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The Graduates’ Satisfaction at Work Through a Generalization of the Fuzzy Least Square Regression Model

  • Francesco CampobassoEmail author
  • Annarita Fanizzi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9157)

Abstract

In previous works we provided some theoretical results on the estimates of a fuzzy linear regression model. In this paper we propose a generalization of such results to a polynomial model with multiplicative factors, which is actually more appropriate than the linear one. In fact, even in a fuzzy approach the growth rate of the dependent variable can vary depending on the values assumed by independent variables as well as on their interaction. In this application case, we regress the overall satisfaction for the working experience, expressed by the second cycle graduates in the 2008 of the University of Bari, on their satisfaction for specific aspects of job. Since the interviewed graduates express their own liking through scores which do not represent an objective measure of the personal opinions, but rather correspond to accumulation values on the submitted scale, the fuzzy approach is adequate to deal with such collected data.

Keywords

Fuzzy least square regression Polynomial model Multiplicative factors Goodness of fit Stepwise selection Satisfaction at work Graduates from University of Bari 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Economics and MathematicsUniversity of BariBariItaly
  2. 2.Inter-University Department of PhysicsUniversity of BariBariItaly

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