Nanyang Institute of Technology, Fanli Business School, Nanyang 473000, China.
Institute of Central China Development, Wuhan University, Wuhan 430072, China.
Int J Environ Res Public Health. 2022 May 16;19(10):6054. doi: 10.3390/ijerph19106054.
Under the background of tightening resource constraints and a deteriorating ecological environment, innovation is aimed at saving energy, reducing consumption, abating pollution and achieving sustainable economic growth. This has gradually become an important way to improve industrial structure, competitiveness and environmental performance worldwide. In this study, we use the super-efficiency SBM model to calculate the innovation efficiency of 283 cities in China from 2009 to 2019. Then, based on the dynamic threshold regression model, we explore the impact of innovation efficiency on ecological footprint in innovative cities or non-innovative cities under different economic development levels. The main conclusions that can be drawn are as follows. (1) Within the research period, the influence of innovation efficiency on ecological footprint in China shows a negative double threshold feature, that is, increasing regional innovation efficiency has an inhibitory effect on ecological footprint. (2) For innovative cities, innovation efficiency has a strong inhibitory effect on ecological footprint, and it becomes stronger and stronger with the growth of night light data; but this inhibitory effect is gradually decreasing with improvement of economic development level in non-innovative cities. (3) Under the threshold of different levels of economic development, the number of scientific human resources, scientific financial resources, scientific information resources and scientific papers has a positive effect on ecological footprint, while the number of patent applications has a negative effect on ecological footprint.
在资源约束趋紧、生态环境恶化的背景下，创新旨在节约能源、减少消耗、减轻污染，实现经济的可持续增长。这逐渐成为全球范围内改善产业结构、竞争力和环境绩效的重要途径。在本研究中，我们使用超效率 SBM 模型来计算 2009 年至 2019 年中国 283 个城市的创新效率。然后，基于动态门槛回归模型，我们探讨了创新效率对创新城市或不同经济发展水平的非创新城市的生态足迹的影响。主要结论如下。（1）在研究期间，创新效率对中国生态足迹的影响呈现出负的双重门槛特征，即增加区域创新效率对生态足迹具有抑制作用。（2）对于创新城市，创新效率对生态足迹具有很强的抑制作用，并且随着夜光数据的增长而变得越来越强；但在非创新城市中，随着经济发展水平的提高，这种抑制作用逐渐减弱。（3）在不同经济发展水平的门槛下，科学人力资源、科学财力、科学信息资源和科学论文数量对生态足迹有正向影响，而专利申请数量对生态足迹有负向影响。
