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Open government data: A systematic literature review of empirical research
Open government data (OGD) holds great potential for firms and the digital economy as a whole and has attracted increasing interest in research and practice in recent years. Governments and organizations worldwide are struggling in exploiting the full potential of OGD and require a comprehensive und...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9487844/ https://www.ncbi.nlm.nih.gov/pubmed/36158525 http://dx.doi.org/10.1007/s12525-022-00582-8 |
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author | Wirtz, Bernd W. Weyerer, Jan C. Becker, Marcel Müller, Wilhelm M. |
author_facet | Wirtz, Bernd W. Weyerer, Jan C. Becker, Marcel Müller, Wilhelm M. |
author_sort | Wirtz, Bernd W. |
collection | PubMed |
description | Open government data (OGD) holds great potential for firms and the digital economy as a whole and has attracted increasing interest in research and practice in recent years. Governments and organizations worldwide are struggling in exploiting the full potential of OGD and require a comprehensive understanding of this phenomenon. Although scientific debates in OGD research are intense and heterogeneous, the field lacks theoretical integration of OGD topics and their systematic consideration in the context of the digital economy. In addition, OGD has been widely neglected by information systems (IS) research, which promises great potential for advancing our knowledge of the OGD concept and its role in the digital economy. To fill in this gap, this study conducts a systematic literature review of 169 empirical OGD studies. In doing so, we develop a theoretical review framework of Antecedents, Decisions, Outcomes (ADO) to unify and grasp the accumulating isolated evidence on OGD in context of the digital economy and provide a theory-informed research agenda to tap the potential of IS research for OGD. Our findings reveal six related key topic clusters of OGD research and substantial gaps, opening up prospective research avenues and particularly outlining how IS research can inform and advance OGD research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12525-022-00582-8. |
format | Online Article Text |
id | pubmed-9487844 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-94878442022-09-21 Open government data: A systematic literature review of empirical research Wirtz, Bernd W. Weyerer, Jan C. Becker, Marcel Müller, Wilhelm M. Electron Mark Research Paper Open government data (OGD) holds great potential for firms and the digital economy as a whole and has attracted increasing interest in research and practice in recent years. Governments and organizations worldwide are struggling in exploiting the full potential of OGD and require a comprehensive understanding of this phenomenon. Although scientific debates in OGD research are intense and heterogeneous, the field lacks theoretical integration of OGD topics and their systematic consideration in the context of the digital economy. In addition, OGD has been widely neglected by information systems (IS) research, which promises great potential for advancing our knowledge of the OGD concept and its role in the digital economy. To fill in this gap, this study conducts a systematic literature review of 169 empirical OGD studies. In doing so, we develop a theoretical review framework of Antecedents, Decisions, Outcomes (ADO) to unify and grasp the accumulating isolated evidence on OGD in context of the digital economy and provide a theory-informed research agenda to tap the potential of IS research for OGD. Our findings reveal six related key topic clusters of OGD research and substantial gaps, opening up prospective research avenues and particularly outlining how IS research can inform and advance OGD research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12525-022-00582-8. Springer Berlin Heidelberg 2022-09-20 2022 /pmc/articles/PMC9487844/ /pubmed/36158525 http://dx.doi.org/10.1007/s12525-022-00582-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Paper Wirtz, Bernd W. Weyerer, Jan C. Becker, Marcel Müller, Wilhelm M. Open government data: A systematic literature review of empirical research |
title | Open government data: A systematic literature review of empirical research |
title_full | Open government data: A systematic literature review of empirical research |
title_fullStr | Open government data: A systematic literature review of empirical research |
title_full_unstemmed | Open government data: A systematic literature review of empirical research |
title_short | Open government data: A systematic literature review of empirical research |
title_sort | open government data: a systematic literature review of empirical research |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9487844/ https://www.ncbi.nlm.nih.gov/pubmed/36158525 http://dx.doi.org/10.1007/s12525-022-00582-8 |
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