Artificial Intelligence Research in Management: A Computational Literature Review

被引:18
|
作者
Arsenyan, Jbid [1 ]
Piepenbrink, Anke [1 ]
机构
[1] Rennes Sch Business, Rennes 35065, France
关键词
Artificial intelligence; Business; Machine learning; Inspection; Bibliographies; Vocabulary; Computational modeling; Artificial intelligence (AI); computational litera-ture review (CLR); latent Dirichlet allocation (LDA); management research; TOPIC LANDSCAPE; AI; OPPORTUNITIES; AUTOMATION;
D O I
10.1109/TEM.2022.3229821
中图分类号
F [经济];
学科分类号
02 ;
摘要
Artificial intelligence (AI) spring of the past decade created an increased interest into the topic in business as well as in academia. This resulted in an upward trend in academic publications, not only in computer science but also in management. This article presents a computational literature review with an abstract-based sampling approach to investigate the status of the management literature to take stock of academic research of the past two decades. We analyze 6324 papers from 1990 to 2020 published in five management-related domains and identify 41 distinct topics. We present the evolution of research pre and post AI spring, emerging topics as well as saturated areas. The findings show that the previously disjointed topic network structure is fully connected by early 2010s and the upward trend in management research starts in the period of 2014-2015. The results provide a comprehensive insight into the potential of AI in management versus underdeveloped areas, and presents, for management scholars and practitioners, suggestions about effective adoption of AI practices.
引用
收藏
页码:5088 / 5100
页数:13
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