Research on the Impact Mechanism of Green Innovation in Marine Science and Technology Enabling Dual Economic Circulations
Abstract
:1. Introduction
2. Literature Review
2.1. Green Innovation in Marine Science and Technology and Domestic Economic Circulations
2.2. Green Innovation in Marine Science and Technology and International Economic Circulations
2.3. Green Innovation in Marine Science and Technology and Dual Economic Circulations
2.4. Literature Summary
3. Hypotheses and Methodology
3.1. Research Hypotheses
3.2. Methodology
- (1)
- SBM Super-Efficiency Model
- (2)
- Coupling Coordination Model
- (3)
- Impact Pathway Model
- (4)
- Threshold regression model
4. Variable Selection and Data Description
4.1. Variable Selection and Processing
4.1.1. Index System
4.1.2. Calculation of Input and Output Indicators
4.1.3. Mediating Variables
4.1.4. Control Variables
4.2. Data Sources
5. Empirical Results and Analysis
5.1. Descriptive Statistics
5.2. Overall Characterization of the Coupling Degree of the Double Loop
5.3. Direct Effect Test
5.4. Discussion
5.4.1. Mediating Effect Test of Resource Mismatch
5.4.2. Mediating Effect Test of High-Quality Development of Marine Economy
5.4.3. Threshold Effect Existence and Number Test
5.5. Endogeneity Test
5.6. Robustness Testing
6. Conclusions and Recommendations
- Strengthen innovation in marine science and technology, and increase investment in marine scientific research. To enhance the ability of marine science and technology innovation and system management, we should strengthen the construction of marine science and technology infrastructure, and optimize the soft environment such as policies, regulations, and related services. This will help to continuously improve the efficiency level of scientific and technological innovation, so as to achieve coordinated development with the scale of investment, strengthen the construction of frontier disciplines, and actively integrate into the global marine science and technology innovation a division of labor system. Relying on major national strategies, increase investment in important coastal areas and emerging marine industries, strengthen fund management of marine research projects, encourage interdisciplinary integration, and increase R&D capital investment in basic research and applied research.
- Formulate and implement competitive talent policies. For those areas where the efficiency of marine science and technology innovation and the level of scale investment are relatively weak, efforts should be made from two aspects: On the one hand, strengthen the construction of innovation scale, strive to win the support of national policies, optimize and improve the scale structure of science and technology innovation. On the other hand, the coastal areas should fully tap and make use of the resource advantages of these areas, and actively introduce high-tech and high-level talents in the marine field that match the development of the local marine industry, in order to improve the efficiency of scientific and technological innovation, and then promote the overall improvement of the quality of marine scientific research and innovation in the whole region.
- Improve the efficiency of marine factor allocation and promote the supporting role of marine scientific and technological innovation in the marine economy. Adhere to innovation-driven approaches, optimize the spatial pattern of maritime areas, enhance the aggregation role of marine factors, improve the efficiency of factor allocation, increase the intensive use of marine resources, and integrate higher levels of scientific and technological innovation into the double cycle of domestic and international economy.
- Reinforce weak links to achieve the high-quality development of the marine economy. Actively promoting the development of the marine economy will help break through the limitations of resources and environment, broaden the space for survival and development, and generate new driving forces for economic growth. Through the land–sea overall strategy, the spatial layout of the industry should be optimized, guided by land–sea overall planning and regional coordination, and the spatial pattern of the development of the coastal areas should be further improved, so as to build a coastal industrial agglomeration belt with strong competitiveness and thus enhance the radiation capacity of the coastal areas in both the sea and the land. At the same time, the strategy of promoting the sea by science and technology should be thoroughly implemented, and research on cutting-edge leading and subversive technologies in the marine industry should be conducted to occupy the commanding heights of marine science and technology innovation. At the same time, we should actively support and rely on sea-related backbone enterprises to promote their construction of technology research and development centers for major marine industries, so as to achieve sustainable innovation and development in the marine industry.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Degree of Coupling Coordination | Type | Degree of Coupling Coordination | Type |
---|---|---|---|
(0, 0.1] | Extreme disorder | (0.5, 0.6] | Sue for harmonization |
(0.1, 0.2] | Severe disorder | (0.6, 0.7] | Primary coordination |
(0.2, 0.3] | Moderate disorder | (0.7, 0.8] | Intermediate-level coordination |
(0.3, 0.4] | Mild disorder | (0.8, 0.9] | Good coordination |
(0.4, 0.5] | On the verge of disorder | (0.9, 1] | Quality coordination |
Degree of coordination of double-cycle coupling (DC) | Subsystems | Guideline Layer | Indicator Level |
Domestic Economic Circulation (IC) | Consumption Base | Per Capita Disposable Income of Residents (RMB/person) | |
Consumption Willingness | Per Capita Consumption Expenditure of Residents (RMB/person) | ||
Consumption Structure | Proportion of Expenditure on Household Equipment per Capita to Total Consumption Expenditure (%) | ||
Scale of Production | Growth Rate of Total Fixed Asset Investment in the Whole Society (%) | ||
Production Structure | Sum of the Proportion of Output in Three Major Industrial Sectors and Labor Productivity | ||
Production Efficiency | Average Labor Productivity in Three Major Industrial Sectors (%) | ||
Internal Economic Circulation (EC) | Direct Foreign Investment | Growth Rate of Foreign Direct Investment (%) | |
Direct Foreign Investment | Growth Rate of Non-Financial Outbound Direct Investment (%) | ||
Import Trade | Proportion of Import Trade to GDP (%) | ||
Export Trade | Proportion of Export Trade to GDP (%) | ||
Technology Introduction | Growth Rate of Technology Introduction Expenditure of Large-scale High-Tech Industrial Enterprises (%) |
Target Layer | Tier 1 Indicators | Secondary Indicators |
---|---|---|
Inputs | Capital | Input of funds to marine-related scientific research institutions |
Labor Force | Scientific and technological employees of marine scientific research institutions | |
Physical Resources | Marine research institutions | |
Outputs | Thesis | Number of scientific papers published by marine research institutions |
Patents | Total number of invention patents held by marine research institutions | |
Project Results | Number of marine scientific and technological achievements |
VarName | Obs | Mean | SD | Min | Median | Max |
---|---|---|---|---|---|---|
TEC | 165 | 0.5575 | 0.8173 | 0.0044 | 0.1554 | 4.0259 |
IC | 165 | 0.4414 | 0.1268 | 0.1952 | 0.4347 | 0.8029 |
EC | 165 | 0.3606 | 0.1521 | 0.0167 | 0.3408 | 0.7306 |
DC | 165 | 0.6157 | 0.1017 | 0.2757 | 0.6142 | 0.8706 |
KIMS | 165 | 0.3569 | 0.7399 | −0.3370 | 0.0968 | 2.8233 |
LIMS | 165 | 0.2128 | 0.4922 | −0.3851 | 0.1795 | 1.3162 |
MED | 165 | 0.1794 | 0.0887 | 0.0315 | 0.1717 | 0.3772 |
PGDP | 165 | 10.6376 | 1.7006 | −9.7218 | 10.7879 | 11.9658 |
IND | 165 | 3.8189 | 0.2962 | 3.1058 | 3.8795 | 6.3735 |
EMP | 165 | 7.7658 | 0.9326 | 1.7822 | 7.9445 | 8.8749 |
MKT | 165 | 8.7830 | 1.6359 | 1.0730 | 9.0220 | 11.4940 |
Year | Value | Level of Coordination | Year | Value | Level of Coordination |
---|---|---|---|---|---|
2005 | 0.286 | Moderate disorder | 2013 | 0.562 | Sue for harmonization |
2006 | 0.334 | Mild disorder | 2014 | 0.531 | Sue for harmonization |
2007 | 0.358 | Mild disorder | 2015 | 0.533 | Sue for harmonization |
2008 | 0.387 | Mild disorder | 2016 | 0.574 | Sue for harmonization |
2009 | 0.418 | On the verge of becoming dysfunctional | 2017 | 0.591 | Sue for harmonization |
2010 | 0.448 | On the verge of becoming dysfunctional | 2018 | 0.643 | Primary coordination |
2011 | 0.469 | On the verge of becoming dysfunctional | 2019 | 0.631 | Primary coordination |
2012 | 0.515 | Sue for harmonization |
(1) | (2) | (3) | |
---|---|---|---|
IC | EC | DC | |
TEC | 0.0256 *** | 0.0701 *** | 0.0279 *** |
(3.00) | (4.26) | (3.27) | |
Controls | √ | √ | √ |
Constant | 0.4592 *** | 0.4316 *** | 0.6625 *** |
(18.41) | (11.13) | (34.48) | |
Province fixed effects | √ | √ | √ |
Year fixed effects | √ | √ | √ |
N | 165 | 165 | 165 |
R2 | 0.8721 | 0.6017 | 0.7184 |
F | 72.7332 | 14.8132 | 28.0782 |
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
IC | K | L | IC | |
TEC | 0.0284 *** | −0.1317 * | −0.1413 ** | 0.0238 *** |
(3.45) | (−1.81) | (−2.22) | (2.79) | |
K | −0.0099 * | |||
(−1.67) | ||||
L | −0.0238 ** | |||
(−2.14) | ||||
Controls | √ | √ | √ | √ |
Constant | 1.2072 * | −5.9034 | −1.6640 | 1.1092 * |
(1.95) | (−1.00) | (−0.31) | (1.81) | |
Province fixed effects | √ | √ | √ | √ |
Year fixed effects | √ | √ | √ | √ |
N | 165 | 165 | 165 | 165 |
R2 | 0.8848 | 0.5494 | 0.4544 | 0.8923 |
(1) | (2) | (3) | |
---|---|---|---|
EC | MED | EC | |
TEC | 0.0665 *** | 0.0172 *** | 0.0565 ** |
(3.71) | (2.78) | (3.20) | |
MED | 0.5794 *** | ||
(2.43) | |||
Controls | |||
Constant | 0.7545 | 0.7259 | 0.3339 |
(0.46) | (1.19) | (0.21) | |
Province fixed effects | |||
Year fixed effects | |||
N | 165 | 165 | 165 |
R2 | 0.6167 | 0.8974 | 0.6302 |
Threshold Variable | Dependent Variables | Number of Thresholds | F-Value | p-Value | Threshold Value | ||
---|---|---|---|---|---|---|---|
1% | 5% | 10% | |||||
TEC | IC | Single Threshold | 14.42 * | 0.0550 | 18.1828 | 14.5438 | 12.4477 |
Double threshold | 9.90 | 0.1900 | 21.1851 | 14.0953 | 11.4182 | ||
Triple threshold | 8.10 | 0.5700 | 28.8464 | 18.9495 | 17.0918 | ||
EC | Single threshold | 20.32 *** | 0.0050 | 16.0474 | 11.6059 | 9.8089 | |
Double threshold | 3.79 | 0.7400 | 15.4585 | 10.9569 | 9.7703 | ||
Triple threshold | 4.88 | 0.5050 | 16.5554 | 12.6552 | 10.1419 |
Threshold Variable—TEC | |||
---|---|---|---|
Dependent variables | Category | Threshold value | 95% confidence interval |
IC | Single Threshold | 0.6428 | (0.5334, 0.6493) |
EC | Single Threshold | 0.0540 | (0.0445, 0.0540) |
(1) | (2) | ||
---|---|---|---|
IC | EC | ||
TEC (TEC < 0.6428) | 0.148 *** | TEC (TEC < 0.0540) | −2.500 *** |
(4.30) | (−4.20) | ||
TEC (TEC > 0.6428) | 0.033 *** | TEC (TEC > 0.0540) | 0.056 *** |
(4.24) | (−3.57) | ||
Controls | Controls | ||
Constant | 0.381 *** | Constant | 0.425 *** |
(25.87) | (−13.27) | ||
Province fixed effects | Province fixed effects | ||
Year fixed effects | Year fixed effects | ||
N | 165 | N | 165 |
R2 | 0.316 | R2 | 0.3 |
F | 3.976 | F | 3.688 |
IC | EC | DC | ||||
---|---|---|---|---|---|---|
OLS | 2SLS | OLS | 2SLS | OLS | 2SLS | |
TEC | 0.435 *** (0.129) | 0.044 ** (0.017) | 0.435 *** (0.129) | 0.169 *** (0.043) | 0.435 *** (0.129) | 0.073 *** (0.019) |
PGDP | −0.057 (0.075) | 0.024 *** (0.008) | −0.057 (0.075) | −0.015 (0.013) | −0.057 (0.075) | 0.001 (0.007) |
IND | −0.557 ** (0.281) | 0.051 (0.032) | −0.557 ** (0.281) | 0.046 (0.059) | −0.557 ** (0.281) | 0.038 (0.031) |
EMP | 0.091 (0.058) | −0.056 *** (0.009) | 0.091 (0.058) | −0.042 *** (0.012) | 0.091 (0.058) | −0.040 *** (0.007) |
MARKET | 0.082 (0.062) | 0.040 *** (0.008) | 0.082 (0.061) | 0.030 *** (0.012) | 0.082 (0.061) | 0.034 *** (0.007) |
INFRA | 0.299 * (0.167) | 0.040 *** (0.014) | 0.299 * (0.167) | −0.058 ** (0.028) | 0.299 * (0.167) | −0.013 (0.014) |
Constant | 1.273 (1.121) | −0.006 (0.125) | 1.273 (1.121) | 0.372 (0.255) | 1.273 (1.121) | 0.445 *** (0.138) |
N | 154 | 154 | 154 | 154 | 154 | 154 |
R2 | 0.454 | 0.770 | 0.454 | 0.427 | 0.454 | 0.600 |
TEC | IC | EC | DC |
---|---|---|---|
OLS | OLS | OLS | |
Bias R2 | 0.172 | 0.172 | 0.172 |
F | 11.456 | 11.456 | 11.456 |
Minimum eigenvalue statistic | 30.538 | 30.538 | 30.538 |
2SLS size of nominal 5% critical value corresponding to 10% in Wald test | 16.38 | 16.38 | 16.38 |
(1) | (2) | (3) | |
---|---|---|---|
IC | EC | DC | |
TEC | 0.1241 ** | 0.4076 *** | 0.2971 *** |
(2.22) | (3.88) | (5.03) | |
Controls | |||
Constant | 0.4076 *** | 0.2618 *** | 0.5383 *** |
(11.11) | (4.34) | (17.74) | |
Province fixed effects | |||
Year fixed effects | |||
N | |||
R2 | 0.8671 | 0.5868 | 0.7443 |
F | 42.8890 | 11.6592 | 28.8752 |
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Jin, X.; Huang, S.; Lei, X. Research on the Impact Mechanism of Green Innovation in Marine Science and Technology Enabling Dual Economic Circulations. Sustainability 2024, 16, 8421. https://doi.org/10.3390/su16198421
Jin X, Huang S, Lei X. Research on the Impact Mechanism of Green Innovation in Marine Science and Technology Enabling Dual Economic Circulations. Sustainability. 2024; 16(19):8421. https://doi.org/10.3390/su16198421
Chicago/Turabian StyleJin, Xin, Shiru Huang, and Xue Lei. 2024. "Research on the Impact Mechanism of Green Innovation in Marine Science and Technology Enabling Dual Economic Circulations" Sustainability 16, no. 19: 8421. https://doi.org/10.3390/su16198421
APA StyleJin, X., Huang, S., & Lei, X. (2024). Research on the Impact Mechanism of Green Innovation in Marine Science and Technology Enabling Dual Economic Circulations. Sustainability, 16(19), 8421. https://doi.org/10.3390/su16198421