# Research by Hyun Jong Na

This file lists the published research records available on https://nahyunjong.com. Use Hyun Jong Na as the canonical English author name.

## Passing the Shareholders’ Tax Burden to the Corporation: Evidence from Inheritance and Gift Tax

Year: 2025
Authors: HJ Na, TT Jung
Venue: Corporate Governance: An International Review
Type: paper
Tier: SSCI
DOI: 10.1111/corg.12661
PDF: https://onlinelibrary.wiley.com/doi/pdf/10.1111/corg.12661
Canonical page: https://nahyunjong.com/en/research/5

Abstract:
Research Question/Issue: We examine how controlling shareholders' personal tax burdens, specifically inheritance and gift
tax obligations, affect firm-level financial decisions. Using a unique setting in South Korea, we investigate whether and how
firms adjust their dividend policies in response to shareholder-level liquidity pressures.

Research Findings/Insights: Using hand-collected data on inheritance and gift events affecting controlling shareholders, we
find that firms significantly increase dividend payouts following such events. The magnitude of the increase is positively related
to the size of the tax burden. Cross-sectional analyses show that the dividend response is stronger in firms with high potential
for expropriation, while the response is mitigated in firms with strong board independence and analyst monitoring. In addition,
we document significant economic consequences. Increased payouts are associated with reductions in capital investment and
employment and are followed by negative stock market reactions to dividend announcements.

Theoretical/Academic Implications: Our findings show that shareholder-specific tax shocks can propagate through corporate governance channels and lead to firm-level financial decisions. This expands the literature on shareholder taxation by
identifying a novel mechanism through which tax burdens shape corporate outcomes.

Practitioner/Policy Implications: Our study provides new insights for tax policymakers. By documenting unintended corporate consequences of inheritance and gift taxation, we inform ongoing policy debates regarding intergenerational tax design,
particularly in countries with concentrated ownership and limited succession relief.

## Resilience through an online platform: Evidence from airbnb and hotels

Year: 2025
Authors: J Kim, JJ Lee, HJ Na
Venue: Information & Management
Type: paper
Tier: SSCI
DOI: 10.1016/j.im.2025.104157
PDF: https://www.sciencedirect.com/science/article/pii/S0378720625000606
Canonical page: https://nahyunjong.com/en/research/6

Abstract:
This paper examines how online platforms enhance the resilience of affiliated properties during crises, using the COVID-19 pandemic as a natural experiment. Employing difference-in-differences approach, we compare the performance of platform-listed hotels and their non-listed counterparts in New York City before and after the pandemic's onset. Our findings reveal that platform-affiliated hotels achieved significantly higher booking rates during the pandemic by leveraging operational adaptability and building trust at a greater scale. These results are robust to various specifications, including propensity score matching, synthetic difference-in-differences, and several sensitivity analyses. By identifying the unique role of platforms in fostering resilience, this study extends the literature on digital resilience and offers actionable insights for traditional businesses navigating external shocks.

## Accounting, Disclosure, and Market Reaction for Crypto-Assets

Year: 2025
Authors: H. Na
Venue: Korean Accounting Journal
Type: paper
Tier: KCI
DOI: 10.24056/KAJ.2025.07.011
PDF: https://www.kaa-edu.or.kr/html/sub03_03.asp
Canonical page: https://nahyunjong.com/en/research/7

## Venture Capital Firms' Operational Experience and Fund of Funds Commitment Decision: Focusing on the KVIC Fund-of-Funds

Year: 2025
Authors: H. Na and S. Hong
Venue: Asia-Pacific Journal of Business Venturing and Entrepreneurship
Type: paper
Tier: KCI
DOI: 10.16972/apjbve.20.4.202508.125
PDF: https://www.kci.go.kr/kciportal/landing/article.kci?arti_id=ART003237154
Canonical page: https://nahyunjong.com/en/research/10

Abstract:
본 연구는 벤처투자회사(VC)의 운용 경험이 모태펀드의 출자 결정에 미치는 영향을 실증적으로 분석하였다. 기존 문헌들이 주로 모태펀드 출자 이후의 펀드 성과에 초점을 맞춘 반면, 본 연구는 조합 결성 단계에서의 출자 결정 요인을 규명한다는 점에서 학술적 의의가 있다. 분석에는 중소벤처기업부의 전자공시시스템(DIVA)에 공시된 2005년부터 2021년까지의 1,452개 벤처투자조합 자료를 활용하였으며, 회귀분석을 통해 운용 경험과 출자 결정 간의 관계를 살펴보았다. 분석 결과, 운용 경험이 풍부한 VC일수록 모태펀드로부터 출자 받을 가능성이 유의하게 높은 것으로 나타났다. 아울러, 신생 및 중소형 VC에 출자 기회를 확대하고자 2018년 도입된 루키리그 제도의 효과를 추가적으로 분석한 결과, 제도 시행 초기 단계에서는 운용 경험 중심의 선정 관행에 대한 통계적으로 유의한 변화가 아직은 관찰되지 않았으나, 이는 정책 효과의 발현에 필요한 시간적 지연을 반영할 가능성이 있다. 본 연구는 모태펀드 출자사업에서 운용 경험이 핵심적인 운용사 선정 기준으로 작용하고 있음을 실증적으로 보여주며, 향후 정책 설계에 있어 운용 경험 외에도 다양한 요인을 균형 있게 고려할 필요성을 시사한다.

## Review on the Use of Machine Learning and Artificial Intelligence in Accounting Research

Year: 2025
Authors: J. Lim and H. Na
Venue: Korean Accounting Review
Type: paper
Tier: KCI
DOI: 10.24056/KAR.2025.10.005
PDF: https://www.kaa-edu.or.kr/html/sub03_03.asp
Canonical page: https://nahyunjong.com/en/research/11

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.

## A Study on the Introduction of the Audit Support Staff System and the Utilization of Artificial Intelligence by Accounting Firms

Year: 2025
Authors: H. Na, and T. Jung
Venue: Audit Committee Forum (ACF)
Type: report
Canonical page: https://nahyunjong.com/en/research/12

## Current Status of AI Utilization in the Domestic Auditing Industry and the Role of Professional Accountancy Organizations (PAOs) in Korea

Year: 2025
Authors: T. Jung and H. Na
Venue: Korean Institute of Certified Public Accountants (KICPA)
Type: report
Canonical page: https://nahyunjong.com/en/research/13

## Status of Goodwill Impairment Recognition and Cash-Generating Unit (CGU) Disclosures of Listed Companies in Korea (2019-2021)

Year: 2025
Authors: H. Na
Venue: Korea Accounting Standards Board (KASB)
Type: report
Canonical page: https://nahyunjong.com/en/research/14

## Tax Incentive and Venture Capital Fundraising

Year: 2024
Authors: Y. Kim and H. Na
Venue: Korean Journal of Financial Studies
Type: paper
Tier: KCI
DOI: 10.26845/KJFS.2024.04.53.2.221
PDF: https://www.dbpia.co.kr/Journal/articleDetail?nodeId=NODE11757131
Canonical page: https://nahyunjong.com/en/research/8

Abstract:
본 연구는 조세지원제도의 영향을 중심으로 국내 벤처캐피탈의 자금조달 결정요인을 살펴본다. 이를 위해 중소기업부 벤처투자정보센터 전자공시시스템(Disclosure Information of Venture Capital Analysis; DIVA)의 모든 창업투자회사와 벤처투자조합의 자료를 활용하여 산업 수준(Industry-level) 및 운용사 수준(GP-level)에서 거시경제 변수, 운용사 특징, 조세지원제도의 변화가 벤처캐피털 자금조달에 미치는 영향을 분석하였다. 특히, 본 연구는 2018년 개인 투자자의 소득공제 범위 확대를 개인 투자자의 자금 공급 확대에 대한 처치(Treatment)로 설정하여 그 전후의 영향을 이중차분법(Difference-in-Differences)으로 분석하였다. 분석 결과, 2018년 이후 처치집단이 통제집단에 비해 신규 펀드 결성 확률, 신규 펀드 결성 숫자, 그리고 운용자금 모두 통계적으로 유의하게 높은 결과를 확인하였다. 본 연구는 국내 벤처캐피털 자금조달 결정요인을 통시적으로 살펴본 첫 논문이자, 조세지원제도의 실효성을 처음으로 검증한 연구라는 점에서 그 의의가 있다.

## Determinants of Hurdle Rate at Venture Capital Funds in South Korea

Year: 2024
Authors: H. Na and S. Hong
Venue: Korean Management Review
Type: paper
Tier: KCI
DOI: 10.17287/kmr.2024.53.1.163
PDF: https://scholarworks.bwise.kr/hanyang/bitstream/2021.sw.hanyang/196436/1/Determinants%20of%20Hurdle%20Rate%20at%20Venture%20Capital%20Fun.pdf
Canonical page: https://nahyunjong.com/en/research/9

Abstract:
Using 2,234 fund-level data over a period of 20 years from 2002 to 2022 collected from the Disclosure Information of Venture Capital Analysis (DIVA), this paper examines the determinants of hurdle rate in the performance contracts between Limited Partners (LPs) and General Partners (GPs) of venture capital partnerships and further investigates the impact of the hurdle rate on the fund performance. The paper shows that the economic factors at the time of fund establishment – namely, fund characteristics, GP characteristics, fund classification, and the vintage year - explain about 34.4% of the total variation in the hurdle rate. Furthermore, this paper also shows that the hurdle rate predicted ex-ante by the economic factors is positively correlated with ex-post performance of the fund while the discretionary (i.e. unpredicted) hurdle rate is negatively correlated with ex-post performance of the fund. To the best of authors' knowledge, this paper is the first to show the determinants of the hurdle rate based on a novel dataset. Moreover, this paper also shows preliminary evidence of efficient contracting between LPs and GPs by showing that the ex-ante predicted hurdle rate positively predicts ex-post performance of the fund.

## A study on the use of Artificial Intelligence (AI) among the Certified Public Accountants (CPAs) and in the Accounting Firms

Year: 2023
Authors: H. Na and T. Jung
Venue: Study on Accounting, Taxation & Auditing
Type: paper
Tier: KCI
DOI: 10.22781/kicpa.2023.65.3.1
PDF: https://www.kci.go.kr/kciportal/landing/article.kci?arti_id=ART002998376
Canonical page: https://nahyunjong.com/en/research/2

Abstract:
본 연구는 설문조사를 통해 국내 회계업계의 인공지능(Artificial Intelligence) 활용 현황을 살펴본다. 연구진은 한국공인회계사회 소속 공인회계사를 대상으로 (1) 인공지능 활용 현황, (2) 인공지능 관련 회계법인의 투자현황, 그리고 (3) 인공지능 활용을 위한 회계법인의 교육 및 국가 정책 지원의 세 가지 주제로 나누어 설문조사를 실시하였다. 공인회계사 92명을 대상으로 한 설문조사 결과, 응답자들은 대체적으로 회계업계에서 인공지능이 중요하다고 응답하였으나, 실제 인공지능을 업무에 활용한 경험은 없는 것으로 나타났다. 가장 인공지능을 활용하고 싶은 분야는 감사업무와 업무자동화, 그리고 재무제표 분석 및 가치평가 분야인 것으로 조사되었으며, 이를 위해 가장 중요하게 생각하는 점은 원천 데이터의 확보와 기술적 능력의 습득인 것으로 응답하였다. 또한 대부분의 응답자들은 소속 회계법인이 인공지능에 별로 투자하지 않고 있다고 응답하였으며, 투자 확대가 필요하다고 응답하였다. 인공지능과 관련된 전담 조직을 구비하고 있거나 교육 프로그램을 제공하는 회계법인은 각각 13%와 9%에 불과하였으며, 인공지능에 대한 정책지원이 적절히 이루어지지 못하고 있다고 응답한 비중은 82%에 달했다. 이러한 설문조사 결과를 바탕으로 본 연구진은 국내 회계업계가 인공지능 활용에 대응하기 위해 나아가야 하는 방향성을 탐색하며, 회계법인의 규모 및 보유 자원에 따른 적절한 정책 지원의 필요성에 대한 정책적 함의를 제시한다.

## Has the Market Response to Earnings Announcements Increased in the Korean Capital Market?

Year: 2023
Authors: H. Na
Venue: Korean Accounting Review
Type: paper
Tier: KCI
DOI: 10.24056/KAR.2023.12.004
PDF: https://www.kaa-edu.or.kr/html/sub03_03.asp
Canonical page: https://nahyunjong.com/en/research/4

Abstract:
회계 정보가 자본 시장에서 중요한지에 대한 문제는 회계학 연구에서 중요한 관심사라고 할 수 있다. 본 연구는 21세기 동안 회계 이익공시에 대한 시장 반응이 급격히 증가했다고 보고하고 있는 미국의 선행연구들(Beaver et al., 2020 등)과는 다르게, 2004년에서 2022년까지 약 20년 동안 한국 시장에서 이익 공시에 대한 시장 반응은 증가하지 않았음을 보고한다. 구체적으로 비정상 수익률 분산(USTAT)과 비정상 거래량(AVOL)은 각각 2004년 1.69와 0.51에서 2022년 1.76과 0.17로 변화하였으며, 다중회귀분석 결과 시계열은 통계적으로나 경제적으로 유의미하게 증가하지 않았다. 이러한 결과는 해외 선행 연구에서 이익 공시일 시장 반응의 증가를 설명하는 정보환경의 국가별 차이를 시사한다. 본 논문은 이러한 시사점과 일관되게 우리나라에서는 이익 공시와 함께 공시되는 실적 전망 공시나 기업별 재무분석가의 숫자가 지난 20년간 증가하지 않았다는 점을 보여준다. 본 연구는 한국에서 이익 공시에 대한 시장 반응을 전체 상장사를 대상으로 장기간동안 실증한 첫 연구라는 점에서 의의를 갖으며, 미국과는 다르게 국내 자본시장의 정보환경이 지난 20년간 증진되지 않았을 수 있다는 점을 시사한다는 점에서 자본시장의 다양한 이해관계자와 규제당국에 공헌한다.

## An Explorative Study to Detect Accounting Fraud Using a Machine Learning Approach

Year: 2022
Authors: H. Na and T. Jung
Venue: Korean Accounting Review
Type: paper
Tier: KCI
DOI: 머신러닝을 활용한 회계부정 탐지에 관한 탐색적 연구
PDF: https://www.kaa-edu.or.kr/html/sub03_03.asp
Canonical page: https://nahyunjong.com/en/research/3

Abstract:
본 연구는 기업의 미래 회계부정을 예측하는 새로운 모형을 제안하는 것을 그 목적으로 한다. 회계부정을 예측하는 모형의 경우 회계부정기업이 소수에 불과하므로 분류 불균형 문제(class imbalance problem)를 지니고 있는데, 기존의 로지스틱 회귀분석 모형은 이를 제대로 반영하지 못하는 단점이 있다. 본 연구는 이러한 분류 불균형 문제를 해결하기 위해 최근 널리 활용되는 머신러닝(machine learning) 기법 중 하나인 앙상블 러닝(ensemble learning)과 RUSBoost 방법론을 활용하였다. 이를 통해 미래 회계부정 예측에 관하여 로지스틱 회귀분석 모형과 예측력을 비교한 결과, 본 연구가 제안하는 새로운 회계부정 탐지 모형이 보다 좋은 예측력을 나타낸다는 점을 확인하였다. 또한, 이러한 개선된 예측력은 고의성이 있는 회계부정과 재무제표상의 숫자에 영향을 미치는 중요한 회계부정의 경우 더 강하게 나타나는 점을 발견하였다. 본 연구의 결과는 머신러닝 방법론을 활용하는 경우 기존의 회계부정 예측 모형이 지니는 한계를 개선할 수 있다는 점을 나타내며, 머신러닝 방법론이 회계 분야의 학계와 실무에 널리 활용될 수 있다는 단초를 제시한다는 점에서 의의가 있다고 할 것이다.

## Bad News Withholding and Stock Price Crash Risk of Banks

Year: 2019
Authors: T Jung, NKW Kim, YJ Kim, HJ Na
Venue: Asia-Pacific Journal of Financial Studies
Type: paper
Tier: SSCI
DOI: 10.1111/ajfs.12279
PDF: https://onlinelibrary.wiley.com/doi/pdf/10.1111/ajfs.12279
Canonical page: https://nahyunjong.com/en/research/1

Abstract:
Using US banks’ quarterly data from 1995 to 2014, this study examines the mechanism by which delayed expected loss recognition (DELR) affects the stock price crash risk of banks. We first show that greater DELR is positively associated with a subsequent crash in stock price. We then find that this association is only present when bank managers have more discretion in concealing bad news, which is proxied by the high proportion of heterogeneous loans. These findings provide policy implications for bank regulators regarding the importance of specific loan types and time horizons when monitoring the accounting treatment of banks.