Skip to main content

Impact of Granularity on Adjustment Behavior in Adaptive Reuse of Business Process Models

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6336))

Abstract

Business process diagrams as exteriorized forms of distributed organizational knowledge can be valuable assets when shared and reused in similar process design tasks. However, little empirical research has been conducted to shed light on the cognitive processes involved during the adaptation of retrieved process models. We hypothesize that model granularity has significant effects on human adjustment behavior irrespective of the editing distances between reuse and solution models. The results of our laboratory experiment, which is dimensioned according to real-world cases, contribute to a more specific classification of adaptation operations and their cognitive efforts, and refine the notion of process similarity. This study follows up on our former research work by amending minor flaws in the experiment setup; it now provides a comprehensive analytical apparatus for further replicated tests as the predictive power of our explorative study, regarding e.g. varied business contexts and task dimensions, remains limited.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Leontiev, A.N.: Activity, Consciousness, and Personality. Prentice-Hall, Englewood Cliffs (1978)

    Google Scholar 

  2. Majchrzak, A., Cooper, L.P., Neece, O.E.: Knowledge Reuse for Innovation. Management Science 50(2), 174–188 (2004)

    Article  Google Scholar 

  3. March, J.G.: Exploration and Exploitation in Organizational Learning. Organization Science 2(1), 71–87 (1991)

    Article  MathSciNet  Google Scholar 

  4. Frakes, W., Kang, K.: Software reuse research: status and future. IEEE Transactions on Software Engineering 31(7), 529–536 (2005)

    Article  Google Scholar 

  5. Rothenberger, M.A., Dooley, K.J., Kulkarni, U.R., Nada, N.: Strategies for Software Reuse: A Principal Component Analysis of Reuse Practices. IEEE Transactions on Software Engineering 29(9), 825–837 (2003)

    Article  Google Scholar 

  6. Kelly, M.: Enhanced Telecom Operations Map (eTOM) - The Business Process Framework, TeleManagement Forum (2007)

    Google Scholar 

  7. Supply-Chain Council: Supply Chain Operations Reference-model Version 8.0, Supply-Chain Council, Inc. (2006)

    Google Scholar 

  8. Holschke, O., Rake, J., Levina, O.: Granularity as a Cognitive Factor in the Effectiveness of Business Process Model Reuse. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A., et al. (eds.) BPM 2009. LNCS, vol. 5701, pp. 245–260. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Fettke, P., Loos, P.: Classification of reference models: a methodology and its application. Information Systems and E-Business Management 1, 35–53 (2003)

    Article  Google Scholar 

  10. Soffer, P., Reinhartz-Berger, I., Sturm, A.: Facilitating Reuse by Specialization of Reference Models for Business Process Design. In: 8th Workshop on Business Process Modeling, Development, and Support (BPMDS 2007) in Conjunction with the 19th International Conference on Advanced Information Systems Engineering, CAiSE 2007 (2007)

    Google Scholar 

  11. Scaife, M., Rogers, Y.: External cognition: how do graphical representations work? International Journal Human-Computer Studies 45, 185–213 (1996)

    Article  Google Scholar 

  12. Larkin, J.H., Simon, H.A.: Why a diagram is (sometimes) worth ten thousand words. Cognitive Science 11, 65–100 (1987)

    Article  Google Scholar 

  13. Prieto-Diaz, R.: Status report: Software reusability. lEEE Software 10(3), 61–66 (1993)

    Article  Google Scholar 

  14. Reijers, H., Mendling, J.: Modularity in process models: review and effects. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 20–35. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  15. Moody, D.L.: The “Physics” of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering. IEEE Transactions on Software Engineering 35(6), 756–779 (2009)

    Article  Google Scholar 

  16. Batra, D., Wishart, N.A.: Comparing a rule-based approach with a pattern-based approach at different levels of complexity of conceptual data modelling tasks. International Journal of Human-Computer Studies 61(4), 397–419 (2004)

    Article  Google Scholar 

  17. Plous, S.: The Psychology of Judgment and Decision Making. McGraw-Hill, New York (1993)

    Google Scholar 

  18. Parsons, J., Saunders, C.: Cognitive Heuristics in Software Engineering: Applying and Extending Anchoring and Adjustment to Artifact Reuse. IEEE Trans. Software Eng., 873–888 (2004)

    Google Scholar 

  19. Yao, Y.: Probabilistic approaches to rough sets. Expert Systems 20(5), 287–297 (2003)

    Article  Google Scholar 

  20. Yao, Y.: A Partition Model of Granular Computing. LNCS Transactions on Rough Sets 1, 232–253 (2004)

    Article  Google Scholar 

  21. United Nations Centre for Trade Facilitation and Electronic Business (UN/CEFACT): Core Components Technical Specification, Version 3.0, United Nations (September 29, 2009)

    Google Scholar 

  22. Gemino, A., Wand, Y.: Evaluating modeling techniques based on models of learning. Requirements Engineering 9(4), 248–260 (2004)

    Article  Google Scholar 

  23. Teo, H.-H., Chan, H.C., Wei, K.K.: Performance Effects of Formal Modeling Language Differences: A Combined Abstraction Level and Construct Complexity Analysis. IEEE Transactions on Professional Communication 49(2), 160–175 (2006)

    Article  Google Scholar 

  24. Mendling, J., Reijers, H.A., Recker, J.: Activity labeling in process modeling: Empirical insights and recommendations. Information Systems 35(4), 467–482 (2009)

    Article  Google Scholar 

  25. Kerlinger, F.N.: Foundations of Behavioral Research, 3rd edn. Holt, Rinehart and Winston, Orlando, FL (1986)

    Google Scholar 

  26. Lindland, I., Sindre, G., Solvberg, A.: Understanding quality in conceptual modeling. IEEE Software 11, 42–49 (1994)

    Article  Google Scholar 

  27. Krogstie, J., Sindre, G., Jørgensen, H.: Process models representing knowledge for action: a revised quality framework. European Journal of Information Systems 15, 91–102 (2006)

    Article  Google Scholar 

  28. Davies, I., Green, P., Rosemann, M., Indulska, M., Gallo, S.: How do practitioners use conceptual modeling in practice? Data & Knowledge Engineering 58, 358–380 (2006)

    Article  Google Scholar 

  29. Khatri, V., Vessey, I., Ramesh, V., Clay, P., Park, S.-J.: Understanding Conceptual Schemas: Exploring the Role of Application and IS Domain Knowledge. Information Systems Research 17(1), 81–99 (2006)

    Article  Google Scholar 

  30. Ehrig, M., Koschmider, A., Oberweis, A.: Measuring Similarity between Semantic Business Process Models. In: Fourth Asia-Pacific Conference on Conceptual Modelling (APCCM 2007). Australian Computer Society, Inc., Ballarat (2007)

    Google Scholar 

  31. Dijkman, R., Dumas, M., García-Banuelos, L.: Graph Matching Algorithms for Business Process Similarity Search. In: Dayal, U., et al. (eds.) BPM 2009. LNCS, vol. 5701, pp. 48–63. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  32. van Dongen, B.F., Dijkman, R.M., Mendling, J.: Measuring Similarity between Business Process Models. In: Bellahsène, Z., Léonard, M. (eds.) CAiSE 2008. LNCS, vol. 5074, pp. 450–464. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  33. Robinson, P.: Task Complexity, Task Difficulty, and Task Production: Exploring Interactions in a Componential Framework. Applied Linguistics 22(1), 27–57 (2001)

    Article  Google Scholar 

  34. Campbell, D.J.: Task Complexity: A Review and Analysis. Academy of Management Review 13(1), 40–52 (1988)

    Article  Google Scholar 

  35. Larkey, L.S.: Automatic Essay Grading Using Text Categorization Techniques. In: 21st annual international ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 90–95. ACM, New York (1998)

    Chapter  Google Scholar 

  36. Prabhu, N.: Second Language Pedagogy. Oxford University Press, Oxford (1987)

    Google Scholar 

  37. Signavio GmbH: Signavio (2009), http://academic.signavio.com [cited 17.3.2010]

  38. Boh, W.F.: Reuse of knowledge assets from repositories: a mixed methods study. Information & Management 45 (July) 365–375 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Holschke, O. (2010). Impact of Granularity on Adjustment Behavior in Adaptive Reuse of Business Process Models . In: Hull, R., Mendling, J., Tai, S. (eds) Business Process Management. BPM 2010. Lecture Notes in Computer Science, vol 6336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15618-2_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15618-2_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15617-5

  • Online ISBN: 978-3-642-15618-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics