Model-driven decision support systems: Concepts and research directions

  • Authors:
  • Daniel J. Power;Ramesh Sharda

  • Affiliations:
  • University of Northern Iowa, Cedar Falls, IA 50614, USA;Oklahoma State University, Stillwater, OK 74078, USA

  • Venue:
  • Decision Support Systems
  • Year:
  • 2007

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Abstract

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.