INTELLIGENT DECISION SUPPORT SYSTEMS FOR BUSINESS APPLICATIONS: WITH AN EXAMPLE OF PORTFOLIO MANAGEMENT DECISION-MAKING

This study involves exploratory research to develop more effective approaches to designing man-machine interfaces. A key objective is to improve DSS development methodologies to allow incorporation of expert system (ES) and artificial intelligence (AI) techniques. We identify the following problems in using AI techniques for DSS development: (1) selection of the software component types (a database model, management science model, or knowledge representation and inferencing scheme) that best fit the tasks to be performed and are appropriate for the users; (2) acquisition of the appropriate predefined software components or construction of new ones; (3) combination of the heterogeneous components into a useful system.; An Intelligent Decision Support System (IDSS) has been proposed to solve the above problems. A rough architecture for an IDSS has been developed that supports the business problem-solving environment by employing a useful subset of knowledge representation and inference techniques. A prototype system for portfolio management decision making has been implemented in Prolog to illustrate and validate the approach. The research makes several practical contributions in the area of DSS analysis and design. Among them are: (1) a new ES development strategy for business problem-solving environments; (2) the architecture for the IDSS which recognizes the need for multiple knowledge representation schemes; (3) the knowledge engineering techniques which can be used as guidelines for other ES developers.