Research on the Differences of Ecological Efficiency of Low-carbon M&A among Enterprises under the Education of Ecological Civilization
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Man-Wen Tian 1, Shu-Rong Yan 2 * , Hui Peng 3
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1 School of Business, Lishui University, Lishui, Zhejiang, China2 College of medicine and health, Lishui University, Lishui, Zhejiang, China3 School of Economics and Management, Shenyang ligong University, Shenyang, China* Corresponding Author

Abstract

Environmental education has a substantial impact on the behavior and performance of mergers and acquisitions. Low-carbon M&A is a new mode of mergers and acquisitions under the education of ecological civilization. This paper first analyses the improvement of ecological efficiency of low-carbon M&A in different regions and industries in China, but there are significant differences in the improvement of environmental efficiency in different regions and industries. The higher efficiency industries are mainly distributed in the capital-intensive industries, followed by labor-intensive industries, while the resource intensive industries are the lowest. The cleaner production industries are significantly higher than the pollution intensive industries. The main reason is that there are significant industrial differences in environmental education, energy structure and low-carbon technology. Regional environmental efficiency is higher in the Yangtze River Delta, followed by the Pearl River Delta, the Circum-Bohai-Sea Region, the worst. The main reason is that there are regional differences in environmental education investment, resource endowment, government intervention, marketization level, environmental policy and ecological civilization education system. Increasing investment in environmental education is one of the key means of improving ecological performance.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, 2017, Volume 13, Issue 8, 5233-5245

https://doi.org/10.12973/eurasia.2017.00997a

Publication date: 16 Aug 2017

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