Can Higher Education, Economic Growth and Innovation Ability Improve Each Other?
Abstract
:1. Introduction
2. Theoretical Backgrounds
3. Materials and Methods
3.1. Study Area
3.2. Establishment of the Index System and Data Source
3.3. Index Weight Verification
- (1)
- Index standardization
- (2)
- The weights (P) of each index were calculated for different prefecture-level cities and years, with α as the total number of prefecture-level cities and β as the number of prefecture-level cities in different years:
- (3)
- The entropy (e) of each index was calculated using the following equation:
- (4)
- The weight wj of each index was calculated with j as the number of indices and 1 − e as the variation coefficients:
3.4. Coefficient Model of the Subsystems
3.5. Coupling Function
3.6. Coupling Coordination Model
4. Results and Discussion
4.1. Coupling Level Analysis
4.2. Economic Growth–Higher Education Coupling Coordination Analysis
4.3. Economic Growth–Innovation Ability Coupling Coordination Analysis
4.4. Higher Education–Innovation Ability Coupling Coordination Analysis
5. Conclusions and Implications
- From 2007 to 2017, the coupling coordination of the 13 prefecture-level cities in Jiangsu increased. This indicated an excellent interaction overall between higher education, economic development, and innovation capacity in Jiangsu, which positively influenced sustainable development in the province.
- In 2017, economic growth and higher education in Nanjing in 2017 underwent synchronized development and steady increases. The remaining regions also exhibited noticeable increases; however, problems arose during development. The economic growth of Lianyungang fell behind higher education development, and the other regions required improvements in the development of higher education. In summary, higher education resources in Jiangsu are excessively concentrated in the capital, which results in uneven spatial distribution. In particular, higher education resources are insufficient in economically disadvantaged Northern Jiangsu. This impedes innovation-based economic development in the district.
- In the economic growth–innovation ability system, the coupling coordination of all regions improved in 2017 compared with the situation in 2007. Only Suqian had moderately coordinated synchronized development in higher education and economic development. The remaining regions exhibited imbalanced development in innovation ability and economic growth, with the development of innovation ability falling behind. This revealed that innovation ability influences economic growth; however, economic growth is not the most crucial factor for regional innovation ability. Enhancing innovation ability substantially promotes regional balanced development.
- In the higher education–innovation ability system, coupling coordination in regions apart from Nanjing required improvement because of their limited higher education resources. Therefore, enhancing the quality of higher education and increasing investment in regional innovation and talent are critical to achieving balanced regional development and industrial transformation.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Coupling System | First-Level Index | Second-Level Index | Unit | Weight |
---|---|---|---|---|
Economic growth subsystem S1 | Economic scale | Gross regional product | Hundred million CNY | 0.2144 |
Total retail sales of consumer goods | Hundred million CNY | 0.2050 | ||
Economic structure | Percentage of GDP of the tertiary industry | % | 0.1518 | |
Tertiary industry employees as a percentage of the total employees | % | 0.1134 | ||
Quality of economy | Disposable income per capita of town residents | CNY | 0.1372 | |
Regional GDP per capita | CNY/person | 0.1782 | ||
Higher education subsystem S2 | Education scale | Numbers of colleges and universities | --- | 0.1622 |
Numbers of full-time teachers in colleges and universities | People | 0.1948 | ||
Numbers of college and university students | People | 0.2054 | ||
Numbers of college and university enrollments | People | 0.1811 | ||
Numbers of college and university graduates | People | 0.1974 | ||
Quality of education | Teacher–student ratio in colleges and universities | % | 0.0591 | |
Innovation ability subsystem S3 | Innovation input | Numbers of above-scale industrial enterprises with R&D activities | --- | 0.1623 |
R&D expenditure of above-scale industrial enterprises | Ten thousand CNY | 0.2408 | ||
R&D expenditure as a percentage of GDP | % | 0.0674 | ||
Number of R&D staff | People | 0.1550 | ||
Innovation output | Patent applications | Pieces | 0.1811 | |
Output values of new products | Ten thousand CNY | 0.1934 |
C Value | Levels of Coupling |
---|---|
0 ≤ C ≤ 0.4 | Uncoupled |
0.4 < C ≤ 0.6 | Slightly coupled |
0.6 < C ≤ 0.8 | Moderately coupled |
0.8 < C ≤ 1 | Highly coupled |
Coupling Coordination (D) | Levels of Coupling | Relationships between S1, S2, and S3 | Grading |
---|---|---|---|
0 < D ≤ 0.4 | Slightly coordinated C | S1−S2 > 0.1 | Slightly coordinated–higher education backwardness, Ca |
S2−S1 > 0.1 | Slightly coordinated–economic growth backwardness, Cb | ||
0 ≤|S1−S2|≤ 0.1 | Slightly coordinated–synchronized development in higher education and economic growth, Cc | ||
S1−S3 > 0.1 | Slightly coordinated–innovation ability backwardness, Cd | ||
S3−S1 > 0.1 | Slightly coordinated–economic growth backwardness, Ce | ||
0 ≤ |S1−S3| ≤ 0.1 | Slightly coordinated–synchronized development in innovation ability and economic growth, Cf | ||
S2−S3 > 0.1 | Slightly coordinated–innovation ability backwardness, Cg | ||
S3−S2 > 0.1 | Slightly coordinated–higher education backwardness, Ch | ||
0 ≤ |S2−S3| ≤ 0.1 | Slightly coordinated–synchronized development in higher education and innovation ability, Ci | ||
0.4 < D ≤ 0.5 | Moderately coordinated B | S1−S2 > 0.1 | Moderately coordinated–higher education backwardness, Ba |
S2−S1 > 0.1 | Moderately coordinated–economic growth backwardness, Bb | ||
0 ≤ |S1−S2 |≤ 0.1 | Moderately coordinated–synchronized development in higher education and economic growth, Bc | ||
S1−S3 > 0.1 | Moderately coordinated–innovation ability backwardness, Bd | ||
S3−S1 > 0.1 | Moderately coordinated–economic growth backwardness, Be | ||
0 ≤ |S1−S3| ≤ 0.1 | Moderately coordinated–synchronized development in innovation ability and economic growth, Bf | ||
S2−S3 > 0.1 | Moderately coordinated–innovation ability backwardness, Bg | ||
S3−S2 > 0.1 | Moderately coordinated–higher education backwardness, Bh | ||
0 ≤ |S2−S3| ≤ 0.1 | Moderately coordinated–synchronized development in higher education and innovation ability, Bi | ||
0.5 < D ≤ 0.8 | Highly coordinated A | S1−S2 > 0.1 | Highly coordinated–higher education backwardness, Aa |
S2−S1 > 0.1 | Highly coordinated–economic growth backwardness, Ab | ||
0 ≤ |S1−S2| ≤ 0.1 | Highly coordinated–synchronized development in higher education and economic growth, Ac | ||
S1−S3 > 0.1 | Highly coordinated–innovation ability backwardness, Ad | ||
S3−S1 > 0.1 | Highly coordinated–economic growth backwardness, Ae | ||
0 ≤ |S1−S3| ≤ 0.1 | Highly coordinated–synchronized development in innovation ability and economic growth, Af | ||
S2−S3 > 0.1 | Highly coordinated–innovation ability backwardness, Ag | ||
S3−S2 > 0.1 | Highly coordinated–higher education backwardness, Ah | ||
0 ≤ |S2−S3| ≤ 0.1 | Highly coordinated–synchronized development in higher education and innovation ability, Ai | ||
0.8 < D < 1 | Exceedingly coordinated S | S1−S2 > 0.1 | Exceedingly coordinated–higher education backwardness, Sa |
S2−S1 > 0.1 | Exceedingly coordinated–economic growth backwardness, Sb | ||
0 ≤ |S1−S2| ≤ 0.1 | Exceedingly coordinated–synchronized development in higher education and economic growth, Sc | ||
S1−S3 > 0.1 | Exceedingly coordinated–innovation ability backwardness, Sd | ||
S3−S1 > 0.1 | Exceedingly coordinated–economic growth backwardness, Se | ||
0 ≤ |S1−S3| ≤ 0.1 | Exceedingly coordinated–synchronized development in innovation ability and economic growth, Sf | ||
S2−S3 > 0.1 | Exceedingly coordinated–innovation ability backwardness, Sg | ||
S3−S2 > 0.1 | Exceedingly coordinated–higher education backwardness, Sh | ||
0 ≤ |S2−S3| ≤ 0.1 | Exceedingly coordinated–synchronized development in higher education and innovation ability, Si |
Region/Year | Index | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Nanjing | C12 | 0.957 | 0.953 | 0.955 | 0.970 | 0.973 | 0.983 | 0.993 | 0.996 | 0.998 | 1.000 | 1.000 |
C23 | 0.893 | 0.873 | 0.897 | 0.909 | 0.923 | 0.943 | 0.973 | 0.975 | 0.979 | 0.984 | 0.984 | |
C13 | 0.983 | 0.976 | 0.986 | 0.981 | 0.985 | 0.987 | 0.994 | 0.992 | 0.989 | 0.989 | 0.988 | |
Wuxi | C12 | 0.964 | 0.956 | 0.948 | 0.933 | 0.908 | 0.894 | 0.883 | 0.869 | 0.862 | 0.841 | 0.823 |
C23 | 0.991 | 0.989 | 0.975 | 0.959 | 0.932 | 0.913 | 0.893 | 0.896 | 0.897 | 0.884 | 0.877 | |
C13 | 0.991 | 0.989 | 0.994 | 0.996 | 0.998 | 0.999 | 1.000 | 0.998 | 0.996 | 0.995 | 0.993 | |
Xuzhou | C12 | 0.998 | 1.000 | 0.999 | 0.993 | 0.989 | 0.981 | 0.971 | 0.960 | 0.949 | 0.938 | 0.927 |
C23 | 0.993 | 0.994 | 0.999 | 1.000 | 0.998 | 0.997 | 0.993 | 0.995 | 0.994 | 0.986 | 0.990 | |
C13 | 0.998 | 0.995 | 0.998 | 0.994 | 0.997 | 0.993 | 0.992 | 0.982 | 0.976 | 0.982 | 0.968 | |
Changzhou | C12 | 1.000 | 0.997 | 0.990 | 0.973 | 0.954 | 0.945 | 0.911 | 0.903 | 0.882 | 0.865 | 0.872 |
C23 | 0.996 | 0.999 | 0.997 | 0.986 | 0.982 | 0.980 | 0.945 | 0.940 | 0.929 | 0.918 | 0.943 | |
C13 | 0.994 | 0.993 | 0.998 | 0.998 | 0.993 | 0.991 | 0.995 | 0.995 | 0.992 | 0.991 | 0.982 | |
Suzhou | C12 | 0.985 | 0.977 | 0.972 | 0.961 | 0.947 | 0.928 | 0.916 | 0.906 | 0.898 | 0.886 | 0.878 |
C23 | 0.999 | 1.000 | 0.999 | 0.990 | 0.977 | 0.974 | 0.954 | 0.958 | 0.959 | 0.944 | 0.943 | |
C13 | 0.979 | 0.979 | 0.983 | 0.990 | 0.993 | 0.987 | 0.993 | 0.988 | 0.984 | 0.988 | 0.985 | |
Nantong | C12 | 0.982 | 0.974 | 0.967 | 0.960 | 0.938 | 0.919 | 0.900 | 0.887 | 0.872 | 0.856 | 0.845 |
C23 | 0.995 | 0.989 | 0.984 | 0.958 | 0.933 | 0.939 | 0.930 | 0.936 | 0.927 | 0.923 | 0.924 | |
C13 | 0.996 | 0.996 | 0.997 | 1.000 | 1.000 | 0.998 | 0.997 | 0.991 | 0.990 | 0.986 | 0.981 | |
Lianyungang | C12 | 0.985 | 0.976 | 0.968 | 0.961 | 0.952 | 0.937 | 0.925 | 0.925 | 0.909 | 0.897 | 0.889 |
C23 | 1.000 | 1.000 | 0.999 | 0.997 | 0.994 | 0.988 | 0.983 | 0.978 | 0.973 | 0.966 | 0.971 | |
C13 | 0.985 | 0.979 | 0.980 | 0.979 | 0.979 | 0.978 | 0.977 | 0.982 | 0.979 | 0.978 | 0.969 | |
Huaian | C12 | 0.996 | 0.994 | 0.991 | 0.978 | 0.969 | 0.957 | 0.942 | 0.928 | 0.915 | 0.902 | 0.895 |
C23 | 0.997 | 0.996 | 0.997 | 0.999 | 1.000 | 1.000 | 0.998 | 0.995 | 0.989 | 0.980 | 0.980 | |
C13 | 0.986 | 0.981 | 0.979 | 0.970 | 0.970 | 0.964 | 0.960 | 0.958 | 0.963 | 0.967 | 0.963 | |
Yancheng | C12 | 0.991 | 0.988 | 0.980 | 0.964 | 0.953 | 0.938 | 0.921 | 0.912 | 0.894 | 0.886 | 0.874 |
C23 | 0.999 | 0.999 | 1.000 | 1.000 | 0.998 | 0.997 | 0.992 | 0.990 | 0.985 | 0.960 | 0.960 | |
C13 | 0.983 | 0.978 | 0.976 | 0.966 | 0.969 | 0.959 | 0.961 | 0.958 | 0.955 | 0.977 | 0.972 | |
Yangzhou | C12 | 0.996 | 0.990 | 0.980 | 0.961 | 0.945 | 0.930 | 0.916 | 0.903 | 0.884 | 0.864 | 0.853 |
C23 | 1.000 | 0.999 | 0.995 | 0.990 | 0.988 | 0.982 | 0.973 | 0.966 | 0.947 | 0.937 | 0.934 | |
C13 | 0.998 | 0.995 | 0.995 | 0.990 | 0.983 | 0.981 | 0.982 | 0.981 | 0.985 | 0.983 | 0.980 | |
Zhenjiang | C12 | 0.996 | 0.991 | 0.985 | 0.971 | 0.950 | 0.931 | 0.910 | 0.901 | 0.886 | 0.876 | 0.871 |
C23 | 1.000 | 1.000 | 1.000 | 0.996 | 0.990 | 0.989 | 0.975 | 0.944 | 0.935 | 0.927 | 0.957 | |
C13 | 0.995 | 0.994 | 0.983 | 0.989 | 0.984 | 0.973 | 0.977 | 0.993 | 0.991 | 0.991 | 0.972 | |
Taizhou | C12 | 0.987 | 0.976 | 0.971 | 0.956 | 0.938 | 0.919 | 0.909 | 0.902 | 0.886 | 0.870 | 0.852 |
C23 | 0.916 | 0.864 | 0.827 | 0.820 | 0.807 | 0.836 | 0.856 | 0.806 | 0.846 | 0.849 | 0.832 | |
C13 | 0.997 | 0.997 | 0.998 | 0.993 | 0.986 | 1.000 | 0.989 | 0.993 | 0.991 | 0.992 | 0.986 | |
Suqian | C12 | 0.999 | 0.993 | 0.991 | 0.972 | 0.960 | 0.958 | 0.942 | 0.981 | 0.915 | 0.899 | 0.885 |
C23 | 1.000 | 1.000 | 1.000 | 0.999 | 0.998 | 0.983 | 0.966 | 0.993 | 0.944 | 0.938 | 0.952 | |
C13 | 0.998 | 0.994 | 0.992 | 0.979 | 0.975 | 0.994 | 0.996 | 0.997 | 0.996 | 0.994 | 0.983 |
Region/Year | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 |
---|---|---|---|---|---|---|---|---|---|---|---|
Nanjing | 0.720 | 0.760 | 0.786 | 0.824 | 0.857 | 0.874 | 0.881 | 0.894 | 0.913 | 0.930 | 0.960 |
Ab | Ab | Ab | Sb | Sb | Sb | Sb | Sb | Sc | Sc | Sc | |
Wuxi | 0.496 | 0.514 | 0.527 | 0.543 | 0.556 | 0.568 | 0.578 | 0.589 | 0.598 | 0.609 | 0.621 |
Ba | Aa | Aa | Aa | Aa | Aa | Aa | Aa | Aa | Aa | Aa | |
Xuzhou | 0.431 | 0.449 | 0.464 | 0.482 | 0.498 | 0.514 | 0.529 | 0.542 | 0.555 | 0.569 | 0.581 |
Bc | Bc | Bc | Bc | Bc | Aa | Aa | Aa | Aa | Aa | Aa | |
Changzhou | 0.457 | 0.480 | 0.498 | 0.516 | 0.525 | 0.546 | 0.545 | 0.554 | 0.564 | 0.576 | 0.604 |
Bc | Bc | Bc | Aa | Aa | Aa | Aa | Aa | Aa | Aa | Aa | |
Suzhou | 0.522 | 0.557 | 0.579 | 0.605 | 0.623 | 0.640 | 0.657 | 0.676 | 0.690 | 0.706 | 0.724 |
Ac | Aa | Aa | Aa | Aa | Aa | Aa | Aa | Aa | Aa | Aa | |
Nantong | 0.423 | 0.441 | 0.453 | 0.457 | 0.468 | 0.483 | 0.499 | 0.514 | 0.527 | 0.540 | 0.556 |
Bc | Bc | Ba | Ba | Ba | Ba | Ba | Aa | Aa | Aa | Aa | |
Lianyungang | 0.373 | 0.383 | 0.390 | 0.403 | 0.410 | 0.420 | 0.432 | 0.433 | 0.443 | 0.450 | 0.459 |
Cc | Cc | Cc | Bc | Bc | Bc | Bb | Bb | Bb | Bb | Bb | |
Huaian | 0.399 | 0.414 | 0.428 | 0.439 | 0.447 | 0.459 | 0.468 | 0.477 | 0.488 | 0.498 | 0.505 |
Cc | Bc | Bc | Bc | Ba | Ba | Ba | Ba | Ba | Ba | Aa | |
Yancheng | 0.392 | 0.406 | 0.416 | 0.433 | 0.441 | 0.452 | 0.464 | 0.469 | 0.482 | 0.494 | 0.506 |
Cc | Bc | Bc | Ba | Ba | Ba | Ba | Ba | Ba | Ba | Aa | |
Yangzhou | 0.418 | 0.433 | 0.446 | 0.467 | 0.483 | 0.500 | 0.512 | 0.520 | 0.531 | 0.541 | 0.555 |
Bc | Bc | Bc | Ba | Ba | Ba | Aa | Aa | Aa | Aa | Aa | |
Zhenjiang | 0.421 | 0.438 | 0.451 | 0.471 | 0.491 | 0.505 | 0.513 | 0.522 | 0.533 | 0.544 | 0.553 |
Bc | Bc | Bc | Ba | Ba | Aa | Aa | Aa | Aa | Aa | Aa | |
Taizhou | 0.385 | 0.397 | 0.409 | 0.430 | 0.444 | 0.458 | 0.463 | 0.476 | 0.489 | 0.503 | 0.515 |
Cc | Cc | Bc | Ba | Ba | Ba | Ba | Ba | Ba | Aa | Aa | |
Suqian | 0.333 | 0.344 | 0.355 | 0.367 | 0.379 | 0.378 | 0.386 | 0.434 | 0.403 | 0.411 | 0.422 |
Cc | Cc | Cc | Cc | Cc | Cc | Ca | Bc | Ba | Ba | Ba |
Region/Year | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 |
---|---|---|---|---|---|---|---|---|---|---|---|
Nanjing | 0.565 | 0.582 | 0.620 | 0.660 | 0.700 | 0.735 | 0.783 | 0.799 | 0.823 | 0.850 | 0.879 |
Ad | Ad | Ad | Ad | Ad | Ad | Ad | Ad | Sd | Sd | Sd | |
Wuxi | 0.530 | 0.555 | 0.590 | 0.628 | 0.672 | 0.705 | 0.737 | 0.747 | 0.758 | 0.784 | 0.807 |
Af | Af | Af | Af | Af | Af | Af | Af | Af | Ad | Sd | |
Xuzhou | 0.407 | 0.424 | 0.456 | 0.484 | 0.516 | 0.534 | 0.561 | 0.568 | 0.586 | 0.619 | 0.623 |
Bf | Bf | Bf | Bf | Af | Af | Af | Ad | Ad | Ad | Ad | |
Changzhou | 0.437 | 0.471 | 0.516 | 0.562 | 0.578 | 0.604 | 0.646 | 0.662 | 0.685 | 0.710 | 0.718 |
Bf | Bf | Af | Af | Af | Ad | Af | Af | Ad | Ad | Ad | |
Suzhou | 0.513 | 0.559 | 0.595 | 0.650 | 0.694 | 0.719 | 0.767 | 0.784 | 0.798 | 0.838 | 0.861 |
Ad | Ad | Ad | Ad | Ad | Ad | Ad | Ad | Ad | Sd | Sd | |
Nantong | 0.444 | 0.475 | 0.495 | 0.530 | 0.565 | 0.578 | 0.605 | 0.618 | 0.642 | 0.661 | 0.679 |
Bf | Bf | Bf | Af | Af | Af | Af | Ad | Ad | Ad | Ad | |
Lianyungang | 0.373 | 0.386 | 0.400 | 0.419 | 0.434 | 0.453 | 0.474 | 0.481 | 0.499 | 0.513 | 0.519 |
Cf | Cf | Bf | Bf | Bd | Bd | Bd | Ad | Ad | Ad | Ad | |
Huaian | 0.384 | 0.397 | 0.411 | 0.432 | 0.448 | 0.465 | 0.482 | 0.501 | 0.526 | 0.551 | 0.558 |
Cf | Cf | Bf | Bf | Bd | Bd | Bd | Ad | Ad | Ad | Ad | |
Yancheng | 0.381 | 0.395 | 0.411 | 0.436 | 0.455 | 0.469 | 0.494 | 0.503 | 0.526 | 0.570 | 0.585 |
Cf | Cf | Bf | Bd | Bd | Bd | Bd | Ad | Ad | Ad | Ad | |
Yangzhou | 0.423 | 0.443 | 0.469 | 0.502 | 0.522 | 0.549 | 0.576 | 0.593 | 0.626 | 0.649 | 0.669 |
Bf | Bf | Bf | Af | Ad | Ad | Ad | Ad | Ad | Ad | Ad | |
Zhenjiang | 0.418 | 0.443 | 0.448 | 0.493 | 0.527 | 0.544 | 0.574 | 0.619 | 0.642 | 0.663 | 0.642 |
Bf | Bf | Bf | Bf | Ad | Ad | Ad | Af | Ad | Ad | Ad | |
Taizhou | 0.402 | 0.425 | 0.446 | 0.471 | 0.490 | 0.557 | 0.537 | 0.565 | 0.588 | 0.617 | 0.633 |
Bf | Bf | Bf | Bf | Bf | Af | Af | Af | Af | Ad | Ad | |
Suqian | 0.331 | 0.345 | 0.356 | 0.374 | 0.391 | 0.415 | 0.441 | 0.461 | 0.479 | 0.492 | 0.495 |
Cf | Cf | Cf | Cf | Cf | Bf | Bf | Bf | Bf | Bf | Bf |
Region/Year | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 |
---|---|---|---|---|---|---|---|---|---|---|---|
Nanjing | 0.656 | 0.680 | 0.722 | 0.747 | 0.786 | 0.806 | 0.833 | 0.838 | 0.847 | 0.863 | 0.888 |
Ag | Ag | Ag | Ag | Ag | Sg | Sg | Sg | Sg | Sg | Sg | |
Wuxi | 0.463 | 0.477 | 0.500 | 0.520 | 0.538 | 0.554 | 0.572 | 0.570 | 0.573 | 0.580 | 0.585 |
Bi | Bi | Bh | Ah | Ah | Ah | Ah | Ah | Ah | Ah | Ah | |
Xuzhou | 0.419 | 0.427 | 0.449 | 0.456 | 0.479 | 0.483 | 0.497 | 0.492 | 0.497 | 0.516 | 0.511 |
Bi | Bi | Bi | Bi | Bi | Bi | Bi | Bi | Bi | Ai | Ai | |
Changzhou | 0.432 | 0.453 | 0.481 | 0.500 | 0.495 | 0.510 | 0.519 | 0.526 | 0.530 | 0.539 | 0.549 |
Bi | Bi | Bi | Bi | Bi | Ah | Ah | Ah | Ah | Ah | Ah | |
Suzhou | 0.471 | 0.502 | 0.528 | 0.564 | 0.587 | 0.591 | 0.620 | 0.626 | 0.630 | 0.652 | 0.664 |
Bi | Ai | Ai | Ai | Ah | Ah | Ah | Ah | Ah | Ah | Ah | |
Nantong | 0.404 | 0.422 | 0.435 | 0.459 | 0.472 | 0.469 | 0.479 | 0.482 | 0.491 | 0.497 | 0.504 |
Bi | Bi | Bi | Bh | Bh | Bh | Bh | Bh | Bh | Bh | Ah | |
Lianyungang | 0.342 | 0.345 | 0.352 | 0.364 | 0.370 | 0.378 | 0.388 | 0.394 | 0.400 | 0.405 | 0.405 |
Ci | Ci | Ci | Ci | Ci | Ci | Ci | Ci | Ci | Bi | Bi | |
Huaian | 0.367 | 0.375 | 0.385 | 0.388 | 0.395 | 0.400 | 0.405 | 0.412 | 0.425 | 0.438 | 0.440 |
Ci | Ci | Ci | Ci | Ci | Bi | Bi | Bi | Bi | Bi | Bi | |
Yancheng | 0.356 | 0.365 | 0.372 | 0.380 | 0.389 | 0.391 | 0.402 | 0.405 | 0.413 | 0.444 | 0.449 |
Ci | Ci | Ci | Ci | Ci | Ci | Bi | Bi | Bi | Bh | Bh | |
Yangzhou | 0.405 | 0.413 | 0.424 | 0.436 | 0.440 | 0.453 | 0.465 | 0.472 | 0.486 | 0.492 | 0.501 |
Bi | Bi | Bi | Bi | Bi | Bi | Bh | Bh | Bh | Bh | Ah | |
Zhenjiang | 0.400 | 0.414 | 0.411 | 0.437 | 0.448 | 0.449 | 0.461 | 0.491 | 0.499 | 0.510 | 0.491 |
Bi | Bi | Bi | Bi | Bi | Bi | Bi | Bh | Bh | Ah | Bh | |
Taizhou | 0.356 | 0.356 | 0.362 | 0.369 | 0.371 | 0.372 | 0.371 | 0.378 | 0.380 | 0.384 | 0.385 |
Ci | Ci | Ci | Ci | Ci | Ch | Ch | Ch | Ch | Ch | Ch | |
Suqian | 0.323 | 0.326 | 0.333 | 0.331 | 0.338 | 0.358 | 0.370 | 0.418 | 0.386 | 0.389 | 0.385 |
Ci | Ci | Ci | Ci | Ci | Ci | Ci | Bi | Ch | Ch | Ci |
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Xu, H.; Hsu, W.-L.; Meen, T.-H.; Zhu, J.H. Can Higher Education, Economic Growth and Innovation Ability Improve Each Other? Sustainability 2020, 12, 2515. https://doi.org/10.3390/su12062515
Xu H, Hsu W-L, Meen T-H, Zhu JH. Can Higher Education, Economic Growth and Innovation Ability Improve Each Other? Sustainability. 2020; 12(6):2515. https://doi.org/10.3390/su12062515
Chicago/Turabian StyleXu, Haiying, Wei-Ling Hsu, Teen-Hang Meen, and Ju Hua Zhu. 2020. "Can Higher Education, Economic Growth and Innovation Ability Improve Each Other?" Sustainability 12, no. 6: 2515. https://doi.org/10.3390/su12062515