基于大数据的浙江省特色小镇人口活力测度与评价

Measurement and Evaluation to Population Vitality of Characteristic Towns in Zhejiang Province based on Big Data

特色小镇自2015年发端于浙江以来已遍布全国,如何客观、科学地评价特色小镇建设情况成为各地政府面临的一个难题。本研究与中国移动通信集团浙江有限公司大数据中心合作,以脱敏后的手机信令数据为基础,构造以人口活力为核心的指标体系,并考察浙江省前三批公布的、共计114个省级创建类特色小镇的人口活力,同时根据评价结果进一步探讨特色小镇人口活力的影响因素。研究发现,浙江省特色小镇在各类人口规模和集聚度上均有不同程度的提升,但不同产业类型的小镇发展情况存在差异。其中,时尚类、数字经济类和金融类等小镇在人口吸引力上有不错的表现,而历史经典类和旅游类特色小镇表现不尽人意,人口规模相对较小。同时,回归结果显示,主导产业特征、小镇建设时长、当地社会经济基础及产业基础等因素,会显著影响特色小镇的人口活力。总体而言,特色小镇的发展符合客观经济规律,其成功的关键并不在于数量、规模、创建时间、初始发展条件等因素,而是取决于是否选择与当地社会经济条件和未来发展规划最为匹配的主导产业。

Characteristic towns have spread all over the country since originated in Zhejiang in 2015.Developing an objective and comprehensive evaluation system of characteristic towns has become crucial for local governments.Cooperating with the Big Data Center of China Mobile Communications Group Zhejiang Co.Ltd.,this research designs a measurement index of population vitality based on the desensitized mobile phone signaling data and investigates the population vitality of 114 provincial-level characteristic towns released by the first three batches of nomination in Zhejiang Province.Furthermore,the factors influencing the population vitality of characteristic towns are explored and summarized.It is found that the population size and concentration of characteristic towns in Zhejiang Province have been improved to varying degrees,but the development of towns with different industrial types is different:characteristic towns with fashion,digital economy or financial services industry witnessed good population vitality,while historical and touristic towns were underperformed with a relatively small population size.Meanwhile,the regression results show that features of leading industries,construction period of towns,local socio-economic background and industrial foundation significantly affect the population vitality of characteristic towns.Generally speaking,the development of characteristic towns conforms to objective economic laws,and the key to their success lies not in factors such as quantity,scale,age and initial development conditions,but in whether to choose the leading industries that best match local social and economic conditions and future development plans.