Amankwah-Amoah, Joseph (2019): Big data analytics and business failures in data-Rich environments: An organizing framework. Forthcoming in: Computers in Industry
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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 categorisation of a number of fruitful avenues for research on data-driven approaches to business failure.
Item Type: | MPRA Paper |
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Original Title: | Big data analytics and business failures in data-Rich environments: An organizing framework. |
Language: | English |
Keywords: | big data analytics; technology; innovation management; big data; business failure |
Subjects: | L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance L - Industrial Organization > L2 - Firm Objectives, Organization, and Behavior |
Item ID: | 91264 |
Depositing User: | Dr. Joseph Amankwah-Amoah |
Date Deposited: | 07 Jan 2019 11:39 |
Last Modified: | 26 Sep 2019 14:36 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/91264 |