Influence of Residential Photovoltaic Promotion Policy on Installation Intention in Typical Regions of China
Abstract
:1. Introduction
2. Literature Review
3. Empirical Strategy
3.1. Theoretical Foundation
3.2. Hypotheses
3.2.1. Perceived Usefulness (PU)
3.2.2. Perceived Ease of Use (PEOU)
3.2.3. Perceived Risk (PR)
3.2.4. Perceived Benefit (PB)
3.2.5. Perceived Guide (PG)
3.2.6. Hypothesis of Mediating Role
3.3. Questionnaire Design
3.4. Data
4. Result and Discussion
4.1. Measurement Invariance Assessment of Composite Model (MICOM)
4.2. Inspection of Structural Model
4.3. Hypothesis Test Results of Bungalow Residents
4.4. Hypothesis Test Results of Building Residents
4.5. Results of Comparative Analysis
4.6. Influence of Demographic Characteristics on Installation Intention
4.7. Analysis of Research Results
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variables | Items |
Respondents of Bungalow Residents (n = 684) |
Respondents of Building Residents (n = 740) | ||||||
---|---|---|---|---|---|---|---|---|---|
Factor Loading | Cronbach’s α | CR | AVE | Factor Loading | Cronbach’s α | CR | AVE | ||
II | 0.813 | 0.889 | 0.728 | 0.838 | 0.901 | 0.752 | |||
II1 | I am interested in considering installing rooftop PV power generation equipment. | 0.855 | 0.904 | ||||||
II2 | I am interested in persuading my family to install household PV power generation equipment for their homes. | 0.860 | 0.842 | ||||||
II3 | I am willing to take the time to learn about photovoltaic equipment for home use information. | 0.844 | 0.855 | ||||||
PU | 0.831 | 0.899 | 0.747 | 0.834 | 0.898 | 0.746 | |||
PU1 | Using rooftop PV power generation equipment can save me electricity costs. | 0.868 | 0.913 | ||||||
PU2 | Using rooftop PV power generation equipment can improve my life quality. | 0.884 | 0.862 | ||||||
PU3 | The use of rooftop PV power generation equipment is conducive to reduce carbon emissions and achieve sustainable development. | 0.841 | 0.813 | ||||||
PEOU | 0.782 | 0.835 | 0.564 | 0.800 | 0.855 | 0.600 | |||
PEOU1 | It is very easy to use rooftop PV power generation equipment. | 0.710 | 0.784 | ||||||
PEOU3 | It does not take much time to learn how to use rooftop PV power generation equipment. | 0.801 | 0.828 | ||||||
PEOU4 | It does not take much time to learn how to maintain roof top PV power generation equipment. | 0.897 | 0.861 | ||||||
PR | 0.810 | 0.887 | 0.723 | 0.799 | 0.878 | 0.707 | |||
PR1 | I am worried about the stability of household PV power generation equipment. | 0.861 | 0.898 | ||||||
PR2 | I am worried about the quality problem of household PV power generation equipment perhaps causing me economic losses. | 0.841 | 0.858 | ||||||
PR3 | I am concerned that the quality of household PV power generation equipment will cause me personal injury. | 0.850 | 0.762 | ||||||
PB | 0.831 | 0.898 | 0.747 | 0.815 | 0.889 | 0.728 | |||
PB1 | The government subsidy for the distributed PV power generation equipment will make me decide to install it. | 0.871 | 0.807 | ||||||
PB2 | The earned tariff for distributed PV power generation equipment was important to my choice of installation. | 0.858 | 0.872 | ||||||
PB3 | Whether the government provides the distributed PV power generation equipment for free is important to my willingness to install it. | 0.863 | 0.880 | ||||||
PG | 0.817 | 0.888 | 0.726 | 0.827 | 0.896 | 0.742 | |||
PG1 | Good publicity will make me decide to install distributed PV power generation equipment. | 0.884 | 0.837 | ||||||
PG2 | Knowing the pros and cons of installing distributed PV power generation equipment is important for me to choose an installation. | 0.860 | 0.866 | ||||||
PG3 | Local party and government departments have installed a distributed system. The photovoltaic equipment is the one reason that drives me to install. | 0.810 | 0.881 |
Item | Attribute | Respondents of Bungalow Residents | Respondents of Building Residents | Total |
---|---|---|---|---|
(n = 684) | (n = 740) | (n = 1424) | ||
Gender | Male | 344 (50.3%) | 388 (52.40%) | 732 (51.40%) |
Female | 340 (49.7%) | 352 (47.60%) | 692 (48.60%) | |
Age | 25~30 years | 186 (27.20%) | 259 (35.00%) | 445 (31.30%) |
31~36 years | 241 (35.2%) | 216 (29.20%) | 457 (32.10%) | |
37~42 years | 184 (26.90%) | 161 (21.80%) | 345 (24.20%) | |
43 years and above | 73 (10.70%) | 104 (14.10%) | 177 (12.40%) | |
Education level | Junior college and below | 274 (42.91%) | 299 (40.40%) | 573 (41.20%) |
Undergraduate | 374 (51.67%) | 401 (54.20%) | 775 (54.40%) | |
Postgraduate and above | 36 (5.52%) | 40 (5.40%) | 76 (5.30%) | |
Average annual income of family members | Below CNY 12,000 | 157 (23.00%) | 40 (5.40%) | 197 (13.80%) |
CNY 12,001~30,000 | 150 (21.90%) | 73 (9.90%) | 223 (15.70%) | |
CNY 30,001~50,000 | 213 (31.10%) | 245 (33.10%) | 458 (32.30%) | |
CNY 50,001~100,000 | 75 (11.00%) | 172 (23.20%) | 247 (17.30%) | |
CNY Above 100,001 | 89 (13.00%) | 210 (28.40%) | 299 (21.00%) |
Variables | Respondents of Bungalow Residents (n = 684) | Respondents of Bungalow Residents (n = 740) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
II | PB | PEOU | PG | PR | PU | II | PB | PEOU | PG | PR | PU | |
II | 0.853 | 0.867 | ||||||||||
PB | 0.084 | 0.864 | 0.197 | 0.853 | ||||||||
PEOU | −0.071 | −0.008 | 0.751 | 0.077 | 0.045 | 0.775 | ||||||
PG | 0.074 | 0.101 | −0.001 | 0.852 | −0.017 | 0.197 | −0.040 | 0.861 | ||||
PR | 0.268 | 0.153 | 0.015 | 0.165 | 0.851 | 0.008 | 0.193 | −0.086 | 0.193 | 0.841 | ||
PU | 0.182 | 0.126 | −0.084 | 0.023 | 0.059 | 0.864 | 0.077 | 0.092 | −0.022 | 0.241 | 0.077 | 0.864 |
Variables | Respondents of Bungalow Residents (n = 684) | Respondents of Building Residents (n = 740) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
II | PB | PEOU | PG | PR | PU | II | PB | PEOU | PG | PR | PU | |
II | ||||||||||||
PB | 0.101 | 0.232 | ||||||||||
PEOU | 0.075 | 0.040 | 0.076 | 0.054 | ||||||||
PG | 0.098 | 0.123 | 0.065 | 0.035 | 0.248 | 0.054 | ||||||
PR | 0.331 | 0.185 | 0.048 | 0.194 | 0.037 | 0.224 | 0.112 | 0.227 | ||||
PU | 0.217 | 0.150 | 0.103 | 0.045 | 0.071 | 0.089 | 0.120 | 0.049 | 0.276 | 0.100 |
Original Correlation | Correlation Permutation Mean | 5.00% | Permutation p-Values | |
---|---|---|---|---|
II | 0.998 | 0.998 | 0.993 | 0.472 |
PB | 0.997 | 0.998 | 0.994 | 0.197 |
PEOU | 0.992 | 0.642 | 0.064 | 0.992 |
PG | 0.993 | 0.998 | 0.994 | 0.060 |
PR | 0.994 | 0.998 | 0.994 | 0.052 |
PU | 0.997 | 0.997 | 0.992 | 0.357 |
Hypothesis | Influence Path | Respondents of Bungalow Residents (n = 684) | Respondents of Building Residents (n = 740) | Comparative Analysis | |||||
---|---|---|---|---|---|---|---|---|---|
Path Coefficient (Significance) | p-Value | Hypothesis Test Results | Path Coefficient (Significance) | p-Value | Hypothesis Test Results | Path Difference | p-Value | ||
H1 | PU ⟶ II | 0.159 (***) | 0.000 | s | 0.078 (*) | 0.046 | s | 0.081 (nse) | 0.142 |
H2 | PEOU ⟶ II | −0.061 (nse) | 0.203 | ns | 0.063 (nse) | 0.179 | ns | −0.124 (nse) | 0.074 |
H3 | PR ⟶ II | 0.252 (***) | 0.000 | s | −0.035 (nse) | 0.379 | ns | 0.287 (***) | 0.000 |
H4 | PB ⟶ II | 0.022 (nse) | 0.557 | ns | 0.207 (***) | 0.000 | s | −0.185 (***) | 0.000 |
H5 | PB ⟶ PU | 0.125 (**) | 0.006 | s | 0.046 (nse) | 0.305 | ns | 0.079 (nse) | 0.220 |
H6 | PB ⟶ PEOU | −0.007 (nse) | 0.908 | ns | 0.055 (nse) | 0.203 | ns | −0.063 (nse) | 0.411 |
H7 | PB ⟶ PR | 0.138 (**) | 0.002 | s | 0.162 (***) | 0.000 | s | −0.024 (ns) | 0.682 |
H8 | PG ⟶ II | 0.026 (nse) | 0.532 | ns | −0.067 (nse) | 0.092 | ns | 0.093 (nse) | 0.103 |
H9 | PG ⟶ PU | 0.011 (nse) | 0.808 | ns | 0.232 (***) | 0.000 | s | −0.222 (***) | 0.000 |
H10 | PG ⟶ PEOU | −0.009 (nse) | 0.918 | ns | −0.055 (nse) | 0.227 | ns | 0.046 (nse) | 0.616 |
H11 | PG ⟶ PR | 0.151 (***) | 0.000 | s | 0.161 (***) | 0.000 | s | 0.010 (nse) | 0.855 |
H12 | PB ⟶ PU ⟶ II | 0.020 (*) | 0.023 | ns | 0.003 (nse) | 0.376 | ns | 0.016 (nse) | 0.091 |
H13 | PB ⟶ PEOU ⟶ II | 0.001 (nse) | 0.912 | ns | −0.002 (nse) | 0.828 | ns | 0.003 (nse) | 0.593 |
H14 | PB ⟶ PR ⟶ II | 0.035 (**) | 0.007 | s | −0.006 (ns) | 0.403 | ns | 0.040 (**) | 0.004 |
H15 | PG ⟶ PU ⟶ II | 0.002 (nse) | 0.816 | ns | 0.018 (nse) | 0.057 | ns | −0.016 (nse) | 0.177 |
H16 | PG ⟶ PEOU ⟶ II | 0.001 (nse) | 0.919 | ns | 0.003 (nse) | 0.371 | ns | −0.002 (nse) | 0.531 |
H17 | PG ⟶ PR ⟶ II | 0.038 (***) | 0.000 | s | −0.006 (nse) | 0.419 | ns | 0.044 (***) | 0.000 |
H18 | PB ⟶ II | 0.055 (***) | 0.000 | s | 0.001 (nse) | 0.879 | ns | 0.054 (**) | 0.002 |
H19 | PG ⟶ II | 0.040 (**) | 0.005 | s | 0.009 (nse) | 0.460 | ns | 0.031 (nse) | 0.096 |
R2 | |||||||||
PU | 0.240 | 0.200 | |||||||
PEOU | 0.180 | 0.160 | |||||||
PR | 0.220 | 0.230 | |||||||
II | 0.393 | 0.401 | |||||||
Q2 | |||||||||
PU | 0.218 | 0.130 | |||||||
PEOU | 0.142 | 0.121 | |||||||
PR | 0.256 | 0.219 | |||||||
II | 0.302 | 0.303 |
Respondents of Bungalow Residents (n = 684) | |||||
---|---|---|---|---|---|
Hypothesis | Influence Path | Path Coefficient (Significance) | t-Value | p-Value | Hypothesis Test Results |
H1 | PU ⟶ II | 0.159 (***) | 4.191 | 0.000 | support |
H2 | PEOU ⟶ II | −0.061 (nse) | 1.274 | 0.203 | non-support |
H3 | PR ⟶ II | 0.252 (***) | 6.863 | 0.000 | support |
H4 | PB ⟶ II | 0.022 (nse) | 0.588 | 0.557 | non-support |
H5 | PB ⟶ PU | 0.125 (**) | 2.736 | 0.006 | support |
H6 | PB ⟶ PEOU | −0.007 (nse) | 0.115 | 0.908 | non-support |
H7 | PB ⟶ PR | 0.138 (**) | 3.087 | 0.002 | support |
H8 | PG ⟶ II | 0.026 (nse) | 0.626 | 0.532 | non-support |
H9 | PG ⟶ PU | 0.011 (nse) | 0.244 | 0.808 | non-support |
H10 | PG ⟶ PEOU | −0.009 (nse) | 0.103 | 0.918 | non-support |
H11 | PG ⟶ PR | 0.151 (***) | 3.746 | 0.000 | support |
H12 | PB ⟶ PU ⟶ II | 0.020 (*) | 2.268 | 0.023 | non-support |
H13 | PB ⟶ PEOU ⟶ II | 0.001 (nse) | 0.110 | 0.912 | non-support |
H14 | PB ⟶ PR ⟶ II | 0.035 (**) | 2.700 | 0.007 | support |
H15 | PG ⟶ PU ⟶ II | 0.002 (nse) | 0.232 | 0.816 | non-support |
H16 | PG ⟶ PEOU ⟶ II | 0.001 (nse) | 0.102 | 0.919 | non-support |
H17 | PG ⟶ PR ⟶ II | 0.038 (***) | 3.218 | 0.000 | support |
H18 | PB ⟶ II (Total indirect effect) | 0.055 (***) | 3.673 | 0.000 | support |
H19 | PG ⟶ II (Total indirect effect) | 0.040 (**) | 2.802 | 0.005 | support |
Respondents of Building Residents (n = 740) | |||||
---|---|---|---|---|---|
Hypothesis | Influence Path | Path Coefficient (Significance) | t-Value | p-Value | Hypothesis Test Results |
H1 | PU ⟶ II | 0.078 (*) | 1.999 | 0.046 | support |
H2 | PEOU ⟶ II | 0.063 (nse) | 1.343 | 0.179 | non-support |
H3 | PR ⟶ II | −0.035 (nse) | 0.879 | 0.379 | non-support |
H4 | PB ⟶ II | 0.207 (***) | 5.411 | 0.000 | support |
H5 | PB ⟶ PU | 0.046 (nse) | 1.027 | 0.305 | support |
H6 | PB ⟶ PEOU | 0.055 (nse) | 1.273 | 0.203 | non-support |
H7 | PB ⟶ PR | 0.162 (***) | 4.130 | 0.000 | support |
H8 | PG ⟶ II | −0.067 (nse) | 1.688 | 0.092 | non-support |
H9 | PG ⟶ PU | 0.232 (***) | 5.790 | 0.000 | support |
H10 | PG ⟶ PEOU | −0.055 (nse) | 1.209 | 0.227 | non-support |
H11 | PG ⟶ PR | 0.161 (***) | 4.078 | 0.000 | support |
H12 | PB ⟶ PU ⟶ II | 0.003 (nse) | 0.886 | 0.376 | non-support |
H13 | PB ⟶ PEOU ⟶ II | −0.002 (nse) | 0.217 | 0.828 | non-support |
H14 | PB ⟶ PR ⟶ II | −0.006 (nse) | 0.837 | 0.403 | non-support |
H15 | PG ⟶ PU ⟶ II | 0.018 (nse) | 1.900 | 0.057 | non-support |
H16 | PG ⟶ PEOU ⟶ II | 0.003 (nse) | 0.895 | 0.371 | non-support |
H17 | PG ⟶ PR ⟶ II | −0.006 (nse) | 0.808 | 0.419 | non-support |
H18 | PB ⟶ II (Total indirect effect) | 0.001 (nse) | 0.152 | 0.879 | non-support |
H19 | PG ⟶ II (Total indirect effect) | 0.009 (nse) | 0.739 | 0.460 | non-support |
Comparative Analysis | |||||
---|---|---|---|---|---|
Hypothesis | Influence Path | Bungalows’ Path Coefficient (Significance) | Buildings’ Path Coefficient (Significance) | Path Difference | p-Value |
H1 | PU ⟶ II | 0.159 (***) | 0.078 (*) | 0.081 (nse) | 0.142 |
H2 | PEOU ⟶ II | −0.061 (nse) | 0.063 (nse) | −0.124 (nse) | 0.074 |
H3 | PR ⟶ II | 0.252 (***) | −0.035 (nse) | 0.287 (***) | 0.000 |
H4 | PB ⟶ II | 0.022 (nse) | 0.207 (***) | −0.185 (***) | 0.000 |
H5 | PB ⟶ PU | 0.125 (**) | 0.046 (nse) | 0.079 (nse) | 0.220 |
H6 | PB ⟶ PEOU | −0.007 (nse) | 0.055 (nse) | −0.063 (nse) | 0.411 |
H7 | PB ⟶ PR | 0.138 (**) | 0.162 (***) | −0.024 (nse) | 0.682 |
H8 | PG ⟶ II | 0.026 (nse) | −0.067 (nse) | 0.093 (nse) | 0.103 |
H9 | PG ⟶ PU | 0.011 (nse) | 0.232 (***) | −0.222 (***) | 0.000 |
H10 | PG ⟶ PEOU | −0.009 (nse) | −0.055 (nse) | 0.046 (nse) | 0.616 |
H11 | PG ⟶ PR | 0.151 (***) | 0.161 (***) | 0.010 (nse) | 0.855 |
H12 | PB ⟶ PU ⟶ II | 0.020 (*) | 0.003 (nse) | 0.016 (nse) | 0.091 |
H13 | PB ⟶ PEOU ⟶ II | 0.001 (nse) | −0.002 (nse) | 0.003 (nse) | 0.593 |
H14 | PB ⟶ PR ⟶ II | 0.035 (**) | −0.006 (nse) | 0.040 (**) | 0.004 |
H15 | PG ⟶ PU ⟶ II | 0.002 (nse) | 0.018 (nse) | −0.016 (nse) | 0.177 |
H16 | PG ⟶ PEOU ⟶ II | 0.001 (nse) | 0.003 (nse) | −0.002 (nse) | 0.531 |
H17 | PG ⟶ PR ⟶ II | 0.038 (***) | −0.006 (nse) | 0.044 (***) | 0.000 |
H18 | PB ⟶ II (Total indirect effect) | 0.055 (***) | 0.001 (nse) | 0.054 (**) | 0.002 |
H19 | PG ⟶ II (Total indirect effect) | 0.040 (**) | 0.009 (nse) | 0.031 (nse) | 0.096 |
Variables | Items | Respondents of Bungalow Residents (n = 684) | Respondents of Building Residents (n = 740) | ||||
---|---|---|---|---|---|---|---|
Mean | Standard Deviations | Sample Size | Mean | Standard Deviations | Sample Size | ||
Gender | Male | 3.269 | 1.213 | 344 | 3.292 | 1.201 | 388 |
Female | 3.062 | 1.205 | 340 | 3.439 | 1.171 | 352 | |
t-value | 2.245 | 2.841 | |||||
p-value | 0.025 | 0.092 | |||||
Age | 25–30 years | 3.299 | 1.203 | 186 | 3.350 | 1.101 | 259 |
31–36 years | 3.089 | 1.157 | 241 | 3.364 | 1.242 | 216 | |
37–42 years | 3.004 | 1.242 | 184 | 3.410 | 1.227 | 161 | |
43 years and above | 3.493 | 1.269 | 73 | 3.314 | 1.241 | 104 | |
f-value | 3.999 | 0.152 | |||||
p-value | 0.008 | 0.928 | |||||
Education Level | Technical school or below | 3.297 | 1.209 | 274 | 3.181 | 1.221 | 299 |
Undergraduate degree | 3.104 | 1.231 | 374 | 3.515 | 1.167 | 401 | |
Master’s degree or above | 2.815 | 0.927 | 36 | 3.192 | 0.948 | 40 | |
f-value | 3.616 | 7.318 | |||||
p-value | 0.027 | 0.001 | |||||
Income Level | CNY 12,000 or below | 3.270 | 1.102 | 157 | 3.908 | 1.140 | 40 |
CNY 12,001–30,000 | 3.096 | 1.217 | 150 | 3.210 | 1.232 | 73 | |
CNY 30,001–50,000 | 3.232 | 1.265 | 213 | 3.457 | 1.156 | 245 | |
CNY 50,001–100,000 | 3.009 | 1.217 | 75 | 3.391 | 1.202 | 210 | |
CNY 100,001 above | 3.079 | 1.259 | 89 | 3.176 | 1.174 | 172 | |
f-value | 0.999 | 4.184 | |||||
p-value | 0.407 | 0.002 |
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Wang, S.; Wu, J.; Peng, Y.; Xu, J.; Leinonen, L.; Wang, Y.; Meng, Z. Influence of Residential Photovoltaic Promotion Policy on Installation Intention in Typical Regions of China. Sustainability 2022, 14, 8659. https://doi.org/10.3390/su14148659
Wang S, Wu J, Peng Y, Xu J, Leinonen L, Wang Y, Meng Z. Influence of Residential Photovoltaic Promotion Policy on Installation Intention in Typical Regions of China. Sustainability. 2022; 14(14):8659. https://doi.org/10.3390/su14148659
Chicago/Turabian StyleWang, Shali, Jiaxi Wu, Yunan Peng, Jane Xu, Lisa Leinonen, Yuyu Wang, and Zheng Meng. 2022. "Influence of Residential Photovoltaic Promotion Policy on Installation Intention in Typical Regions of China" Sustainability 14, no. 14: 8659. https://doi.org/10.3390/su14148659
APA StyleWang, S., Wu, J., Peng, Y., Xu, J., Leinonen, L., Wang, Y., & Meng, Z. (2022). Influence of Residential Photovoltaic Promotion Policy on Installation Intention in Typical Regions of China. Sustainability, 14(14), 8659. https://doi.org/10.3390/su14148659