Evaluation of Decision-Making Support Systems

IntroductIon 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 enabled by the advent of the Internet combined with BLOCKINartificial-intelligence BLOCKIN(AI) BLOCKINtechniques, BLOCKINhave extended the reach of DSSs to assist with decisions in BLOCKINreal BLOCKINtime BLOCKINwith BLOCKINmultiple BLOCKINinformaftion BLOCKINflows BLOCKINand dynamic data across geographical boundaries. All of these systems can be grouped under the broad BLOCKINclassification BLOCKINof BLOCKINdecision-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 BLOCKINto BLOCKINquantify. Many researchers identify a single metric, or a series of single metrics, for evaluation of the DMSS in supporting decision making, if it is evaluated at all (Phillips-Wren, Mora, For-gionne, Garrido, & Gupta, 2006). The authors suggest outcome criteria such as decreased cost, or BLOCKINprocess BLOCKINcriteria BLOCKINsuch BLOCKINas BLOCKINincreased BLOCKINefficiency, BLOCKINto justify the DMSS. Yet no single integrated metric is proposed to determine the value of the DMSS to the decision maker. The objective of this article is to review literature-based evaluation criteria and to provide a multicriteria evaluation model that determines the precise decision-making contributions of a DMSS. The model is implemented with the analytical hierarchy process (AHP), a formalized multicriteria method. this article focuses on the performance and evaluation of a planned or real DMSS in supporting decision making. study develops a DMSS evaluation model from a design research paradigm, that is, to be built and evaluated (Hevner & March, 2003).