Spatiotemporal differentiation and influencing factors of primary, secondary, and tertiary industries integration in China’s four major tea-producing regions
[Objective] Industrial integration not only enhances the overall competitiveness of the tea industry but also promotes diversified local economic development, serving as an important means to improve the new quality productive forces of agriculture and revitalize rural areas. Exploring the spatiotem...
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Science Press, PR China
2024-12-01
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| Series: | Ziyuan Kexue |
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| Online Access: | https://www.resci.cn/fileup/1007-7588/PDF/1736920363577-1968075944.pdf |
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| author | ZHENG Feifei, ZHAN Huilong, LEI Guoquan, CHEN Meiying |
| author_facet | ZHENG Feifei, ZHAN Huilong, LEI Guoquan, CHEN Meiying |
| author_sort | ZHENG Feifei, ZHAN Huilong, LEI Guoquan, CHEN Meiying |
| collection | DOAJ |
| description | [Objective] Industrial integration not only enhances the overall competitiveness of the tea industry but also promotes diversified local economic development, serving as an important means to improve the new quality productive forces of agriculture and revitalize rural areas. Exploring the spatiotemporal evolution patterns and influencing factors of the integration of primary, secondary, and tertiary industries in China’s four major tea-producing regions is of significant importance for promoting the upgrading of the tea industry and driving economic growth in these regions. [Methods] Based on the policy background of primary, secondary, and tertiary industries integration, this study focused on 44 major tea-producing areas of China’s four tea-producing regions. The entropy method was employed to measure the level of industrial integration in these areas across five dimensions: actors, technology, products, business, and markets. Using spatial analysis techniques such as kernel density estimation, convergence analysis, the diamond model, and Multi-scale Geographically Weighted Regression, the study explored the spatiotemporal change patterns of industrial integration and the spatial heterogeneity of influencing factors. [Results] (1) From 2012 to 2021, the level of industrial integration in four major tea regions consistently improved, showing a fluctuated development trend; (2) A typical pattern of spatial agglomeration and convergence was observed in these regions, with the overall level of integration increasing, the number of highly integrated areas growing, and the gap between different regions narrowing; (3) The influencing factors of industrial integration exhibited significant spatial heterogeneity: the Southern and Southwest regions are predominantly shaped by foreign investment, land resources, and educational spending; the South and North of Yangtze River regions are predominantly influenced by land resources. [Conclusion] Tailored strategies for integrating primary, secondary, and tertiary industries should align with the unique resources and economic characteristics of each tea-producing region. Emphasis should be placed on improving land use efficiency, investment environments, and education, to enhance inter-industry synergy and cross-regional collaboration, promoting sustainable economic growth. |
| format | Article |
| id | doaj-art-81c4dd85cc2d4f7c8de0934675476b1a |
| institution | Kabale University |
| issn | 1007-7588 |
| language | zho |
| publishDate | 2024-12-01 |
| publisher | Science Press, PR China |
| record_format | Article |
| series | Ziyuan Kexue |
| spelling | doaj-art-81c4dd85cc2d4f7c8de0934675476b1a2025-01-15T12:16:31ZzhoScience Press, PR ChinaZiyuan Kexue1007-75882024-12-0146122532254510.18402/resci.2024.12.14Spatiotemporal differentiation and influencing factors of primary, secondary, and tertiary industries integration in China’s four major tea-producing regionsZHENG Feifei, ZHAN Huilong, LEI Guoquan, CHEN Meiying01. Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China;2. Center for Rural Social Development, Ministry of Agriculture and Rural Affairs, Beijing 100122, China;3. College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China;4. College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China[Objective] Industrial integration not only enhances the overall competitiveness of the tea industry but also promotes diversified local economic development, serving as an important means to improve the new quality productive forces of agriculture and revitalize rural areas. Exploring the spatiotemporal evolution patterns and influencing factors of the integration of primary, secondary, and tertiary industries in China’s four major tea-producing regions is of significant importance for promoting the upgrading of the tea industry and driving economic growth in these regions. [Methods] Based on the policy background of primary, secondary, and tertiary industries integration, this study focused on 44 major tea-producing areas of China’s four tea-producing regions. The entropy method was employed to measure the level of industrial integration in these areas across five dimensions: actors, technology, products, business, and markets. Using spatial analysis techniques such as kernel density estimation, convergence analysis, the diamond model, and Multi-scale Geographically Weighted Regression, the study explored the spatiotemporal change patterns of industrial integration and the spatial heterogeneity of influencing factors. [Results] (1) From 2012 to 2021, the level of industrial integration in four major tea regions consistently improved, showing a fluctuated development trend; (2) A typical pattern of spatial agglomeration and convergence was observed in these regions, with the overall level of integration increasing, the number of highly integrated areas growing, and the gap between different regions narrowing; (3) The influencing factors of industrial integration exhibited significant spatial heterogeneity: the Southern and Southwest regions are predominantly shaped by foreign investment, land resources, and educational spending; the South and North of Yangtze River regions are predominantly influenced by land resources. [Conclusion] Tailored strategies for integrating primary, secondary, and tertiary industries should align with the unique resources and economic characteristics of each tea-producing region. Emphasis should be placed on improving land use efficiency, investment environments, and education, to enhance inter-industry synergy and cross-regional collaboration, promoting sustainable economic growth.https://www.resci.cn/fileup/1007-7588/PDF/1736920363577-1968075944.pdfprimary, secondary, and tertiary industries integration|spatiotemporal differentiation|influencing factors|multi-scale geographically weighted regression (mgwr)|four major tea-producing regions|china |
| spellingShingle | ZHENG Feifei, ZHAN Huilong, LEI Guoquan, CHEN Meiying Spatiotemporal differentiation and influencing factors of primary, secondary, and tertiary industries integration in China’s four major tea-producing regions Ziyuan Kexue primary, secondary, and tertiary industries integration|spatiotemporal differentiation|influencing factors|multi-scale geographically weighted regression (mgwr)|four major tea-producing regions|china |
| title | Spatiotemporal differentiation and influencing factors of primary, secondary, and tertiary industries integration in China’s four major tea-producing regions |
| title_full | Spatiotemporal differentiation and influencing factors of primary, secondary, and tertiary industries integration in China’s four major tea-producing regions |
| title_fullStr | Spatiotemporal differentiation and influencing factors of primary, secondary, and tertiary industries integration in China’s four major tea-producing regions |
| title_full_unstemmed | Spatiotemporal differentiation and influencing factors of primary, secondary, and tertiary industries integration in China’s four major tea-producing regions |
| title_short | Spatiotemporal differentiation and influencing factors of primary, secondary, and tertiary industries integration in China’s four major tea-producing regions |
| title_sort | spatiotemporal differentiation and influencing factors of primary secondary and tertiary industries integration in china s four major tea producing regions |
| topic | primary, secondary, and tertiary industries integration|spatiotemporal differentiation|influencing factors|multi-scale geographically weighted regression (mgwr)|four major tea-producing regions|china |
| url | https://www.resci.cn/fileup/1007-7588/PDF/1736920363577-1968075944.pdf |
| work_keys_str_mv | AT zhengfeifeizhanhuilongleiguoquanchenmeiying spatiotemporaldifferentiationandinfluencingfactorsofprimarysecondaryandtertiaryindustriesintegrationinchinasfourmajorteaproducingregions |