A Dynamic DEA Model for Evaluating the Efficiency of Cultural Industry Development
Pages 164 - 168
Abstract
The development efficiency of regional cultural industry is the result of multiple factors. Based on the actual characteristics of China's cultural industry input and output, this paper uses the dynamic DEA model to establish a cultural industry efficiency evaluation model, and analyzes the cultural industry input and output efficiency of 31 provinces (autonomous regions) in 2013-2015. Taking Shaanxi Province as an example, this paper uses dynamic DEA model to analyze the development efficiency of Shaanxi cultural industry. The results show that technological progress and technological efficiency change contribute to the overall development efficiency of the industry, especially the driving effect of the emerging cultural industry is obvious. However, the resources of historical relics are more redundant and the level of development needs to be improved. Finally, the comprehensive evaluation results and the actual problems, put forward to enhance the level of cultural industry development policy recommendations.
References
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Qian Zhao, Xiuyun Yang, and Yuan Lei, etal. 2015. Technical efficiency of cultural and creative industries in China: industry differences and influencing factors J.Exploration of economic issues, Res.11(Nov.2015), 88--97.
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Yang Zhao.andJian Wei. 2015.Research on the Technical Efficiency of Regional Cultural Industry in China: Based on the Random Frontier Analysis Model.J. Research on Financial Issues.Res.1 (Jan.2015), 30--36.
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Index Terms
- A Dynamic DEA Model for Evaluating the Efficiency of Cultural Industry Development
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Published In
January 2019
292 pages
ISBN:9781450361897
DOI:10.1145/3312662
Copyright © 2019 ACM.
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- China University of Geosciences
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 12 January 2019
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- Refereed limited
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ICMSS 2019
ICMSS 2019: 2019 3rd International Conference on Management Engineering, Software Engineering and Service Sciences
January 12 - 14, 2019
Wuhan, China
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