DOI

Previous research assumes that poor quality of Open Government Data (OGD), OGD portals, and the services provided for OGD may result in reduced trust of citizens in OGD. However, studies that empirically test this assumption are scarce. Using the Information Systems (IS) Success Model as a theoretical basis, this study aims to examine the effects of data quality, system quality, and service quality on citizens’ trust in OGD.We used Structural Equation Modeling (SEM) to analyze the 200 responses to our online questionnaire. We found that trust in OGD can be predicted by citizens’ perceptions of OGD system quality and service quality. Furthermore, citizens’ perception of service quality positively influences their perceptions of data and system quality, whereas citizens’ perception of system quality positively influences their perception of data quality. This study is among the first that quantitatively examines the effects of data quality, service quality, and system quality on citizen’s trust in OGD. It contributes to the scientific literature by providing an operationalization of elements of the IS Success Model in the context of OGD and by developing and applying a model of factors influencing citizen’s trust in OGD. While previous research finds that perceived data quality is the most crucial driver for trust in OGD, our study finds that citizens’ perception of OGD service quality is a more important driver for trust in OGD. With regard to the practical contributions of this study, open data policymakers should be aware that citizens’ perceptions on data quality can be greatly improved when appropriate human services are provided (e.g., designated civil servants offering support or help to data users) in addition to the provision of OGD portal functionalities (e.g., data visualization and comparison tools).
Original languageEnglish
Title of host publicationProceedings of the 21st Annual International Conference on Digital Government Research
Subtitle of host publicationIntelligent Government in the Intelligent Information Society, DGO 2020
EditorsSeok-Jin Eom, Jooho Lee
PublisherAssociation for Computing Machinery (ACM)
Pages310–318
Number of pages9
ISBN (Electronic)978-1-4503-8791-0
DOIs
Publication statusPublished - 2020

Publication series

NameACM International Conference Proceeding Series

    Research areas

  • Citizen engagement, Data quality, Information Systems Success Model, Open Government Data, Service quality, Structural Equation Modeling, Systems quality, Trust

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