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Discovery Rules for Depicting Tacit Knowledge Usage and Management in Fractal Enterprise Models

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Perspectives in Business Informatics Research (BIR 2024)

Abstract

The paper introduces rules to help identify and depict in a model enterprise activities that engage tacit knowledge. This is done using a specific enterprise modeling technique called Fractal Enterprise Model (FEM). However, the result can be of interest to researchers and practitioners using other modeling techniques. Though representing tacit knowledge is more or less mandatory for research and practice of Knowledge Management (KM), it is very seldom depicted explicitly in enterprise models of any kind. The type of rules presented in this paper follows our suggestion to consider the so-called discovery power of enterprise modeling languages alongside its expressive power.

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Notes

  1. 1.

    The term degree used in the informal definition does not imply that discovery power is a quantitative parameter. As the discovery power of different modeling languages lies in different areas, a quantitative description does not make much sense. The high discovery in the area that lies outside the current project goals will be irrelevant to the project. For example, a language with good discovery power related to tacit knowledge may not be useful for a project that is not intended to depict such knowledge.

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Acknowledgment

The work of the first author was partly supported by the Estonian Research Council (grant PRG1226). The authors are also grateful to the anonymous reviewers whose comments helped improve the text.

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Correspondence to Ilia Bider .

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Bider, I., Perjons, E. (2024). Discovery Rules for Depicting Tacit Knowledge Usage and Management in Fractal Enterprise Models. In: Řepa, V., Matulevičius, R., Laurenzi, E. (eds) Perspectives in Business Informatics Research. BIR 2024. Lecture Notes in Business Information Processing, vol 529. Springer, Cham. https://doi.org/10.1007/978-3-031-71333-0_14

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  • DOI: https://doi.org/10.1007/978-3-031-71333-0_14

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