Propose a decision support system (DSS) for blue collar cashier personnel recruitment by using a multiple criteria decision making (MCDM) approach
2018
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Advisor: Dr. Öğr. Üyesi Çağla Şeneler
Abstract (EN)
In terms of human resources management, personnel recruitment selection and placement are a significant process so that, the process of determining the appropriate blue-collar cashier personnel for recruitment. Personnel recruitment selection and placement, frequently occurs because of decisions made by a group decision based on the evaluation of candidates by various criteria and individual judgment transmitter. Whereas the corporations that they could gain competitive advantage and this advantage may continue, according to the correct blue-collar personnel for the correct job it depends on the equitable criteria chosen. There are personnel recruitment selection and placement problems, decision making, becoming more than the number of candidates and the terms of many criteria involved in the decision which effect on multiple criteria decision-making problems. In literature, numerous methods are available with respect to personnel selection. Anyhow, it is observed that in these methods, the interdependency of personnel selection reasons was not considered by human resources department. In the proposed study, the possibility of better human resources management with an application was discussed by using ANP for criteria weighting and ELECTRE for alternative ranking. The application which helps human resources department to determine the best candidate, was developed and pilot study was done for a position of blue collar cashier recruitment in a company of retail sector. The results were given as consistency as expected by decision makers and proved its accuracy.
Author
Sinan Yılmaz Yürüten
Institution
How to Cite
Sinan Yılmaz Yürüten (Master Thesis). Propose a decision support system (DSS) for blue collar cashier personnel recruitment by using a multiple criteria decision making (MCDM) approach, 2018, Yeditepe University.
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