Analysis of synergies between vocational education and regional economic development
25 wrz 2025
O artykule
Data publikacji: 25 wrz 2025
Otrzymano: 09 sty 2025
Przyjęty: 20 kwi 2025
DOI: https://doi.org/10.2478/amns-2025-1017
Słowa kluczowe
© 2025 Shuai Xiao, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
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Figure 6.

Education development level of Hunan province
| City | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 |
|---|---|---|---|---|---|---|
| Changsha | 0.0451 | 0.0394 | 0.0527 | 0.0324 | 0.0916 | 0.0946 |
| Zhuzhou | 0.0346 | 0.0445 | 0.0283 | 0.0459 | 0.0354 | 0.0452 |
| Xiangtan | 0.0402 | 0.0416 | 0.0469 | 0.0431 | 0.0483 | 0.0518 |
| Hengyang | 0.0387 | 0.0448 | 0.0412 | 0.0451 | 0.0411 | 0.0815 |
| Chengzhou | 0.0415 | 0.1084 | 0.0445 | 0.0946 | 0.0431 | 0.0562 |
| Yongzhou | 0.1028 | 0.1011 | 0.0927 | 0.1012 | 0.1028 | 0.0597 |
| Shaoyang | 0.0937 | 0.0445 | 0.0836 | 0.0438 | 0.1017 | 0.2018 |
| Zhangjiajie | 0.0413 | 0.0618 | 0.0416 | 0.0601 | 0.0236 | 0.1369 |
| Huaihua | 0.0628 | 0.0623 | 0.0459 | 0.0583 | 0.0945 | 0.0364 |
| Loudi | 0.0543 | 0.0317 | 0.0613 | 0.0319 | 0.0675 | 0.1251 |
| Xiangxi | 0.0283 | 0.0563 | 0.0327 | 0.0462 | 0.0346 | 0.0912 |
| Yueyang | 0.0276 | 0.0414 | 0.0543 | 0.0405 | 0.0651 | 0.0348 |
| Changde | 0.0348 | 0.0357 | 0.0412 | 0.0358 | 0.0328 | 0.0406 |
| Yiyang | 0.0269 | 0.0346 | 0.0365 | 0.0393 | 0.0308 | 0.0513 |
| City | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
| Changsha | 0.1121 | 0.1427 | 0.1136 | 0.1145 | 0.1495 | 0.1342 |
| Zhuzhou | 0.0638 | 0.0516 | 0.0594 | 0.0463 | 0.0612 | 0.0683 |
| Xiangtan | 0.1527 | 0.1359 | 0.1238 | 0.1258 | 0.1283 | 0.1632 |
| Hengyang | 0.0465 | 0.0453 | 0.0354 | 0.0427 | 0.0435 | 0.0438 |
| Chengzhou | 0.0563 | 0.0672 | 0.0541 | 0.0604 | 0.0763 | 0.0945 |
| Yongzhou | 0.3042 | 0.3359 | 0.3721 | 0.3924 | 0.3653 | 0.4231 |
| Shaoyang | 0.1839 | 0.2146 | 0.2263 | 0.2335 | 0.2352 | 0.3046 |
| Zhangjiajie | 0.0756 | 0.1017 | 0.0885 | 0.0948 | 0.1174 | 0.1186 |
| Huaihua | 0.2324 | 0.2641 | 0.2462 | 0.2126 | 0.2165 | 0.3672 |
| Loudi | 0.1435 | 0.1829 | 0.2063 | 0.2634 | 0.2732 | 0.3164 |
| Xiangxi | 0.0469 | 0.0462 | 0.0346 | 0.0351 | 0.0516 | 0.0469 |
| Yueyang | 0.0512 | 0.0462 | 0.0431 | 0.0384 | 0.0358 | 0.0385 |
| Changde | 0.0465 | 0.0551 | 0.0495 | 0.0842 | 0.0842 | 0.0614 |
| Yiyang | 0.0515 | 0.0576 | 0.0534 | 0.0426 | 0.0316 | 0.1208 |
Benchmark regression
| Variable | Model (1) | Model (2) | Model (3) | Model (4) | Model (5) |
|---|---|---|---|---|---|
| VEDL | 0.315*** |
0.302*** |
0.289*** |
0.264*** |
0.227** |
| Net | - | 0.245*** |
0.237*** |
0.226*** |
0.208*** |
| Cul | - | - | 0.078** |
0.067** |
0.062** |
| Med | - | - | - | 1.249*** |
1.109*** |
| ER | - | - | - | - | 4.124 |
| (Con_) | 0.084*** |
0.073*** |
0.072*** |
0.071*** |
-0.081** |
| Individual effect | YES | YES | YES | YES | YES |
| Time effect | YES | YES | YES | YES | YES |
| R square | 0.6845 | 0.6861 | 0.6924 | 0.7059 | 0.7306 |
Regional economic development level evaluation system
| Primary Index | Secondary Index | Code |
|---|---|---|
| Innovative development | GDP growth rate | ID1 |
| R&d intensity | ID2 | |
| Investment efficiency | ID3 | |
| Technical activity | ID4 | |
| Coordination development | Demand structure | CD1 |
| Urban and rural structure | CD2 | |
| Industrial structure | CD3 | |
| Government debt | CD4 | |
| Green development | Energy consumption elasticity | GD1 |
| Unit output waste water | GD2 | |
| Unit output waste gas | GD3 | |
| Openness development | Foreign trade dependency | OD1 |
| Investment proportion of foreign investment | OD2 | |
| Market degree | OD3 | |
| Sharing development | Proportion of worker’s remuneration | SD1 |
| Income growth elasticity of residents | SD2 | |
| The urban and rural consumption gap | SD3 | |
| The proportion of people’s financial spending | SD4 |
Coupling Coordination Level Classification
| Dissonance decay | Coordinated development | ||
|---|---|---|---|
| D | Type | D | Type |
| 0.00~0.10 | Extreme dissonance decay | 0.51~0.60 | Reluctance coordinated development |
| 0.11~0.20 | Severity dissonance decay | 0.61~0.70 | Primary coordinated development |
| 0.21~0.30 | Medium dissonance decay | 0.71~0.80 | Medium coordinated development |
| 0.31~0.40 | Light dissonance decay | 0.81~0.90 | Benign coordinated development |
| 0.41~0.50 | Verge dissonance decay | 0.91~1.00 | Quality coordinated development |
The benchmark regression results of the partition domain
| Variable | Model (1) | Model (2) | Model (3) | Model (4) |
|---|---|---|---|---|
| VEDL | 0.186***(3.154) | 0.075***(4.572) | 0.036(0.312) | 0.137(0.854) |
| Net | 0.153***(3.725) | 0.081***(3.162) | 0.025(0.818) | 0.045(0.729) |
| Cul | 0.015**(0.037) | 0.074**(1.253) | 0.043(1.107) | 0.551**(2.427) |
| Med | 0.131***(1.429) | 0.025***(1.248) | 0.093**(2.317) | 0.261**(2.515) |
| ER | 0.169(4.345) | 0.038(0.924) | 0.005(0.154) | 0.023(0.167) |
| (Con_) | 0.424***(7.126) | -0.008 (-0.259) | 0.031(1.469) | -0.057(-0.426) |
| Individual effect | YES | YES | YES | YES |
| Time effect | YES | YES | YES | YES |
| R square | 0.8465 | 0.8213 | 0.8024 | 0.8158 |
Regional economic development level of Hunan province
| City | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 |
|---|---|---|---|---|---|---|
| Changsha | 0.3924 | 0.4015 | 0.4432 | 0.4638 | 0.4801 | 0.4923 |
| Zhuzhou | 0.1665 | 0.1821 | 0.3024 | 0.1334 | 0.1912 | 0.2325 |
| Xiangtan | 0.1485 | 0.1583 | 0.1549 | 0.2062 | 0.1874 | 0.1964 |
| Hengyang | 0.1169 | 0.1665 | 0.1942 | 0.2126 | 0.2189 | 0.2237 |
| Chengzhou | 0.1234 | 0.1667 | 0.1789 | 0.1994 | 0.2045 | 0.2132 |
| Yongzhou | 0.1345 | 0.1388 | 0.1762 | 0.1753 | 0.1806 | 0.1942 |
| Shaoyang | 0.1451 | 0.1604 | 0.1789 | 0.1724 | 0.1965 | 0.2013 |
| Zhangjiajie | 0.1931 | 0.1785 | 0.2011 | 0.2248 | 0.2185 | 0.2232 |
| Huaihua | 0.1651 | 0.2012 | 0.2073 | 0.2284 | 0.2251 | 0.2407 |
| Loudi | 0.1785 | 0.1951 | 0.1614 | 0.2054 | 0.1891 | 0.1782 |
| Xiangxi | 0.1562 | 0.1648 | 0.1606 | 0.1714 | 0.1769 | 0.1851 |
| Yueyang | 0.1711 | 0.1764 | 0.1826 | 0.2185 | 0.1994 | 0.2095 |
| Changde | 0.1624 | 0.1826 | 0.1803 | 0.2014 | 0.2036 | 0.2152 |
| Yiyang | 0.1704 | 0.1775 | 0.1821 | 0.1954 | 0.1785 | 0.1938 |
| City | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
| Changsha | 0.5165 | 0.5628 | 0.5732 | 0.6315 | 0.6824 | 0.7735 |
| Zhuzhou | 0.2468 | 0.2569 | 0.2683 | 0.3134 | 0.3162 | 0.3389 |
| Xiangtan | 0.2016 | 0.2169 | 0.2243 | 0.2468 | 0.2531 | 0.2659 |
| Hengyang | 0.2415 | 0.2608 | 0.2536 | 0.2913 | 0.2874 | 0.3365 |
| Chengzhou | 0.2435 | 0.2565 | 0.2443 | 0.2672 | 0.3048 | 0.3121 |
| Yongzhou | 0.2126 | 0.2238 | 0.2287 | 0.2386 | 0.2751 | 0.2795 |
| Shaoyang | 0.2153 | 0.2243 | 0.2089 | 0.2415 | 0.2854 | 0.2769 |
| Zhangjiajie | 0.2254 | 0.2306 | 0.2234 | 0.2418 | 0.2459 | 0.2342 |
| Huaihua | 0.2335 | 0.2415 | 0.2342 | 0.2685 | 0.2812 | 0.2836 |
| Loudi | 0.1465 | 0.2489 | 0.1942 | 0.2188 | 0.2375 | 0.2354 |
| Xiangxi | 0.1846 | 0.1905 | 0.1959 | 0.2043 | 0.2058 | 0.2169 |
| Yueyang | 0.2184 | 0.2093 | 0.1945 | 0.2214 | 0.2325 | 0.2682 |
| Changde | 0.2413 | 0.2453 | 0.2236 | 0.2683 | 0.2694 | 0.2751 |
| Yiyang | 0.1952 | 0.2214 | 0.1816 | 0.2124 | 0.2032 | 0.2056 |
Intergroup differences of coupling coordination
| Year | CZT-XN | CZT-XX | CZT-DTH | XN-XX | XN-DTH | XX-DTH |
|---|---|---|---|---|---|---|
| 2012 | 0.1681 | 0.2694 | 0.1406 | 0.1679 | 0.0742 | 0.1865 |
| 2013 | 0.1745 | 0.2725 | 0.1418 | 0.1715 | 0.0801 | 0.1943 |
| 2014 | 0.1738 | 0.2731 | 0.1422 | 0.1665 | 0.0804 | 0.1924 |
| 2015 | 0.1651 | 0.2624 | 0.1342 | 0.1689 | 0.0815 | 0.1915 |
| 2016 | 0.1616 | 0.2695 | 0.1398 | 0.1782 | 0.0821 | 0.1945 |
| 2017 | 0.1638 | 0.2675 | 0.1412 | 0.1721 | 0.0789 | 0.1884 |
| 2018 | 0.1642 | 0.2654 | 0.1485 | 0.1745 | 0.0775 | 0.1793 |
| 2019 | 0.1694 | 0.2649 | 0.1579 | 0.1673 | 0.0752 | 0.1684 |
| 2020 | 0.1685 | 0.2721 | 0.1609 | 0.1741 | 0.0719 | 0.1725 |
| 2021 | 0.1682 | 0.2678 | 0.1663 | 0.1724 | 0.0743 | 0.1625 |
| 2022 | 0.1645 | 0.2654 | 0.1635 | 0.1712 | 0.0711 | 0.1614 |
| 2023 | 0.1581 | 0.2613 | 0.1669 | 0.1693 | 0.0706 | 0.1532 |
Coupling and coordination of two systems
| Changzhutan | Xiangnan | |||
|---|---|---|---|---|
| Year | D | Relation | D | Relation |
| 2012 | 0.2203 | Medium dissonance decay | 0.2089 | Medium dissonance decay |
| 2013 | 0.2255 | Medium dissonance decay | 0.2403 | Medium dissonance decay |
| 2014 | 0.2378 | Medium dissonance decay | 0.2284 | Medium dissonance decay |
| 2015 | 0.2281 | Medium dissonance decay | 0.2504 | Medium dissonance decay |
| 2016 | 0.2543 | Medium dissonance decay | 0.2367 | Medium dissonance decay |
| 2017 | 0.2646 | Medium dissonance decay | 0.2425 | Medium dissonance decay |
| 2018 | 0.3063 | Medium dissonance decay | 0.2980 | Medium dissonance decay |
| 2019 | 0.3123 | Light dissonance decay | 0.3100 | Light dissonance decay |
| 2020 | 0.3062 | Medium dissonance decay | 0.3107 | Light dissonance decay |
| 2021 | 0.3121 | Light dissonance decay | 0.3236 | Light dissonance decay |
| 2022 | 0.3295 | Light dissonance decay | 0.3288 | Light dissonance decay |
| 2023 | 0.3440 | Light dissonance decay | 0.3469 | Light dissonance decay |
| Year | Xiangxi | Dongtinghu | ||
| D | Relation | D | Relation | |
| 2012 | 0.2202 | Medium dissonance decay | 0.1880 | Severity dissonance decay |
| 2013 | 0.2192 | Medium dissonance decay | 0.2020 | Medium dissonance decay |
| 2014 | 0.2216 | Medium dissonance decay | 0.2114 | Medium dissonance decay |
| 2015 | 0.2215 | Medium dissonance decay | 0.2108 | Medium dissonance decay |
| 2016 | 0.2386 | Medium dissonance decay | 0.2135 | Medium dissonance decay |
| 2017 | 0.2793 | Medium dissonance decay | 0.2160 | Medium dissonance decay |
| 2018 | 0.2879 | Medium dissonance decay | 0.2282 | Medium dissonance decay |
| 2019 | 0.3097 | Medium dissonance decay | 0.2337 | Medium dissonance decay |
| 2020 | 0.3034 | Medium dissonance decay | 0.2221 | Medium dissonance decay |
| 2021 | 0.3151 | Light dissonance decay | 0.2382 | Medium dissonance decay |
| 2022 | 0.3255 | Light dissonance decay | 0.2334 | Medium dissonance decay |
| 2023 | 0.3463 | Light dissonance decay | 0.2603 | Medium dissonance decay |
Professional education development level evaluation index system
| Primary Index | Secondary Index | Code |
|---|---|---|
| Education guarantee | Funding input | JY1 |
| Teacher construction | JY2 | |
| Teaching condition | JY3 | |
| Culture quality | Promotion level | PY1 |
| Employment level | PY2 | |
| Student comprehensive quality | PY3 | |
| Education scale | PY4 | |
| Social achievement | Graduate evaluation | SH1 |
| Enterprise evaluation | SH2 | |
| Service area industry capacity | SH3 |
Robustness test results
| Variable | Model (1) | Model (2) | Model (3) |
|---|---|---|---|
| VEDL | 0.182***(2.467) | 0.051***(1.573) | 0.124***(2.085) |
| Net | 0.314***(2.672) | 0.074***(1.516) | 0.085***(1.672) |
| Cul | 0.085**(2.538) | 0.079**(2.427) | 0.088**(2.469) |
| Med | 1.248***(3.569) | 1.159***(3.208) | 1.171***(3.423) |
| ER | 3.586 (1.642) | 3.271 (1.353) | 3.329 (1.427) |
| (Con_) | 0.174***(3.156) | 0.169***(3.048) | 0.165***(3.012) |
| Individual effect | YES | YES | YES |
| Time effect | YES | YES | YES |
| R square | 0.4271 | 0.6859 | 0.4063 |
