Skip to main content

Analysis of Imprecise Enterprise Models

Part of the Lecture Notes in Business Information Processing book series (LNBIP,volume 248)


Enterprises have a large amount of Information Technology (IT) elements for supporting their business. Enterprise models represent the state of IT and business elements and the relation between them in a certain moment. However, in some cases it is difficult to build models that accurately represent the enterprise because information may vary fast over time, or because the granularity of the model may be inadequate for its purpose. When models that are imprecise and do not represent accurately the enterprise are used to perform analysis, it is necessary to evaluate their suitability and determine whether they can be used or if better models have to be constructed. In this paper, we focus on this problem and propose an approach for evaluating the level of imprecision of enterprise models based on the impact and sensitivity of imprecise information regarding an analysis method.


  • Enterprise modeling
  • Enterprise analysis
  • Models imprecision

This is a preview of subscription content, access via your institution.

Buying options

USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions


  1. 1.


  1. Jonkers, H., Lankhorst, M., Van Buuren, R., Hoppenbrouwers, S., Bonsangue, M., Van Der Torre, L.: Concepts for modeling enterprise architectures. Int. J. Coop. Inf. Syst. 13(03), 257–287 (2004)

    CrossRef  Google Scholar 

  2. Bézivin, J.: On the unification power of models. Softw. Syst. Model. 4(2), 171–188 (2005)

    CrossRef  Google Scholar 

  3. Ludewig, J.: Models in software engineering–an introduction. Softw. Syst. Model. 2(1), 5–14 (2003)

    CrossRef  Google Scholar 

  4. Lankhorst, M.: Enterprise architecture at work: Modelling, communication and analysis. Springer, Heidelberg (2013)

    CrossRef  Google Scholar 

  5. Lagerström, R., Franke, U., Johnson, P., Ullberg, J.: A method for creating enterprise architecture metamodels-applied to systems modifiability analysis. Int. J. Comput. Sci. Appl. 6(5), 89–120 (2009)

    Google Scholar 

  6. Kurpjuweit, S., Winter, R.: Viewpoint-based Meta Model Engineering. In: Proceedings of the 2nd International Workshop on Enterprise Modelling and Information Systems Architectures, pp. 143–161 (2007)

    Google Scholar 

  7. Frank, U.: Multi-perspective enterprise modeling: foundational concepts, prospects and future research challenges. Softw. Syst. Model. 13(3), 941–962 (2014)

    CrossRef  Google Scholar 

  8. Avila, O., Goepp, V., Kiefer, F.: Understanding and classifying information system alignment approaches. J. Comput. Inf. Syst. 50(1), 2–14 (2009)

    Google Scholar 

  9. Henricksen, K., Indulska, J.: Modelling and using imperfect context information. In: Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops, 2004, pp. 33–37. IEEE (2004)

    Google Scholar 

  10. Buckl, S., Matthes, F., Schweda, C.M.: Classifying enterprise architecture analysis approaches. In: Poler, R., van Sinderen, M., Sanchis, R. (eds.) IWEI 2009. LNBIP, vol. 38, pp. 66–79. Springer, Heidelberg (2009)

    CrossRef  Google Scholar 

  11. Florez, H., Sanchez, M., Villalobos, J.: A catalog of automated analysis methods for enterprise models. SpringerPlus 5, 1–24 (2016)

    CrossRef  Google Scholar 

  12. Holschke, O.: Impact of granularity on adjustment behavior in adaptive reuse of business process models. In: Hull, R., Mendling, J., Tai, S. (eds.) BPM 2010. LNCS, vol. 6336, pp. 112–127. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  13. Florez, H., Sanchez, M., Villalobos, J.: iArchiMate: a tool for managing imperfection in enterprise models. In: 18th IEEE International Enterprise Distributed Object Computing Conference Workshops and Demonstrations (EDOCW), pp. 201–210. IEEE (2014)

    Google Scholar 

  14. Johnson, P., Johansson, E., Sommestad, T., Ullberg, J.: A tool for enterprise architecture analysis. In: 11th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2007), pp. 142–142. IEEE, October 2007

    Google Scholar 

  15. Florez, H., Sanchez, M., Villalobos, J.: Extensible model-based approach for supporting automatic enterprise analysis. In: 18th IEEE International Enterprise Distributed Object Computing Conference (EDOC), pp. 32–41 (2014)

    Google Scholar 

  16. Morrissey, J.M.: Imprecise information and uncertainty in information systems. ACM Trans. Inf. Syst. (TOIS) 8(2), 159–180 (1990)

    CrossRef  Google Scholar 

  17. Loshin, D.: The practitioner’s guide to data quality improvement. Elsevier, Amsterdam (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Hector Florez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Florez, H., Sánchez, M., Villalobos, J. (2016). Analysis of Imprecise Enterprise Models. In: Schmidt, R., Guédria, W., Bider, I., Guerreiro, S. (eds) Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2016 2016. Lecture Notes in Business Information Processing, vol 248. Springer, Cham.

Download citation