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Predicting residents' adoption intention for smart waste classification and collection system

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  • Cudjoe, Dan
  • Zhang, Huiming
  • Wang, Hong

Abstract

Smart waste classification and collection systems improve workload balances while promoting environmental sustainability. Consumer acceptability is critical for effectively implementing novel and upcoming techniques to enhance ecological sustainability and minimize pollution. The current study looked at the factors that impact Chinese residents' intention to use smart waste classification and collection systems, using Shanghai as a case study. The study extended an integrated theory of planned behavior and technology acceptance model with community engagement. 514 valid responses from a questionnaire survey were examined using structural equation modeling. The main findings indicate that residents' adoption intentions are influenced by their attitudes, subjective norms, perceived behavioral control, and perceived usefulness. There was no statistically significant link between adoption intention and community engagement. However, community engagement influence residents' intention via attitude. The study provides a robust standard for understanding smart waste classification and collection systems adoption intention in ecological sustainability and pro-environmental consumption. Also, the study provides policymakers and stakeholders with comprehensive policy recommendations to promote public patronage and involvement in local community smart waste classification systems initiatives.

Suggested Citation

  • Cudjoe, Dan & Zhang, Huiming & Wang, Hong, 2023. "Predicting residents' adoption intention for smart waste classification and collection system," Technology in Society, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:teinso:v:75:y:2023:i:c:s0160791x23001860
    DOI: 10.1016/j.techsoc.2023.102381
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    References listed on IDEAS

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