Journal of Intelligent Manufacturing

, Volume 21, Issue 3, pp 311–320 | Cite as

Managing collaboration performance to govern virtual organizations

  • Ingo WestphalEmail author
  • Klaus-Dieter Thoben
  • Marcus Seifert


The ability to collaborate with partners will become an essential core competence that is required from companies when they are going to take up future challenges. Growing complexity of products and services, increasing global competition and accelerated business processes will exceed in many cases the capabilities and capacities of single companies. The involvement of other companies can help to overcome these limitations. However, only what is measured can be managed. Consequently it is necessary to assess the effectiveness and efficiency of how partners work together in joint processes for a common goal. In other word: the collaboration performance has to be measured. But traditional Performance Measurement (PM) methodologies and indicators are designed to assess the performance of single companies or static cooperation like in supply chains. Evaluation and management of collaboration performance as a particular performance perspective in cooperation is not covered by existing approaches so far. Therefore there is still a need for an approach that provides an information basis for the management of collaboration when companies work together in in cooperation. In this paper, which is initially based on a paper presented on the ProVE conference in 2007, different perspectives of collaboration performance are identified and structured. The considerations are based on Virtual Organisations VOs, a particular type of cooperation that requires usually intensive collaborative interactions between the partners.


Collaboration performance Virtual organization Commitment 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Bamford, J., Ernst, D., & Fubini, D. G. (2004). Wie man Weltklasse Joint Venture startet. Harvard Business Manager, 26, May.Google Scholar
  2. Beamon B.M. (1999) Measuring supply chain performance. International Journal of Operations and Production Management 19(3): 275–292CrossRefGoogle Scholar
  3. Bullinger, H.-J, Kiss-Preußinger, E., & Spath, D. (Eds.) (2003). Automobilentwicklung in Deutschland—wie sicher in die Zukunft. Study of Fraunhofer IAO, PROMIND, MVI Group, Stuttgart.Google Scholar
  4. Camarinha-Matos L.M., Abreu A. (2007) Performance indicators for collaborative networks based on collaboration benefits. Journal of Production Planning & Control 18(7): 592–609CrossRefGoogle Scholar
  5. Camarinha-Matos L.M., Afsarmanesh H. (2008) Collaborative networks: Reference modeling. Springer, New yorkGoogle Scholar
  6. Dürmüller, C. (2002). Checkliste für erfolgreiche Allianzen. New Management, No. 6.Google Scholar
  7. ECLOEAD Project, Work Package 3, Deliverable 3.11., 2005.
  8. Graser, F., Jansson, K., Eschenbächer, J., Westphal, I., & Negretto, U. (2005). Towards performance measurement in virtual organisations—potentials, needs, and research challenges. In Proceedings Pro-VE 2005.Google Scholar
  9. Gunasekaran A., Patel C., Tirtiroglu E. (2001) Performance measures and metrics in a supply chain environment. International Journal of Operations & Production Management, Bradford 21(1/2): 71CrossRefGoogle Scholar
  10. Hieber, R. (2002). Collaborative performance measurement in logistics networks : the model, approach and assigned KPIs. Logistik- Management, Nürnberg, 4(2).Google Scholar
  11. Höbig, M. (2002). Modellgestützte Bewertung der Kooperationsfähigkeit produzierender Unternehmen. Fortschritt-Berichte VDI Reihe 16 Nr. 140. Düsseldorf: VDI Verlag.Google Scholar
  12. Jana, P., Narag, A. S., & Knox, A. (2007). Measuring efficiency of a supply chain.Google Scholar
  13. Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard— measures that drive performance. Harvard Business Review, January–February.Google Scholar
  14. Kellen, V. (2003). Business performance measurement; Chicago 2003Google Scholar
  15. Klingebiel, N. (Ed.). (2001). Performance measurement & balanced scorecard. München: Verlag Vahlen.Google Scholar
  16. Kürümlüoglu, M., Nøstdal, R., & Karvonen, I. (2005). Base concepts. In L. Camarinha-Matos, H. Afsarmanesh. & M. Ollus (Eds.), Virtual organizations. Systems and practices. Springer.Google Scholar
  17. Leseure M., Shaw N., Chapman G. (2001) Performance measurement in organisational networks: An exploratory case study. International Journal of Business Performance Management 3(1): 30–46CrossRefGoogle Scholar
  18. Macbeth, D.-K. (2005) Performance measurement in supply chains. Presentation of the IMS-NOW SIg Meeting in Glasgow on 24 Feb 2005.Google Scholar
  19. Reichwald, R., Dannenberg, J., Kelp, R., & Hensel, J. (2005). Management von Unternehmensnetzwerken in der Automobilindustrie— Ergebnisdokumentation für Interviewpartner. Technische Universität München.Google Scholar
  20. Rolstadas A. (1998) Enterprise performance measurement. International Journal of Operations & Production Management 18(9/10): 989–999CrossRefGoogle Scholar
  21. Sandt J. (2005) Performance measurement—Übersicht über Forschungsentwicklung und—stand. Zeitschrift für Controlling & Management 49(6): 429–447Google Scholar
  22. Schweier, H. (2004). Aspekte eines Controlling logistischer Netzwerke. In J. Gericke, M. Kaczmarek, S. Neweling, A. Schulze im Hove, A. Sonnek & F. Stüllenberg (Eds.), Management von Unternehmensnetzwerken. Hamburg: Verlag Dr. Kovač.Google Scholar
  23. Seifert, M. (2007). Unterstützung der Konsortialbildung in Virtuellen Organisationen durch prospectives Performance Measurement. Universität Bremen.Google Scholar
  24. Sennheiser, A. (2004). Determinant based selection of benchmarking partners and logistics performance indicators. PhD-Thesis, ETH Zürich.Google Scholar
  25. Simatupang T.M., Sridharan R. (2004) A benchmarking supply chain collaboration: An empirical study. Benchmarking, An International Journal 11(5): 484–503CrossRefGoogle Scholar
  26. Sivadasan S., Efstathiou J., Frizelle G., Shirazi R., Calinescu A. (2002) An information-theoretic methodology for measuring the operational complexity of the supplier–customer systems. International Journal of Operations & Production 22: 80–102CrossRefGoogle Scholar
  27. Skandia: Visualizing Intellectual Capital in Skandia., Accessed 15 Feb 2007.
  28. Stewart, T. A. (1999). Intellectual capital: The new wealth of organizations. London: Currency Doubleday.Google Scholar
  29. Thoben K.-D., Jagdev H.S. (2001) Typological issues in enterprise networks. Production Planning & Control 12(5): 421–436CrossRefGoogle Scholar
  30. Weber, D. (2005). Strategische Planung im Unternehmensnetzwerk am Beispiel industrieller Dienstleistungen im Industrieanlagenbau Elektronikfertigung. Dissertation, Technische Universität. Braunschweig: Shaker Verlag.Google Scholar
  31. Weber, F. (2007). Formale Interaktionsanalyse—Ein Beitrag zur systematischen Gestaltung von Informations—und Kommunikationsstrukturen im Concurrent Enterprise durch die Berücksichtigung von Informationseigenschaften. Universität Bremen.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Ingo Westphal
    • 1
    Email author
  • Klaus-Dieter Thoben
    • 1
  • Marcus Seifert
    • 1
  1. 1.Bremen Institute for Production and Logistics (BIBA)BremenGermany

Personalised recommendations