Two dimensional model designing to evaluate employees performance using fuzzy approach

Performance management in different organizations is a major of today’s management studies, which is noticed due to employees’ performance improvement. Performance evaluation is a process by which employees are evaluated in pre-defined seasons and manners. In this research, first using related researches, for employees’ performance general and special evaluations some criteria have been acquired. These employees are active in software development section. Special criteria are those that have been explored for the main active sections, such as IT, Software engineering, Finance, Sales and Marketing and Project Control, in software development companies. Afterwards, using job descriptions of each of these sections, another group of criteria have been drawn. The set of criteria drawn out of job descriptions and related studies were called primary criteria. Then these primary criteria were handed to the experts, after interviewing with whom, the secondary general and special criteria related with four aforementioned active sections have been explored. For each section the number of suitable samples was computed, and the questionnaires related to general and special performance evaluation have been designed and distributed. After gathering the questionnaires and exploration of data, the employees were rated using regular and fuzzy Topsis. Then the results of these two approached were compared and Fuzzy Topsis was chosen as a better method to continue the study. Eventually, the employees of each group were rated twice, once based on general criteria with respect to all the employees and once based on special criteria with resspect to employees in their own section. Results showed that the employees who are the worst or best in their own section were not necessarily the worst or best in the whole organization. The study group was Tehran Science and Technology Parks.

کلیدواژه ها:

Employees’ performance evaluation ، Performance Management ، Performance evaluation criteria ، Fuzzy TOPSIS ، Regular TOPSIS ، Decision making ، Rating