The Classification Study On User Experience Factors Of Government Data Open Platform Based On Kano Model

In recent years,the process of opening up government data in China has continued to accelerate,and the number of open data platforms at all levels of government has increased.Looking at the construction of China's government data open platform,its focus is mostly on the uploading and opening of the data itself,and lack of attention to the user experience.At the same time,due to the limited resources of the government,it is impossible to spend too much energy and funds to pay attention to the user's use and acquisition experience when building the government data open platform.To this end,from the perspective of user experience,this paper screens and analyzes the factors affecting user experience in the construction of government data open platform,explores the elements that have the potential to improve user experience,and provides reference for the targeted construction of government data open platform to optimize user experience.In order to find a breakthrough in balancing data openness and user experience improvement.Firstly,the thesis defines and explains the related concepts of the government data open platform and the model theory used.Through the classic user experience model,the screening criteria for the user experience elements of the government data open platform are set,and the government data evaluation project is open for reference.Based on the fundamental source of China's open government data evaluation project and the existing open data platform of all levels of government,the Delphi method is used to finalize the user experience elements of the government data open platform.Then,using the Kano model's questionnaire processing method,traditional classification and Better-Worse classification method,each user experience element is classified and accurately identified to improve user satisfaction and prevent users when improving certain user experience elements.The impact of satisfaction.Thirdly,the user experience coefficient scatter plot is drawn according to the Better-Worse classification result of each element and the element drop calculation formula.Based on the figure,the elements with improved potential of user experience are identified by improving the feature screening line,and The foundation introduces the concept of key factor screening lines,and identifies the relatively important part of the improvement factor,which is the key element of the user experience improvement of the government data open platform.The results show that there are 45 user experience elements in the government data open platform.Among the 45 elements,7 are glamour factors,26 are one-dimensional factors,6 are mandatory factors,4 are non-differential factors,and 2 Belong to the inverse factor.In addition,through the sensitivity ranking,36 elements need to be improved,and 7 elements such as “recommended feedback function” are selected as key factors,in order to provide reference for the government data open platform to rationally allocate resources to improve service quality.