Building novel capabilities to enable business intelligence agility: results from a quantitative study
Tobias Knabke () and
Sebastian Olbrich ()
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Tobias Knabke: University of Duisburg-Essen
Sebastian Olbrich: European Business School
Information Systems and e-Business Management, 2018, vol. 16, issue 3, No 2, 493-546
Abstract:
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.
Keywords: Business intelligence; Agility; Dynamic capabilities (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)
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DOI: 10.1007/s10257-017-0361-z
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