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

IF 2 Q3 BUSINESS Maritime Business Review Pub Date : 2024-07-22 DOI:10.1108/mabr-10-2023-0069
Jiyoon An
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引用次数: 0

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.

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海运物流与大数据的数字化转型:回顾与研究趋势
本文对现有研究进行了总结和归纳,同时对未来研究的结论进行了批判性评估,以推动海运物流和大数据数字化转型的学术研究。设计/方法/途径以 "海运*"和 "大数据 "为搜索关键词,对 Scopus 数据库中的 159 篇期刊论文进行了文献计量分析。该分析通过关键词共现、共引和书目耦合分析确定主题,从而帮助找出研究差距。分析确定了海事物流和大数据数字化转型学术研究的新兴主题及其关系,从而确定了研究集群。通过研究现有研究的理论、背景、特点和方法,提供了未来的研究方向。原创性/价值本研究以文献计量分析和 TCCM 框架为基础,旨在了解学术演变,为管理者和学者提供回顾性和前瞻性的见解。
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来源期刊
CiteScore
4.80
自引率
0.00%
发文量
19
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