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Research Article | Open Access

Research on the efficiency of agro-tourism integration in China: Based on the DEA cross-efficiency model

Huajin LiSongbiao ZhangYue DengHuilin Wang( )
Hunan Institute of Innovation and Development, Hunan University of Science and Technology, Xiangtan 411201, China
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Abstract

The efficiency of agro-tourism integration has become an important research object in evaluating agricultural efficiency. However, traditional efficiency evaluation theories and methods assume that all decision-making units are independent of each other and cannot effectively deal with the complex relationship between agriculture and tourism development. Based on the cooperative relationship between agriculture and tourism, this study constructed a data envelopment analysis (DEA) model based on cross-efficiency. It used ten input variables and six output variables from the agricultural and tourism systems to analyze the efficiency of agro-tourism integration in 31 provinces in mainland China from 2010 to 2019. The research results show that the efficiency of agro-tourism integration in China is relatively high and tourism significantly promotes agriculture. Still, the promotion efficiency of agriculture on tourism is low and the integration efficiency of agriculture and tourism in different provinces is significantly different with spatially differentiated features. From the perspective of dynamic trends, hot and sub-hot spots continue to gather in the developed eastern provinces, while cold spots and sub-cold spots mainly gather in the northwest region. Finally, eight indicators were selected to analyze the reasons for forming the spatial differentiation characteristics of China's efficiency of agro-tourism integration.

CLC number: 90C08

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AIMS Mathematics
Pages 23164-23182

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Cite this article:
Li H, Zhang S, Deng Y, et al. Research on the efficiency of agro-tourism integration in China: Based on the DEA cross-efficiency model. AIMS Mathematics, 2023, 8(10): 23164-23182. https://doi.org/10.3934/math.20231178

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Received: 03 May 2023
Revised: 27 June 2023
Accepted: 12 July 2023
Published: 15 October 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)