Big data analytics and business failures in data-Rich environments: An organizing framework

Joseph Amankwah-Amoah

MPRA Paper from University Library of Munich, Germany

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.

Keywords: big data analytics; technology; innovation management; big data; business failure (search for similar items in EconPapers)
JEL-codes: L1 L2 (search for similar items in EconPapers)
Date: 2019-01-01
New Economics Papers: this item is included in nep-big and nep-cfn
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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