Critical success factors of decision support systems: An experimental study
ACM SIGMIS Database
Price and value of decision support systems
MIS Quarterly
A study of user interface aids for model-oriented decision support systems
Management Science
An evaluation of empirical research in managerial support systems
T.H.E. Journal (Technological Horizons in Education)
Task-technology fit and individual performance
MIS Quarterly
A structural model of end user computing satisfaction and user performance
Information and Management
Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
Improving Decision Making by Means of a Marketing Decision Support System
Management Science
An experimental study of the human/computer interface
Communications of the ACM
Principles of Information Systems for Management
Principles of Information Systems for Management
Decision Support in the Data Warehouse
Decision Support in the Data Warehouse
The benefits of data warehousing: why some organizations realize exceptional payoffs
Information and Management
A Data Warehouse for Policy Making: A Case Study
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 7 - Volume 7
Identification Of Factors Affecting The Implementation Of Data Warehousing
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 7 - Volume 7
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 7 - Volume 7
The DeLone and McLean Model of Information Systems Success: A Ten-Year Update
Journal of Management Information Systems
A UML-based data warehouse design method
Decision Support Systems
Data warehouse enhancement: A semantic cube model approach
Information Sciences: an International Journal
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Organizations implement data warehouses to overcome the limitations of DSS by adding this database component and thereby improve decision performance. However, no empirical evidence is available to show the effects of a data warehouse (DW) on decision quality and performance. To examine this, a laboratory experiment was conducted. The data warehouse variables considered were the time horizon of the data and its level of aggregation.It was found that using a full data warehouse resulted in significantly better performance and that using it resulted in better performance than using a partial data warehouse (long-time history with no aggregated data). However, using a partial data warehouse was not significantly better than not using a data warehouse at all.