Big data analytics and enterprises: a bibliometric synthesis of the literature

被引：138
|
作者：
Khanra, Sayantan [1 ,2 ]
Dhir, Amandeep [1 ,3 ,4 ]
Mantymaki, Matti [1 ]
机构：
[1] Univ Turku, Turku Sch Econ, Turku, Finland
[2] Indian Inst Management Rohtak, Rohtak, Haryana, India
[3] LUT Univ, Sch Business & Management, Lappeenranta, Finland
[4] North West Univ, Optentia Res Focus Area, Vanderbijlpark, South Africa
来源：
ENTERPRISE INFORMATION SYSTEMS | 2020年 / 14卷 / 06期
基金：
芬兰科学院;
关键词：
bibliometric analysis; big data analytics; content analysis; predictive analytics; network analysis; prestige analysis; SUPPLY CHAIN MANAGEMENT; PREDICTIVE ANALYTICS; DATA SCIENCE; BUSINESS; COCITATION; IMPACT; PERFORMANCE; EVOLUTION; PARADIGM; INSIGHTS;
D O I：
10.1080/17517575.2020.1734241
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Understanding the developmental trajectories of big data analytics in the corporate context is highly relevant for information systems research and practice. This study presents a comprehensive bibliometric analysis of applications of big data analytics in enterprises. The sample for this study contained a total of 1727 articles from the Scopus database. The sample was analyzed with techniques such as bibliographic coupling, citation analysis, co-word analysis, and co-authorship analysis. Findings from the co-citation analysis identified four major thematic areas in the extant literature. The evolution of these thematic areas was documented with dynamic co-citation analysis.
引用
收藏
页码：737 / 768
页数：32
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