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.