基于城乡融合的科创城市与特色小镇协同发展路径研究——以环巢湖地区为例

当前,我国科技创新发展战略主要聚焦于大中型城市,偏向大中型城市的创新政策将会造成创新要素在城乡之间分配不平等、城乡差距扩大。城乡科技创新的协同有助于城乡之间创新要素的流动、减少城乡差距,但乡村受制于产业基础薄弱、与城市空间障碍大等原因,较难与城市形成创新协同。特色小镇是科创城市与乡村的联结点,特色小镇与科创城市协同发展,有助于辐射带动乡村发展,促进城乡融合和社会公平。科创城市与特色小镇的协同路径包括空间互补联动、产业协同布局、功能复合开发等。本研究以安徽省环巢湖区域为例,分析了科创城市与特色小镇协同的先决条件,探究了科创城市与特色小镇的协同发展路径,以期为今后特色小镇的发展提供一定的参考。

徐州市构建科创中心城市的机制和路径研究

科创中国的背景下,为了大力推动徐州市建设高水平、品牌化的科创中心城市,主要在理清科创中心城市的内涵前提下,对国内外科创中心城市的建设趋势与特点进行分析,对徐州市的科创中心城市建设优势、劣势、机会、挑战等进行SWOT分析,立足徐州市的独特资源、区位、交通等优势以及市场机遇,提出适合徐州市的科创中心城市建设路径,旨在促进徐州市建设科创中心城市,为我国其他城市提供方法借鉴。

内陆地区构建科创中心城市的机制与路径研究

分析我国内陆地区形成科技创新中心城市的基本态势,指出部分内陆地区大城市正在面临发展科创产业的历史性机遇,初步具备孕育科创产业的科技资源与经济基础,但也普遍存在创新氛围不浓、创新投入不足、缺少科创企业和创新配套服务机构等问题。提出构建内陆科创中心城市的机制与路径,即要构建有利于科技创新的制度与政策环境,形成以研究型大学和科研机构为创新动力源,以科创企业为龙头,以一流的法律、会计、审计、信息服务、融资机构为中介的区域创新生态系统,并与发达国家及沿海地区紧密互动以获得创新溢出效应。并进一步提出在构建内陆科创中心城市时,应注意避免过度投资、重复投资、经济金融化等现象,实现包容性发展。

高层次青年海归科技人才发展状况及政策优化研究——以上海为例

在全球科创中心城市建设背景下,高层次青年海归科技人才的引领作用更加凸显。基于2022年上海市青年科技人才专项调研和访谈数据,筛选其中的高层次海归科技人才并对他们的价值观念、事业发展、生活适应等方面的问题进行研究。调研发现,高层次青年海归科技人才在价值观念上积极向上,在事业发展上信心充足,在生活适应上融入城市,取得了较好的发展成绩;但在科研资助、平台支持、科技攻关等人才政策方面还存在改进空间,在人才激励、人才评价、学习交流等工作机制方面仍需完善,在工作生活平衡、家庭住房、子女教育等人才服务方面还需提升。最后据此提出相关对策建议。

对标全球,持续提升上海科技创新能级研究

当前,全球正处于新一轮科技革命和产业变革的重大机遇期,全球科技创新呈现格局叠加演变、前沿领域竞争加剧、创新范式变革、创新主体多元等特征趋势。上海科创中心建设步入功能升级关键跃升期,需要对标全球最高标准、最好水平,以科技创新培育新质生产力、打造战略新优势。本研究立足“百年未有之大变局”重要论断,基于全球主要科技创新中心城市(都市圈)跟踪评估,分析全球科创演进格局与发展趋势,从基础研究、硬核产业、要素活力、创新生态等维度开展国际国内对标分析,并围绕创新策源力、资源配置力、科创转化力、开放链接力,提出强化功能、提升上海国际科技创新中心能级的建议举措。

Spatio-temporal evolution of urban innovation structure based on zip code geodatabase: An empirical study from Shanghai and Beijing

In today's world, the innovation of science and technology has become the key support for improving comprehensive national strength and changing the mode of social production and lifestyle. The country that possesses world-class scientific and technological innovation cities maximizes the attraction of global innovation factors and wins a strategic initiative in international competition. Based on the urban zip code geodatabase, an evaluation system of urban innovation with the perspective of innovation outputs, and the spatial evolutionary mode, concerning the structure of innovation space of Shanghai and Beijing from 1991 to 2014, was developed. The results of the research indicated that the zip code geodatabase provided a new perspective for studying the evolving spatial structure of urban innovation. The resulting evaluation of the spatial structure of urban innovation using the urban zip code geodatabase established by connecting random edge points, was relatively effective. The study illustrates the value of this methodology. During the study period, the spatial structure of innovation of Shanghai and Beijing demonstrated many common features: with the increase in urban space units participating in innovation year by year, the overall gap of regional innovation outputs has narrowed, and the trend towards spatial agglomeration has strengthened. The evolving spatial structure of innovation of Shanghai and Beijing demonstrated differences between the common features during the 25 years as well: in the trend towards the suburbanization of innovation resources, the spatial structure of innovation of Shanghai evolved from a single-core to a multi-core structure. A radiation effect related to traffic arteries as spatial diffusion corridors was prominent. Accordingly, a spatial correlation effect of its innovation outputs also indicated a hollowness in the city center; the spatial structure of innovation of Beijing had a single-core oriented structure all the way. Together with the tendency for innovation resources to be agglomerated in the city center, the spatial correlation effect of innovation outputs reflected the characteristics of the evolutionary feature where "rural area encircles cities". The innovation spatial structure of Shanghai and Beijing have intrinsic consistency with the spatial structure of their respective regions(Yangtze River Delta urban agglomeration and Beijing-Tianjin-Hebei metropolitan region), which suggested that the principle of proportional and disproportional distribution of a city-scale pattern of technological and innovational activities is closely related to its regional innovation pattern.