The purpose of this dissertation is to examine the external factors that influence an organizations' business intelligence (BI) data collection strategy when mediated by BI attributes. In this dissertation, data warehousing strategies are used as the basis on which to frame the exploration of BI data collection strategies. The attributes include BI insightfulness, BI consistency, and the organizational transformation attribute of BI. The research population consisted of IT professionals and top level managers involved in developing and managing BI. Data was collected from a range of industries and organizations within the United States. An online survey was used to collect …
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The purpose of this dissertation is to examine the external factors that influence an organizations' business intelligence (BI) data collection strategy when mediated by BI attributes. In this dissertation, data warehousing strategies are used as the basis on which to frame the exploration of BI data collection strategies. The attributes include BI insightfulness, BI consistency, and the organizational transformation attribute of BI. The research population consisted of IT professionals and top level managers involved in developing and managing BI. Data was collected from a range of industries and organizations within the United States. An online survey was used to collect the data to empirically test the proposed relationships. Data was analyzed using partial least square path modeling (PLS). The results of this study suggest that there exists a positive relationship between institutional isomorphism and BI consistency. The results also indicate that there exists a positive relationship between BI consistency and BI comprehensive data collection strategy, and the organizational transformation attribute of BI and BI comprehensive data collection strategy. These findings provide a theoretical lens to better understand the motivators and the success factors related to collecting the huge amounts of data required for BI. This study also provides managers with a mental model on which to base decisions about the data required to accomplish their goals for BI.
This dissertation is part of the following collection of related materials.
UNT Theses and Dissertations
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