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Zhang Huilin, Lai Qifu, Li Chunshuo, Li Hufeng, Huang Jielong. Spatio-Temporal Distribution and Its Influencing Factors of "One Village One Product" Demonstration Villages and Towns in China[J]. Journal of Beijing Forestry University (Social Science), 2023, 22(3): 84-95. DOI: 10.13931/j.cnki.bjfuss.2022148
Citation: Zhang Huilin, Lai Qifu, Li Chunshuo, Li Hufeng, Huang Jielong. Spatio-Temporal Distribution and Its Influencing Factors of "One Village One Product" Demonstration Villages and Towns in China[J]. Journal of Beijing Forestry University (Social Science), 2023, 22(3): 84-95. DOI: 10.13931/j.cnki.bjfuss.2022148

Spatio-Temporal Distribution and Its Influencing Factors of "One Village One Product" Demonstration Villages and Towns in China

  • "OneVillage One product" is an important development model for rural industrial revitalization. The first to eleventh batches of 3780 national "One Village One Product" demonstration villages and towns are used as the research objects, and their spatial and temporal evolution characteristics and influencing factors are analyzed by using kernel density analysis, average nearest neighbor algorithm, standard deviation ellipse, quantile regression, and other methods. The results show that the spatial distribution of "One Village One Product" model villages and towns is uneven, mostly concentrated in the relatively developed economic regions such as Beijing-Tianjin-Hebei-Southwestern Shandong contiguous area, Sichuan Basin, Yangtze River Delta, and Pearl River Delta, reflecting the large difference in the level of rural industrial revitalization in different regions. The industrial structures of model villages and towns are different, relying mainly on primary products and primary industries, and the proportion of secondary and tertiary industries such as leisure agriculture and rural services is too small. Natural and human conditions and socio-economic factors together influence the formation and distribution of model villages and towns, among which socio-economic indicators such as local fiscal expenditure, road network density, regional per capita GDP, the gross output value of agriculture, forestry, animal husbandry and fishery, and per capita disposable income have positive relationships with the number of model villages and towns. Accordingly, improving measures are proposed such as increasing financial transfer payments, attaching importance to the synergistic development of urban and rural industries, and promoting the creation of high-end agricultural brands.
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