Knowledge generating decision support systems: Managing the trade-off between generating knowledge and supporting decisions

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Abstract

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. Assuming that a DSS is generally composed of a database, a model and an user interface (Power D.J. (2002) Decision Support Systems: Concepts and Resources for Managers, Quorum Books, Westport), and considering that it can be classified as open or closed, the following main conditions for effectively manage an open DSS are discussed: - 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.

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Caserio, C. (2012). Knowledge generating decision support systems: Managing the trade-off between generating knowledge and supporting decisions. In Information Systems: Crossroads for Organization, Management, Accounting and Engineering: ItAIS: The Italian Association for Information Systems (pp. 303–311). Springer New York. https://doi.org/10.1007/978-3-7908-2789-7_34

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