These are qualitative or quantitative metrics on which the DMSS is evaluated.
Published in Chapter:
Evaluation of Decision-Making Support Systems
Gloria E. Phillips-Wren (Loyola College in Maryland, USA), Manuel Mora (Autonomous University of Aguascalientes, Mexico), and Guisseppi Forgionne (University of Maryland, Baltimore County, USA)
Copyright: © 2008
|Pages: 9
DOI: 10.4018/978-1-59904-843-7.ch037
Abstract
Decision support systems (DSSs) have been researched extensively over the years with the purpose of aiding the decision maker (DM) in an increasingly complex and rapidly changing environment (Sprague & Watson, 1996; Turban & Aronson, 1998). Newer intelligent systems, enabled by the advent of the Internet combined with artificial-intelligence (AI) techniques, have extended the reach of DSSs to assist with decisions in real time with multiple informaftion flows and dynamic data across geographical boundaries. All of these systems can be grouped under the broad classification of decision-making support systems (DMSS) and aim to improve human decision making. A DMSS in combination with the human DM can produce better decisions by, for example (Holsapple & Whinston, 1996), supplementing the DM’s abilities; aiding one or more of Simon’s (1997) phases of intelligence, design, and choice in decision making; facilitating problem solving; assisting with unstructured or semistructured problems (Keen & Scott Morton, 1978); providing expert guidance; and managing knowledge. Yet, the specific contribution of a DMSS toward improving decisions remains difficult to quantify.