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Towards Detecting Misalignment Symptoms: An Alignment Perspective-Driven Architecture-Matching Framework

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Enterprise and Organizational Modeling and Simulation (EOMAS 2015)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 231))

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Abstract

When assessing the harmony between business and information systems most of traditional studies deal with the presence and the achievement of strategic alignment. On the contrary, exiguous attention is paid to the phenomenon of strategic misalignment, which means the absence or difficulties of business-IT alignment. This paper deals with strategic misalignment between business and information systems. It proposes an enterprise architecture (EA)-based approach to detect the symptoms of misalignment in enterprise architecture models. The proposed framework aims to perform an EA-based systematic analysis of mismatches between the business dimension and the IT dimension. It collects typical misalignment symptoms along the traditional alignment perspectives and connects them to relevant EA analysis types. The paper discusses the typical signs of strategic misalignment between business and information systems detected in different EA domain matches. Suitable EA analysis types are recommended to the detected signs of misalignment.

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Authors and Affiliations

  1. Department of Information Systems, Corvinus University of Budapest, Budapest, Hungary

    Dóra Őri

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  1. Dóra Őri
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Correspondence to Dóra Őri .

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Editors and Affiliations

  1. Delft University of Technology, Delft, Zuid-Holland, The Netherlands

    Joseph Barjis

  2. Czech Technical University in Prague, Prague, Czech Republic

    Robert Pergl

  3. Higher School of Economics, National Research University, Nizhny Novgorod, Russia

    Eduard Babkin

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Őri, D. (2015). Towards Detecting Misalignment Symptoms: An Alignment Perspective-Driven Architecture-Matching Framework. In: Barjis, J., Pergl, R., Babkin, E. (eds) Enterprise and Organizational Modeling and Simulation. EOMAS 2015. Lecture Notes in Business Information Processing, vol 231. Springer, Cham. https://doi.org/10.1007/978-3-319-24626-0_16

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  • DOI: https://doi.org/10.1007/978-3-319-24626-0_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24625-3

  • Online ISBN: 978-3-319-24626-0

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