Abstract
An efficiency evaluation of China’s regional sustainable innovation, evaluating industrial waste and total energy consumption, is the main research subject in this paper. It focuses on a regional measurement and comparison of these undesirable outputs of Chinese firm activities, such as industrial SO2 and CO2 emissions. By applying a data envelopment analysis–slack-based measure (DEA–SBM) model with undesirable outputs indicators, the regional innovation efficiency was evaluated for 30 provinces in China, from 2002 to 2014. The results indicate that the sustainable innovation efficiency of overall China is still relatively low, and varies significantly in different regions. Central and Western China have similar sustainable innovation efficiencies, which are much lower than the sustainable innovation efficiency in Eastern China. Furthermore, the data indicate that regional sustainable innovation efficiency disparities among these three areas are decreasing. Based on these findings, reasons for the sustainable innovation efficiency gap among the different regions were analyzed. To scholars, this paper extends the research on regional sustainable innovation efficiency by implementing an undesirable output perspective to the DEA–SBM model. The findings also provide Chinese policy makers with useful decision support insights for regional sustainable innovation, and energy conservation and emission reduction policies.
Highlights
A country’s technological innovation activities always have obvious regional characteristics [1,2,3,4], and the efficiency of regional innovation can differ among regions [5,6,7,8]
By evaluating the regional sustainable innovation efficiency of 30 provinces in China from 2002 to 2014, using the slack-based measure (SBM) model, this study focuses on the following research question: what are the differences between sustainable innovation efficiencies of different regions in China and which trends in these differences can be estimated?
Within a set of comparable decision-making units (DMUs), data envelopment analysis (DEA) provides an ordinal ranking of relative efficiency, and identifies the best practices leading to the identification of an efficient frontier, which means more output cannot be obtained by increasing input
Summary
A country’s technological innovation activities always have obvious regional characteristics [1,2,3,4], and the efficiency of regional innovation can differ among regions [5,6,7,8]. The evaluation of sustainable innovation efficiency, especially in China, with its large population of 1395 million inhabitants, and large industrial activity, counting up to a yearly gross domestic product (GDP) of 90,030.9 trillion Yuan (which equals 13.605 trillion dollars) in 2018 [11], is an important topic. Insights coming from such evaluations can help to define policy and institutional actions to improve China’s environmentally sustainable innovation and production. By evaluating the regional sustainable innovation efficiency of 30 provinces in China from 2002 to 2014, using the slack-based measure (SBM) model, this study focuses on the following research question: what are the differences between sustainable innovation efficiencies of different regions in China and which trends in these differences can be estimated?
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