Determinants of Intention to Adopt Recycled Water: Evidence from Four High-Water-Stress Provinces in China
Abstract
:1. Introduction
2. Literature Review
3. Theoretical Basis and Research Hypothesis
3.1. Theoretical Basis
3.2. Research Hypothesis
3.2.1. Information Disclosure Factor
3.2.2. Psychological Factors
3.2.3. Policy Factors
4. Methodology
4.1. Questionnaire Design
4.2. Survey Area
4.3. Data Acquisition and Sample Description
- (1)
- Online pre-survey. We posted the questionnaire online for a pre-survey and made several revisions to the overall logic of the questionnaire and the comprehensibility of the questions based on the feedback from the respondents.
- (2)
- Offline pre-survey. An offline pre-survey was organized after the online pre-survey. We invited relevant experts and public representatives to conduct in-depth interviews, and made further revisions to the questions included in the questionnaire. It is worth noting that the questionnaire length was reduced to ensure that residents had enough patience to complete it.
- (3)
- Formal survey. After preliminary investigations, the research team conducted investigations for more than two months in four provinces: Shandong, Henan, Shanghai, and Beijing. Considering that most recycled water use in the community is on a household basis, only one copy was answered per household to make sure that the survey samples were representative, and a total of 10–15 households were surveyed per community.
- (4)
- Data screening. In the end, we distributed 831 questionnaires, and 107 of them were deleted after further screening. We screened the data according to the following criteria: questionnaires with more than 10 unanswered questions and questionnaires that gave the same response to over 10 consecutive questions were deleted. We obtained a total of 724 valid questionnaires after eliminating invalid questionnaires, including 188 surveys from Beijing, 191 from Shandong, 186 from Heinan, and 179 from Shanghai, and the effective rate was 87.12%.
5. Results
5.1. Reliability and Validity Tests
5.2. Influence Path Analysis
5.3. Moderating Effect Analysis of Policy Instruments
6. Discussion
6.1. The Direct Role of Recycled Water Information Disclosure and the Mediating Role of Psychological Factors
6.2. The Prominent Role of Herd Mentality
6.3. Differences in the Moderating Role of Policy Instruments
7. Conclusions and Policy Implications
7.1. Conclusions
7.2. Policy Implications
7.3. Limitations and Future Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Latent Variables | Observed Variables | Definition |
---|---|---|
Recycled water information disclosure (RWID) | RWID1 | Do you know where the recycled water comes from? |
RWID2 | Do you know the quality of recycled water? | |
RWID3 | Do you know the price of recycled water? | |
Trust (T) | T1 | I am confident that the water authorities will provide a good water supply |
T2 | I think the Water Authority has good intentions in managing the water supply. | |
T3 | I can rely on the water department to provide a quality water supply | |
Awareness of water environment protection (AWEP) | AWEP1 | I have a responsibility to protect the water environment |
AWEP2 | All residents should take responsibility for protecting the city’s water environment. | |
AWEP3 | I will recycle water in my daily life | |
Herd mentality (HM) | HM1 | The more people use recycled water, the more I want to use it |
HM2 | Other people’s opinions on recycled water affect my opinion directly. | |
HM3 | My friends’ use of recycled water prompted me to embrace it | |
Command-and-control policy instruments (CC) | CC1 | If discharging sewage is prohibited, I will follow the rules. |
CC2 | If there’s a fine for wasting water, I will follow the rules. | |
CC3 | If water conservation was a regulatory requirement, I would comply | |
Economic incentive policy instruments (EI) | EI1 | If the government strengthens the construction of recycled water for households, I will consider using it. |
EI2 | If there is a subsidy to purchase household recycled water equipment, I will consider buying it. | |
EI3 | If recycled water is subsidized, I will consider using it. | |
Publicity-and-guidance policy Instruments (PG) | PG1 | If the community strongly promotes the use of recycled water, I would consider using it. |
PG2 | I would consider using recycled water if I had read in the news that it was affordable and convenient. | |
PG3 | I would be willing to attend a training session about the usage of recycled water if I am free. | |
Adoption intention (AI) | AI1 | I can accept the use of recycled water for purposes other than drinking in my daily life. |
AI2 | I will be using recycled water a lot. | |
AI3 | I feel honored to use recycled water. |
Items | Sample Characteristics | Frequency | Percentage (%) |
---|---|---|---|
Gender | Female | 368 | 50.83% |
Male | 356 | 49.17% | |
Age | Under 18 years | 2 | 0.28% |
18–30 years | 284 | 39.23% | |
30–50 years | 376 | 51.93% | |
Over 50 years | 62 | 8.56% | |
Education | Middle school degree or below | 38 | 5.25% |
High school degree | 86 | 11.88% | |
Associate degree | 292 | 40.33% | |
Bachelor’s degree | 286 | 39.50% | |
Master’s degree or more | 22 | 3.04% | |
Income level annual (yuan) | Less than 10,000 | 2 | 0.28% |
10,000 to less than 30,000 | 61 | 8.43% | |
30,000 to less than 50,000 | 279 | 38.54% | |
50,000 to less than 100,000 | 241 | 33.29% | |
100,000 or more | 141 | 19.48% |
Likert-Scaled Construct | Number of Items | Cronbach’s Alpha | Standardized Factor Loadings | AVE | CR |
---|---|---|---|---|---|
RWID | 3 | 0.884 | 0.845 | 0.717 | 0.884 |
0.861 | |||||
0.835 | |||||
T | 3 | 0.871 | 0.791 | 0.702 | 0.875 |
0.825 | |||||
0.883 | |||||
AWEP | 3 | 0.825 | 0.825 | 0.616 | 0.828 |
0.744 | |||||
0.781 | |||||
HM | 3 | 0.851 | 0.859 | 0.662 | 0.854 |
0.803 | |||||
0.771 | |||||
AI | 3 | 0.864 | 0.874 | 0.686 | 0.867 |
0.826 | |||||
0.775 | |||||
CC | 3 | 0.832 | 0.766 | 0.624 | 0.833 |
0.8 | |||||
0.802 | |||||
EI | 3 | 0.873 | 0.905 | 0.696 | 0.872 |
0.774 | |||||
0.814 | |||||
PG | 3 | 0.873 | 0.905 | 0.694 | 0.871 |
0.77 | |||||
0.816 |
Latent Variables | RWID | T | AWEP | HM | AI |
---|---|---|---|---|---|
RWID | 0.847 | ||||
T | 0.326 | 0.838 | |||
AWEP | 0.383 | 0.125 | 0.785 | ||
HM | 0.313 | 0.102 | 0.120 | 0.814 | |
AI | 0.436 | 0.240 | 0.384 | 0.533 | 0.828 |
Index | CMIN/DF | GFI | AGFI | NFI | IFI | TLI | CFI | RMSEA |
---|---|---|---|---|---|---|---|---|
Model results | 4.657 | 0.931 | 0.9 | 0.936 | 0.949 | 0.935 | 0.949 | 0.071 |
Standard | 1 < CMIN/DF < 5 | >0.9 | >0.9 | >0.9 | >0.9 | >0.9 | >0.9 | <0.08 |
Hypothesis | Path | UnStd. Coefficient | Std. Coefficient | S.E. | CR | p | Results |
---|---|---|---|---|---|---|---|
H1 | RWID→AI | 0.155 | 0.166 | 0.041 | 3.818 | *** | Supported |
H2a | RWID→T | 0.283 | 0.326 | 0.037 | 7.715 | *** | Supported |
H2b | RWID→AWEP | 0.334 | 0.383 | 0.038 | 8.742 | *** | Supported |
H2c | RWID→HM | 0.288 | 0.313 | 0.039 | 7.318 | *** | Supported |
H3a | T→AI | 0.118 | 0.109 | 0.04 | 2.914 | 0.004 | Supported |
H3b | AWEP→AI | 0.273 | 0.254 | 0.044 | 6.233 | *** | Supported |
H3c | HM→AI | 0.448 | 0.44 | 0.042 | 10.77 | *** | Supported |
Relationship | Point Estimate | Boot SE | Bias-Corrected 95% CI | |
---|---|---|---|---|
Lower | Upper | |||
Total effect | 0.409 | 0.042 | 0.329 | 0.491 |
Direct effect | 0.155 | 0.038 | 0.081 | 0.232 |
Indirect effect | 0.254 | 0.034 | 0.192 | 0.325 |
RWID→T→AI | 0.033 | 0.014 | 0.008 | 0.064 |
RWID→AWEP→AI | 0.091 | 0.021 | 0.056 | 0.139 |
RWID→HM→AI | 0.129 | 0.025 | 0.086 | 0.181 |
Variables | Model 1 | Model 2 | Model 3 | Model 4 |
---|---|---|---|---|
T | 0.100 ** | 0.095 ** | 0.103 *** | 0.103 *** |
AWEP | 0.248 *** | 0.243 *** | 0.248 *** | 0.249 *** |
HM | 0.339 *** | 0.339 *** | 0.341 *** | 0.340 *** |
CC | 0.182 *** | 0.198 *** | 0.185 *** | 0.184 *** |
EI | −0.0002 | 0.046 | 0.005 | 0.019 |
PG | 0.087 | 0.034 | 0.083 | 0.069 |
CC × T | −0.053 | |||
CC × AWEP | −0.050 | |||
CC × HM | −0.078 * | |||
EI × T | −0.047 | |||
EI × AWEP | −0.045 | |||
EI × HM | 0.076 ** | |||
PG × T | −0.046 | |||
PG × AWEP | −0.055 | |||
PG × HM | 0.082 ** | |||
R2 | 0.375 | 0.390 | 0.383 | 0.384 |
Adjust R2 | 0.369 | 0.382 | 0.375 | 0.376 |
F-value | 71.555 *** | 50.623 *** | 49.178 *** | 49.453 *** |
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Liu, L.; Wang, W.; Njie, Y. Determinants of Intention to Adopt Recycled Water: Evidence from Four High-Water-Stress Provinces in China. Sustainability 2024, 16, 6158. https://doi.org/10.3390/su16146158
Liu L, Wang W, Njie Y. Determinants of Intention to Adopt Recycled Water: Evidence from Four High-Water-Stress Provinces in China. Sustainability. 2024; 16(14):6158. https://doi.org/10.3390/su16146158
Chicago/Turabian StyleLiu, Lin, Weidong Wang, and Yahya Njie. 2024. "Determinants of Intention to Adopt Recycled Water: Evidence from Four High-Water-Stress Provinces in China" Sustainability 16, no. 14: 6158. https://doi.org/10.3390/su16146158
APA StyleLiu, L., Wang, W., & Njie, Y. (2024). Determinants of Intention to Adopt Recycled Water: Evidence from Four High-Water-Stress Provinces in China. Sustainability, 16(14), 6158. https://doi.org/10.3390/su16146158