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The “dark side” of big data analytics : uncovering path dependency risks of big data analytics investments
Citation Link: https://doi.org/10.15480/882.2605
Publikationstyp
Conference Paper
Date Issued
2019
Sprache
English
Author(s)
TORE-DOI
TORE-URI
Citation
Proceedings of the 27th European Conference on Information Systems (ECIS) : research-in-progress papers. - AIS Electronic Library (AISeL), 2019.
Contribution to Conference
Publisher Link
Publisher
Association for Information Systems, AIS
Recently, information systems (IS) literature has shown an increasing interest in Big Data and Analy-tics (BDA) to gain competitive advantages. The predominant literature focuses on operational effec-tiveness and how companies use historical information and uncover hidden patterns to differentiate from competition. This paper addresses how the prevailing line of reasoning is limited and how stra-tegic risks from companies’ BDA-applications are neglected. Drawing on the theory of path depend-ency and resource-based view, it aims to expand the hitherto strongly IT-capability-oriented view of competitive advantages from BDA, in particular through greater involvement in current strategy re-search and bydisclosing previously underexposed risk dimensions. A qualitative research shall be conducted to explore possible strategic risk dimensions associated with BDA-investments in greater detail. To reconstruct the process of BDA-investments and capability-building of firms in the maritime logistics sector, a qualitative process study seems appropriate to explore constitutive features of path formation and detect early indicators for path dependency.
Subjects
Big data and Analytics
strategic risks
path dependency theory
qualitative process study
MLE@TUHH
DDC Class
004: Informatik
330: Wirtschaft
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THE ?DARK SIDE? OF BIG DATA ANALYTICS ? UNCOVERING PATH DEPENDEN.pdf
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