A proposed sustainable and digital collection and classification center model to manage e-waste in emerging economies

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Date

2021

Authors

Yigit Kazancoglu
Melisa Ozbiltekin
Yesim Deniz Ozkan Ozen
Muhittin Sagnak

Journal Title

Journal ISSN

Volume Title

Publisher

EMERALD GROUP PUBLISHING LTD

Open Access Color

Green Open Access

Yes

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Publicly Funded

No
Impulse
Top 10%
Influence
Average
Popularity
Top 10%

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Abstract

Purpose This study aims to propose an electronic waste collection and classification system to enhance social environmental and economic sustainability by integrating data-driven technologies in emerging economies. Design/methodology/approach GM (1 1) model under grey prediction is used in this study in order to estimate the trend of the amount of collected electronic waste in emerging economies. Findings It is revealed that the amount of collected electronic waste is increasing day by day and within the framework of sustainability in the process of collecting and classification of electronic waste digital technologies were found to be lacking. It has been determined that this deficiency together with the increasing amount of electronic waste has caused environmental social and economic damage to emerging economies. Originality/value The main originality of this study is integrating electronic waste collection and classification processes with data-driven technologies and sustainability which is a relatively new subject.

Description

Keywords

Digitalization, Data-driven technologies, Sustainability, Waste management, Electronic waste, Forecasting, Grey method, ELECTRONIC WASTE, DEVELOPING-COUNTRIES, FLOW-ANALYSIS, GENERATION, PREDICTION, FUTURE, POPULATION, APPLIANCES, BUSINESS, INITIATIVES

Fields of Science

01 natural sciences, 0105 earth and related environmental sciences

Citation

WoS Q

Scopus Q

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OpenCitations Citation Count
29

Source

Journal of Enterprise Information Management

Volume

34

Issue

Start Page

267

End Page

291
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Citations

CrossRef : 27

Scopus : 44

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Mendeley Readers : 144

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