Estimation of computer waste quantities using forecasting techniques

Abstract

Technology changes rapidly over years providing continuously more options for computer alternatives and making life easier for economic, intra-relation or any other transactions. However, the introduction of new technology “pushes” old Information and Communication Technology (ICT) products to non-use. E-waste is defined as the quantities of ICT products which are not in use and is bivariate function of the sold quantities, and the probability that specific computers quantity will be regarded as obsolete. In this paper, an e-waste generation model is presented, which is applied to the following regions: Western and Eastern Europe, Asia/Pacific, Japan/Australia/New Zealand, North and South America. Furthermore, cumulative computer sales were retrieved for selected countries of the regions so as to compute obsolete computer quantities. In order to provide robust results for the forecasted quantities, a selection of forecasting models, namely (i) Bass, (ii) Gompertz, (iii) Logistic, (iv) Trend model, (v) Level model, (vi) AutoRegressive Moving Average (ARMA), and (vii) Exponential Smoothing were applied, depicting for each country that model which would provide better results in terms of minimum error indices (Mean Absolute Error and Mean Square Error) for the in-sample estimation. As new technology does not diffuse in all the regions of the world with the same speed due to different socio-economic factors, the lifespan distribution, which provides the probability of a certain quantity of computers to be considered as obsolete, is not adequately modeled in the literature. The time horizon for the forecasted quantities is 2014-2030, while the results show a very sharp increase in the USA and United Kingdom, due to the fact of decreasing computer lifespan and increasing sales.

Publication DOI: https://doi.org/10.1016/j.jclepro.2015.09.119
Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School > Aston India Foundation for Applied Research
Additional Information: © 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: e-waste generation,lifespan,forecasting,distribution fitting,Industrial and Manufacturing Engineering,Renewable Energy, Sustainability and the Environment,Environmental Science(all),Strategy and Management
Publication ISSN: 1879-1786
Last Modified: 05 Jan 2024 08:18
Date Deposited: 11 Nov 2015 13:45
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2016-01-20
Published Online Date: 2015-10-22
Accepted Date: 2015-09-27
Submitted Date: 2015-02-23
Authors: Petridis, Nikolaos
Stiakakis, Emmanouil
Petridis, Konstantinos (ORCID Profile 0000-0002-0733-9336)
Dey, Prasanta (ORCID Profile 0000-0002-9984-5374)

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