ORIGINAL RESEARCH
Can Smart Waste Bins Solve the Dilemma of Household Solid Waste Sorting in China? A Case Study of Fuzhou City
Li-Ping Zhang 1  
,   Zu-Ping Zhu 1, 2  
 
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1
School of Economics and Management, Fuzhou University, Fuzhou Fujian, China
2
Fujian Soft Science Research Center, Fuzhou Fujian, China
CORRESPONDING AUTHOR
Zu-Ping Zhu   

Fuzhou University, China
Submission date: 2019-10-25
Final revision date: 2019-12-18
Acceptance date: 2019-12-26
Online publication date: 2020-04-10
Publication date: 2020-06-08
 
Pol. J. Environ. Stud. 2020;29(5):3943–3954
 
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ABSTRACT
The increased amount of household solid waste (HSW) is one of the most serious environmental problems in China. The Chinese government has formulated some policies to promote HSW source sorting since 2000, but the problems of resident’s intention have not been solved. At present, the Chinese government is launching a new nationwide campaign. In order to improve resident’s willingness of HSW source sorting, some cities are installing smart waste bins in residential areas, since such bins can record inhabitants’ HSW source sorting behavior conveniently. In this study, we try to understand how perceived external pressure and economic incentive moderate the relationships between perceived values and inhabitants’ intention of HSW source sorting in the smart waste bin context. By using the hierarchical regression method to explore six different models which could show contributions of variables at different levels, we found that resident’s perceived environmental value, perceived emotional value and perceived social value were positively related to their intention of HSW source sorting. We also found that perceived external pressure could significantly moderate the relationships between perceived emotional value/perceived social value and intention of HSW source sorting and that the three-way interactions of perceived external pressure, perceived environmental value/perceived emotional value/perceived sacrifice and economic incentive could also exert obvious influences according to our statistical analysis.
eISSN:2083-5906
ISSN:1230-1485