{"title":"Developing Industry 4.0-based e-waste management: a decision-aided tool equipped with continuous function-valued intuitionistic fuzzy sets","authors":"B. Aydoğan, G. Özçelik, M. Ünver","doi":"10.1007/s13762-024-05977-y","DOIUrl":null,"url":null,"abstract":"<div><p>Electronic waste (e-waste) is a global problem with an increasing environmental impact every day. The impact on the environment, on the lives of living beings, and on the pollution and destruction of nature is escalating day by day. Given the scale of the problem, there is an urgent need to identify and implement solutions. The strategies to be developed should be innovative and aligned with today’s technological advancements, including artificial intelligence. To this end, the aim of this study is to present an original fuzzy decision-aided framework for ensuring sustainable e-waste management within the context of key Industry 4.0 strategies. This study uses original data and is supported by expert opinion. Additionally, the advantages of continuous function-valued intuitionistic fuzzy sets (CFVIFSs), an innovative approach, are utilized. The criteria weighting is enhanced by the Kullback–Leibler divergence measure formed with these CFVIFSs, adding another dimension to the study. Results are achieved using Goal Programming (GP) approach in strategy selection. In addition, detailed and comparative analyses are conducted to evaluate strategy rankings from different perspectives. In the sensitivity analysis, the rankings are obtained according to the varying weights of criteria. Furthermore, The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and The Simple Additive Weighting (SAW) method are employed for the comparative analysis. Moreover, Spearman’s rank correlation coefficients are calculated to examine the consistency of each case. Overall, this study, which brings together different perspectives, provides valuable managerial insights to a global problem.</p></div>","PeriodicalId":589,"journal":{"name":"International Journal of Environmental Science and Technology","volume":"22 8","pages":"6595 - 6620"},"PeriodicalIF":3.0000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Environmental Science and Technology","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s13762-024-05977-y","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Electronic waste (e-waste) is a global problem with an increasing environmental impact every day. The impact on the environment, on the lives of living beings, and on the pollution and destruction of nature is escalating day by day. Given the scale of the problem, there is an urgent need to identify and implement solutions. The strategies to be developed should be innovative and aligned with today’s technological advancements, including artificial intelligence. To this end, the aim of this study is to present an original fuzzy decision-aided framework for ensuring sustainable e-waste management within the context of key Industry 4.0 strategies. This study uses original data and is supported by expert opinion. Additionally, the advantages of continuous function-valued intuitionistic fuzzy sets (CFVIFSs), an innovative approach, are utilized. The criteria weighting is enhanced by the Kullback–Leibler divergence measure formed with these CFVIFSs, adding another dimension to the study. Results are achieved using Goal Programming (GP) approach in strategy selection. In addition, detailed and comparative analyses are conducted to evaluate strategy rankings from different perspectives. In the sensitivity analysis, the rankings are obtained according to the varying weights of criteria. Furthermore, The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and The Simple Additive Weighting (SAW) method are employed for the comparative analysis. Moreover, Spearman’s rank correlation coefficients are calculated to examine the consistency of each case. Overall, this study, which brings together different perspectives, provides valuable managerial insights to a global problem.
期刊介绍:
International Journal of Environmental Science and Technology (IJEST) is an international scholarly refereed research journal which aims to promote the theory and practice of environmental science and technology, innovation, engineering and management.
A broad outline of the journal''s scope includes: peer reviewed original research articles, case and technical reports, reviews and analyses papers, short communications and notes to the editor, in interdisciplinary information on the practice and status of research in environmental science and technology, both natural and man made.
The main aspects of research areas include, but are not exclusive to; environmental chemistry and biology, environments pollution control and abatement technology, transport and fate of pollutants in the environment, concentrations and dispersion of wastes in air, water, and soil, point and non-point sources pollution, heavy metals and organic compounds in the environment, atmospheric pollutants and trace gases, solid and hazardous waste management; soil biodegradation and bioremediation of contaminated sites; environmental impact assessment, industrial ecology, ecological and human risk assessment; improved energy management and auditing efficiency and environmental standards and criteria.