Study on the Coupling Coordination Relationship Between Rural Tourism and Agricultural Green Development Level: A Case Study of Jiangxi Province
Against the background of global climate change, agricultural ecosystems face extreme weather, resource shortages, and carbon emission pressures, necessitating green transitions. Rural tourism, a key driver of rural revitalization, injects momentum into green agriculture through ecological resource...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
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| Series: | Agriculture |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-0472/15/8/874 |
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| Summary: | Against the background of global climate change, agricultural ecosystems face extreme weather, resource shortages, and carbon emission pressures, necessitating green transitions. Rural tourism, a key driver of rural revitalization, injects momentum into green agriculture through ecological resource monetization, low-carbon technology adoption, and industrial restructuring. This study evaluates rural tourism and agricultural green development levels in Jiangxi Province (2008–2022) using the entropy weight method and explores their spatiotemporal coordination via a coupling coordination degree model and spatial autocorrelation analysis. The study reveals the following: (1) Rural tourism and agricultural green development in Jiangxi Province demonstrate an upward trend overall, though with significant regional disparities. Regions such as Nanchang and Jiujiang exhibit higher coordination levels, while areas like Pingxiang and Xinyu persistently cluster in low-value agglomerations. (2) The coupling coordination degree transitions from “marginal imbalance” to “intermediate coordination”, with Nanchang City achieving “good coordination” status in 2022, forming a high-value radiation zone encompassing Nanchang, Jiujiang, and Yichun. Low-value regions remain constrained by inadequate resource exploitation and technological lag. (3) Global spatial autocorrelation analysis reveals significant positive agglomeration effects (Moran’s I values range from 0.148 to 0.312). Local spatial associations show coexisting patterns of ‘high-high’ synergy and ‘low-low’ lock-in”. The study proposes targeted policy interventions, industrial convergence enhancement, and regional coordination mechanism optimization to mitigate spatial disparities and foster high-quality synergetic development. This study establishes theoretical foundations for agricultural green transition integrated with rural tourism development while offering referential pathways for analogous regions confronting climate change challenges. |
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| ISSN: | 2077-0472 |