Skip to main content
SpringerLink
Log in
Book cover

International Conference on Knowledge Management in Organizations

KMO 2018: Knowledge Management in Organizations pp 26–35Cite as

A Model for Data Analysis in SMEs Based on Process Importance

  • Conference paper
  • First Online:

  • 2813 Accesses

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 877))

Abstract

Data analysis technology enables businesses to enrich their business value creation by extracting knowledge. This knowledge extraction is done by knowledge workers. Businesses are seldom able to analyse all their data because the workload for the responsible persons would be too high. So the question which most of the businesses have to deal with is: “Where to start the data analysis” with the fundamental view of increasing the quality of business decisions and process stability. Therefore, the authors conducted a qualitative study based on expert interviews (n = 12) to select the important business processes in a company to start with data analysis enabling efficient business decisions. The result of the study is a set of factors which allows knowledge workers to filter the important knowledge intensive business processes to focus on.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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

References

  1. Maier, R., Hädrich, T., Peinl, R.: Enterprise Knowledge Infrastructures, 2nd edn. Springer, Heidelberg (2009). https://doi.org/10.1007/3-540-27514-2

    Book  Google Scholar 

  2. Maier, R.: Knowledge Management Systems: Information and Communication Technologies for Knowledge Management, 3rd edn. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-71408-8

    Book  Google Scholar 

  3. Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36, 1165–1188 (2012)

    Google Scholar 

  4. Davenport, T.: Competing on analytics. Harv. Bus. Rev. 84, 88–98 (2006)

    Google Scholar 

  5. Wildemann, H.: Wissensmanagement: Leitfaden für die Gestaltung und Implementierung eines aktiven Wissensmanagmeents in Unternehmen. TCW, München (2000)

    Google Scholar 

  6. Remus, U.: Prozessorientiertes Wissensmanagement: Konzepte und Modellierung. University Regensburg, Regensburg (2002)

    Google Scholar 

  7. Edwards, J.S., Kidd, J.B.: Bridging the gap from the general to the specific by linking knowledge management to business processes. In: Hlupic, V. (ed.) Knowledge and Business Process Management, pp. 117–136. Idea Group Publisherauch, Herhsey (2003)

    Google Scholar 

  8. Nonaka, I., Takeuchi, H.: The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, Oxford (1995)

    Google Scholar 

  9. Wildemann, H.: Wissensmanagement: Leitfaden für die Gestaltung und Implementierung eines aktiven Wissensmanagements in Unternehmen. TCW, Munich (2000)

    Google Scholar 

  10. Probst, G., Raub, S., Romhardt, K.: Wissen managen: Wie Unternehmen ihre wertvollste Ressource optimal nutzen. Springer, Wiesbaden (2012). https://doi.org/10.1007/978-3-8349-4563-1

    Book  Google Scholar 

  11. Delahaye, B.: Knowledge management in an SME. Int. J. Organ. Behav. 9, 604–614 (2003)

    Google Scholar 

  12. Statistics Austria. https://www.statistik.at/web_de/statistiken/index.html. Accessed 20 Dec 2017

  13. Desouza, K.C., Awazu, Y.: Knowledge management at SMEs: five peculiarities. J. Knowl. Manag. 10, 32–43 (2006)

    Article  Google Scholar 

  14. Porter, M.: Competitive Advantage: Creating and Sustaining Superior Performance, New York (1985)

    Google Scholar 

  15. Thiesse, F.: Prozessorientiertes Wissensmanagement: Konzepte, Methoden. Fallbeispiele. University St. Gallen, St. Gallen (2001)

    Google Scholar 

  16. Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery in databases. AI Mag. 17, 37–53 (1996)

    Google Scholar 

  17. Bryman, A., Bell, E.: Business Research Methods. Oxford University Press, Oxford (2015)

    Google Scholar 

  18. Carroll, J., Swatman, P.: Structured-case: a methodological framework for building theory in information systems research. Eur. J. Inf. Syst. 9, 235–242 (2000)

    Article  Google Scholar 

  19. Carroll, J., Dawson, L., Swatman, P.: Using case studies to build theory: structure and rigour. In: Proceedings of the 9th Australasian Conference on Information Systems (1998)

    Google Scholar 

  20. Kromrey, H.: Empirische Sozialforschung. UTB, Stuttgart (2002)

    Book  Google Scholar 

  21. Glaser, B.: Theoretical Sensitivity: Advances in the Methodology of Grounded Theory. Sociology Press, Mill Valley (1978)

    Google Scholar 

  22. Heinrich, L., Heinzl, A., Roithmayr, F.: Wirtschaftsinformatik Lexikon, 7th edn. Oldenburg, Wien (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Management Center Innsbruck, Management, Communication and IT, Innsbruck, Austria

    Christian Ploder

  2. Web Technologies and Applications, University of Applied Science FH Kufstein Tirol, Kufstein, Austria

    Michael Kohlegger

Authors
  1. Christian Ploder
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael Kohlegger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christian Ploder .

Editor information

Editors and Affiliations

  1. School of Computing, Staffordshire University, Stafford, United Kingdom

    Lorna Uden

  2. University of Žilina, Žilina, Slovakia

    Branislav Hadzima

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    I-Hsien Ting

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ploder, C., Kohlegger, M. (2018). A Model for Data Analysis in SMEs Based on Process Importance. In: Uden, L., Hadzima, B., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2018. Communications in Computer and Information Science, vol 877. Springer, Cham. https://doi.org/10.1007/978-3-319-95204-8_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-95204-8_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95203-1

  • Online ISBN: 978-3-319-95204-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation