A comparative modeling approach to a large decision support system

A comparative modeling approach is proposed for a decision support framework enabling users to have access to different modeling techniques within a single system (depending on the problem and the resources available). Three modeling techniques were selected to illustrate a marketing strategic decision support system: analytic, heuristic, and data-driven. The preimplementation choice and the trade-offs of each technique are explained qualitatively. Subsequently, the unification of the three techniques is discussed, and the benefits and problems associated with the comparative modeling approach are evaluated. Hean Lee Poh received his Diplom-Ingenieur in electrical engineering from the University of Paderborn, Germany, in 1982, his M.S. in computer science from California Institute of Technology in 1987, and his M.S. and Ph.D. in engineering-economic systems from Stanford University in 1991. His main research interests are neural network algorithms and their application in marketing strategies, financial modeling, and decision support systems. He is also interested in quantitative business modeling. He teaches courses in fourth-generation languages and information systems research methodology. He has been with the National University of Singapore since 1984 and is currently a lecturer.