Affiliations: Krannert Graduate School of Management, Management Information Research Center, Purdue University, West Lafayette, IN 47907, USA
Note: [*] Research supported in part by the National Science Foundation, Grant IST-8108519 and Grant ECS-8116135, and a gift from the IBM Corporation to the Management Information Research Center. Opinions expressed are those of the authors.
Abstract: The principal applicability of artificial intelligence techniques to management lies within the context of decision support systems. These are systems that facilitate or enhance decision making activities. An extensive decision support system has the ability to draw upon various kinds of application specific knowledge in solving problems posed by a manager. This includes large volumes of empirical knowledge, a variety of modeling knowledge, and reasoning knowledge. All of these types of knowledge can be represented in the DSS's knowledge system and can be utilized by the DSS's problem processor in responding to requests stated in terms of the DSS's language system. Research in the DSS field is increasingly exploring ways in which AI techniques can be used in addressing such DSS implementation issues.
Keywords: Data base management, decision making, decision support system, knowledge system, language system, management, problem processor, software integration
