Research On The Factors Influencing User Experience Of Local Government Open Data Platform

Since the US federal government data open platform was launched in 2009,government data opening has been rapidly advanced in many countries and regions.The government data opening has become a hot issue in the fields of public management and big data in recent years.With the promotion and development of local government data,there has been on an upsurge in the construction of government data open platforms in recent years.Platform is a portal for users to access and utilize data,and a bridge between data providers and users.The user experience of platform can directly and objectively reflect the ability and level of local government data opening.Domestic and foreign scholars pay more attention to the quality of the existing platform of government open data,and pay less attention to the actual experience of users.In this context,the followings are the main work of this thesis.Firstly,the concept of government data and public data,the difference between government data opening and government information publicity,and the concept of local government public data open platform are defined in this thesis.The development and adaptation analysis of the theoretical basis of the research,including the demand hierarchy theory and the stakeholder theory,are briefly described.Secondly,this thesis takes the Shanghai Government Data Service Platform as the representative case of the local government data open platform.From the perspective of user perception,combining the evaluations for service quality of information system,indicator system of public sector website's service quality evaluation,and current situation of local government data opening.The user experience is divided into five dimensions(interface function,data availability,service response,user care,personalized service)and 20 experience contents,and then 46 factors influencing the user experience of the local government data open platform are identified.Combined with the demand hierarchy theory and the stakeholder theory,the platform service objects are identified from the perspective of users,and the research hypotheses on various service objects are carried out from five experience dimensions.Furthermore,the KANO binary structure is used to design the questionnaire and the questionnaire survey is carried out.Combing the KANO model,the binary matrix classification method and the Better-Worse coefficient calculation method,the 46 influencing factors are classified,and the research hypotheses are carried out.The verification shows that different types of users have different experiences on the interface function of government data open platform,data availability,service response,and user care,but the experience of personalized service is consistent.Finally,the sensitivity R is introduced,and the sensitivity matrix is formed based on the four-quadrant scatter plot of the influencing factors SI and DSI values,thereby the factors improving the user experience of the data open platform are prioritized,and the key factors affecting the user experience are screened,focusing on seven key factors.Based on the current situation of the Shanghai Government Data Service Platform,the thesis analyzes the causes and proposes countermeasures and suggestions for improving the user experience of the platform,and provides reference for the construction of data open platforms of other local governments.This thesis is based on qualitative and quantitative analysis of the user experience of the local government data open platform,which mainly has the following two innovations: First,based on the existing index system of information system service quality,public sector website service quality and the evaluation of the local government data opening status quo,using the SERVQUAL model,it identifies the factors influencing the user experience of the local government data open platform,including 5 dimensions,20 experience contents,and 46 factors influencing the user experience.Second,it classifies the 46 factors that influence user experience by using the method of binary matrix classification and Better-Worse coefficient calculation,which overcomes the shortcoming of frequency classification.