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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 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.
References
Bider, I., Perjons, E.: On the concept of discovery power of enterprise modeling languages and its relation to their expressive power. In Malinova Mandelburger, M., Guerreiro, S. (eds.) Advances in Enterprise Engineering XVII. EDEWC 2023, LNBIP, vol. 510, pp. 92–106 (2024)
Bider, I., Perjons, E., Elias, M., Johannesson, P.: A fractal enterprise model and its application for business development. SoSyM 16(3), 663–689 (2017)
Bider, I., Perjons, E., Klyukina, V.: Tool support for fractal enterprise modeling. In: Domain-Specific Conceptual Modeling, pp. 205–229. Springer, Heidelberg (2022)
Polanyi, M.S.: Knowing and Being. University of Chicago, Chicago (1969)
Polanyi, M.: The Structure of Consciousness. Brain LXXXVIII, pp. 799–810 (1965)
Nonaka, I.: A dynamic theory of organizational knowledge creation. Organ. Sci. 5(1), 14–37 (1994)
Hevner, A., March, S.T., Park, J.: Design science in information systems research. MIS Q. 28(1), 75–105 (2004)
Bider, I., Johannesson, P., Perjons, E.: Design science research as movement between individual and generic situation-problem-solution spaces. In: Organizational Systems. An Interdisciplinary Discourse, pp. 35–61. Springer, Cham (2013)
Andersson, B., Bider, I., Perjons, E.: Business process support as a basis for computerized knowledge management. In: Althoff, K., Dengel, A., Bergmann, R., Nick, M., Roth-Berghofer, T. (eds.) Professional Knowledge Management (WM 2005). LNAI, vol. 3782, pp. 542–553. Springer, Heidelberg (2005). https://doi.org/10.1007/11590019_61
Bider, I.: Analysis of agile software development from the knowledge transformation perspective. In: Perspectives in Business Informatics Research. LNBIP, vol. 194, pp. 143–157. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11370-8_11
Bider, I.: Can the systems perspective help in attaining success in software engineering projects? Inquiry into the area of applicability for agile software development. In: Jacobson, J., Lawson, H. (eds.) Software Engineering in the Systems Context: addressing frontiers, practice and education, pp. 423–466. College Publications, London (2015)
Bider, I., Perjons, E.: Identity management in an institution of higher education: a case study using structural coupling and fractal enterprise model. CSIMQ (27), 60–86 (2021)
Bider, I.: Integrating models of observing and observed activities based on an example of empirical research in information systems discipline. CSIMQ, Forthcoming (2023)
Rao, S., Nayak, A.: Enterprise ontology model for tacit knowledge externalization in socio-technical enterprises. Interdiscip. J. Inf. Knowl. Manag. 12, 99–124 (2017)
Dietz, J.L.G.: Understanding and modelling business processes with DEMO. In: 18th International Conference on Conceptual Modelling (ER 1999), pp. 188–202 (1999)
Supulniece, I., Businska, L., Kirikova, M.: Towards extending BPMN with the knowledge dimension. In: BPMDS 2010 and EMMSAD 2010. LNBIP, vol. 50, pp. 69–81. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13051-9_7
Gronau, N., Korf, R., Müller, C.: KMDL-capturing, analysing and improving knowledge-intensive business processes. J. Comput. Sci. 4, 452–472 (2005)
Calhau, R.F., Almeida, J.P.A., Kokkula, S., Guizzardi, G.: Modeling competencies in enterprise architecture: from knowledge, skills, and attitudes to organizational capabilities. Softw. Syst. Model. (2024)
Karagiannis, D., Buchmann, R., Walch, M.: How can diagrammatic conceptual modelling support knowledge management? In: Proceedings of the 25th European Conference on Information Systems (ECIS), Guimarães, 5–10 June 2017, pp. 1568–1583 (2017)
ADOxx.org: ADOxx. https://www.adoxx.org. Accessed January 2024
Smajevic, M., Hacks, S., Bork, D.: Using knowledge graphs to detect enterprise architecture smells. In: Serral, E., Stirna, J., Ralyté, J., Grabis, J., (eds.) The Practice of Enterprise Modeling. PoEM 2021. LNBIP, vol. 432, pp. 48–63. Springer, Heidelberg (2021). https://doi.org/10.1007/978-3-030-91279-6_4
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-031-71333-0_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-71332-3
Online ISBN: 978-3-031-71333-0
eBook Packages: Computer ScienceComputer Science (R0)