Abstract
Based on the scale, distribution, and structure of scientific and technological resource allocation, the basic characteristics of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang were analyzed, and the relevant panel data of the three places and the whole region were analyzed using the data envelopment analysis (DEA)-Malmquist index model, spanning the period of 2010–2019. The results show that the overall efficiency of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang shows an upward trend during the study period, which is attributed to the significant increase in the rate of technological progress. The rapid growth in Chongqing and Mianyang is attributed to good policy support, rapid renewal of facilities and institutions, and improved management experience. The relative slowdown in the rate of technological progress in Chengdu may be due to industrial restructuring, coupled with a shift in economic technology from high growth to high quality development. At the same time, Chengdu–Chongqing–Mianyang region is more inclined to cultivate its own R&D capabilities, and the accumulation and upgrading of innovation management technologies are insufficient to meet its innovation needs. Finally, the study proposes countermeasures to improve the efficiency of science and technology resource allocation in Chengdu–Chongqing–Mianyang from macro and micro perspectives.
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Acknowledgements
This research was funded by the Major Project of Sichuan Philosophy and Social Science Planning Research (Grant No. SC21ZDZT010), Major Project of Sichuan Philosophy and Social Science Planning Project (Grant No. SC20ZDCY001), China’s Post-doctoral Science Fund Project (Grant No. 2018M631069), Opening Project of Think Tank on Ecological Barrier Construction of Upper Yangtze River and Yellow River in Sichuan Province (Grant No. 202207), General Project of Research Center for Science and Technology Innovation and New Economy in Chengdu-Chongqing Economic Circle (Grant No.CYCX2021YB08), Key and General Project of Mineral Resources Research Center in Sichuan Province (Grant Nos. SCKCZY2021-ZD002 and SCKCZY2022-YB004) and Key Project of Sichuan Leisure Sports Industry Development and Research Center (Grant No. XXTYCY2021A01). We also acknowledge support from the Key Project of Chengdu Water Ecological Civilization Construction Research Key Base (Grant No. SST2021-2022-03), Key Project of Chengdu Park City Demonstration Zone Construction Research Center (Grant No. GYCS2021-ZD001), General Project of Sichuan Disaster Economy Research Center (Grant No. ZHJJ2021-YB001) and National Park Research Center Project of Sichuan Province Social Science Key Research Base (Extension) (Grant No. GJGY2020-ZD001).
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Appendix 1: Table 1 Changes in the allocation efficiency of science and technology resources in the CYM region
Appendix 1: Table 1 Changes in the allocation efficiency of science and technology resources in the CYM region
Year | Decision unit | Technical efficiency | Technological progress rate | Pure technical efficiency | Scale efficiency | Return to scale | TFP | |||
|---|---|---|---|---|---|---|---|---|---|---|
Effch | Growth rate (%) | Techch | Growth rate (%) | Pech | Sech | Tfpch | Growth rate (%) | |||
2010–2011 | Chengdu | 1.000 | 0.0 | 2.392 | 139.2 | 1.000 | 1.000 | Constant | 2.392 | 139.2 |
Chongqing | 1.000 | 0.0 | 0.850 | − 15.0 | 1.000 | 1.000 | Constant | 0.850 | − 15 | |
Mianyang | 0.945 | − 5.5 | 2.407 | 140.7 | 1.000 | 0.945 | Reduce | 2.275 | 127.5 | |
CYM | 0.949 | − 5.1 | 1.457 | 15.7 | 1.000 | 0.949 | Reduce | 1.382 | 38.2 | |
2011–2012 | Chengdu | 1.000 | 0.0 | 1.046 | 4.6 | 1.000 | 1.000 | Constant | 1.046 | 4.6 |
Chongqing | 1.000 | 0.0 | 1.548 | 54.8 | 1.000 | 1.000 | Constant | 1.548 | 54.8 | |
Mianyang | 0.522 | − 47.8 | 1.087 | 8.7 | 1.000 | 0.522 | Reduce | 0.567 | − 43.3 | |
CYM | 0.839 | 16.1 | 1.171 | 17.1 | 1.000 | 0.839 | Reduce | 0.983 | − 1.7 | |
2012–2013 | Chengdu | 1.000 | 0.0 | 1.238 | 23.8 | 1.000 | 1.000 | Constant | 1.238 | 23.8 |
Chongqing | 0.986 | − 1.4 | 0.578 | − 42.2 | 1.000 | 0.986 | Reduce | 0.570 | − 43.0 | |
Mianyang | 2.299 | 129.9 | 0.983 | − 1.7 | 1.000 | 2.299 | Increase | 2.259 | 125.9 | |
CYM | 1.182 | 18.2 | 0.829 | − 17.1 | 1.000 | 1.182 | Increase | 0.980 | − 2.0 | |
2013–2014 | Chengdu | 1.000 | 0.0 | 0.328 | − 67.2 | 1.000 | 1.000 | Constant | 0.328 | − 67.2 |
Chongqing | 1.015 | 1.5 | 1.450 | 45.0 | 1.000 | 1.015 | Increase | 1.472 | 47.2 | |
Mianyang | 3.764 | 276.4 | 0.254 | − 74.6 | 1.000 | 3.764 | Increase | 0.955 | − 4.5 | |
CYM | 1.154 | 15.4 | 0.658 | − 34.2 | 1.000 | 1.154 | Increase | 0.759 | − 24.1 | |
2014–2015 | Chengdu | 1.000 | 0.0 | 2.041 | 104.1 | 1.000 | 1.000 | Constant | 2.041 | 104.1 |
Chongqing | 1.000 | 0.0 | 1.739 | 73.9 | 1.000 | 1.000 | Constant | 1.739 | 73.9 | |
Mianyang | 0.271 | − 72.9 | 7.868 | 686.8 | 1.000 | 0.271 | Reduce | 2.133 | 113.3 | |
CYM | 0.865 | − 13.5 | 3.226 | 222.6 | 1.000 | 0.865 | Reduce | 2.790 | 179.0 | |
2015–2016 | Chengdu | 1.000 | 0.0 | 0.342 | − 65.8 | 1.000 | 1.000 | Constant | 0.342 | − 65.8 |
Chongqing | 1.000 | 0.0 | 0.540 | 46.0 | 1.000 | 1.000 | Constant | 0.540 | − 46.0 | |
Mianyang | 0.699 | − 30.1 | 0.724 | − 27.6 | 0.993 | 0.704 | Reduce | 0.506 | − 49.4 | |
CYM | 0.884 | − 11.6 | 0.515 | − 48.5 | 1.000 | 0.884 | Reduce | 0.455 | − 54.5 | |
2016–2017 | Chengdu | 1.000 | 0.0 | 1.027 | 2.7 | 1.000 | 1.000 | Constant | 1.027 | 2.7 |
Chongqing | 1.000 | 0.0 | 0.692 | − 30.8 | 1.000 | 1.000 | Constant | 0.692 | − 30.8 | |
Mianyang | 1.054 | 5.4 | 1.003 | 0.3 | 0.950 | 1.109 | Increase | 1.057 | 5.7 | |
CYM | 0.985 | − 1.5 | 0.954 | − 4.6 | 1.000 | 0.985 | Reduce | 0.940 | − 6.0 | |
2017–2018 | Chengdu | 1.000 | 0.0 | 1.382 | 38.2 | 1.000 | 1.000 | Constant | 1.382 | 38.2 |
Chongqing | 1.000 | 0.0 | 1.320 | 32.0 | 1.000 | 1.000 | Constant | 1.320 | 32.0 | |
Mianyang | 1.010 | 1.0 | 1.078 | 7.8 | 0.990 | 1.020 | Increase | 1.089 | 8.9 | |
CYM | 0.992 | − 0.8 | 1.235 | 23.5 | 1.000 | 0.992 | Reduce | 1.225 | 22.5 | |
2018–2019 | Chengdu | 1.000 | 0.0 | 0.895 | − 10.5 | 1.000 | 1.000 | Constant | 0.895 | − 10.5 |
Chongqing | 1.000 | 0.0 | 1.255 | 25.5 | 1.000 | 1.000 | Constant | 1.255 | 25.5 | |
Mianyang | 0.994 | − 0.6 | 1.058 | 5.8 | 0.922 | 1.078 | Increase | 1.052 | 5.2 | |
CYM | 0.984 | − 1.6 | 1.066 | 6.6 | 1.000 | 0.984 | Increase | 1.049 | 4.9 | |
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Li, R., Luo, Y., Chen, B. et al. Efficiency of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang Urban agglomeration: based on DEA–Malmquist index model. Environ Dev Sustain 26, 10461–10483 (2024). https://doi.org/10.1007/s10668-023-03153-9
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DOI: https://doi.org/10.1007/s10668-023-03153-9