[Purpose/Significance] The degree of government data collaboration is an important factor affecting the smartness of government service, which is of great significance for the quantitative analysis, the accurate smart service construction, and the smartness level promotion. [Method/Process] The supernetwork model was used to abstract the mathematical model of the government data collaboration process, and the index system of the measurement was constructed with the applicable network analysis index. With the representative cities as the case, the collaborative effect of government data was analyzed from three levels of the “point-line-plane”. [Result/Conclusion] It was found that the index measurement value can realize the feature mapping of the actual city data coordination, and obtain the driving effect of each node in the network, including the correlation effect of scene-data link and the collaboration effect of the overall network at the macro level, which is conducive to improve the precise regulation of the government intelligent services.
Pu Hongyu
,
Ma Jie
,
Zhang Yunkai
,
Wang Jue
. Research on Measurement of Government Data Collaboration Effect for Government Service Scenario[J]. Library and Information Service, 2024
, 68(5)
: 3
-12
.
DOI: 10.13266/j.issn.0252-3116.2024.05.001
[1] ROBERTS N.Public deliberation in an age of direct citizen participation[J].The American review of public administration, 2004(4):315-353.
[2] ANDERSON S, BOHMAN P R, BURMEISTER O K, et al.User needs and e-government accessibility:the future impact of WCAG 2.0[C]//User-centered interaction paradigms for universal access in the information society:8th ERCIM workshop on user interfaces for all.Berlin:Springer, 2004:289-304.
[3] WESCOTT C G.E-government in the Asia-Pacific region:progress and challenges[J].Systemics, cybernetics and informatics, 2004, 3(6):37-42.
[4] KU-MAHAMUD K R, CHEPA N, OMAR M H, et al.Community perception on smart engagement:case of Kubang Pasu local government[J].Baghdad science journal, 2021, 18(2):0975.
[5] CRIADO J, VILLODRE J.Delivering public services through social media in European local governments.an interpretative framework using semantic algorithms[J].Local government studies, 2020, 47(2):253-275.
[6] YANNOUKAKOU A, ARAKA I.Access to government information:right to information and open government data synergy[J].Procedia-social and behavioral sciences, 2014(147):332-340.
[7] 朱锐勋.基于云计算的政府信息资源协同共享及实现途径[J].计算机与网络, 2014, 40(10):71-74.(ZHU R X.On the implementation of government information resource collaborating and sharing with the approach of cloud computing[J].Computer & network, 2014, 40(10):71-74.)
[8] 张建光.智慧政务信息生态协同演化机制研究[D].北京:中央财经大学, 2016.(ZHANG J G.Research on smart government information ecosystem synergetics evolution mechanism[D].Beijing:Central University of Finance and Economics, 2016.)
[9] 马捷, 蒲泓宇, 张云开, 等.基于关联数据的政府智慧服务框架与信息协同机制[J].情报理论与实践, 2018, 41(11):20-26.(MA J, PU H Y, ZHANG Y K, et al.Government smart service framework and information collaboration mechanism based on linked data[J].Information studies:theory & application, 2018, 41(11):20-26.)
[10] 何苗, 叶战备.政务数据协同治理的有效运行机制[J].特区经济, 2023(3):67-70.(HE M, YE Z B.Effective operational mechanisms for collaborative governance of government data[J].Special zone economy, 2023(3):67-70.)
[11] 姜申未, 代冰凝.数字政府的演进与转型研究[J].特区经济, 2023(2):55-58.(JIANG W S, DAI B N.Research on evolution and transformation of digital government[J].Special zone economy, 2023(2):55-58.)
[12] 孙玺菁, 司守奎.复杂网络算法与应用[M].北京:国防工业出版社, 2015:1-2.(SUN S J, SI S K.Complex network algorithms and applications[M].Beijing:National Defence Industry Press, 2015:1-2.
[13] NAGURNEY A.On the relationship between supply chain and transportation network equilibria:a supernetwork equivalence with computations[J].Transportation research part e, 2006, 42(4):293-316.
[14] CHEN T, SHAO Y, HAN Y.Collaborative innovation model research based on knowledge-supernetwork and TRIZ[J].Journal of computational & theoretical nanoscience, 2015, 15(1):269-272.
[15] DAFERMOS J.Traffic assignment and resource allocation in transportation networks:Stella C.Dafermos Johns Hopkins University, 11 June 1968 F.T.Sparrow 140 Journal of Research of the National Bureau of Standards[J].Transportation research, 1969, 3(4):498.
[16] DAFERMOS J, STELLA C.The traffic assignment problem for multiclass-user transportation networks[J].Transportation science, 1972, 6(1):73-87.
[17] DAFERMOS J, STELLA C.Toll patterns for multiclass-user transportation networks[J].Transportation science, 1973, 7(3):211-223.
[18] DAFERMOS J, STELLA C.An extended traffic assignment model with applications to two-way traffic[J].Transportation science, 1971, 5(4):366-389.
[19] NAGURNEY A, WAKOLBINGER T.Supernetworks:an introduction to the concept and its applications with a specific focus on knowledge supernetworks[J].International journal of knowledge, culture and change management, 2005, 4(1):1-16.
[20] JOHNSON J H.Hypernetworks in the science of complex systems[M].Singapore:World Scientific, 2013:1-10.
[21] 王志平, 王众托.超网络理论及其应用[M].北京:科学出版社, 2008.(WANG Z P, WANG Z T.Supernetwork theory and its application[M].Beijing:China Science Publishing & Media, 2008.)
[22] DURUGBO C, HUTABARAT W, TIWARI A, et al.Modelling collaboration using complex networks[J].Information sciences.2011, 181(15):3143-3161.
[23] DURUGBO C.Modelling strategic information for networks during collaboration[C]//Proceedings of the 2011 international conference on computational aspects of social networks.Salamanca:IEEE, 2011:267-272.
[24] 龙怡, 李国秋.G to C电子政务中政府信息共享路径研究——基于上海市个人网上办事项目的社会网络分析[J].情报杂志, 2016, 35(9):174-181.(LONG Y, LI G Q.On the path of government information sharing in G to C services:a social network analysis based on the citizens' services in Shanghai[J].Journal of intelligence, 2016, 35(9):174-181.)
[25] 周向红, 姚轶力, 刘雨欣.数据要素流动背景下城市治理关键节点识别及影响因素分析——以上海市两区51个部门的数据为例[J].东南学术, 2023(1):137-149, 247.(ZHOU X H, YAO Y L, LIU Y X.An analysis on identification of key nodes of urban governance under the background of data element circulation and its influencing factors:exemplified by the data from 51 departments in two districts of Shanghai[J].Southeast academic research, 2023(1):137-149, 247.)
[26] 温雪梅.城市群政府数据共享的网络结构研究——以长三角区域为例[J].图书情报工作, 2023, 67(10):26-37.(WEN X M.Research on the network structure of government data sharing in urban agglomerations:a case study of the Yangtze River Delta region[J].Library and information service, 2023, 67(10):26-37.)
[27] 汪小帆.复杂网络理论及其应用[M].北京:清华大学出版社, 2006.
[28] 肖雯雯.产业超网络建模及其应用研究——以山东省蓝色经济为例[D].青岛:山东大学, 2018.(XIAO W W.Research on the modeling of industry supernetwork and its application:taking the blue economy of Shandong Province as an example[D].Qingdao:Shandong University, 2018.)
[29] 商丽媛.国民经济动员物流网络及应变响应研究[D].南京:南京航空航天大学, 2015.(SHANG L Y.Study on the national economy mobilization logistics network and its response to emergency incidents[D].Nanjing:Nanjing University of Aeronautics and Astronautics, 2015.)
[30] 德勤.超级智能城市2.0:人工智能引领新风尚[R].伦敦:德勤, 2022:18-20.(Deloitte.Super smart city 2.0:AI leads the way[R].London:Deloitte, 2022:18-20.)
[31] 清华大学数据治理研究中心.2020数字政府发展指数报告[R].北京:清华大学数据治理研究中心, 2020:10-16.(Tsinghua University Data Governance Research Center.2020 digital government development index report[R].Beijing:Tsinghua University Data Governance Research Center, 2020:10-16.)
