A Bibliometric Analysis of Research on Big Data and Its Potential to Value Creation and Capture

Abstract

The emergence of big data is a radical shift in the business context, leading to a change in value creation and capture. This phenomenon is a newborn concept in the business and management literature confirmed by the growing number of publications over recent years. This paper presents an updating comprehensive bibliometric analysis to describe and assess the scientific landscape of value creation and capture based on leveraging big data in the literature. Bibliometrix and VOSviewer were selected as software tools for descriptive and network bibliometric analysis based on the Web of Science Core Collection database from 2011 till 2020. By implementing bibliometric analysis such as analysis of citations and co-occurrence of keywords, we have recognized the most prominent and influential authors, papers, journals, countries, and four potential clusters of current trends in studies. These four trends of value creation and capture from big data studies are: 1) strengthening the basic knowledge of value creation in the big data era, 2) data-driven business model and value capturing, 3) dynamic capabilities and centrality of knowledge, and 4) digital transformation of the service industry. Finally, by identifying the existing research gaps, future research directions in each cluster are demonstrated.