Job Satisfaction Evaluation Using Fuzzy Approach

Abstract

Likert-type scale that employs ordinal values to represent linguistics terms has been very popular in the studies on job satisfaction evaluation. In this work, it is argued that the use of ordinal values in Likert scale does not offer the best way in representing the linguistic terms. This paper proposes the use of fuzzy sets to represent linguistic terms in Likert-type scale and employs the technique using fuzzy conjoint method in job satisfaction evaluation. Experimental results show that the analysis using fuzzy conjoint method produced consistent result compared to the analysis using the percentage. However, the fuzzy membership values obtained from fuzzy conjoint method can be used to compare the decisions between criteria used to measure job satisfaction, and hence is very useful in providing additional information for decision-making.

An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery

“…Azadeh et al (2006) O ? Rasmani and Shahari (2007) O O O Calisir and Gumussoy (2007) O O ? Mohammad Fam et al (2007) O ?…”

“…Likert-type scale that employs ordinal values to represent linguistics terms has been very popular in the studies related to job satisfaction evaluation. Rasmani and Shahari (2007) showed that the ordinal values in Likert scale does not offer the best way in representing the linguistic terms. They proposed the use of fuzzy sets to represent linguistic terms in Likert-type scale.…”

A unique algorithm for the assessment and improvement of job satisfaction by resilience engineering: Hazardous labs

“…Calisir and Gumussoy (2007) used an analysis to assess the impact of IT professionals' demographic features, work stress and work characteristics on job satisfaction. Rasmani and Shahari (2007) proposed the use of fuzzy sets to exhibit linguistic terms in Likert-type scale. They also employed the fuzzy conjoint method in job satisfaction assessment.…”

Job satisfaction evaluation based on fuzzy conjoint method with continuous fuzzy sets

“…where ( , ) j R y A is the fuzzy set calculated on the basis of responses given by respondents, and ( , ) j F x l is the standard fuzzy set defined for linguistic label l. This similarity measure was used by [8] to evaluate job satisfaction; by [21] to evaluate software usability; by [7] to measure student expectations and by [4] to measure teacher beliefs on learning mathematics. Wang [9] introduced similarity between two fuzzy sets, R and F, based on Set-Theoretic approach as follows:…”

“…Thus, some values from the interval 0-1 with some tolerance zones are assigned to each linguistic term. Currently, in FCM, each linguistic term is expected to be represented by discrete fuzzy sets (see for examples: [3][4][5][6][7][8]). It can be observed that little effort has been made to utilise continuous fuzzy sets in the FCM process although it is expected that the use of continuous fuzzy sets may result in different decision outcomes.…”