Uncovering residents’ behaviors, attitudes, and WTP for recycling e-waste: a case study of Zhuhai city, China

Examination of Factors Relative to the Intention to Recycle

“…Analyzing data from a survey collected from 850 students from high-ranking educational institutions in China, Ramzan et al ( 2019) reported that students had no (20%) or low (61%) awareness of e-waste and no (30%) or low (56%) awareness of recycling; 40% had never or only a little (53%) participated in recycling in the past; 66% had no idea of the relevant laws, while 23% had only a low awareness; and 42% ignored recycling programs and 55% had only a low awareness of the initiatives. In another study conducted in China, a survey of 474 families living in a city reported that 76% of the respondents were aware of the threat to the environment due to the improper processing of e-waste, although only 38% were willing to pay a fee (Cai et al, 2020). A study of 430 consumers in a Brazilian city reported that a majority of the respondents were not aware of the law regulating electronic devices due to a lack of advertising, 72% were not aware of the law enforcing the recycling of mobile phones, although 71% knew they contain toxic substances (Damke et al, 2018).…”

Students’ Awareness of E-waste and Its Disposal Practices: a Conceptual Framework

“…They must organize awareness campaigns, provide high or marginal bene ts for ewaste disposal, and penalize non-e-waste disposal. Quantitative studies like Cai et al (2020) and Delcea et al (2020) also emphasized the governmental role in increasing e-waste disposal. The results also concluded that the organizations producing e-devices must develop a sustainable channel for the disposal and extraction of precision metals.…”

Why do Spanish households separate their e-waste for proper disposal? An econometric analysis

“…The adequate estimation procedure for these models is the maximum likelihood (ML), which requires solving a Aprile and Fiorillo (2019) Probit model Arbués and Villanúa (2016) Bivariate probit model Barr et al (2001) Chi-squared test Cluster analysis Principal component analysis Budak and Oguz (2008) Logistic regression Byrne and O'Regan (2014) Frequency analysis Cross tabulation Chi-squared test Cai et al (2020) Binary regression model Crociata et al (2015) Bivariate probit model Czajkowski et al (2017) Hybrid multinomial logit Hybrid mixed logit Darby and Obara (2005) Frequency analysis Cross tabulation De Feo and De Gisi (2010) Chi-squared test Frequency analysis Do Valle et al (2004) Logistic regression Principal component analysis Dwivedy and Mittal (2013) Logistic regression Ferrara and Missios (2005) Ordered probit model Hage et al (2009) Ordered probit model Islam et al (2020) Multinomial logistic regression Frequency analysis Cross tabulation Chi-squared test Jafari et al (2017) Logistic regression Keuschnigg and Kratz (2018) Binary logistic regressions Lakhan (2015) Unpaired t-test Lee and Paik (2011) Ordinary least squares Liu et al (2020) Confirmatory factor analysis Structural equation model Lo and Liu (2018) Ordinary least squares Martinho et al (2017) Frequency analysis Cross tabulation Chi-squared test Nguyen et al (2018) Factor analysis Analysis of moment structures Nixon et al (2009) Rank-ordered logit model Principal component analysis Oskamp et al (1998) Hierarchical multiple regressions Principal component analysis Pearson et al (2012) Logistic regression Chi-squared test Independent group t-test Sobel test Pérez-Belis et al (2015b) Ordinal logistic regression Chi-squared test Perry and Williams (2007) Frequency analysis Purcell and Magette (2010) Logistic regression Sidique et al (2010) Poisson regression model Factor analysis …”