Abstract

In order to face the challenges of internationalization and to cope more efficiently with the uncertainty of foreign expansion, firms are called to analyze an increasing amount of real-time semi-structured and unstructured datasets. In this sense, big data analytics (BDA) can become strategic in stimulating the international growth of small and medium-sized enterprises (SMEs). However, the specific relationship between BDA and internationalization has been analyzed fragmentarily within the mainstream literature. With the purpose of shedding light on this relationship, the authors drew on resource-based view (RBV) and collected data through a questionnaire directed to CEOs of 266 SMEs, receiving 103 responses. A quantitative analysis based on an Ordinary Least Squares (OLS) regression showed that the relationship between governance of BDA infrastructure and the degree of internationalization (DOI) is not significant, while the direct effect of BDA capabilities as well as the interaction term between BDA infrastructure and BDA capabilities are positive and significant. This suggests that the governance of BDA per se is not enough for enhancing internationalization in SMEs. On the contrary, this article points out the relevance of developing specific BDA capabilities and the existence of a positive interplay between governance of BDA infrastructure and BDA capabilities that can exploit the new knowledge coming from BDA in SME international growth.

Highlights

  • In the last years, the increasing amount of data that companies have been called to process and their potential key role in making strategic decisions has attracted the attention of managers and scholars (De Mauro et al 2018; Erevelles et al 2016; Gnizy 2018; Lopez-Nicolas and Soto-Acosta 2010; Sivarajah et al 2017)

  • We introduce an interaction term in our third hypothesis: H3 Within the context of small and medium-sized enterprises (SMEs), there is an interplay between the governance of big data analytics (BDA) infrastructure and BDA capabilities, resulting in positive interdependencies that lead to a higher degree of internationalization

  • Model 2, on the other hand, is implemented to test the impact of the two independent variables while in Model 3, the interaction terms are proposed to look at the interaction effect between the two independent variables

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Summary

Introduction

The increasing amount of data that companies have been called to process and their potential key role in making strategic decisions has attracted the attention of managers and scholars (De Mauro et al 2018; Erevelles et al 2016; Gnizy 2018; Lopez-Nicolas and Soto-Acosta 2010; Sivarajah et al 2017). Previous studies suggest that BDA can enhance the quality of decision processes (Kowalczyk and Buxmann 2015); agility (Ashrafi et al 2019; Cheng et al 2020; Gunasekaran et al 2018; Rialti et al 2020); organizational and/or supply chain performance (Akter et al 2016; Gunasekaran et al 2017; Mishra et al 2018; Shokouhyar et al 2020; Wamba et al 2017a, b); innovation capabilities (Mikalef et al 2019b); and value creation (Seddon et al 2017). Some key promises of BDA, such as internationalization, remain somehow unexplored (Ardito et al 2019; Dam et al 2019)

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