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Information Systems Frontiers

, Volume 13, Issue 5, pp 621–636 | Cite as

SimKnowledge—Analyzing impact of knowledge management measures on team organizations with multi agent-based simulation

  • René PeinlEmail author
  • Ronald Maier
Article

Abstract

Even though there is abundant literature on successful cases of organizations applying knowledge management (KM) measures, many KM initiatives have failed to achieve their knowledge and business goals. In order to foster decisions about the design of such initiatives, information is required on success factors and barriers when selecting KM measures. Multi agent-based simulation (MABS) is suggested as instrument to investigate potential effects of KM measures on dependent variables such as sharing of knowledge in organizations or business performance. For such a simulation, the concept of knowledge sharing, influencing factors and their impact on business and knowledge goals are modeled based on an extensive multi-disciplinary literature survey. An extensive domain model is operationalized in a simulation model which is then further simplified and implemented in a MABS tool used for a series of experiments contrasting results with/without KM measures, specifically skill and experience management. Skill management is found highly sensitive with respect to conditions of application and has no significant impact on knowledge or business goals. Experience management positively impacts knowledge and business goals. Personal documentation leads to specialist, project debriefings to generalist knowledge workers. Finally, the paper discusses the simulation’s limitations and further areas of application.

Keywords

Knowledge management Knowledge sharing Knowledge work Multi agent-based simulation Team organization 

References

  1. Alavi, M., & Leidner, D. E. (2001). Review: knowledge management and knowledge management systems: conceptual foundations and research issues. Management Information Systems Quarterly, 25(1), 107–136.CrossRefGoogle Scholar
  2. Alvesson, M. (2004). Knowledge work and knowledge-intensive firms. Oxford: Oxford University Press.Google Scholar
  3. Anderson, J. R. (1976). Language, memory, and thought. Hillsdale: Erlbaum.Google Scholar
  4. Anderson, J. R. (1996). ACT—a simple theory of complex cognition. American Psychologist, 51, 355–365.CrossRefGoogle Scholar
  5. Anjewierden, A., Shostak, I., & de Hoog, R. (2002). KMsim—a meta-modelling approach and environment for creating process-oriented knowledge management simulations, 13th European Conference on Knowledge Acquisition, Management and Modelling (EKAW), Sigüenza, 65–79.Google Scholar
  6. Argote, L., et al. (2000). Knowledge transfer in organizations—learning from the experience of others. Organizational Behavior and Human Decision Processes, 82(1), 1–8.CrossRefGoogle Scholar
  7. Berends, H., van der Bij, H., Debackere, K., & Weggeman, M. (2004). Knowledge sharing mechanisms in industrial research, Working Paper 04.04, Eindhoven Centre for Innovation Studies, Eindhoven.Google Scholar
  8. Berends, H., van der Bij, H., Debackere, K., & Weggeman, M. (2006). Knowledge sharing mechanisms in industrial research. R&D Management, 36(1), 85–95.CrossRefGoogle Scholar
  9. Bishop, J., Bouchlaghem, D., Glass, J., & Matsumoto, I. (2008). Ensuring the effectiveness of a knowledge management initiative. Journal of Knowledge Management, 12(4), 16–29.CrossRefGoogle Scholar
  10. Boer, N.-I., & Berends, H. (2003). The relational dimension of knowledge sharing—an empirical study of an industrial research group, 4th European Conference on Organizational Knowledge, Learning and Capabilities (OKLC 2003), Barcelona, Spain.Google Scholar
  11. Boer, N.-I., van Baalen, P. J., & Kumar, K. (2002). An activity theory approach for studying the situatedness of knowledge sharing. 35th Hawaii International Conference on System Sciences (HICSS 2002). 2002. Big Island, Hawaii.Google Scholar
  12. Canals, A., Boisot, M., & MacMillan, I. (2004). Evolution of knowledge management strategies in organizational populations: a simulation model. IN3-UOC Working Paper Series, WP04-007.Google Scholar
  13. Carley, K. M. (1992). Organizational learning and personnel turnover. Organization Science, 3(1), 20–46.CrossRefGoogle Scholar
  14. Carley, K. M. (2002). Information technology and knowledge distribution in C3I teams. Command and Control Research and Technology Symposium. 2002. Naval Postgraduate School, Monterey, CA.Google Scholar
  15. Clancey, W. J. (1997). Situated cognition—on human knowledge and computer representation. Cambridge: Cambridge University Press.Google Scholar
  16. Cohen, D. (1998). Toward a knowledge context—report on the First Annual U.C. Berkeley forum on knowledge and the firm. California Management Review, 40(3), 22–39.Google Scholar
  17. Cowan, R., & Jonard, N. (2004). Network structure and the diffusion of knowledge. Journal of Economic Dynamics & Control, 28(8), 1557–1575.CrossRefGoogle Scholar
  18. Davenport, T. H., Probst, G. J. B. (2002). Knowledge management case book. Best Practises, 2nd ed., Erlangen.Google Scholar
  19. Davenport, T. H., Jarvenpaa, S. L., & Beers, M. C. (1996). Improving knowledge work processes. Sloan Management Review, 37(4), 53–65.Google Scholar
  20. Dervisoglua, G., & Berberb, A. (2004). Knowledge flow during the product development process and role of the mediator—a model presentation. 37th Hawaii International Conference on System Sciences (HICSS 2004), Big Island, Hawaii.Google Scholar
  21. Dreyfus, H. (2002). A phenomenoloy of skill acquisition as the basis for a Merleau-Pontian non-representationalist cognitive science, International Conference Foundations and the Ontological Quest. Prospects for the New Millenium, Rome, Pontifical Lateran University.Google Scholar
  22. Drucker, P. F. (1994). The age of social transformation. The Atlantic Monthly, 274(5), 53–80.Google Scholar
  23. Elliman, T., Eatock, J., & Spencer, N. (2005). Modelling knowledge worker behaviour in business process studies. Journal of Enterprise Information Management, 18(1), 79–94.CrossRefGoogle Scholar
  24. Engeström, Y. (2000). Activity theory and the social construction of knowledge—a story of four Umpires. Organization, 7(2), 301–310.CrossRefGoogle Scholar
  25. Fayol, M. (1994). From declarative and procedural knowledge to the management of declarative and procedural knowledge. European Journal of Psychology of Education, 9(3), 179–190.CrossRefGoogle Scholar
  26. Fiske, A. P. (1991). Structures of social life—the four elementary forms of human relations. New York: Free Press.Google Scholar
  27. Gobet, F., Lane, P. C. R., Croker, S., Cheng, P. C. H., Jones, G., Oliver, I., et al. (2001). Chunking mechanisms in human learning. Trends in Cognitive Sciences, 5(6), 236–243.CrossRefGoogle Scholar
  28. Graefe, G. (2003). Incredible information on the internet—biased information provision and a lack of credibility as a cause of insufficient information quality, 8th International Conference on Information Quality (ICIQ 2003), Cambridge, MA.Google Scholar
  29. Hanakawa, N., Matsumoto, K.-I., & Torii, K. (2002). A knowledge-based software process simulation model. Annals of Software Engineering, 14, 383–406.CrossRefGoogle Scholar
  30. Hansen, M. T., Nohria, N., & Tierney, T. (1999). What’s your strategy for managing knowledge? Harvard Business Review, 77(3–4), 106–116.Google Scholar
  31. Holsapple, C. W. (Ed.). (2003). Handbook on knowledge management, vol. 1+2. Berlin: Springer.Google Scholar
  32. Holsapple, C. W., & Joshi, K. D. (2000). An investigation of factors that influence the management of knowledge in organizations. Journal of Strategic Information Systems, 9(2–3), 235–261.CrossRefGoogle Scholar
  33. Inuzuka, A. (2003). How to share knowledge effectively? In T. Terano, H. Deguchi, & K. Takadama (Eds.), Meeting the challenge of social problems via agent-based simulation (pp. 123–137). Tokio: Springer.CrossRefGoogle Scholar
  34. Laird, J. E., Newell, A. F., & Rosenbloom, P. S. (1986). Chunking in soar—the anatomy of a general learning mechanism. Machine Learning, 1(1), 11–46.Google Scholar
  35. Lang, J., van der Torre, L., & Weydert, E. (2000). Utilitarian desires. Autonomous Agents and Multi-Agent Systems, 5(3), 329–363.CrossRefGoogle Scholar
  36. Lethbridge, T. C. (1999). The relevance of education to software practitioners—data from the 1998 Survey, Technical Report TR-99-06, School of Information Technology and Engineering, University of Ottawa.Google Scholar
  37. Maier, R. (2007). Knowledge management systems—information and communication technologies for knowledge management (3rd ed.). Berlin: Springer.Google Scholar
  38. Maier, R., Thalmann, S., Bayer, F., Krüger, M., Nitz, H., & Sandow, A. (2008). Optimizing assignment of knowledge workers to office space using knowledge management criteria—the flexible office case. Journal of Universal Computer Science, 14(4), 508–525.Google Scholar
  39. Maier, R., Hädrich, T., & Peinl, R. (2009). Enterprise knowledge infrastructures (2nd ed.). Berlin: Springer.Google Scholar
  40. Martinez-Miranda, J., & Aldea, A. (2002). A social agent model to simulate human behaviour in teamwork, 3rd Workshop on Agent-Based Simulation, Passau, 18–23Google Scholar
  41. Meredith, R., & Burstein, F. (2000). Getting the message across with communicative knowledge management. Australian Conference on Knowledge Management and Intelligent Decision Support (ACKMIDS), Monash University, Australia.Google Scholar
  42. Mi, P., & Scacchi, W. (1990). A knowledge-based environment for modeling and simulating software engineering processes. IEEE Transactions on Knowledge and Data Engineering, 2(3), 283–294.CrossRefGoogle Scholar
  43. Moreno, A., Valls, A., & Marín, M. (2003). Multi-agent simulation of work teams, 3rd International/Central and Eastern European Conference on Multi-Agent Systems, CEEMAS, Prague, Czech Republic, 281–291.Google Scholar
  44. Müller, J. P. (1996). The design of intelligent agents—a layered approach. Berlin: Springer.Google Scholar
  45. Nissen, M. E. (2002). An extended model of knowledge-flow dynamics. Communications of the Association for Information Systems, 8, 251–266 (online).Google Scholar
  46. Nissen, M. E. (2006). Harnessing knowledge dynamics: Principled organizational knowing & learning. Hershey: IRM Press.Google Scholar
  47. Nissen, M. E., & Levitt, R. E. (2004). Agent-based modeling of knowledge flows: Illustration from the Domain of Information Systems Design, 37th Hawaii International Conference on System Sciences (HICSS 2004), Big Island, Hawaii.Google Scholar
  48. Nissen, M. E., Kamel, M., & Sengupta, K. (2000). Integrated analysis and design of knowledge systems and processes. Information Resources Management Journal, 13(1), 23–43.CrossRefGoogle Scholar
  49. Nonaka, I. (1991). The knowledge-creating company. Harvard Business Review, 69(11–12), 96–104.Google Scholar
  50. Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37.CrossRefGoogle Scholar
  51. Paauwe, J. (2004). HRM and performance—achieving long term viability. New York: Oxford University Press.Google Scholar
  52. Peinl, R. (2008). Multiagentensimulation der Wissensweitergabe in Organisationen am Beispiel von Individualsoftwareherstellern, PhD Thesis, Martin Luther University Halle-Wittenberg, Germany.Google Scholar
  53. Petre, M., & Blackwell, A. F. (1997). A glimpse of expert programmers’ mental imagery. 7th Workshop on Empirical studies of programmers, Alexandria, VA, 109–123.Google Scholar
  54. Pinder, C. C. (1998). Work motivation in organizational behavior. Upper Saddle River: Prentice Hall.Google Scholar
  55. Polanyi, M. (1966). The Tacit Dimension, London.Google Scholar
  56. Probst, G., Raub, S., Romhardt, K. (1998). Wissen managen: Wie Unternehmen ihre wertvollste Ressource optimal nutzen, 2nd edition, Wiesbaden.Google Scholar
  57. Rao, A. S., & Georgeff, M. P. (1995). BDI agents: from theory to practice. Technical Note 56, Australian Artificial Intelligence Institute.Google Scholar
  58. Rich, E. H., & Duchessi, P. (2004). Modeling the sustainability of knowledge management programs, 37th Hawaii International Conference on System Sciences (HICSS 2004), Big Island, Hawaii.Google Scholar
  59. Rubinstein, A. (2002). Modeling bounded rationality, 3rd print. Cambridge: MIT Press.Google Scholar
  60. Ruthruff, E., Remington, R. W., & Johnston, J. C. (2001). Switching between simple cognitive tasks: the interaction of top-down and bottom-up factors. Journal of Experimental Psychology: Human Perception and Performance, 27, 1404–1419.CrossRefGoogle Scholar
  61. Shostak, I., Anjewierden, A., de Hoog, R. (2002). Modelling and Simulating Process-Oriented Knowledge Management, Proceedings of the 3rd European Conference on Knowledge Management (ECKM), Dublin, Ireland, S. 634–648.Google Scholar
  62. Song, M., van der Bij, H., & Weggeman, M. (2003). An empirical investigation into the antecedents of knowledge dissemination at the strategic business unit level. Journal of Product Innovation Management, 20(2), 163–179.CrossRefGoogle Scholar
  63. Squire, L. R. (1987). Memory and brain. New York: Oxford.Google Scholar
  64. Starbuck, W. H. (1992). Learning by knowledge-intensive firms. Journal of Management Studies, 29(6), 713–740.CrossRefGoogle Scholar
  65. Steers, R. M., Mowday, R. T., & Shapiro, D. L. (2004). The future of work motivation theory. Academy of Management Review, 29(3), 379–387.Google Scholar
  66. Sveiby, K.-E., & Lloyd, T. (1987). Managing knowhow. London: Bloomsbury Publishing.Google Scholar
  67. Szulanski, G. (1996). Exploring internal stickiness: Impediments to the transfer of best practice within the firm, in: Strategic Management Journal, Vol. 17, 1996, Winter Special Issue, 27–43.Google Scholar
  68. Thomas-Hunt, M. C., Ogden, T. Y., & Neale, M. A. (2003). Who’s really sharing? Effects of social and expert status on knowledge exchange within groups. Management Science, 49(4), 464.CrossRefGoogle Scholar
  69. Tsai, W. (2001). Knowledge transfer in intraorganizational networks—effects of network position and absorptive capacity on business unit innovation and performance. Academy of Management Journal, 44(5), 996.CrossRefGoogle Scholar
  70. Tsui, E. (2005). The role of IT in KM: where are we now and where are we heading? Journal of Knowledge Management, 9(1), 3–6.CrossRefGoogle Scholar
  71. Turner, S. F., Bettis, R. A., & Burton, R. M. (2002). Exploring depth versus breadth in knowledge management strategies. Computational & Mathematical Organization Theory, 8(1), 49–73.CrossRefGoogle Scholar
  72. Urban, C., & Schmidt, B. (2001). PECS—agent-based modelling of human behaviour, emotional and intelligent II—the tangled knot of social cognition, AAAI Fall Symposium 2001, North Falmouth, MA.Google Scholar
  73. Wang, J., Gwebu, K., Shanker, M., & Troutt, M. D. (2009). An application of agent-based simulation to knowledge sharing. Decision Support Systems, 46, 532–541.CrossRefGoogle Scholar
  74. Wiig, K. M. (1988). Management of knowledge: perspectives of a new opportunity. In: T. Bernold (Ed.), User interfaces: gateway or bottleneck? Proceedings of the Technology Assessment and Management Conference of the Gottlieb Duttweiler Institute Rüschlikon/Zurich (CH), 20–21 October, 1986, Amsterdam, 101–116.Google Scholar
  75. Wolff, E. N. (2005). The growth of information workers. Communications of the ACM, 48(10), 37–42.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.IPI GmbHLichtenauGermany
  2. 2.Department of Information SystemsUniversity of InnsbruckInnsbruckAustria

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