{"title":"Acceptance of E-waste Recycling Among Young Adults: An Empirical Study","authors":"M. Aboelmaged","doi":"10.1109/SusTech47890.2020.9150485","DOIUrl":null,"url":null,"abstract":"This paper integrates habits into the Theory of Planned Behavior and the Technology Acceptance Model to predict waste electrical and electronic equipment (WEEE) or the e-waste recycling intention among young adults. This study adopts the structural equation modelling (SEM) technique, using the partial least squares (PLS) approach as a multivariate statistical method to analyze the survey data. The findings show that the integrated model has good explanatory power and confirms its robustness in predicting the e-waste recycling intention among young adults. The role of habits and perceived usefulness are demonstrated as strong predictors of young adults' e-waste recycling intention, as well as their attitudes. The paper concludes with several social and practical implications that can foster e-waste recycling initiatives in the UAE.","PeriodicalId":184112,"journal":{"name":"2020 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"46 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Conference on Technologies for Sustainability (SusTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SusTech47890.2020.9150485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper integrates habits into the Theory of Planned Behavior and the Technology Acceptance Model to predict waste electrical and electronic equipment (WEEE) or the e-waste recycling intention among young adults. This study adopts the structural equation modelling (SEM) technique, using the partial least squares (PLS) approach as a multivariate statistical method to analyze the survey data. The findings show that the integrated model has good explanatory power and confirms its robustness in predicting the e-waste recycling intention among young adults. The role of habits and perceived usefulness are demonstrated as strong predictors of young adults' e-waste recycling intention, as well as their attitudes. The paper concludes with several social and practical implications that can foster e-waste recycling initiatives in the UAE.