Abstract
An important difference between expert systems and more conventional DSS is that many expert systems contain explicit representations of metaknowledge. Metaknowledge is information about the content and structure of an expert system – for example, a description of the information contained in the system or an explanation of how the system works. This information may be useful in helping a user to interpret the output of the system or otherwise to use the system more effectively. We examine here the organizational implications of a particular type of metaknowledge – knowledge about the varietey of information sources available to a manager that may help him to solve a particular decision problem. This information may come from people, organizational units, and decision support systems, the latter in the form of stored data, data analysis procedures, text files, decision models, and knowledge-bases. Thus, a knowledge-based DSS may help a manager to interact more productively with a network of people and computers. We are concerned here with the ways in which this might be accomplished.
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