Abstract
Business Process Management is considered to be an up-to-date approach to an organization’s operation, while process structures offer a sense of order. Knowledge resources are treated as inseparable elements of operation of processes. Moreover Knowledge Management may not be separate from Business Process Management. Modeling of the process of Knowledge Management is intended to systematize these informal rules and relations existing in process-based organizations. The main aim of this paper is to identify the modeling of the process of Knowledge Management in enterprises, which implemented Business Process Management. The article presents selected research results carried out in Poland on 122 process-oriented enterprises.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bitkowska, A.: Od klasycznego do zintegrowanego zarzadzania procesowego [From Classic to Integrated Business Process Management]. C.H. Beck, Warszawa (2019)
Burlton, R.: Business Process Management: Profiting From Process. SAMS. Pearson Education, London (2001)
Davenport, T., Prusak, L.: Working Knowledge: How Organizations Manage What They Know. Harvard Business School Press, Boston (1997)
Guide to the Business Process Management Common Body of Knowledge
Harmon, P.: Business Process Change, 2nd edn. Morgan Kaufmann Publishers, Burlington (2007)
Hislop, D.: Knowledge Management in Organizations: A Critical Introduction. Oxford University Press, Oxford (2013)
Indulska, M., Green, P., Recker, J.C., Rosemann, M.: Business process modelling: perceived benefits. In: 28th International Conference on Conceptual Modelling, 9–12 November 2009, Gramado, Brazil (2009)
Jeston, J., Nelis, J.: Business Process Management: Practical Guidelines to Successful Implementations. Routledge, London and New York (2014)
Maier, R., Remus, U.: Defining process-oriented knowledge management strategies. Knowl. Process Manag. 7(4), 103 (2002)
Nonaka, I., Takeuchi, H.: The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation, p. 284. Oxford University Press, New York (1995)
Probst, G., Raub, S., Romhardt, K.: Managing Knowledge. Wiley, London (2000)
Process Classification Framework PCF APQC, Cross Industry. https://www.apqc.org. Accessed 12 June 2019
Recker, J., Rosemann, M., Indulska, M., Green, P.: Business process modelling: a comparative analysis. J. Assoc. Inf. Syst. 10, 333–363 (2009)
Richter-von Hagen, C., Ratz, D., Povalej, R.: A genetic algorithm approach to self-organizing knowledge intensive processes. In: Proceedings of I-KNOW 2005, Graz, Austria (2005)
Smith, H., Fingar, P.: Business Process Management: The Third Wave. Meghan-Kiffer Press, Tampa (2003)
Trocki, M.: Inteligencja procesowa, czyli inteligentne zarządzanie procesowe [Process intelligence, Intelligent Business Process Management]. Studia i Prace Kolegium Zarządzania i Finansów Szkoły Głównej Handlowej, Zeszyt Naukowy, nr 149, Warszawa (2016)
Vaccaro, A., Parente, R., Veloso, F.M.: Knowledge management tools, inter-organizational relationships, innovation and firm performance. Technol. Forecast. Soc. Change 77(7), 1076–1089 (2010)
Zhu, P.: Knowledge Management (KM) vs. Business Process Management (BPM) (2015). http://futureofcio.blogspot.de/2013/10/knowledge-management-km-vs-business.html. Accessed 12 June 2019
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Bitkowska, A. (2019). Business Process Management vs Modeling of the Process of Knowledge Management in Contemporary Enterprises. In: Di Ciccio, C., et al. Business Process Management: Blockchain and Central and Eastern Europe Forum. BPM 2019. Lecture Notes in Business Information Processing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-030-30429-4_22
Download citation
DOI: https://doi.org/10.1007/978-3-030-30429-4_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30428-7
Online ISBN: 978-3-030-30429-4
eBook Packages: Computer ScienceComputer Science (R0)