Decision support systems: the next decade
Decision Support Systems
An active modeling system for econometric analysis
Decision Support Systems
Decision support systems: scope and potential
Proceedings of the conference on First specialized conference on decision support systems
A DSS user interface model to provide consistency and adaptability
Decision Support Systems - Special issue on user interfaces
A psychological approach to decision support systems
Management Science
Verification and validation of simulation models
Proceedings of the 30th conference on Winter simulation
The development of an adaptive decision support system
Decision Support Systems
Communications of the ACM
The Architecture of Cognition
Simulation Using Promodel
A new paradigm for computer-based decision support
Decision Support Systems - Special issue: Decision support systems: Directions for the next decade
Decision station: situating decision support systems
Decision Support Systems
Decision support systems evolution: framework, case study and research agenda
European Journal of Information Systems
Special section: research in integrating learning capabilities into information systems
Journal of Management Information Systems - Special section: Research in integrating learning capabilities into information systems
Manager's Guide to Making Decisions About Information Systems
Manager's Guide to Making Decisions About Information Systems
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In this paper, the function of a data-centred decision-support system (DSS) is simulated to investigate whether the incorporation of human pattern-recognition abilities significantly improves the performance of a system. Two decision making scenarios are considered. In one scenario, there is no human interaction, whereas the other scenario uses the pattern-recognition capabilities of humans. The simulation is performed by mining 10,000 records in 980 replications. The DSS has the ability to take corrective actions with the purpose of keeping the incoming data records within a given set of upper and lower boundaries. The results indicate that incorporating pattern-recognition ability in a DSS significantly improves the system's performance. However, the impact of human input is not linear with respect to system performance. Our study shows that a moderate degree of human intervention will usually provide the greatest positive impact on the system's performance.