摘要
以“Web of Science”合著论文数据为基础构建中国城市旅游知识创新网络,对2011-2014年、2015-2018年、2019-2022年3个时段网络的空间与拓扑结构演化特征进行分析,继而引用加权指数随机图模型(ERGM)定量研究内生和外生效应对网络形成与演化的影响。结果显示:(1)网络规模扩张迅速,整体联系强度与数量均稳步提升,空间格局由以香港地区为单一中心辐射的简单结构向多中心辐射的复杂网络转变。(2)网络的“小世界”特征逐渐显著,城市的择优连接倾向明显。(3)网络中节点的中心度差异较大,香港地区、澳门地区、广州、北京是旅游知识创新的中心城市。(4)从驱动机制看,自组织性、择优连接、旅游科研投入、国内旅游收入、人均地区生产总值、社会邻近性等多重因素共同作用于旅游知识创新网络的形成与演化,城市属性变量的正向影响强于多维邻近性。国际化视阈下中国城市旅游知识创新网络的结构及其形成机制的探讨,对于挖掘城市旅游知识国际化水平、增强城市间旅游知识合作和培育创新增长极具有重要意义。
Knowledge innovation network is the macro-geographical characterization of the cooperative relationship of micro-innovation subjects.The exploration of the structure of Chinese city tourism knowledge innovation network and its formation mechanism under the in-ternationalization perspective is of great significance for tapping the internationalization level of city tourism knowledge,enhancing intercity tourism knowledge cooperation and cultivating innovation growth poles.We constructed the tourism knowledge innovation network of Chinese cities with the co-authored thesis data of cities in“Web of science”,and analyzed the spatial and topological evolution characteristics of the network in the time periods of 2011—2014,2015—2018,2019-2022.The spatial and topological evolution characteristics of the network are analyzed in three periods of time,and then the weighted exponential random graph model(ERGM)is in-voked to quantitatively study the influence of endogenous and exogenous factors on the forma-tion and evolution of the network.The results show:1)The scale of the network is expanding rapidly,and the overall strength and number of links are steadily increasing,with the spatial pattern changing from a simple structure with Hong Kong region as the single center of radiation to a complex network with multiple centers of radiation;2)The“small world”character of the net-work is becoming more pronounced,and there is a clear tendency for cities to connect on the basis of merit;3)The centrality of the nodes in the network varies widely,with Hong Kong region,Macao region,Guangzhou,and Beijing being the central cities for tourism knowledge innovation;4)In terms of the driving mechanism,multiple factors such as self-organization,meritocratic connectivity,tourism research investment,domestic tourism income,per capita gross regional product,and social proximity combine to contribute to the formation and evolution of the tourism knowledge and innovation network,with the positive influence of city attribute variables being stronger than that of multidimensional proximity.
作者
王钊
张曼琦
崔悦
Wang Zhao;Zhang Manqi;Cui Yue(College of Tourism,Hunan Normal University,Changsha 410081,Hunan,China)
出处
《地理科学》
北大核心
2025年第1期141-152,共12页
Scientia Geographica Sinica
基金
国家自然科学基金项目(42101205)
湖南省自然科学基金项目(2022JJ40273)
国土资源评价与利用湖南省重点实验室开放课题(SYS-ZX-202305)资助。
关键词
旅游知识创新
科研合著论文
国际化视阈
加权指数随机图模型(ERGM)
tourism knowledge innovation
scientific collaboration papers
internationalization perspective
exponential random graph model(ERGM)
