A Meta-Framework for Efficacious Adaptive Enterprise Architectures

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Business Information Systems Workshops (BIS 2016)

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Abstract

Tuning enterprise architectures to stay competitive and fit is an enduring challenge for organizations. This study postulates a meta-framework for Efficacious Adaptive Enterprise Architectures (EA), the 2EA framework. We use fundamental long-standing principles found in complex adaptive systems. These principles explain adaptive success. Also, we set forward managerial implications about the dynamics of EA to function effectively on four architectural levels, i.e. enterprise environment, enterprise, enterprise systems and infrastructure. Principles of efficacious adaptation have not been incorporated into current EA frameworks and methods underlining an improvement area. Subsequently, we extend baseline work into a meta-framework and evaluate it accordingly following the design science method. Our meta-framework supports organizations to assess and adapt EA capabilities – modular units of functionality within the organization – to the continuously changing environment, stakeholder interests and internal organizational dynamics. Our research contributes to foundational work on EA and can be used for strategic EA development and maturation.

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Notes

  1. 1.

    The authors in the current article refer to the field of Complexity Science. Complexity science will be addressed in Subsect. 1.2 and Sect. 2 more extensively.

  2. 2.

    Complexity science and CAS thinking search for generative simple rules in nature that underpin complexity and do not embrace the radical holism of systems theory.

  3. 3.

    This complementarity principle does not occur in the original work of McKelvey. We add this principle based on its longstanding tradition and its impact on modern economics and business management.

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van de Wetering, R., Bos, R. (2017). A Meta-Framework for Efficacious Adaptive Enterprise Architectures. In: Abramowicz, W., Alt, R., Franczyk, B. (eds) Business Information Systems Workshops. BIS 2016. Lecture Notes in Business Information Processing, vol 263. Springer, Cham. https://doi.org/10.1007/978-3-319-52464-1_25

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