Modeling of Open Government Data for Public Sector Organizations Using the Potential Theories and Determinants—A Systematic Review
School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
Department of Examinations, Virtual University of Pakistan, Lahore 54500, Pakistan
Department of Computer Science and IT, University of Sargodha, Sargodha 40100, Pakistan
Azman Hashim International Business School, Universiti Teknologi Malaysia, Kuala Lumpur 54100, Malaysia
College of Engineering and IT, Ajman University, Ajman 346, UAE
Institute of IR4.0, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
Quaid-i-Azam School of Management Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan
Author to whom correspondence should be addressed.
Informatics 2020, 7(3), 24; https://doi.org/10.3390/informatics7030024
Received: 26 May 2020 / Revised: 19 July 2020 / Accepted: 19 July 2020 / Published: 21 July 2020
Open government data (OGD) has huge potential to increase transparency, accountability, and participation while improving efficiency in operations, data-driven and evidence-based policymaking, and trust in government institutions. Despite its potential benefits, OGD has not been widely and successfully adopted in public sector organizations, particularly in developing countries. Therefore, the purpose of this study is to explore the theories/frameworks and potential determinants that influence the OGD adoption in public sector organizations. To ascertain the various determinants of OGD adoption in public sector organizations, this study involved a systematic review of already established theories and determinants addressed in the public sector open data domain. The review revealed that the TOE (technology, organization, environment) framework was dominantly employed over theories in the earlier studies to understand organizational adoption to OGD followed by institutional theory. The results, concerning potential determinants, revealed that some of the most frequently addressed determinants are an organization’s digitization/digitalization capacity, compliance pressure, financial resources, legislation, policy, regulations, organizational culture, political leadership commitment, top-management support, and data quality. The findings will enrich researchers to empirically investigate the exposed determinants and improve the understanding of decision-makers to leverage OGD adoption by taking relevant measures.