Model-driven decision support systems: Concepts and research directions

In some decision situations, quantitative models embedded in a Decision Support System (DSS) can help managers make better decisions. Model-driven DSS use algebraic, decision analytic, financial, simulation, and optimization models to provide decision support. This category of DSS is continuing to e...

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Published in:Decision Support Systems 2007-04, Vol.43 (3), p.1044-1061
Main Authors: Power, Daniel J., Sharda, Ramesh
Format: Article
Language:English
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Decision support systems
DSS concepts
Managers
Quantitative models
Research questions
Studies
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description In some decision situations, quantitative models embedded in a Decision Support System (DSS) can help managers make better decisions. Model-driven DSS use algebraic, decision analytic, financial, simulation, and optimization models to provide decision support. This category of DSS is continuing to evolve, but research can resolve a variety of behavioral and technical issues that impact system performance, acceptance and adoption. This article includes a brief survey of prior research. It focuses on model-driven DSS built using decision analysis, optimization, and simulation technologies; implementation using spreadsheet and web technologies; issues associated with the user interface; and behavioral and technical research questions.
doi_str_mv 10.1016/j.dss.2005.05.030
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1873-5797
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subjects Decision support systems
DSS concepts
Managers
Quantitative models
Research questions
Studies
title Model-driven decision support systems: Concepts and research directions
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