The effects of data warehousing (DW) as a DSS database component on decision performance: An experimental study of DW in DSS contexts

Many organizations implement data warehousing (DW) as IT infrastructure to enhance the system quality and/or information quality of decision support systems (DSS) and thus to improve the decision performance of DSS users. However, no empirical evidence is available on the effects of DW on decision performance. To examine the effects of DW on decision performance, a laboratory experiment was conducted. Two levels of task complexity and three different DSS database characteristics (a traditional DSS database, DW with long-time history, and DW with long-time history and aggregated data) yielded a 2 x 3 factorial design with one within-subjects factor (task complexity) and one between-subjects factor (DSS database).; The results show that the decision performance of DSS users supported with both long-time history and aggregated data was significantly higher than that for DSS users supported only with a traditional database. However, the performance of DSS users supported with both long-time history and aggregated data was not significantly different from that of DW groups with long-time history only. Also, no significant difference was found between the traditional DSS group and the DW group with long-time history only. Therefore, the findings of this study imply that to improve decision performance of DSS users, a DW must provide both long-time history and aggregated data. Providing long-time history without aggregation does not, in most cases, meet the information requirements of the decision tasks in DSS contexts. The findings also indicate that DSS users can expect to improve their decision performance by enhancing individual components of a DSS, without necessarily improving the whole information system.; These findings expand the understanding of the effects of DW on decision performance. They also support the idea that the basic concepts of established IS models and theory (such as the IS success model, the conceptual theory of an advanced information technology, and technology-task fit model) are still valid in the context of a data warehouse and decision support systems.