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International Conference on Research Challenges in Information Science

RCIS 2020: Research Challenges in Information Science pp 95–111Cite as

Structural Coupling, Strategy and Fractal Enterprise Modeling

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 385))

Abstract

The concept of structural coupling, which comes from the biological cybernetics, has been found useful for organizational decision making on the higher level, such as management of organizational identity and strategy development. However, currently, there is no systematic procedure for finding all elements (other organizations, markets, etc.) of the environment to which a given organization is structurally coupled, or will be coupled after redesign. The paper tries to fill the gap by employing enterprise modeling to identify structural couplings. More specifically, an extended Fractal Enterprise Model (FEM) is used for this end. FEM connects enterprise processes with assets that are used in and are managed by these processes. The extended FEM adds concepts to represent external elements and their connections to the enterprise. The paper drafts rules for identifying structural couplings in the model by analyzing FEMs that represent different phases of the development of a company which the author co-founded and worked for over 20 years.

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Acknowledgements

The author expresses his gratitude to the anonymous reviewers whose comments helped to improve the text.

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Authors and Affiliations

  1. DSV, Stockholm University, Stockholm, Sweden

    Ilia Bider

Authors
  1. Ilia Bider
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Correspondence to Ilia Bider .

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Editors and Affiliations

  1. Utrecht University, Utrecht, The Netherlands

    Fabiano Dalpiaz

  2. Stockholm University, Kista, Sweden

    Jelena Zdravkovic

  3. The Institute of Digital Innovation and Research, Dublin, Ireland

    Pericles Loucopoulos

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Bider, I. (2020). Structural Coupling, Strategy and Fractal Enterprise Modeling. In: Dalpiaz, F., Zdravkovic, J., Loucopoulos, P. (eds) Research Challenges in Information Science. RCIS 2020. Lecture Notes in Business Information Processing, vol 385. Springer, Cham. https://doi.org/10.1007/978-3-030-50316-1_6

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  • DOI: https://doi.org/10.1007/978-3-030-50316-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50315-4

  • Online ISBN: 978-3-030-50316-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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