
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>Coupling and Coordination Relationship between Economic and Ecologic-Environmental Developments in China’s Key State-Owned Forest Areas
doi: 10.3390/su142315899
China’s key state-owned forest areas are important ecological conservation areas and its forest management belongs to several forest industry groups. Therefore, the ecological improvement and economic development of the key state-owned forest areas should be balanced. This study developed an integrated evaluation model of coupling and coordination, by employing the data of the key forest areas from 2001 to 2019, to investigate the coupling and coordination relationship between the efficiency of economic development and the level of ecological development, using the DEA model. The results suggest that the indices of ecological development in the key state-owned forest areas increased from 2001 to 2019, and especially in 2015, to a better status, due to the policy of completely stopping logging. The other finding was that the coupling degree between the efficiency of economic development and the level of ecological development was in an antagonistic stage, which showed a slow upward trend of the coupling degree and coupling coordination degree and then evolved to a medium and high coordination coupling situation. The reason was that, with the implementation of the ecological protection policy and the industrial transformation of the forest industry group, the ecological environment improved and the development of enterprises was further optimized. Moreover, this study further identified the main factors that affect the coupling and coordination degree of the key state-owned forest areas, including the proportion of tertiary industry, economic growth rate, forest park area, and investment in wildlife and plant protection and natural resource conservation areas. The factors were divided into three principal components. The most significant impact on the economic and ecological coupling coordination of the key state-owned forest areas was the first principal component, meaning that ecological improvement was the most important factor. The second principal component was mainly social coupling coordination, while the third principal component had little effect on economic and ecological coupling coordination.
- Beijing Normal University China (People's Republic of)
- BEIJING NORMAL UNIVERSITY China (People's Republic of)
- Beijing Normal University China (People's Republic of)
- BEIJING NORMAL UNIVERSITY China (People's Republic of)
- Neijiang Normal University China (People's Republic of)
Environmental effects of industries and plants, entropy weight method, TJ807-830, entropy weight method; principal components analysis; ecological environment; economic development, TD194-195, economic development, ecological environment, Renewable energy sources, Environmental sciences, principal components analysis, GE1-350
Environmental effects of industries and plants, entropy weight method, TJ807-830, entropy weight method; principal components analysis; ecological environment; economic development, TD194-195, economic development, ecological environment, Renewable energy sources, Environmental sciences, principal components analysis, GE1-350
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).9 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
