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Multi-perspective enterprise modeling: foundational concepts, prospects and future research challenges

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Abstract

The paper presents a method for multi- perspective enterprise modeling (MEMO) and a corresponding (meta-) modeling environment. An extensive analysis of requirements for enterprise modeling serves to motivate and assess the method. The method is based on an elaborate conception of multi-perspective enterprise models and on an extensible language architecture. The language architecture is comprised of a meta modeling language and an extensible set of integrated domain-specific modeling languages (DSML). The DSML are supplemented with process models and with guidelines for their reflective use. The corresponding modeling environment integrates editors for various DSML into multi-language model editors. It includes a meta model editor which enables the convenient use, development and extension of the set of supported DSML and supports the generation of respective graphical model editors. Thus, it also serves as a foundation for method engineering. MEMO covers both software engineering as well as social, managerial and economic aspects of the firm. The presentation of MEMO is supplemented with a comparative overview of other approaches to enterprise modeling. The paper concludes bys summarizing fundamental technical, epistemological and political challenges for enterprise modeling research and discusses potential paths for future research.

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Notes

  1. For a comprehensive documentation of the reference models see http://www.wi-inf.uni-duisburg-essen.de/FGFrank/ecomod/.

  2. http://www.metacase.com/.

  3. http://www.semture.de/de/cubetto-toolset.

  4. While “TOGAF” looks like an acronym, it seems not to be dissolved in the official documents.

  5. http://www.opengroup.org/archimate/doc/ts_archimate/.

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Correspondence to Ulrich Frank.

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Communicated by Dr. Tony Clark, Balbir Barn, Alan Brown, and Florian Matthes.

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Frank, U. Multi-perspective enterprise modeling: foundational concepts, prospects and future research challenges. Softw Syst Model 13, 941–962 (2014). https://doi.org/10.1007/s10270-012-0273-9

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