Application of fuzzy logic in job satisfaction performance problem

被引:2
|
作者
Eyupoglu, Serife Z. [1 ]
Gardashova, Latafat A. [2 ]
Allahyerdiyev, Rashad A. [3 ]
Saner, T. [4 ]
机构
[1] Near Eeast Univ, Dept Business Adm, POB 99138, TR-10 North Cyprus, Mersin, Turkey
[2] Azerbaijan State Oil & Ind Univ, Dept Comp Engn, Azadlyg Ave 20, AZ-1009 Baku, Azerbaijan
[3] Azerbaijan State Oil & Ind Univ, BA Programs, Azadlyg Ave 20, AZ-1009 Baku, Azerbaijan
[4] Near East Univ, Sch Tourism & Hotel Management, POB 99138, TR-10 North Cyprus, Mersin, Turkey
来源
12TH INTERNATIONAL CONFERENCE ON APPLICATION OF FUZZY SYSTEMS AND SOFT COMPUTING, ICAFS 2016 | 2016年 / 102卷
关键词
job satisfaction; fuzzy logic; possibility measure; expert system; fuzzy inference; Minnesota Satisfaction Questionnaire; quality measure-degree of truth; fuzzy arithmetic mean;
D O I
10.1016/j.procs.2016.09.388
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2016 The Authors. Published by Elsevier B.V.
引用
收藏
页码:190 / 197
页数:8
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