长三角乡村生态产品商品化格局及影响因素分析

Analysis on the pattern and determinants of rural ecological products commodification in the Yangtze River Delta

以POI数据等为基本数据,通过空间计量手段刻画和测度长三角典型乡村生态产品商品化的空间分布特征;从供需角度构建影响因素指标体系,分析自然资源禀赋和市场经济条件对商品化格局的影响及其作用机制。结果表明:(1)长三角乡村生态产品商品化主要集聚在苏南、浙北地区。(2)市场经济条件是商品化格局主要影响因素,地区交通条件、城镇居民人均可支配收入和服务业产业基础的正向影响显著。(3)影响因素的作用具有明显空间异质性:在沿海地区,地区交通条件对商品化的促进作用更强;在经济发展水平相对较高的地区,城镇居民人均可支配收入的正向影响更显著;在服务业发达地区,服务业产业基础的正向影响更强,地区长期从事农业生产带来的负向影响更弱。

Research on the commodification of ecological products has important implications for guiding the ecological transformation of current economic and social development.In this paper,we take the Yangtze River Delta as a case study and employ data related to agro-product geographical indication,point of interest(POI)and enterprises in 2022.With the help of ArcGIS and SPSS Software,we explore the spatial pattern and determinants of rural ecological products commodification in the Yangtze River Delta(YRD).In the first place,we use the method of Kernel Density Analysis to explore the spatial pattern of rural ecological products commodification in the study area.In the second place,based on economic demand and supply,we take the natural resource endowment and market economic conditions as the factor layer to construct a determinants index system to explain the commodification pattern.In the third place,we compare the GWR model with the traditional OLS model to further investigate the determinants of the commodification pattern in the YRD.Based on the analysis,the primary conclusions can be summarized as follows.(1)The commodification pattern exhibited agglomeration characteristics in Southern Jiangsu and Northern Zhejiang.Up to now,three high-density areas have been formed:Huzhou-Hangzhou,the coast of Lake Taihu,and Hefei city.In addition,sub-high-density areas have been formed in the suburbs of many large cities.(2)The market economy is the main factor affecting the formation of commodification pattern,in which regional traffic conditions,per capita disposable income of urban residents,and industrial base of service industry have significant positive effects.(3)In the model selection,we compare the GWR model with the traditional OLS model.The result shows that GWR is better,indicating that the impact of the indicators varies across space.In coastal areas,the commodification pattern is greatly affected by the regional traffic conditions.In areas with a higher level of economic development,the positive impact of the per capita disposable income index of urban residents is more significant.In areas with a developed service industry,the positive effect of the service industry base is more significant,while the negative impact brought by long-term agricultural production is weaker.