Finally, the article concludes with remarks on the limitations of the proposed model and directions for future research.