Korean Accounting Review (KAR) is the official journal of the Korean Accounting Association. The Korean Accounting Association (KAA) is the largest and oldest academic organization of accounting scholars and practitioners in Korea. It aims to create a fertile environment for innovation and collaborative research, to foster and improve research for the development and the promotion of accounting, and to develop a powerful network among scholars, practitioners, and authorities concerned with political decision making in this field.
A Review of Financial Accounting Research: Milestone Papers and Emerging Themes (1968-2025)
Yongtae Kim
DOI:10.24056/KAR.2025.10.001 KAR Vol.50(No.5) 1-80, 2025
Abstract
This paper provides a review of financial accounting research, spanning over 50 years of scholarly development from Ball and Brown (1968) to contemporary applications of machine learning and labor market analysis. I examine 28 milestone papers that have fundamentally shaped the field, discussing the historical context that led to their emergence, their innovations, and their profound influence on subsequent research streams. The review is structured chronologically to illuminate the intellectual progression of the field, providing readers with essential context for understanding how modern financial accounting research developed. I conclude by examining two emerging themes― the interaction of accounting and labor economics, and machine learning applications―that represent the current frontier of the discipline.
Key Words
literature review, financial accounting research, capital markets research, milestone papers, emerging themes
Trends and Future Directions in Financial Accounting Research in Korea: A Focus on Disclosure and Standard Developments 국내 재무회계 연구 동향과 전망: 공시와 회계기준의 변화를 중심으로
문두철 Doocheol Moon , 송민섭 Minsup Song , 조형진 Hyungjin Cho
DOI:10.24056/KAR.2025.10.002 KAR Vol.50(No.5) 81-108, 2025
Abstract
This study examines the trends in Korean financial accounting research over the past decade, with a focus on corporate disclosure and the adoption and revision of financial accounting standards, and proposes future research directions. While Kim(2025) systematically analyzes the evolution of U.S. financial accounting research, this paper highlights research developments shaped by the Korean institutional context following the full adoption of IFRS in 2011. Between 2015 and the first half of 2025, articles published in the Korean Accounting Review and the Korean Accounting Journal show that, despite a decline in the number of all publications, these two research areas have consistently accounted for 6-14% of annual publications. In the field of disclosure, the most frequently studied topics have been management earnings forecasts and management discussion and analysis(MD&A) disclosures. Studies on management earnings forecasts have explored the determinants of disclosure and their economic effects. Research on MD&A initially had focused on whether key items were disclosed during the 2010s, but shifted in the 2020s toward the question of whether such items are disclosed regularly. The adoption of IFRS brought structural changes to the disclosure system and financial statements, sparking extensive debates on various aspects of accounting information such as discretionary accruals and value relevance. Following its adoption, major revisions to standards on consolidated financial statements, fair value measurement, financial instruments, and revenue recognition further expanded scholarly interest in corporate disclosure and information usefulness. This study further provides suggestions for future research.
Key Words
회계학연구, 회계저널, 공시, 회계기준의 변화, 문헌연구, Korean accounting review, Korean accounting journal, corporate disclosure, accounting standards change, literature review
Review of Managerial Accounting Literature: Focusing on Empirical Studies in the 2010s and 2020s
Sera Choi , Iny Hwang
DOI:10.24056/KAR.2025.10.003 KAR Vol.50(No.5) 109-168, 2025
Abstract
This paper synthesizes recent advances in management accounting research, following seminal editorial and review works to highlight the discipline’s evolving scope. Guided by Krishnan’s (2015) call for broad inquiry into decision-making roles and information use within organizations, the study systematically reviews contributions from the 2010s and 2020s. The first part traces the development of established themes, including performance evaluation, compensation schemes, and cost management. The second part explores emerging agendas, such as behavioral research in diverse control environments and employee-centered perspectives, reflecting experimental studies and sustainability-driven industry practices. By integrating empirical findings and selective theoretical perspectives, the review offers a comprehensive overview of recent studies and proposes avenues for further research, emphasizing the ongoing expansion and interdisciplinary nature of managerial accounting scholarship.
A Review and Future Research Directions of Empirical Tax Accounting Research 실증 세무회계 연구의 동향과 미래 연구 방향
전규안 Kyu An Jeon , 선우희연 Hee-yeon Sunwoo
DOI:10.24056/KAR.2025.10.004 KAR Vol.50(No.5) 169-232, 2025
Abstract
This paper aims to derive key implications from prior studies and suggest directions for future research. To this end, we review domestic and international trends in tax accounting research over the past decade that have employed empirical methods. Specifically, the literature review is organized into six main areas of tax accounting. First, we examine studies on the information effects of corporate income tax accounting. Second, we review tax avoidance literature, focusing on theoretical frameworks, measurement proxies, determinants, consequences, tax uncertainty, and time-series analyses of avoidance behaviors. Third, we analyze studies on the role of taxation in corporate decision-making, particularly in relation to investment, financing structures, and other managerial choices. Fourth, we explore the relationship between taxation and asset pricing, including dividend taxation, capital gains taxation, and implicit taxes. Fifth, we examine research on taxation and income shifting, with particular attention to shifts across countries, among domestic firms, and across time. Sixth, we survey the expanding literature on sustainability (ESG, CSR) and taxation, emphasizing its links to tax avoidance and sustainability disclosure. By organizing prior findings by field, this study provides a comprehensive overview of tax accounting research, offering clear insights and identifying fruitful avenues for future research. The results are expected to benefit not only academics, but also policymakers designing tax regulations and practitioners addressing tax issues in corporate settings.
Key Words
실증 세무회계 연구, 법인세회계의 정보효과, 조세회피와 기업의사결정, 조세와 소득이전, 지속가능성과 조세, empirical tax accounting research, informational role of tax accounting, corporate tax avoidance and corporate decisions, income shifting, sustainability and tax
Review on the Use of Machine Learning and Artificial Intelligence in Accounting Research 회계학에서 머신러닝 및 인공지능 활용에 관한 문헌 연구
임지해 Jee-hae Lim , 나현종 Hyun Jong Na
DOI:10.24056/KAR.2025.10.005 KAR Vol.50(No.5) 233-272, 2025
Abstract
This study (1) systematically analyzes and compares the current state of accounting research utilizing machine learning and artificial intelligence (ML/AI) technologies between international and domestic contexts from 2015 to 2025, (2) diagnoses the current position of domestic research, and (3) propose future development directions. The rapid advancement of ML/AI technologies has created unprecedented opportunities for accounting research to expand beyond traditional methodological boundaries, enabling researchers to address previously intractable questions and develop novel theoretical insights. Against this backdrop, understanding the current landscape and identifying research gaps becomes crucial for advancing the field.
To achieve these objectives, we conducted a comprehensive literature review by selecting 61 papers from major international accounting journals and 13 papers from Korean Citation Index (KCI) registered journals. Our analysis employed a multidimensional classification framework consisting of three key dimensions: ML/AI utilization types, research topics, and data types. The ML/AI utilization types were further categorized into four distinct areas: predictive research (forecasting future outcomes), diagnostic research (quantifying previously unmeasurable concepts), descriptive research (discovering new phenomena through data exploration), and prescriptive research (developing practical solutions and recommendations). This comprehensive framework allows for a nuanced understanding of how ML/AI technologies are being integrated into accounting research across different methodological approaches.
We find that international research has experienced dramatic growth since 2022, demonstrating a balanced development between predictive (37.7%), measurement (34.4%), descriptive (13.1%) and prescriptive (13.1%) research. The measurement research domain has achieved particularly innovative outcomes by quantifying previously unmeasurable concepts such as earnings virality, CEO depression, and voice delivery quality, thereby expanding the theoretical horizons of accounting research. These developments represent a shift in accounting research methodology, moving beyond traditional archival approaches to embrace data-driven, inductive methodologies that can uncover hidden patterns and relationships in financial data. By research topics, the development has been evenly distributed across auditing (27.9%), capital market research (24.6%), and financial reporting (24.6%), indicating a broad-based adoption of ML/AI technologies across different accounting subfields. In terms of data utilization, researchers have diversely employed structured financial data (47.5%), textual data (21.3%), and alternative data (18.0%), showcasing the versatility of ML/AI applications in processing various data formats and sources.
In stark contrast, domestic research exhibits significant temporal and qualitative gaps compared to international counterparts. Korean accounting research in this domain began 3-4 years later than international research and shows substantial disparities in both scale and quality. Domestic research demonstrates a pronounced concentration on prediction-focused studies (61.5%) and reliance on structured financial data (76.9%), resulting in limited research scope and methodological approaches. More critically, while international research extends theoretical boundaries through the development of novel measurement indicators and creative research designs, domestic research primarily remains confined to performance verification of methodologies. This gap reflects deeper structural challenges including limited access to alternative data sources, insufficient interdisciplinary collaboration, or inadequate computational resources.
The academic contributions of this study are threefold. First, this research represents the first systematic literature review of ML/AI-related accounting research, providing an objective assessment of the current status. By establishing a comprehensive baseline understanding, this study serves as a foundation for future research and policy development in this rapidly evolving field. Second, through our multidimensional classification framework encompassing utilization types, research topics, and data types, we analyze the multilayered impact of ML/AI technologies on accounting research. This framework provides a structured approach for understanding the diverse ways in which ML/AI can contribute to accounting knowledge and practice. Third, through systematic comparison between international and domestic research, we specifically identify the current position of domestic research and concrete development challenges, providing actionable insights for improving the research landscape.
Our findings reveal that ML/AI technologies are driving a paradigm shift in accounting research methodology, enabling the quantification of previously unmeasurable concepts and suggesting the possibility of supplementally utilizing data-driven inductive approaches to discover new theoretical insights. This methodological evolution has important implications for how accounting researchers approach their work, moving from purely theory-driven deductive approaches to embracing the potential of data-driven discovery.
Finally, this study proposes that future research development requires advancement across four key areas corresponding to our classification framework. In predictive research, there is a need for theory-based research designs that go beyond simple performance improvement to provide meaningful accounting insights. In measurement research, the quantification of domestically unique concepts that differentiate from international precedents could make significant contributions to accounting scholarship in the Korean context. In explanatory research, the utilization of alternative data to discover new phenomena represents a promising avenue for expanding accounting knowledge. In prescriptive research, the development of systematic educational methodologies is essential for building ML/AI capabilities within the accounting profession. Through these multifaceted approaches, we expect that domestic accounting research can play a more distinctive and leading role in the global ML/AI accounting research ecosystem, ultimately contributing to both theoretical advancement and practical improvement in accounting practice.
Environmental, Social, and Governance (ESG) in Accounting and Capital Markets: A Literature Review on Economic Relevance, Disclosure Frictions, and Valuation Implications
Aaron Yoon
DOI:10.24056/KAR.2025.10.006 KAR Vol.50(No.5) 273-286, 2025
Abstract
In this literature review, I examine the evolving role of environmental, social, and governance (ESG) factors in accounting and capital markets. I organize the existing research into four major themes: (1) the historical development of ESG as a concept distinct from socially responsible investing (SRI) and corporate social responsibility (CSR); (2) the capital market effects of ESG disclosures and the ways investors incorporate ESG information into their decision-making processes; (3) frictions in ESG reporting, including disagreements among ESG rating agencies and evidence of greenwashing; and (4) the value relevance of ESG risk, particularly in relation to firm valuation models and carbon disclosures. I also discuss the implications of ESG standardization for emerging markets, where global comparability and local relevance can conflict. By synthesizing findings from recent empirical studies and conceptual frameworks, the aim of this manuscript is to clarify how ESG relates to economic outcomes and to identify opportunities for future research in financial reporting, assurance, and investment analysis.
Discussion of “Environmental, Social, and Governance (ESG) in Accounting and Capital Markets: A Literature Review on Economic Relevance, Disclosure Frictions, and Valuation Implications”
Boxian Wang , Jiyoon Lee
DOI:10.24056/KAR.2025.10.007 KAR Vol.50(No.5) 287-307, 2025
Abstract
Yoon (2025) provides a comprehensive literature review on environmental, social, and governance (ESG) in accounting and capital markets, with a primary focus on studies from developed economies. Recognizing that institutional, regulatory, and capital market environments differ substantially across countries, we complement Yoon (2025) by reviewing ESG studies on Korean firms, which remain underrepresented in the original review. We categorize the literature into five areas: (1) the effect of ESG performance on firm outcomes, (2) the external and internal drivers of ESG performance, (3) ESG disclosure practices―including carbon disclosure, (4) individual ESG dimensions, particularly environmental and social aspects, and (5) extended topics such as ESG committees, ESG-related news, and ESG-related financial instruments. By synthesizing findings from the Korean capital market, this discussion provides a structured foundation for future research on the ESG practices of Korean firms and offers a reference framework for scholars examining ESG issues in other late adopters or transitional markets.
Key Words
ESG performance, carbon disclosure, korean capital market
