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Title: The “dark side” of big data analytics : uncovering path dependency risks of big data analytics investments
Language: English
Authors: Wrona, Thomas 
Reinecke, Pauline 
Keywords: Big data and Analytics; strategic risks; path dependency theory; qualitative process study
Issue Date: 2019
Publisher: Association for Information Systems, AIS
Source: Proceedings of the 27th European Conference on Information Systems (ECIS) : research-in-progress papers. - AIS Electronic Library (AISeL), 2019.
Abstract (english): 
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.
Conference: 27th European Conference on Information Systems (ECIS) 
DOI: 10.15480/882.2605
ISBN: 978-1-7336325-0-8
Institute: Strategisches und Internationales Management W-10 
Document Type: Chapter/Article (Proceedings)
License: In Copyright In Copyright
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