Modern government and business units routinely collect and store structured data of general interest to them. In the course of their operations, these organisations often need to take decisions that do not directly follow from the available data. Specialised managerial skills are needed to interpret the data and derive useful conclusions. Subjective assumptions and judgments are made by the mangers to interpret the data. Where the data volume is large, it may be difficult to sift the data, as the managerial skills may not be available for the repeated evaluation of every entity in the database. A decision support system is needed that can be easily reprogrammed to cater for the subjective judgments and biases of the decision-makers. In this paper, we develop a model for a decision support system to identify promising entities based on the subjective preferences. The model can easily be integrated with a relational database system/tool such as Microsoft Access to examine entities in the database and to highlight those that have superior potential based on the decision-makers subjective judgments.

Item Type:	Refereed Conference Paper
Research Division:	Information and Computing Sciences
Research Group:	Information Systems
Research Field:	Decision Support and Group Support Systems
Objective Division:	Information and Communication Services
Objective Group:	Computer Software and Services
Objective Field:	Application Tools and System Utilities
UTAS Author:	Malhotra, V (Dr Vishv Malhotra)
ID Code:	23550
Year Published:	2001
Deposited By:	Computing
Deposited On:	2001-08-01
Last Modified:	2017-04-07
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