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[ Article ]
korean management review - Vol. 54, No. 6, pp. 1459-1483
Abbreviation: kmr
ISSN: 1226-1874 (Print)
Print publication date 31 Dec 2025
Received 30 Sep 2025 Revised 05 Nov 2025 Accepted 25 Nov 2025
DOI: https://doi.org/10.17287/kmr.2025.54.6.1459
Exploring Academia Research Gaps in Management Studies on Artificial Intelligence: An Industry-Based Comparative Analysis
Minbeom Yoon ; Jaehui Kim ; Hee-Woong Kim
(First Author) Master's Student, Graduate School of Information, Yonsei University, Korea (minbeom_y@yonsei.ac.kr)

(Co-Author) Ph.D. Student, Graduate School of Information, Yonsei University, Korea (keemjaehee@yonsei.ac.kr)

(Corresponding Author) Professor, Graduate School of Information, Yonsei University, Korea (kimhw@yonsei.ac.kr)

경영학계 AI 학술 연구의 공백 탐색: 산업 트렌드 기반 비교 분석
윤민범 ; 김재희 ; 김희웅

(주저자) 연세대학교 정보대학원 석사과정

(공저자) 연세대학교 정보대학원 박사과정

(교신저자) 연세대학교 정보대학원 교수
Copyright 2025 THE KOREAN ACADEMIC SOCIETY OF BUSINESS ADMINISTRATION This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted, distribution, and reproduction in any medium, provided the original work is properly cited.


Funding Information ▼ Ministry of Education National Research Foundation of Korea NRF-2023S1A5A2A03084147

Abstract

This study aims to explore research gaps and suggest future research directions in the field of business administration by comparatively analyzing artificial intelligence (AI) research topics in industry and academia. For this purpose, the analysis subjects include 14,032 AI-related industry articles collected from January 2020 to May 2025, and 1,130 AI-related abstracts selected from 26,086 business administration paper abstracts from the same period. BERTopic-based topic modeling and keyword co-occurrence network analysis were employed as analytical methods. The analysis results revealed, first, that a comparison of topics via BERTopic identified key industry-focused topics that have been relatively overlooked in business administration academia. Second, the keyword co-occurrence network analysis showed that the industry exhibits a hub-and-spoke structure centered on ‘AI’, whereas academia displays a polycentric structure, interpreted as a characteristic of an early research stage. This study proposes specific future research themes for the business administration field by connecting these derived industry-focused topics with the 9 detailed tracks of the Korean Management Review (published by the Korean Academic Society of Business Administration). This research is significant as it empirically analyzes the gap between academia and industry and suggests practical and academic directions for the expansion of AI research in business administration.

초록

본 연구는 산업계와 경영학계에서 다루는 인공지능(AI) 연구 주제를 비교 분석하여, 경영학 분야의 연구 공백을 탐색하고 향후 연구 방향을 제시하는 것을 목적으로 한다. 이를 위해 2020년 1월부터 2025년 5월까지 수집된 AI 관련 산업 기사 14,032건과, 동 기간 경영학 논문 26,086편의 초록 중 AI 관련 초록 1,130편을 분석 대상으로 삼았다. 연구 방법으로는 BERTopic 기반 토픽모델링과 키워드 공출현 네트워크 분석을 활용하였다. 분석 결과, 첫째, BERTopic 토픽 비교를 통해 경영학계에서 상대적으로 주목하지 않았던 산업계 중심의 주요 토픽들을 식별하였다. 둘째, 키워드 공출현 네트워크 분석에서 산업계는 ‘AI’를 중심으로 한 허브 앤 스포크(Hub-and-Spoke)형 구조를 보인 반면, 경영학계는 여러 주제가 분산된 다중심적(Polycentric) 구조를 나타내며 이는 초기 연구 단계의 특성으로 해석되었다. 본 연구는 이렇게 도출된 산업계 중심 토픽을 한국경영학회 ‘경영학연구’의 9개 세부 트랙과 연결하여, 경영학 분야의 구체적인 미래 연구 주제를 제안한다. 본 연구는 학계와 산업계 간의 간극을 실증적으로 분석하고 경영학 AI 연구의 실무적·학문적 확장 방향을 제시한다는 점에서 의의가 있다.


Keywords: AI, Keyword Co-occurrence Network Analysis, BERTopic, Industry-Specific Topics 키워드: 키워드 공출현 네트워크 분석, 산업 중심 토픽

Acknowledgments

이 논문은 2023년 대한민국 교육부와 한국연구재단의 공동연구지원사업의 지원을 받아 수행된 연구임(NRF-2023S1A5A2A03084147).

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∙ 저자 윤민범은 연세대학교 정보대학원 석사과정에 재학 중이다. 주요 관심분야는 데이터마이닝, 데이터 애널리틱스, 디지털 비즈니스, Generative AI 등이다.

∙ 저자 김재희는 연세대학교 정보대학원에서 박사과정을 진행 중이며, 디지털 서비스 연구실에서 Design Science using AI 연구를 진행 중이다. 주요 관심분야는 AI based Social Science, Design Science, LLM 등이다.

∙ 저자 김희웅은 National University of Singapore 정보시스템학과에서 근무한 후, 현재 연세대학교 정보대학원 교수로 재직 중이다. 주요 연구분야는 디지털 비즈니스, 정보시스템 관리 및 활용 등이다. 관련 연구들은 MIS Quarterly, Information Systems Research, Journal of Management Information Systems 등에 60여 편의 논문이 게재되었다. MIS Quarterly의 Associate Editor로 활동해왔다.