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|Title:||Critical value factors in business intelligence systems implementation success: An empirical analysis of system and information quality|
|Keywords:||Business intelligence;Systems quality;Information quality|
|Citation:||2015 International Conference on Information Systems (ICIS2015-SIGDSA), Texas, USA, (13-16 December 2015)|
|Abstract:||Business Intelligence (BI) systems have been rated as a leading technology for the last several years. However, organizations have struggled to ensure that high quality information is provided to and from BI systems. This suggests that organizations have recognized the value of information and the potential opportunities available but are challenged by the lack of success in Business Intelligence Systems Implementation (BISI). Therefore, our research addresses the preponderance of failed BI system projects, promulgated by a lack of attention to Systems Quality (SQ) and Information Quality (IQ) in BISI. The main purpose of this study is to determine how an organization may gain benefits by uncovering the antecedents and critical value factors (CVFs) of SQ and IQ necessary to derive greater BISI success. We approached these issues through adopting ‘critical value factors’ (CVF) as a conceptual ‘lens’. Following an initial pilot study, we undertook an empirical analysis of 1,300 survey invitations to BI analysts. We used exploratory factor analysis (EFA) techniques to uncover the CVFs of SQ and IQ of BISI. Our study demonstrates that there is a significant effect in the relationships of perceived IQ of BISI to perceived user information satisfaction thereby confirming the importance BI system users place on information and the output produced. Our study also reported that there is a significant effect in the relationships of perceived IQ of BISI to perceived user information and SQ satisfaction thereby confirming the importance BI system users place on information and the system output produced. We believe our research will be of benefit to both academics and practitioners in attempting to ensure BI systems implementation success|
|Appears in Collections:||Brunel Business School Research Papers|
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