Abstract
Improving regional innovation efficiency is the key to developing an innovative country. Exploring the spatio-temporal evolution characteristics of regional innovation efficiency is crucial in the formulation of regional policies and the choice of innovation models. This study used the superdata envelopment analysis method with undesirable outputs in evaluating the innovation efficiency of Chinese provinces. To assess the spatial spillover effects of innovation factors, the spatial autocorrelation and spatial Durbin model were adopted to characterize the spatio-temporal evolution, spatial correlation, and mechanisms of innovation efficiency. The highlights of the results are as follows: (1) The time-series changes in innovation efficiency showed a general trend from declining to increasing. (2) There were pronounced regional differences in innovation efficiency. The innovation efficiencies at the provincial level evolved from being decentralized to concentrated. The innovation efficiency was relatively stable in the eastern region and increased significantly in the central and western regions. The east–center–west evolution pattern gradually weakened. (3) The innovative efficiency exhibited spatial dependence, and the spatial agglomeration continued to increase. The extent of hot spots expanded, while cold spots shrunk slightly. (4) The scientific research environment, entrepreneurial environment, labor quality, and market environment were the essential elements that improved innovation efficiency. The impact of the different factors on innovation efficiency at different periods exhibited significant spatial heterogeneity.
Highlights
Innovation can reinforce the dominance of developed economies and further increase inequalities between regions or countries [1]; this is a way to promote the efficient output of production resources, which can improve the quality of the ecological environment, that is, the driving force for sustainable economic and social development [2]
Is made up of 50 decision-making units (DMUs) (17.92%), operating on the production frontier, while the maximum value of bias-corrected efficiency scores is 0.8904, indicating that there is no efficient area in our sample after correcting for bias
The results suggest that the financial environment negatively affected innovation efficiency in 2010 and 2018 while having a positive impact in 2014
Summary
Innovation can reinforce the dominance of developed economies and further increase inequalities between regions or countries [1]; this is a way to promote the efficient output of production resources, which can improve the quality of the ecological environment, that is, the driving force for sustainable economic and social development [2]. Innovation efficiency is an indicator that characterizes the input–output relationship of innovation resources. China has emphasized the key role of technological innovation in socio-economic transformation development, leading to regional heterogeneity in innovation development [3]. Understanding the regional heterogeneity in China’s innovation efficiency can help decision makers improve policies and strategies to make the country more innovative and globally competitive. One crucial indicator of innovation is innovation efficiency, used to measure the input–. Numerous studies on innovation efficiency have been conducted in terms of content, scale, and methods, in particular, on evaluating
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