Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 21, Pages: 1-7
Abhyankar Minal and Metkewar Pravin
Symbiosis Institute of Computer Studies and Research, [email protected]
Objectives: To propose a model for ranking the performance of the employees of FMCG sector. Methods/Statistical Analysis: In this paper, authors have used Min Max Method. The data for 100 employees have been generated for identifying the performance of employees through linguistic theory model. The main factors which affect the performance of the employee can be mainly categorized in four sections: job performance, job capacities, job behavior and personal. For each performance criterion the linguistic values has been assigned. Then the relative importance of linguistic variables is calculated. Findings: The major step in the decision making process is to establish a fuzzy association relation between a precise category and every employee’s performance for that group. Considering the significance allocated to each criterion set the highest value for that grouping, the association relation is established by taking the complement of the category set importance. This complement produces a smallest performance value assigned to all employees as per the category. At the end, combined the performances of the employee across all groups in order to achieve a complete assessment by applying the min function to the set. Author got the results that 80 employees needed training in job performance as they have overall rating 0.2; whereas 16 employees needed training in job capacities as they have overall rating 0.40 and 4 employees can be promoted as they have overall rating 0.41 which is highest. Applications/Improvements: The proposed approach of fuzzy evaluation methodology can be used for other sectors like evaluation of students, evaluation of product or quality assessment of software, teacher or supplier evaluation with small modifications.
Keywords: Fast Moving Consumer Goods (FMCG), Fuzzy Numbers, Fuzzy MCDM, Linguistic Variables
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