Earticle

초록

영어

The rapid evolution of artificial intelligence, particularly Generative AI, has widened the gap between industrial practice and Information Systems research. To address this issue, this study investigates the industry-academia speed gap and proposes future research agendas to bridge this divide. We conceptualize this gap as a structural temporal asynchrony driven by distinct knowledge production mechanisms. Methodologically, we employ a computationally assisted Systematic Literature Review (SLR) that integrates Latent Dirichlet Allocation and embedding- based semantic similarity analysis to compare discourse patterns across industry news and IS academic papers. Our analysis reveals that industry and academia interpret identical phenomena through different lenses, even within shared thematic areas. Furthermore, we identify unique topic clusters that emerge exclusively within each domain. Based on these findings, we propose an expanded AI research framework by extending Padmanabhan et al. (2022) and present a research agenda directing scholars toward underrepresented yet industrially significant areas. This approach facilitates more timely and substantial contributions to the IS field while providing rigorous insights to assist in establishing corporate mid-to-long-term strategies.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Related Work
2.1. Sociotechnical Perspective: The Core Identity of IS
2.2. Taxonomy of AI-based Research in IS
2.3. AI Literature Review in IS Research
Ⅲ. Methodology
3.1. Systematic Literature Review Framework
3.2. Planning: Scope and Review Protocol
3.3. Selection: Data Collection and Practical Screening
3.4. Extraction: Preprocessing and Topic Modeling
3.5. Execution: Topic Comparison and Research Type Mapping
Ⅳ. Results
4.1. Topic Modeling Results
4.2. Comparison of Industry and Academia Topics
4.3. Mapping Topics to IS Research Types
Ⅴ. Key Findings
5.1. Interpretation of the Industry-Academia Gap
5.2. Research Agenda for Future IS Research
Ⅵ. Discussion and Implications
6.1. Implications for Research
6.2. Implications for Practice
6.3. Limitations and Future Research Directions
Ⅶ. Conclusion
Acknowledgement

키워드

저자

• Jaehui Kim [ PhD Student, Graduate School of Information, Yonsei University, Korea ]
• Hyunjung Choi [ Master’s Student, Graduate School of Information, Yonsei University, Korea ]
• Hee-Woong Kim [ Professor, Graduate School of Information, Yonsei University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  Asia Pacific Journal of Information Systems

• 간기

  계간

• pISSN

  2288-5404

• eISSN

  2288-6818

• 수록기간

  1990~2026

• 등재여부

  KCI 등재,SCOPUS

• 십진분류

  KDC 325 DDC 658