茶叶主产地三产融合驱动机制及空间溢出效应

DRIVING MECHANISM AND SPATIAL SPILLOVER EFFECTS OF PRIMARY, SECONDARY, AND TERTIARY INDUSTRIES INTEGRATION IN TEA-PRODUCING REGIONS

关键词:  茶叶主产地  三产融合  融合水平  驱动机制  空间溢出

Key words:  major tea-producing regions  integration of primary, secondary, and tertiary industries  integration level  driving mechanism  spatial spillover

摘要:

目的 通过构建茶叶主产地三产融合的驱动机制，探讨驱动因素如何通过空间联系影响当地及周边地区的产业融合，以期为茶叶主产地制定科学的区域发展战略和产业优化政策提供理论参考和实践指导。方法 文章收集2012—2021年中国44个茶叶主产地的面板数据，运用熵值法测度各茶叶主产地三产融合水平，采用Moran指数检验三产融合的空间自相关性，通过空间计量模型（SAR、SEM、SDM）剖析驱动茶叶主产地三产融合的重要因素及其空间效应。结果 （1）茶叶主产地三产融合水平在过去10年间持续提升，并呈现出显著的空间集聚特征。（2）教育投入、经济发展、城镇化、外商投资和农业基础设施、土地资源等因素对茶叶主产地三产融合具有显著的正向影响，尤其是经济发展水平和土地利用情况在空间上显示出正向溢出效应，不仅对当地的三产融合发展有积极作用，还能促进邻近地区的三产融合。结论 发挥茶叶主产地三产融合的空间集聚效应、优化驱动要素、推进区域协调发展，可以有效促进茶叶主产地三产融合的深度发展。

Abstract:

This research aims to explore how the driving factors influence the industrial development of surrounding areas through spatial linkages by investigating the driving mechanisms behind the integration of primary, secondary, and tertiary industries in major tea-producing regions, so as to provide both theoretical support and practical insights for developing effective regional strategies and policies for industrial upgrading in tea-producing areas. Using the panel data from 44 tea-producing cities in China from 2012 to 2021, this study employed the entropy method to quantify the level of industrial integration in each region, applied Moran's Index to examine the spatial autocorrelation of industrial integration, and adopted the spatial econometric models, including the spatial autoregressive model (SAR), spatial error model (SEM), and spatial durbin model (SDM), to identify key factors driving industrial integration and their spatial effects. The findings revealed that the level of industrial integration in tea-producing regions had consistently increased over the past decade, demonstrating significant spatial clustering characteristics. Factors such as educationinvestment, economic development, urbanization, foreign direct investment, agricultural infrastructure, and land resource positively impacted industrial integration. Notably, economic development and land use efficiency exhibited positive spatial spillover effects, promoting industrial integration not only within the region but also in neighboring areas. Based on these results, this study concludes that leveraging the agglomeration effects of industrial integration, optimizing driving factors, and promoting coordinated regional development can significantly enhance the depth of industrial integration in tea-producing regions.