Decision Support as Knowledge Creation: A Business Intelligence Design Theory
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; tha...
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| Veröffentlicht in: | International journal of business intelligence research 2010-01, Vol.1 (1), p.29-47 |
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| container_title | International journal of business intelligence research |
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| creator | Steiger, David M |
| description | 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. |
| doi_str_mv | 10.4018/jbir.2010071703 |
| format | Article |
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| issn | 1947-3591 1947-3605 |
| language | eng |
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| source | ProQuest Central (Alumni Edition); ProQuest Central Korea; ProQuest Central UK/Ireland; Alma/SFX Local Collection; ProQuest Central |
| subjects | Business Decision making Decision support systems Decision theory Design engineering Information management Intelligence Intelligence (information) Mathematical models Spirals |
| title | Decision Support as Knowledge Creation: A Business Intelligence Design Theory |
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