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Big Data Analytics and Business Failures in Data-Rich Environments: An Organizing Framework
Amankwah-Amoah, J. Adomako, Samuel
Amankwah-Amoah, J.
Adomako, Samuel
Publication Date
2019-02
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© 2019 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
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openAccess
Accepted for publication
17/12/2018
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Abstract
In view of the burgeoning scholarly works on big data and big data analytical capabilities, there remains limited research on how different access to big data and different big data analytic capabilities possessed by firms can generate diverse conditions leading to business failure. To fill this gap in the existing literature, an integrated framework was developed that entailed two approaches to big data as an asset (i.e. threshold resource and distinctive resource) and two types of competences in big data analytics (i.e. threshold competence and distinctive/core competence). The analysis provides insights into how ordinary big data analytic capability and mere possession of big data are more likely to create conditions for business failure. The study extends the existing streams of research by shedding light on decisions and processes in facilitating or hampering firms’ ability to harness big data to mitigate the cause of business failures. The analysis led to the categorization of a number of fruitful avenues for research on data-driven approaches to business failure.
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Accepted manuscript
Citation
Amankwah-Amoah J and Adomako S (2019) Big Data Analytics and Business Failures in Data-Rich Environments: An Organizing Framework. Computers in Industry. 105: 204-212.
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Article