Management Structure Based Government Enterprise Architecture Framework Adaption in Situ

Abstract
The fragmentation of the public sector makes it difficult to manage strategically and architecturally as a whole. Enterprise Architecture (EA) is considered as an improvement to that. Architectural modeling and visualization of the general management strategy plans along with parallel database development in a local government forms the primary data in the longitudinal case study using Action Design Research Method. To find a proper organizational fit for the EA framework in public sector, we reflect on how the current state architectural descriptions got organized in situ in a deep corporate hierarchy, and what were the emerging management needs in re-organizing the content of the descriptions. We suggest the EA framework in public sector as a strategic corporate management tool. As for the current state EA descriptions, we propose implementing the framework not as a static, but as a dynamic data model of the current management structures.
Main Authors
Format
Conferences Conference paper
Published
2017
Series
Subjects
Publication in research information system
Publisher
Springer
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202012107034Käytä tätä linkitykseen.
Parent publication ISBN
978-3-319-70240-7
Review status
Peer reviewed
ISSN
1865-1348
DOI
https://doi.org/10.1007/978-3-319-70241-4_18
Conference
IFIP Working Conference on The Practice of Enterprise Modeling
Language
English
Published in
Lecture Notes in Business Information Processing
Is part of publication
PoEM 2017: The Practice of Enterprise Modeling : 10th IFIP WG 8.1. Working Conference, Proceedings
Citation
  • Valtonen, K. (2017). Management Structure Based Government Enterprise Architecture Framework Adaption in Situ. In G. Poels, F. Gailly, E. S. Asensio, & M. Snoeck (Eds.), PoEM 2017: The Practice of Enterprise Modeling : 10th IFIP WG 8.1. Working Conference, Proceedings (pp. 267-282). Springer. Lecture Notes in Business Information Processing, 305. https://doi.org/10.1007/978-3-319-70241-4_18
License
In CopyrightOpen Access
Copyright© IFIP International Federation for Information Processing 2017

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