A Personnel Selection Problem in Healthcare System Using Fuzzy-TOPSIS Approach (Journal of Nonlinear Modeling and Analysis, 2024)
The methods of multiple criteria decision-making (MCDM) areincreasingly becoming the most desired tools for making daily decisions invarious fields of human endeavors. Staff employment in any sector requires athorough evaluation of the applicant before selection to ensure effective andefficient service delivery. Besides, healthcare is one of the most complicatedorganizations dealing with human lives. This paper has developed a staff selection model considering a fuzzy environment by using the technique for orderpreference similar to the ideal solution (TOPSIS) method. For the deliveryand promotion of quality healthcare systems, medical staff selection is crucial to the system. Therefore, the study evaluates medical staff by using theexpert’s linguistic judgement under the criteria of skill, experience and ability to respond to a problem. The expert’s vagueness in judgments has beenrepresented by using fuzzy triangular numbers. The study determines thecloseness coefficient, the measures of separation and the ideal solutions of theTOPSIS method. The most appropriate medical staff are ranked and selectedbased on the available criteria. The Fuzzy-TOPSIS method is simple and canhelp other organizations achieve proper ranking, evaluation and selection ofqualified candidates, as it takes imprecise information into account.
Keywords: Fuzzy-TOPSIS; triangular fuzzy number; separation measure; closeness coefficient; ideal solution.