Knowledge-intensive Business Processes—A Case Study for Disease Management in Farming

  • Dagmar Auer
  • Stefan Nadschläger
  • Josef Küng
Conference paper
Part of the Lecture Notes in Information Systems and Organisation book series (LNISO, volume 12)


Knowledge-intensive business processes (KIBPs) are strongly connected with knowledge work (KW). Thus, the definition of KW determines the relevant area of KIBPs. KW characteristics such as rather unstructured processes, user-driven, relying on knowledge, need for flexibility, adaptability, creativity and autonomy of knowledge workers are also associated with KIBPs. However, several authors argue based on their empirical findings that KW often also involves predefined, repetitive tasks besides a lot of creative work. Furthermore, latest trends put more emphasis on the practice of knowing. Based on our understanding of KW, we study a farming business process, which is not regarded as a typical KW domain. However, when looking at the details, many KIBP characteristics can be identified. Based on a use case dealing with disease management, particularly plant protection, in farming, we evaluate our understanding of KIBPs and thus, prepare the basis for the requirements definition concerning supporting models and methods with respect to adequate IT support.


Knowledge-intensive business processes Knowledge work Knowledge management Knowledge processing Farming process 



The scenario in this paper comes from the EU-PF7-Project Nr. 604659 CLAFIS—Crops Livestock and Forests Integrated System for Intelligent Automation, Processing and Control. The research for this paper is partially supported by this EU project and the State of Upper Austria.


  1. 1.
    Drucker, P.F.: Landmarks of Tomorrow: A Report on the New ‘Post-Modern’ World. Harper & Brothers, New York (1959)Google Scholar
  2. 2.
    OECD: OECD Skills Outlook 2013: First Results from the Survey of Adult Skills. OECD Publishing, Paris (2013)Google Scholar
  3. 3.
    Warhurst, C., Thompson, P.: Mapping knowledge in work: proxies or practices? Work Employ Soc. 20(4), 787–800 (2006)Google Scholar
  4. 4.
    Rennstam, J., Ashcraft, K.L.: Knowing work: cultivating a practice-based epistemology of knowledge in organization studies. Hum. Relat. 67(1), 3–25 (2013)Google Scholar
  5. 5.
    CLAFIS: Crop, livestock and forests integrated system for intelligent automation (clafis).
  6. 6.
    Weske, M.: Business Process Management—Concepts, Languages, Architectures, 2nd edn. Springer, Berlin (2012)Google Scholar
  7. 7.
    van der Aalst, W.M.P., Weske, M., Grünbauer, D.: Case handling: a new paradigm for business process support. Data Knowl. Eng. 53(2), 129–162 (2005) (Elsevier B.V.)Google Scholar
  8. 8.
    Pesic, M., van der Aalst, W.M.P.: A declarative approach for flexible business processes management. In: Hutchison, D., et al. (eds.) Business Process Management Workshops, LNCS, vol. 4103, pp. 169–180. Springer, Heidelberg (2006)Google Scholar
  9. 9.
    Reichert, M., Weber, B.: Enabling Flexibility in Process-Aware Information Systems: Challenges, Methods, Technologies, 1st edn. Springer, Heidelberg (2012)Google Scholar
  10. 10.
    Jiménez-Ramírez, A., Weber, B., Barba, I., Del Valle, C.: Generating optimized configurable business process models in scenarios subject to uncertainty. Inf. Softw. Technol. 57, 571–594 (2015) (Elsevier)Google Scholar
  11. 11.
  12. 12.
    OMG, Case Management Model and Notation (CMMN): Version 1.0, formal/2014-05-05,
  13. 13.
    Künzle, V., Reichert, M.: Towards object-aware process management systems: Issues, challenges, benefits. In: Halpin, T., Krogstie, J., Nurcan, S., Proper, E., Schmidt, R., Soffer, P., Ukor, R. (eds.) Enterprise, Business-Process and Information Systems Modeling, 10th International Workshop, BPMDS 2009, and 14th International Conference, EMMSAD 2009, held at CAiSE 2009, Amsterdam, The Netherlands, June 8-9, 2009. Proceedings, LNBIP, vol. 29, pp. 197–210. Springer, Heidelberg (2009)Google Scholar
  14. 14.
    Polanyi, M., Sen, A.K.: The tacit dimension. reissue, with a new foreword by Amartya Sen. Univ. of Chicago Press, Chicago Ill. (2009)Google Scholar
  15. 15.
    Nonaka, I.: The knowledge-creating company. reprint of the 1991 article, managing for the long term, best of hbr, nov.-dec. 1991. Harv. Bus. Rev. 162–171 (2007) (Boston)Google Scholar
  16. 16.
    Dalkir, K.: Knowledge Management in Theory and Practice, 1st edn. Elsevier, USA (2005)Google Scholar
  17. 17.
    McElroy, M.W.: The New Knowledge Management: Complexity, Learning, and Sustainable Innovation. Butterworth-Heinemann, Amsterdam (2003)Google Scholar
  18. 18.
    Lehner, F.: Wissensmanagement: Grundlagen, Methoden und technische Unterstützung, 3rd edn. Hanser, München (2009)Google Scholar
  19. 19.
    Liu S., Parmelee, M.: Introduction to knowledge management,
  20. 20.
    Frey-Luxemburger M.: Wissensmanagement - Grundlagen und praktische Anwendung: Eine Einführung in das IT-gestützte Management der Ressource Wissen. Vieweg+Teubner Verlag, Wiesbaden (2014)Google Scholar
  21. 21.
    Schulz von Thun, F.: Miteinander reden: 1: Störungen und Klärungen. Psychologie der zwischenmenschlichen Kommunikation. Rowohlt, Reinbek bei Hamburg (1985)Google Scholar
  22. 22.
    Bassiliades, N., Governatori, G., Paschke, A. (eds): Rule-Based Reasoning, Programming, and Applications—5th International Symposium, RuleML 2011—Europe, Barcelona, Spain, July 19–21, 2011. Proceedings, LNCS, vol. 6826. Springer (2011)Google Scholar
  23. 23.
    Kelter, J., Rief, S., Bauer, W., Haner, U.E.: Information Work 2009: Office 21-Studie; über die Potenziale von Informations- und Kommunikationstechnologien bei Büro- und Wissensarbeit. Fraunhofer-IRB-Verlag, Stuttgart (2009)Google Scholar
  24. 24.
    Davenport, T.H.: Thinking for a Living: How to get better Performance and Results from Knowledge Workers. Harvard Business School Press, Boston Mass (2005)Google Scholar
  25. 25.
    Isik, Ö., Mertens, W., Van den Bergh, J.: Practices of knowledge intensive process management: quantitative insights. Bus. Process Manag. J. 19(3), 515–534 (2013)Google Scholar
  26. 26.
    Maier, R.: Knowledge Management Systems—Information and Communication Technologies for Knowledge Management, (3rd edn.). Springer, Berlin (2007)Google Scholar
  27. 27.
    Drucker, P.F.: The new society of organizations. Harv. Bus. Rev. 95–104 (1992)Google Scholar
  28. 28.
    Thompson, P., Warhurst, C., Callaghan, G.: Ignorant theory and knowledgeable workers: Interrogating the connections between knowledge, skills and services. J. Manag. Stud. 38(7), 923–942 (2001)Google Scholar
  29. 29.
    Ramírez, Y.W., Nembhard, D.A.: Measuring knowledge worker productivity: a taxonomy. J. Intellect. Capital 5(4), 602–628 (2004)Google Scholar
  30. 30.
    Marjanovic, O.: Towards IS supported coordination in emergent business processes. Bus. Proc. Manag. J. 11(5), 476–487 (2005)Google Scholar
  31. 31.
    Gronau N., Weber, E.: Management of knowledge intensive business processes. In: Desel, J., Pernici, B., Weske M. (eds.): Business Process Management: Second International Conference, BPM 2004. Potsdam, Germany, June 17–18, 2004. LNCS, vol. 3080, pp. 163–178. Springer (2004)Google Scholar
  32. 32.
    Karagiannis, D., Telesko, R.: The EU-project PROMOTE: A process-oriented approach for knowledge management. In: PAKM 2000, Third International Conference on Practical Aspects of Knowledge Management, Proceedings, ser. CEUR Workshop Proceedings, Reimer, U. Ed., vol. 34. (2000)Google Scholar
  33. 33.
    Papavassiliou, G., Mentzas, G., Abecker, A.: Integrating knowledge modelling in business process management, In: Wrycza, S. (ed): Proceedings of the 10th European Conference on Information Systems, Information Systems and the Future of the Digital Economy, ECIS 2002, Gdansk, Poland, June 6–8 2002, pp. 851–861.
  34. 34.
    Remus, U.: Prozessorientiertes Wissensmanagement: Konzepte und Modellierung. Ph.D. dissertation, Universität Regensburg, Regensburg, 31 May 2002
  35. 35.
    Telesko R., Karagiannis, D.: Process-based knowledge management: experiences with two projects. In: Wrycza, S. (ed): Proceedings of the 10th European Conference on Information Systems, Information Systems and the Future of the Digital Economy, ECIS 2002, Gdansk, Poland, June 6–8, 2002, pp. 964–973.
  36. 36.
    Sorensen, C., Pesonen, L., Fountas, S., Suomi, P., Bochtis, D., Bildsøe, P., Pedersen, S.: A user-centric approach for information modelling in arable farming. Comput. Electron. Agric. 73(1): 44–55 (2010) (Elsevier)Google Scholar
  37. 37.
    van der Aalst, W.M.P., Pesic, M., Schonenberg, H.: Declarative workflows: balancing between flexibility and support. Comput. Sci.—R&D, 23(2), 99–113 (2009) (Springer)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute for Application Oriented Knowledge Processing (FAW), Johannes Kepler University Linz (JKU)LinzAustria

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