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Waste Household Electronic Appliance Recycling Influencing And Charaterization Of Urban Resident

Posted on:2016-03-28Degree:MasterType:Thesis
Country:ChinaCandidate:B B YangFull Text:PDF
GTID:2309330485983213Subject:Transportation planning and management
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The exponential growth of e-waste may further be compounded by a reduction of the useful life of existing devices driven by the ever faster release of products with new features. The need to better understand what motivates people to adopt pro-environmental behaviors (PEB) has taken a new urgency with the increasing emphasis on sustainability. Learn residents recycling behavior is the key to build reverse logistics system.First, the connotation of recycling behavior of waste household electronic appliance is described. We summarize the factors of waste household electronic appliance recycling behaviors with reference to researches both at home and abroad. Furthermore, we establish a model of factors that can influence recycling behaviors. In this model, the dependent variable is aste household electronic appliance recycling behaviors and the independent variables are personal characteristics, situational and demographics factors. In addition, we conducted a survey at E Meishan city and collect massive data through 853 questionnaires. We use ANOVA, logistic regression and structural equation modeling to do empirical researches. The results showed that the most important variables that influence individual behavior of waste home appliances internal variables is the internal variables, the second are the external variable environmental knowledge and economic motives, but also with a certain demographic variables the statistical significance; Laws and Regulations has moderating effects on the route of Internal variable-Recycling behavior.Finally, based on the research results put forward suggestions on how to improve the residents’determinants of waste home appliances.
Keywords/Search Tags:reverse logistics, waste household electronic appliance, recycling behavior, logistic regression, structural equation modeling
PDF Full Text Request
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