Imani Raeesi Vanan; Mohammad Reza Taghva; Delnia Amir Ashayeri
Abstract
In this research, for the purpose of evaluating the performance of knowledge management systems as an improving infrastructure for organizational learning and performance in software development industry, a fuzzy inference system is designed and evaluated. At first, input variables were extracted ...
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In this research, for the purpose of evaluating the performance of knowledge management systems as an improving infrastructure for organizational learning and performance in software development industry, a fuzzy inference system is designed and evaluated. At first, input variables were extracted as the performance evaluators of knowledge management system. Then, if-then rules were identified through the utilization of experts’ opinions and inserted to the fuzzy rule-base. The output of inference system was also designed for performance evaluation of knowledge management system. The designed system, through a comprehensive assessment of knowledge management systems, can enable organizations to identify the strengths, weaknesses, current condition, and future decisions making for the purpose of performance improvement. For the validation of fuzzy inference system, a comparison was made between system outputs and experts viewpoints. Considering the very small difference between the average of experts’ opinions and system output, it can be stated that the system has an appropriate precision and validity for future assessment.
Zahra Jalaeian Zafarani; Mehdi Seifbarghy Seifbarghy
Volume 1, Issue 3 , June 2014, , Pages 1-18
Abstract
In this paper, we propose a new model on personnel performance evaluationconsidering the job specifications so that the personnel are evaluatedbased on the job rather than only individual specifications. This is the majorcontribution of this paper. Based on the proposed model, for both individualand ...
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In this paper, we propose a new model on personnel performance evaluationconsidering the job specifications so that the personnel are evaluatedbased on the job rather than only individual specifications. This is the majorcontribution of this paper. Based on the proposed model, for both individualand job specifications, the corresponding criteria are determinedwith different factors. The individual criteria are obtained from differentresearches and are filtered and classified into three social, technical andmanagement groups. The job specifications are also collected from the aprevious valid research. We have used the pair wise comparison of normaland fuzzy AHP in order to determine the factor numbers of the individualcriteria and normal AHP in order to determine the factor numbers of thejob criteria. Finally, each personnel is given score (at most 5) regardingthe criteria and all the personnels are ranked using TOPSIS method. Thewhole steps are presented in the form of a decision support system and isimplemented in the Export Developing Bank of
