Application of Fuzzy Logic in Job Satisfaction Performance Problem

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• 作者：Serife Z. Eyupoglu^a ; Latafat A. Gardashova^b ; ^{latsham@yandex.ru" class="auth_mail" title="E-mail the corresponding author} ; Rashad A. Allahverdiyev^c ; T. Saner^d
• 关键词：job satisfaction ; fuzzy logic ; possibility measure ; expert system ; fuzzy inference ; Minnesota Satisfaction Questionnaire ; quality measure-degree of truth ; fuzzy arithmetic mean
• 刊名：Procedia Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：102
• 期：Complete
• 页码：190-197
• 全文大小：122 K

文摘

Job satisfaction has been a popular topic of research for many decades. The interest in this topic has attracted psychologists, management scholars and, more recently, economists. Most of the studies conducted in the area of job satisfaction have been based on statistical methods. However these methods cannot account for the fact that basic facets of job satisfaction, such as Activity, Independence, Variety, Social status, and Supervision-human relations, to name but a few, are evaluated based on perceptions which do not provide precise numeric information. Information supported by perceptions can be processed more adequately by using fuzzy logic. In this paper we suggest fuzzy if-then rules based expert system to describe relations between job factors and overall job satisfaction.