A Case Study on Evaluating Personnel and Jobs Jointly with

Topics: Fuzzy logic, Fuzzy set, Membership function Pages: 12 (3302 words) Published: June 18, 2013
International Journal of Industrial Engineering, 18(4), 169-179, 2011.

A CASE STUDY ON EVALUATING PERSONNEL AND JOBS JOINTLY WITH FUZZY DISTANCE SETS İsmail Özdaban*, Coşkun Özkan** *Istanbul Technical University, Department of Industrial Engineering, Istanbul, Turkey. E-mail: iozdaban@artcraft.com.tr **Kocaeli University, Department of Industrial Engineering, Kocaeli, Turkey. E-mail: coskunozkan@kou.edu.tr In this research, a case study of fuzzy approach on personnel evaluation and job evaluation together was performed. A newer fuzzy distance measurement formula was developed and used to determine fuzzy distances. Although there have been many researches on personel evaluation and job evaluation concepts together, it is not found any research in which these to concepts were examined. Evaluating personel and job together gave some advantages like comparability of data, useness of model and managing the two concepts together. Model gave detailed information on an organization. Results showed that suggested formula and method could be used for small, medium or large companies easily, and allowed to evaluate two concepts together even there are many personel and jobs in an organization. Keywords: Fuzzy Sets, Personnel Evaluation, Job Evaluation, Human Resources, Human Capital (Received 2 November 2008; Accepted in revised form 24 January 2011)

1. INTRODUCTİON
Human capital is the most important and useful components for organizations in competition area. To support the organization effectively, management information system (MIS) managers must manage their human resources effectively (Chen et.al., 2005). Making the right decisions about human resources policies can determine success in companies (Cano´ s et al. 2008). Like successful evaluation in an organization, the probability of a successful and timely completion of a project is also improved when decision makers choose employees with the skill and competency set that best matches the multi-criteria demands of the project (Shipley et al., 2009). Within the realm of project management, it has been demonstrated that a fuzzy logic model could help in the selection of new product introductions (Shipley et al., 1995) because it allows for subjective evaluation by the decision maker under conditions of uncertainty and ambiguity. The decision maker faces similar conditions when selecting project team members (Shipley et al., 2009). In this research, personnel evaluation and job evaluation processes determined together based on fuzzy set theory, at the beginning of the research, personnel evaluation and job evaluation processes determined separately, current jobs and personnel related to these jobs classified according to their fuzzy distances, grouped in a scale table which was generated in this research, afterwards they compared according to their fuzzy distances and group numbers, and results were discussed. Results showed that fuzzy approach gave more detailed research opportunity within a job group. With using this method, it is possible to determine whether current personnel are able to work or not, even it is possible to determine position of a personnel in same job group. Thus, some further suggestions were made according to results like education needing of company or staff, amount and quality of educations according to personnel evaluation criteria and job evaluation factors, current position of jobs etc. Three possible personnel position were found and possible positions discussed.

2. METHOD
µ ( x) → [0,1] , where µA(x), ∀x ∈ E , Let E be a universe set. A fuzzy set A of E is defined by a membership function A indicates the degree of x in A. Let A+ and A- be positive and negative ideal solution; d+ and d- defined as alternative’s distance to positive and negative ideal solution (Jahanshahloo et al., 2006). A triangular fuzzy number A is a fuzzy number with piecewise linear membership function µA defined by (Wang et al., 2007);

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