Knowledge Generating Decision Support Systems: Managing the Trade-Off Between Generating Knowledge and Supporting Decisions
The aim of the paper is to analyze the effectiveness of Decision Support Systems (DSS) in the business planning area, especially with regard to the trade-off between supporting decisions and generating knowledge.
The research hypothesis is that different conditions and approaches in managing the planning DSS may strengthen either decisional support or the knowledge generation capability.
The IT tools used;
The formalization criteria which defines relationships between the variables;
The interaction between the decision maker and the model;
The interaction between the decision maker and organizational context, according to Nonaka’s framework (Nonaka I. (1991) The Knowledge-Creating Company, Harvard Business Review, Nov/Dec, Vol. 69(6):96–104).
The paper also discusses the reasons why a closed model is more suitable for supporting decisions, and an open model is more appropriate for generating knowledge. In addition, the research hypothesis will be empirically tested with a panel of users.
KeywordsDecision Maker Open Model Expert System Decision Support System Tacit Knowledge
- 2.McGraw K. And Harbison-Briggs K.A (1989) Knowledge Acquisition: Principles and Guidelines, Prentice-Hall, NJ.Google Scholar
- 6.Simon H.A. (1960) The New Science of Management Decision, Harper and Row, Prentice Hall.Google Scholar
- 7.Power D.J. (2002) Decision Support Systems: Concepts and Resources for Managers, Quorum Books, Westport.Google Scholar
- 9.Larman C. (2007) Agile and Iterative Development: A Manager’s Guide, Addison-Wesley, Pearson Education.Google Scholar
- 10.Kent B. (2000) Extreme Programming Explained: Embrace Change, Addison-Wesley.Google Scholar
- 11.Drucker P. (1995) The Post-Capitalist Executive: Managing in a Time of Great Change, Penguin, New York.Google Scholar
- 12.Sanin C., Szczerbicki E. (2004) Knowledge Supply Chain System: A Conceptual Model, Knowledge Management: Selected Issues, Szuwarzynski A. (Ed), Gdansk University Press/Gdansk, 79–97.Google Scholar
- 13.Sanin C., Szczerbicki E., Toro C. (2007) An OWL Ontology of Set of Experience Knowledge Structure, Journal of Universal Computer Science, vol. 13(2):209–223.Google Scholar
- 14.Caserio C., Marchi L. (2010) Generating Knowledge by Combining Prediction Models with Information Technology, D'Atri A., De Marco M., Braccini A.M., Cabiddu F. (Ed) Management of the Interconnected World, 1st edition, Springer, 2010, 307–314.Google Scholar
- 15.Kontio J., Bragge J., Lenthola L. (2008) The Focus Group Method as an Empirical Tool in Software Engineering, Shull F., Singer J., Sjøberg D.I.K. (Ed) Guide to Advanced Empirical Software Engineering, Springer.Google Scholar
- 16.Morgan D.L. (1997) Focus Group as Qualitative Research, Sage Publications, Thousand Oaks, CA.Google Scholar
- 17.Nonaka I. (1991) The Knowledge-Creating Company, Harvard Business Review, Nov/Dec, Vol. 69(6):96–104.Google Scholar
- 19.- (1988) Planning for learning, Harvard Business Review, Mar/Apr, Vol. 66(2):70–74.Google Scholar