Maritime logistics and digital transformation with big data: review and research trend

Abstract

Purpose: This paper summarizes and synthesizes existing research while critically assessing findings for future studies to advance the scholarship of maritime logistics and digital transformation with big data. Design/methodology/approach: A bibliometric analysis was conducted on 159 journal articles from the Scopus database with search keywords “maritime*” and “big data.” This analysis helps identify research gaps by identifying themes via keyword co-occurrence, co-citation and bibliographic coupling analysis. The Theory-Context-Characteristics-Methodology (TCCM) framework was applied to understand the findings of bibliometric analysis and provide a research agenda. Findings: The analyses identified emerging themes of the scholarship of maritime logistics and digital transformation with big data and their relationships to identify research clusters. Future research directions were provided by examining existing research's theory, context, characteristics and method. Originality/value: This research is grounded in bibliometric analysis and the TCCM framework to understand the scholarly evolution, giving managers and academics retrospective and prospective insights.