School of Public Policy and Administration, Nanchang University, Nanchang City, Jiangxi, China.
PLoS One. 2022 Sep 29;17(9):e0274875. doi: 10.1371/journal.pone.0274875. eCollection 2022.
Green innovation has become the goal for promoting the transformation and upgrading heavy pollution industries in the context of high-quality development, and the key factor for the success of green innovation is increasing the green innovation efficiency of heavy pollution industries. To understand the current situation of China's industrial innovation and get out of the dilemma, we use non-expected Slacks-based model (SBM) to measure green innovation efficiency in Chinese industry, Lasso regression to screen the influencing factors of heavy pollution industries, tobit regression to study the influence degree and direction of different influencing factors on green innovation efficiency of heavy pollution industry. The results show that: (1) The green innovation efficiency of the 16 heavily polluting industries studied in this paper is generally low; (2) Coordination, green and openness all have a positive impact on the green innovation efficiency of the industry. (3) A certain degree of government scientific research support is conducive to improving the efficiency of industrial green innovation and exceeding the limit will have a restraining effect on enterprise innovation. According to the results, we put forward the corresponding policy implications.
绿色创新已成为推动高发展质量背景下重污染产业转型升级的目标,而绿色创新成功的关键因素是提高重污染产业的绿色创新效率。为了了解中国工业创新的现状并摆脱困境,我们使用非期望的基于 Slacks 的模型(SBM)来衡量中国工业的绿色创新效率,使用套索回归筛选重污染产业的影响因素,使用 Tobit 回归研究不同影响因素对重污染产业绿色创新效率的影响程度和方向。结果表明:(1)本文研究的 16 个重污染行业的绿色创新效率普遍较低;(2)协调、绿色和开放度都对产业的绿色创新效率有正向影响。(3)一定程度的政府科研支持有利于提高产业绿色创新效率,超过限制将对企业创新产生抑制作用。根据结果,我们提出了相应的政策含义。