Big data and dynamic capabilities: a bibliometric analysis and systematic literature review

TLDR

Recent studies on big data’s effects on organizations rely on dynamic capabilities theory but lack systematic synthesis, and to date minimal attention has been paid to systematizing this literature. The purpose of this paper is to systematize the literature on big data and dynamic capabilities. The authors conducted a bibliometric analysis of 170 Web of Science Core Collection papers and integrated the results with a systematic literature review. The analysis identified five thematic clusters—big data and supply chain management, knowledge management, decision making, business process management, and big data analytics—and the review clarified each cluster’s content.

Abstract

Purpose Recently, several manuscripts about the effects of big data on organizations used dynamic capabilities as their main theoretical approach. However, these manuscripts still lack systematization. Consequently, the purpose of this paper is to systematize the literature on big data and dynamic capabilities. Design/methodology/approach A bibliometric analysis was performed on 170 manuscripts extracted from the Clarivate Analytics Web of Science Core Collection database. The bibliometric analysis was integrated with a literature review. Findings The bibliometric analysis revealed four clusters of papers on big data and dynamic capabilities: big data and supply chain management, knowledge management, decision making, business process management and big data analytics. The systematic literature review helped to clarify each clusters’ content. Originality/value To the authors’ best knowledge, minimal attention has been paid to systematizing the literature on big data and dynamic capabilities.