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A Multivariate Regression Model for Waste Glass Prediction


Natter, Martin; Weber, Andreas; Bach, Heinz; Mild, Andreas (2002). A Multivariate Regression Model for Waste Glass Prediction. Forum Ware, 30:101-102.

Abstract

In this paper, the authors develop a model to predict collected amounts of glass at the regional level of municipalities. Learning about the factors that influence the amount of collected glass is a prerequisite for the evaluation and reorganisation of collection systems. Furthermore, such a model provides essential input for decisions like restructuring activities, implementation of legal directives or investments into new recycling plants. The authors hypothesise that the amount of collected glass depends on both, the waste glass potential and factors which influence the convenience such as the density of collection sites. The authors develop a multivariate regression model providing valuable insights about the relationship between demographic parameters and the amount of collected waste glass, as well as between logistic parameters and collected waste glass. The aim of such a model is the identification of parameters which significantly influence the amount of collected waste in order to provide decision makers with a tool for accurate planning. A significant positive impact of the logarithmic number of collection sites on the amount of waste glass collected was found. A significant impact of the percentage of city area, overnight stays per person, percentage of employees in the service sector, indices of purchasing power and percentage of alpine area were identified. The model explains the amount of collected waste glass and can help to estimate the waste glass potential.

Abstract

In this paper, the authors develop a model to predict collected amounts of glass at the regional level of municipalities. Learning about the factors that influence the amount of collected glass is a prerequisite for the evaluation and reorganisation of collection systems. Furthermore, such a model provides essential input for decisions like restructuring activities, implementation of legal directives or investments into new recycling plants. The authors hypothesise that the amount of collected glass depends on both, the waste glass potential and factors which influence the convenience such as the density of collection sites. The authors develop a multivariate regression model providing valuable insights about the relationship between demographic parameters and the amount of collected waste glass, as well as between logistic parameters and collected waste glass. The aim of such a model is the identification of parameters which significantly influence the amount of collected waste in order to provide decision makers with a tool for accurate planning. A significant positive impact of the logarithmic number of collection sites on the amount of waste glass collected was found. A significant impact of the percentage of city area, overnight stays per person, percentage of employees in the service sector, indices of purchasing power and percentage of alpine area were identified. The model explains the amount of collected waste glass and can help to estimate the waste glass potential.

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Additional indexing

Other titles:Multivariates Regressionsmodell für die Vorhersage der Sammelmenge von Altglas
Item Type:Journal Article, not refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Business Administration
Dewey Decimal Classification:330 Economics
Language:English
Date:2002
Deposited On:09 Dec 2016 11:08
Last Modified:10 Dec 2016 04:08
Publisher:Deutsche Gesellschaft fuer Warenkunde und Technologie
ISSN:0340-7705
Related URLs:https://www.tib.eu/ (Publisher)
Other Identification Number:merlin-id:14208

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