Zeleti, Fatemeh Ahmadi and Ojo, Adegboyega (2016) Critical Factors for Dynamic Capabilities in Open Government Data Enabled Organizations. In: Proceedings of the 17th International Digital Government Research Conference on Digital Government Research. ACM Digital Library, pp. 86-96. ISBN 978-1-4503-4339-8
Preview
AO_crtical.pdf
Download (824kB) | Preview
Abstract
Open data (OD) is increasingly considered as a core resource for
many organizations in the emerging data economy. Open data-driven organizations (ODDOs) like any other organizations must
develop capabilities for competitiveness and agility in addition to
processes for creating value from OD to survive. While questions
about the extent to which OD could be used for competitive
advantage has been raised in past studies, no previous study has
investigated the salient factors for agility in a dynamic data
ecosystem. This paper bridges the knowledge gap by developing
an operationalization of the Dynamic Capability Theory for
ODDOs. As a first step towards determining the critical factors
for developing dynamic capabilities (DCs) in these organizations,
we analyzed the information gathered from an expert interview on
the saliency of the different aspects and stages of dynamic
capability in developing the agility of an up-stream organization
or OD supplier in the data ecosystem. Our findings suggest that
critical factors for DCs differ for organizations in the upstream
and downstream sectors, albeit some core elements are shared
across sectors in data ecosystem.
Item Type: | Book Section |
---|---|
Keywords: | Open Data, Open Government Data; Dynamic Capabilities; Dynamic Capability Theory; Dynamic Capability Framework; Competitive Advantage of a Firm ; |
Academic Unit: | Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI Faculty of Social Sciences > School of Business |
Item ID: | 15815 |
Identification Number: | 10.1145/2912160.2912164 |
Depositing User: | Adegboyega Ojo |
Date Deposited: | 12 Apr 2022 13:47 |
Publisher: | ACM Digital Library |
Refereed: | Yes |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/15815 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only (login required)
Downloads
Downloads per month over past year