A methodology for structured modeling on the Masic decision support system generator

The desk-top computing revolution has given birth to a new breed of managers--the self starters, accentuating the importance of end-user computing. The rapidly evolving technology offers numerous possibilities for communicating and delivering management science (MS) in ways that managers are more likely to accept. The complexity of modeling, however, still hinders MS modeling system from being an integral part of the organization\u27s information systems. In turn, information systems--particularly, decision support systems--are lacking the analytic capability sufficient enough to support management decision makings. This study aims to develop a methodology for integrating the user, data, and models within the framework of decision support systems (DSS). By providing a robust mechanism for model representation compatible with database management systems, this research attempts to alleviate the persisting MS problem--the complexity of modeling. As such, this research is not concerned with algorithmic properties of MS models, but rather with the descriptive representation and manipulation of models that would eventually be solved by the algorithms. To achieve this purpose, the entity-relationship (E/R) approach will be presented as the main idea for the proposed methodology. The E/R approach will make it possible for a database management system (DBMS) to perform both model and dialogue management functions as well as the data management function. Viewing models as data will allow the application of well-established database principles for the design of the model base. Hence, both data and models can be managed by one single DBMS via the user\u27s queries. Integration of the user, models, and data within a DSS will help both MS and DSS fulfill their original promises to managers. Supported by DSS functions, MS will be able to achieve the successful implementation. In turn, DSS enhanced by the analytic capabilities of MS, will truly become an integral part of managers\u27 decision-making processes