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Decision Support as Knowledge Creation: A Business Intelligence Design Theory

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  • David M. Steiger

    (University of Maine, USA)

Abstract

The primary purpose of decision support systems (DSS) is to improve the quality of decisions. Since decisions are based on an individual’s mental model, improving decision quality is a function of discovering the decision maker’s mental model, and updating and/or enhancing it with new knowledge; that is, the purpose of decision support is knowledge creation. This article suggests that BI techniques can be applied to knowledge creation as an enabling technology. Specifically, the authors propose a business intelligence design theory for DSS as knowledge creation, a prescriptive theory based on Nonaka’s knowledge spiral that indicates how BI can be focused internally on the decision maker to discover and enhance his/her mental model and improve the quality of decisions.

Suggested Citation

  • David M. Steiger, 2010. "Decision Support as Knowledge Creation: A Business Intelligence Design Theory," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 1(1), pages 29-47, January.
  • Handle: RePEc:igg:jbir00:v:1:y:2010:i:1:p:29-47
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    Cited by:

    1. Qingxin Meng & Keli Xiao & Dazhong Shen & Hengshu Zhu & Hui Xiong, 2022. "Fine-Grained Job Salary Benchmarking with a Nonparametric Dirichlet Process–Based Latent Factor Model," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2443-2463, September.

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