title: Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model.
abstract: In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique.
authors.affiliation: Department of Economics, Faculty of Business and Management, Brno University of Technology, Czech Republic. Electronic address: stepan.vesely@mail.muni.cz.
authors.forename: Stepan
authors.initials: S
authors.lastname: Vesely
authors.affiliation: Department of Psychology, Norwegian University of Science and Technology, Norway. Electronic address: christian.klockner@svt.ntnu.no.
authors.forename: Christian A
authors.initials: CA
authors.lastname: Klöckner
authors.affiliation: Department of Economics, Faculty of Business and Management, Brno University of Technology, Czech Republic. Electronic address: dohnal@fbm.vutbr.cz.
authors.forename: Mirko
authors.initials: M
authors.lastname: Dohnal
mesh_terms: D017143:Fuzzy Logic; D006801:Humans; D016014:Linear Models; D059027:Recycling / Q000706:statistics & numerical data
keywords: Empirical test; Fuzzy logic; Prediction; Recycling behaviour