Can Public Environmental Concern Drive Changes in Residents’ Green Consumption Behavior?
Abstract
:1. Introduction
- March 2015: Under the Dome documentary raises awareness of environmental issues related to coal burning.
- March 2017: The 2017 Work Plan for Air Pollution Prevention and Control in the Beijing–Tianjin–Hebei Region and surrounding areas was officially released.
- March 2018: Pilot implementation of the household waste classification system begins.
- September 2020: The “dual carbon” targets are officially proposed.
- Data source: Baidu search index; Note: Data visualization using Python 3.13.3
2. Literature Review and Research Hypotheses
2.1. Research on Public Environmental Concern
2.2. Research on Green Consumption
2.3. Critical Review of the Literature
2.4. Influence Mechanism and Research Hypothesis
3. Residents’ Green Consumption Measurement
3.1. Indicator System
3.2. Data Sources
3.3. Calculation Methods
3.4. Current Development of RGC
4. Research Framework
4.1. Model Framework Design
4.2. Variable Selection
4.3. Descriptive Statistics
5. Empirical Results Examination
5.1. Baseline Regression
5.2. Mechanism Analysis
5.3. Robustness Tests
5.3.1. Changing Sample Period
5.3.2. Lagging Independent Variables
5.3.3. Substituting the Independent Variable
5.4. Endogeneity Test
5.5. Heterogeneity Analysis
5.5.1. Regional Heterogeneity
5.5.2. Pollution Emission Heterogeneity
5.5.3. Innovation Foundation Heterogeneity
6. Discussion
7. Conclusion and Recommendations
7.1. Research Conclusion
7.2. Policy Implications
7.3. Limitations and Future Research Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Primary Indicator | Secondary Indicator | Unit | Indicator Attribute | Weight |
---|---|---|---|---|
Green manufacturing processes | Fertilizer applied per unit of cultivated and irrigated land | Tons per hectare | − | 0.0993 |
Per capita solar water heater area in rural areas | Square meters per person | + | 0.1286 | |
Sulfur dioxide emissions relative to GDP | Tons per RMB 1 billion | − | 0.0438 | |
Energy consumption intensity | Tons of standard coal per RMB 10,000 | − | 0.0459 | |
Sustainable lifestyles | Daily energy consumption per person | Tons of standard coal per person | − | 0.0558 |
Per capita public bus and electric vehicle operations | Vehicles per 10,000 people | + | 0.1189 | |
Per capita private car ownership | Vehicles per person | − | 0.1154 | |
Per capita daily water consumption | Liters | − | 0.0810 | |
Environmental ecosystems | Proportion of household waste subjected to harmless treatment | % | + | 0.0556 |
Per capita park green space area | Square meters per person | + | 0.0891 | |
Urban green coverage rate | % | + | 0.1015 | |
Percentage of GDP spent on energy saving and environmental protection | % | + | 0.0651 |
Variable | N | Mean | sd | Min | Max | |
---|---|---|---|---|---|---|
Dependent Variable | RGC | 390 | 3.128 | 0.164 | 2.765 | 3.517 |
Core Independent Variable | PEC | 390 | 4.577 | 0.431 | 2.878 | 5.372 |
Control Variables | URB | 390 | −0.519 | 0.194 | −1.049 | −0.110 |
RES | 390 | 10.09 | 0.443 | 9.043 | 11.35 | |
GOV | 390 | −1.434 | 0.384 | −2.254 | −0.277 | |
EDU | 390 | 8.595 | 1.089 | 6.004 | 12.16 | |
LE | 390 | 12.22 | 0.753 | 9.410 | 15.04 | |
IND | 390 | 0.228 | 0.386 | −0.640 | 1.739 |
Variables | (1) | (2) | (3) | (4) | (5) | (6) | (7) |
---|---|---|---|---|---|---|---|
PEC | 0.107 *** | 0.222 *** | 0.226 *** | 0.307 *** | 0.308 *** | 0.313 *** | 0.261 *** |
(0.0210) | (0.0764) | (0.0779) | (0.0697) | (0.0697) | (0.0696) | (0.0668) | |
URB | −1.176 *** | −1.145 *** | −1.311 *** | −1.314 *** | −1.313 *** | −1.287 *** | |
(0.113) | (0.150) | (0.134) | (0.134) | (0.134) | (0.128) | ||
RES | −0.0635 | 0.401 ** | 0.458 ** | 0.444 ** | 0.454 ** | ||
(0.203) | (0.187) | (0.194) | (0.193) | (0.184) | |||
GOV | 0.473 *** | 0.484 *** | 0.479 *** | 0.350 *** | |||
(0.0493) | (0.0501) | (0.0501) | (0.0522) | ||||
EDU | −0.0372 | −0.0404 | −0.0346 | ||||
(0.0321) | (0.0321) | (0.0305) | |||||
LE | 0.0169 | 0.0188 * | |||||
(0.0104) | (0.00994) | ||||||
IND | 0.219 *** | ||||||
(0.0360) | |||||||
Constant | 2.915 *** | 0.773 ** | 1.380 | −2.794 | −3.038 * | −3.103 * | −3.210 * |
(0.0986) | (0.357) | (1.976) | (1.811) | (1.822) | (1.818) | (1.730) | |
Time Fixed | YES | YES | YES | YES | YES | YES | YES |
Region Fixed | YES | YES | YES | YES | YES | YES | YES |
N | 390 | 390 | 390 | 390 | 390 | 390 | 390 |
adj. R2 | 0.086 | 0.409 | 0.409 | 0.534 | 0.536 | 0.539 | 0.584 |
Variables | (1) | (2) | (3) | (4) | (5) | (6) |
---|---|---|---|---|---|---|
GTI | RGC | CER | RGC | MER | RGC | |
PEC | 0.203 * | 0.233 *** | 1.133 | 0.258 *** | 0.711 *** | 0.259 *** |
(0.108) | (0.0811) | (10.79) | (0.0875) | (0.3232) | (0.0915) | |
GTI | 0.139 *** | |||||
(0.0364) | ||||||
CER | 0.00224 *** | |||||
(0.000647) | ||||||
MER | 0.00226 *** | |||||
(0.00106) | ||||||
Constant | −30.96 *** | 1.020 | −557.6 *** | −2.023 | −470.1 ** | −2.435 |
(2.364) | (2.551) | (160.2) | (2.263) | (199.4) | (4.739) | |
Controls | YES | YES | YES | YES | YES | YES |
Time Fixed | YES | YES | YES | YES | YES | YES |
Region Fixed | YES | YES | YES | YES | YES | YES |
N | 390 | 390 | 390 | 390 | 390 | 390 |
adj. R2 | 0.994 | 0.846 | 0.678 | 0.850 | 0.814 | 0842 |
Variables | (1) | (2) | (3) |
---|---|---|---|
Changing Sample Period | Lagging Independent Variables | Replacing Independent Variable | |
L.RGC | |||
PEC | 0.217 *** | ||
(0.0597) | |||
L.PEC | 0.221 *** | ||
(0.0619) | |||
PEC2 | 0.0624 ** | ||
(0.0270) | |||
Constant | 1.961 | −2.745 | 1.252 |
(1.823) | (1.666) | (1.463) | |
Controls | YES | YES | YES |
Time Fixed | YES | YES | YES |
Region Fixed | YES | YES | YES |
N | 300 | 360 | 390 |
adj. R2 | 0.251 | 0.591 | 0.239 |
AR(1) | |||
AR(2) | |||
Hansen Test |
Variables | (1) SYS-GMM | (2) Add Control Variables | (3) First Stage | (4) Second Stage |
---|---|---|---|---|
RGC | RGC | PEC | RGC | |
L.RGC | 0.554 *** | |||
(0.0403) | ||||
PEC | 0.228 ** | 0.223 ** | 0.7084 *** | |
(0.0933) | (0.0914) | (0.2488) | ||
IV | 0.0004 *** | |||
(0.0001) | ||||
Constant | −0.0403 | −2.536 | ||
(0.442) | (4.696) | |||
Controls | YES | YES | YES | YES |
Time Fixed | YES | YES | YES | YES |
Region Fixed | YES | YES | YES | YES |
N | 360 | 390 | 390 | 390 |
adj. R2 | 0.844 | |||
AR (1) | 0.005 | |||
AR (2) | 0.645 | |||
Hansen Test | 0.716 | |||
Kleibergen–Paap LM | 14.34 | |||
Kleibergen–Paap rk Wald F | 16.23 | |||
Hansen J | 0.000 |
Variables | Region | Pollution Emission | Innovation Foundation | |||
---|---|---|---|---|---|---|
(1) Eastern | (2) Central–Western | (3) High | (4) Low | (5) High | (6) Low | |
PEC | 0.141 ** | 0.405 *** | 0.276 *** | 0.068 | 0.331 *** | 0.258 *** |
(0.066) | (0.092) | (0.104) | (0.064) | (0.120) | (0.073) | |
Constant | −9.692 *** | −2.696 | 4.118 | −3.746 | −2.868 | 3.772 |
(2.060) | (2.859) | (3.743) | (2.273) | (2.325) | (2.671) | |
Controls | YES | YES | YES | YES | YES | YES |
Time Fixed | YES | YES | YES | YES | YES | YES |
Region Fixed | YES | YES | YES | YES | YES | YES |
adj. R2 | 0.5420 | 0.6754 | 0.7261 | 0.5103 | 0.4858 | 0.7138 |
N | 143 | 247 | 195 | 195 | 195 | 195 |
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Zhao, J.; Li, Y.; Wu, T.; Jiang, W. Can Public Environmental Concern Drive Changes in Residents’ Green Consumption Behavior? Sustainability 2025, 17, 5352. https://doi.org/10.3390/su17125352
Zhao J, Li Y, Wu T, Jiang W. Can Public Environmental Concern Drive Changes in Residents’ Green Consumption Behavior? Sustainability. 2025; 17(12):5352. https://doi.org/10.3390/su17125352
Chicago/Turabian StyleZhao, Jing, Yaya Li, Tian Wu, and Wen Jiang. 2025. "Can Public Environmental Concern Drive Changes in Residents’ Green Consumption Behavior?" Sustainability 17, no. 12: 5352. https://doi.org/10.3390/su17125352
APA StyleZhao, J., Li, Y., Wu, T., & Jiang, W. (2025). Can Public Environmental Concern Drive Changes in Residents’ Green Consumption Behavior? Sustainability, 17(12), 5352. https://doi.org/10.3390/su17125352