Can Green Innovation and New Urbanization Be Synergistic Development? Empirical Evidence from Yangtze River Delta City Group in China
Abstract
:1. Introduction
2. Materials and Methods
2.1. The Introduction to the Yangtze River Delta City Group
2.2. Constructing Index System
Variable | Indicator and Introduction | References |
---|---|---|
Input | The full-time equivalence of R&D personnel | Zhang [54]; Wang [48] |
Intramural expenditure on R&D | Zeng [12] | |
Energy input (total energy consumption) | Dai [35] | |
The volume of books in public libraries | ||
Desirable output | Number of domestic granted invention patents | Chen [55] |
Sales revenue of new products | Feng [56] | |
Industrial added value | Luo [57] | |
Undesirable output | Industrial wastewater emissions | Dai [35]; Zeng [12] |
Industrial SO2 emissions | Dai [35]; Zeng [12] | |
Industrial solid waste emissions | Dai [35]; Zeng [12] |
2.3. Data Sources
2.4. Comprehensive Evaluation Method
2.4.1. SBM Model
2.4.2. Entropy Method
2.5. Coupling Coordination Degree Model
2.6. Spatial Autocorrelation Analysis
2.7. Geographical Detector
3. Results
3.1. The Green Innovation and New Urbanization Development in the Yangtze River Delta City Group
3.1.1. An Overview of the Development of the Yangtze River Delta City Group
3.1.2. Analysis of the Green Innovation and New Urbanization System Typical Index
3.1.3. Analysis of Green Innovation and New Urbanization Coupling Coordination Degree Development
3.2. The Coupling Coordination Analysis of Green Innovation and New Urbanization in the Yangtze River Delta City Group
3.2.1. Coupling Coordination Index
3.2.2. Urban Scale Characteristics in the Yangtze River Delta City Group
3.3. Spatiotemporal Analysis of Coupling Coordination Degree of Green Innovation and New Urbanization
3.3.1. Evolution Characteristics of Spatial Distribution Differences
3.3.2. Spatial Autocorrelation Analysis
4. Influence of the Index Factors of Coupling Coordination Degree between Green Innovation (GI) and New Urbanization (NU) of Yangtze River Delta in China
4.1. Variables
4.2. The Driving Factors of the Coupling Coordination Degree between Green Innovation and New Urbanization
5. Discussion
5.1. Green Innovation and New Urbanization Is a Synergistic Effect between the Two
5.2. The Intensity and Coupling Coordination between Green Innovation and New Urbanization Are Affected by the Level of Economic Development
5.3. Green Innovation and New Urbanization Have a Positive Spatial Correlation and Regional Agglomeration
6. Conclusions and Policy Implication
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Index | Including and Introduction | Property | References |
---|---|---|---|
Population urbanization | The proportion of the urban population in the total population | + | Wu [17,31] |
Economic urbanization | The proportion of the non-agricultural economy in GDP | + | Zhao [59] |
Spatial urbanization | The proportion of the built-up area of the city | + | Zhang [6] |
Social urbanization | Retail sales of consumer goods per capita | + | Jiang [60] |
Ecological urbanization | Park green area per capita | + | Zhang [61] |
Environment pollution | Wastewater discharge | − | Zhang [6] |
PM2.5 (average annual PM2.5) | − | Wu [17] |
Coordination Interval | Coordination Level |
---|---|
0.00 < D ≤ 0.34 | General disorder |
0.34 < D ≤ 0.36 | Preliminary disorder |
0.36 < D ≤ 0.39 | Preliminary coordination |
0.39 < D ≤ 0.42 | Moderate coordination |
0.42 < D ≤ 1.00 | Quality coordination |
Index | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|---|---|---|---|---|---|
Wastewater discharge (billion tons) | 5.39 | 4.93 | 4.71 | 4.51 | 4.31 | 4.34 | 3.79 | 3.51 | 3.43 | 3.40 | 3.06 |
PM2.5 (average annual of PM2.5 for 26 cities) (Mg/m3) | 51.17 | 53.86 | 47.15 | 47.92 | 51.47 | 46.57 | 39.17 | 39.02 | 36.15 | 35.24 | 34.17 |
The proportion of urban population in the total population (%) | 59.11 | 63.01 | 62.82 | 62.64 | 62.46 | 62.29 | 62.13 | 61.98 | 61.84 | 62.79 | 61.97 |
The proportion of non-agricultural economy in GDP (%) | 89.22 | 91.59 | 91.53 | 91.47 | 91.42 | 91.36 | 91.31 | 91.26 | 91.22 | 91.46 | 91.06 |
The proportion of built-up area of the city (%) | 6.52 | 6.43 | 6.37 | 6.31 | 6.25 | 6.19 | 6.13 | 6.07 | 6.01 | 6.01 | 6.00 |
Retail sales of consumer goods per capita (104 CNY) | 2.46 | 2.85 | 2.84 | 2.83 | 2.82 | 2.81 | 2.80 | 2.79 | 2.78 | 2.80 | 2.84 |
Park green area per capita (sq.m.per.person) | 13.55 | 13.88 | 13.91 | 13.93 | 13.97 | 14.00 | 14.03 | 14.06 | 14.10 | 14.21 | 14.23 |
Year | Ui | Uu | C | D |
---|---|---|---|---|
2010 | 0.383 | 0.0374 | 0.285 | 0.361 |
2011 | 0.326 | 0.0342 | 0.293 | 0.363 |
2012 | 0.381 | 0.0387 | 0.289 | 0.364 |
2013 | 0.409 | 0.0415 | 0.289 | 0.370 |
2014 | 0.431 | 0.0428 | 0.287 | 0.374 |
2015 | 0.452 | 0.0439 | 0.284 | 0.376 |
2016 | 0.599 | 0.0467 | 0.259 | 0.384 |
2017 | 0.648 | 0.0489 | 0.255 | 0.388 |
2018 | 0.719 | 0.0506 | 0.248 | 0.392 |
2019 | 0.823 | 0.0574 | 0.247 | 0.405 |
2020 | 0.821 | 0.0566 | 0.246 | 0.403 |
Name | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|---|---|---|---|---|---|
Shanghai | 0.4420 | 0.4459 | 0.4469 | 0.4498 | 0.4501 | 0.4531 | 0.4616 | 0.4744 | 0.4876 | 0.4999 | 0.5020 |
Nanjing | 0.3848 | 0.3870 | 0.3882 | 0.3892 | 0.3913 | 0.4021 | 0.4154 | 0.4187 | 0.4290 | 0.4498 | 0.4790 |
Wuxi | 0.3859 | 0.3880 | 0.3881 | 0.3885 | 0.3891 | 0.3909 | 0.3996 | 0.4000 | 0.4080 | 0.4187 | 0.4194 |
Changzhou | 0.3666 | 0.3634 | 0.3640 | 0.3647 | 0.3701 | 0.3722 | 0.3848 | 0.3868 | 0.3898 | 0.4000 | 0.4002 |
Suzhou | 0.3915 | 0.3968 | 0.3980 | 0.3991 | 0.3997 | 0.4095 | 0.4186 | 0.4199 | 0.4236 | 0.4355 | 0.4654 |
Nantong | 0.3632 | 0.3630 | 0.3631 | 0.3652 | 0.3682 | 0.3697 | 0.3724 | 0.3812 | 0.3883 | 0.3997 | 0.3999 |
Yangzhou | 0.3583 | 0.3590 | 0.3601 | 0.3671 | 0.3690 | 0.3713 | 0.3786 | 0.3812 | 0.3872 | 0.3872 | 0.3897 |
Zhengjiang | 0.3651 | 0.3680 | 0.3691 | 0.3701 | 0.3751 | 0.3777 | 0.3786 | 0.3790 | 0.3859 | 0.3859 | 0.3869 |
Tàizhou | 0.3493 | 0.3503 | 0.3520 | 0.3600 | 0.3621 | 0.3686 | 0.3690 | 0.3690 | 0.3743 | 0.3755 | 0.3753 |
Yancheng | 0.3407 | 0.3418 | 0.3450 | 0.3512 | 0.3551 | 0.3587 | 0.3786 | 0.3859 | 0.3880 | 0.3890 | 0.3888 |
Hangzhou | 0.3947 | 0.3965 | 0.3991 | 0.4014 | 0.4041 | 0.4211 | 0.4252 | 0.4262 | 0.4316 | 0.4447 | 0.4596 |
Ningbo | 0.3825 | 0.3871 | 0.3880 | 0.3991 | 0.3995 | 0.4010 | 0.4017 | 0.4029 | 0.4160 | 0.4199 | 0.4265 |
Jiaxing | 0.4057 | 0.4070 | 0.4090 | 0.4091 | 0.4194 | 0.4095 | 0.4096 | 0.4198 | 0.4301 | 0.4291 | 0.4290 |
Huzhou | 0.3576 | 0.3593 | 0.3620 | 0.3671 | 0.3675 | 0.3692 | 0.3749 | 0.3821 | 0.3945 | 0.3985 | 0.3955 |
Shaoxing | 0.3560 | 0.3570 | 0.3588 | 0.3601 | 0.3642 | 0.3646 | 0.3686 | 0.3702 | 0.3760 | 0.3780 | 0.3761 |
Zhoushan | 0.3448 | 0.3509 | 0.3520 | 0.3551 | 0.3573 | 0.3594 | 0.3642 | 0.3690 | 0.3697 | 0.3699 | 0.3690 |
Taizhou | 0.3563 | 0.3581 | 0.3611 | 0.3674 | 0.3679 | 0.3715 | 0.3773 | 0.3797 | 0.3801 | 0.3831 | 0.3805 |
Jinhua | 0.3483 | 0.3501 | 0.3555 | 0.3591 | 0.3601 | 0.3634 | 0.3684 | 0.3712 | 0.3757 | 0.3787 | 0.3877 |
Hefei | 0.3666 | 0.3700 | 0.3730 | 0.3800 | 0.3833 | 0.3854 | 0.3989 | 0.4010 | 0.4015 | 0.4129 | 0.4224 |
Wuhu | 0.3541 | 0.3601 | 0.3614 | 0.3654 | 0.3656 | 0.3657 | 0.3700 | 0.3743 | 0.3748 | 0.3778 | 0.3758 |
Maanshan | 0.3288 | 0.3327 | 0.3367 | 0.3401 | 0.3451 | 0.3460 | 0.3583 | 0.3595 | 0.3614 | 0.3654 | 0.3653 |
Tongling | 0.3387 | 0.3404 | 0.3404 | 0.3441 | 0.3474 | 0.3478 | 0.3541 | 0.3598 | 0.3602 | 0.3642 | 0.3632 |
Anqing | 0.3198 | 0.3216 | 0.3226 | 0.3232 | 0.3286 | 0.3300 | 0.3372 | 0.3400 | 0.3470 | 0.3479 | 0.3479 |
Chuzhou | 0.3217 | 0.3222 | 0.3223 | 0.3345 | 0.3348 | 0.3366 | 0.3392 | 0.3401 | 0.3500 | 0.3500 | 0.3499 |
Chizhou | 0.3151 | 0.3161 | 0.3175 | 0.3290 | 0.3300 | 0.3315 | 0.3413 | 0.3481 | 0.3515 | 0.3575 | 0.3501 |
Xuancheng | 0.3199 | 0.3240 | 0.3252 | 0.3381 | 0.3388 | 0.3426 | 0.3574 | 0.3600 | 0.3685 | 0.3695 | 0.3672 |
Year | The Top Three | Average of D | The Last Three | Average of D |
---|---|---|---|---|
2010 | Shanghai Jiaxing Hangzhou | 0.414 | Xuancheng Anqing Chizhou | 0.318 |
2011 | Shanghai Jiaxing Suzhou | 0.417 | Chuzhou Anqing Chizhou | 0.320 |
2012 | Shanghai Jiaxing Hangzhou | 0.418 | Anqing Chuzhou Chizhou | 0.321 |
2013 | Shanghai Jiaxing Hangzhou | 0.420 | Chuzhou Chizhou Anqing | 0.329 |
2014 | Shanghai Jiaxing Hangzhou | 0.421 | Chuzhou Chizhou Anqing | 0.331 |
2015 | Shanghai Hangzhou Jiaxing | 0.428 | Chuzhou Chizhou Anqing | 0.333 |
2016 | Shanghai Hangzhou Suzhou | 0.435 | Chizhou Chuzhou Anqing | 0.339 |
2017 | Shanghai Hangzhou Suzhou | 0.440 | Chizhou Chuzhou Anqing | 0.343 |
2018 | Shanghai Hangzhou Nanjing | 0.449 | Chizhou Chuzhou Anqing | 0.349 |
2019 | Shanghai Nanjing Hangzhou | 0.465 | Chizhou Chuzhou Anqing | 0.352 |
2020 | Shanghai Nanjing Suzhou | 0.482 | Chizhou Chuzhou Anqing | 0.349 |
Target Layer | System Layer | Indicator Layer | Unit | Code Name |
---|---|---|---|---|
Natural resources | Forest resources | Forest coverage | % | N1 |
Solar radiation | Hours of sunshine | Hours/year | N2 | |
Water resources | annual precipitation | Mm/year | N3 | |
The temperature conditions | Mean temperature | °C | N4 | |
Economic development | Economic development | GDP per capita | 104 CNY/person | E1 |
Industrial structure | The proportion of the output value of the tertiary industry in GDP | % | E2 | |
Industrialization level | The proportion of total industrial output value in GDP | % | E3 | |
Digital economy development level | Number of Internet broadband access users | 104 persons | E4 | |
Telecom business revenue | 106 CNY | |||
Information transmission, computer services, and software practitioners | 104 persons | |||
Mobile phone penetration | 104/person | |||
Digital finance development | ||||
Social conditions | Social carrying capacity | Density of population | Persons/km2 | S1 |
The level of government input | The proportion of local fiscal expenditure in GDP | % | S2 | |
People’s wealth level | Average annual savings per capita | 104 CNY/person | S3 | |
Educational standards | Average years of schooling per person | Years/person | S4 |
Detection Factors | N1 | N2 | N3 | N4 | S1 | S2 | S3 | S4 | E1 | E2 | E3 | E4 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
N1 | 0.046 | |||||||||||
N2 | 0.097 | 0.023 | ||||||||||
N3 | 0.078 | 0.089 | 0.049 | |||||||||
N4 | 0.084 | 0.077 | 0.073 | 0.025 | ||||||||
S1 | 0.930 | 0.052 | 0.097 | 0.075 | 0.037 | |||||||
S2 | 0.130 | 0.100 | 0.147 | 0.220 | 0.126 | 0.085 | ||||||
S3 | 0.054 | 0.050 | 0.087 | 0.059 | 0.080 | 0.120 | 0.028 | |||||
S4 | 0.117 | 0.938 | 0.109 | 0.104 | 0.094 | 0.147 | 0.104 | 0.069 | ||||
E1 | 0.173 | 0.138 | 0.167 | 0.144 | 0.096 | 0.249 | 0.123 | 0.230 | 0.116 | |||
E2 | 0.111 | 0.106 | 0.113 | 0.123 | 0.108 | 0.183 | 0.116 | 0.114 | 0.225 | 0.105 | ||
E3 | 0.114 | 0.104 | 0.120 | 0.108 | 0.102 | 0.141 | 0.179 | 0.121 | 0.224 | 0.215 | 0.092 | |
E4 | 0.103 | 0.081 | 0.110 | 0.095 | 0.089 | 0.158 | 0.096 | 0.127 | 0.166 | 0.265 | 0.171 | 0.057 |
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Ma, L.; Hong, Y.; Chen, X.; Quan, X. Can Green Innovation and New Urbanization Be Synergistic Development? Empirical Evidence from Yangtze River Delta City Group in China. Sustainability 2022, 14, 5765. https://doi.org/10.3390/su14105765
Ma L, Hong Y, Chen X, Quan X. Can Green Innovation and New Urbanization Be Synergistic Development? Empirical Evidence from Yangtze River Delta City Group in China. Sustainability. 2022; 14(10):5765. https://doi.org/10.3390/su14105765
Chicago/Turabian StyleMa, Lindong, Yuanxiao Hong, Xihui Chen, and Xiaoyong Quan. 2022. "Can Green Innovation and New Urbanization Be Synergistic Development? Empirical Evidence from Yangtze River Delta City Group in China" Sustainability 14, no. 10: 5765. https://doi.org/10.3390/su14105765