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Erschienen in: Information Systems and e-Business Management 3/2018

22.08.2017 | Original Article

Building novel capabilities to enable business intelligence agility: results from a quantitative study

verfasst von: Tobias Knabke, Sebastian Olbrich

Erschienen in: Information Systems and e-Business Management | Ausgabe 3/2018

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Abstract

The class of business intelligence (BI) systems is widely used to guide decisions in all kinds of organizations and across hierarchical levels and functions. Organizations have launched many initiatives to accomplish adequate and timely decision support as an important factor to achieve and sustain competitive advantage. Given today’s turbulent environments it is increasingly challenging to bridge the gap between establishing a long-term strategy and quickly adopting to the dynamics in market competition. BI must address this field of tension as it was originally used to retrospectively reflect an organization’s performance and build upon stability and efficiency. This study aims to understand and achieve an agile BI from a dynamic capability perspective. Therefore, we investigate how dynamic BI capabilities, i.e., adoption of assets, market understanding, and intimacy as well as business operations, impact the agility of BI. Starting from a literature review of dynamic capabilities in information systems and BI, we propose hypotheses to connect dynamic BI capabilities with the agility to provide information. The derived hypotheses were tested using partial least squares structural equation modeling on data collected in a questionnaire-based survey. The results show that the lens of dynamic capabilities provides useful means to foster BI agility. The study identifies that technological advancements like in-memory technology seem to be a technology enabler for BI agility. However, an adequate adoption and integration of BI assets as well as the focus on market orientation and business operations are crucial to reach BI agility.

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Fußnoten
1
BI agility may then enable further concepts, e.g., sustainable corporate advantage. But, a study beyond BI agility is not in the scope of this paper.
 
2
The result of the measurement item validation from the pre-study is shown in Appendix G.
 
3
For the questionnaire statements as well as the detailed literature sources for the items please refer to Appendix A, Table 10.
 
4
Tables 11 and 12 in Appendix B provide detailed information about the participants.
 
5
Below, the steps general evaluation and organization-specific evaluation are also referred to as general view and organization-specific implementations.
 
6
See Appendix C for details.
 
7
Further details are shown in Appendix D.
 
8
Further details are available in Appendix E.
 
9
Details for the model evaluation with controlled organization size can be found in Appendix H.
 
10
Further details of the model validation are shown in Appendix D.
 
11
Indirect effects represent a relationship between constructs via a third construct, e.g., a mediator. If x is the path coefficient between an independent and a mediator variable and y is the path coefficient between the mediator variable and the dependent variable, the indirect effect is the product of x and y. If only one path exists between two variables the total effect equals the direct effect.
 
12
Further details of the model validation are shown in Appendix E.
 
13
Further details can be found in Appendix F.
 
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Metadaten
Titel
Building novel capabilities to enable business intelligence agility: results from a quantitative study
verfasst von
Tobias Knabke
Sebastian Olbrich
Publikationsdatum
22.08.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Information Systems and e-Business Management / Ausgabe 3/2018
Print ISSN: 1617-9846
Elektronische ISSN: 1617-9854
DOI
https://doi.org/10.1007/s10257-017-0361-z

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