How can internationally operating SMEs successfully integrate Big Data with solutions of external providers?
Translated title
Author
Term
4. Term
Publication year
2021
Submitted on
2021-06-02
Pages
62
Abstract
The current slow adaptation of Big Data (BD) in internationally operating small- and medium sized businesses (IOSMEs) has been identified as a problem of economic importance. By analyzing the challenges and achievable benefits of BD adoption, this thesis will look into beneficiary options that support such a implementation with regards to the limited capabilities of IOSMEs. Further, through a comparative case study of external service providers that enable IOSMEs to conduct Big Data Analytics (BDA) their relation towards overcoming these challenges will be examined. With investigating BD through the Resource Based View and the Resource Dependency Theory in combination with the insights from the empirical analysis, it was established that a sustainable competitive advantage through the utilization of external service providers cannot be realized. The critical point in achieving such a competitive advantage proved to be the build-up of internal BDA capabilities that inherit the properties of the VRIO framework. However, the utilization of external service providers supports IOSMEs in overcoming challenges when adopting BD, which makes it a viable option in the early adaptation phase.
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