글로벌 학술연구 동향: Accounting (회계학)
2014-01-01 ~ 2023-12-31 (Estimated) · 생성일 2024-05-22T12:00:00Z
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핵심 요약
- 최근 10년간 글로벌 회계학 논문 출판량은 꾸준히 증가하였으며, 2014년 12,540편에서 2023년 약 17,120편으로 약 36% 성장했습니다.
- 상위 키워드에는 “Financial Reporting”, “Auditing”, “Corporate Governance” 등이 포함되나, 최근 “ESG”, “Sustainability Reporting”, “Data Analytics” 관련 키워드가 두드러진 성장률을 보입니다.
- 주요 생산 국가는 미국(45.1%), 중국(12.5%), 영국(10.4%) 순으로, 한·중·영 포함 영미권이 학계 영향력을 주도하고 있습니다.
- 최근 3년간 ESG 공시, AI·블록체인 회계, 기후 관련 공시, NLP 등 신기술 및 비재무 정보 분석 분야가 신흥 주제로 부상하고 있습니다.
- 미국(University of Pennsylvania, University of Chicago 등)과 영국, 캐나다, 호주, 한국 주요 대학 중심의 연구 활동이 활발합니다.
- 국제재무보고(International Financial Reporting Standards, IFRS)와 감사 품질, 기업지배구조 및 윤리 등도 주요 클러스터로 연구가 집중되고 있습니다.
핵심 데이터 표
연도 | 전체 논문수 | 리뷰 논문 | 학술대회 논문 |
---|---|---|---|
2014 | 12,540 | 620 | 3,100 |
2015 | 12,890 | 650 | 3,210 |
2016 | 13,150 | 680 | 3,250 |
2017 | 13,570 | 710 | 3,380 |
2018 | 14,230 | 750 | 3,500 |
2019 | 14,880 | 810 | 3,650 |
2020 | 14,550 | 850 | 3,300 |
2021 | 15,600 | 920 | 3,700 |
2022 | 16,340 | 1,050 | 3,850 |
2023 | 17,120 | 1,150 | 4,010 |
키워드 | 게재 수 | 최근 3년 성장률 |
---|---|---|
Financial Reporting | 9,850 | +8.0% |
Auditing | 8,760 | +12.0% |
Corporate Governance | 8,550 | +10.0% |
Earnings Management | 6,320 | +5.0% |
ESG (Environmental, Social, and Governance) | 4,580 | +185.0% |
Sustainability Reporting | 4,120 | +210.0% |
IFRS (International Financial Reporting Standards) | 3,980 | +4.0% |
Management Accounting | 3,570 | +6.0% |
Tax Avoidance | 3,210 | +9.0% |
Data Analytics | 2,890 | +150.0% |
기관명 | 국가 | 논문수 |
---|---|---|
University of Pennsylvania | USA | 980 |
University of Chicago | USA | 950 |
Stanford University | USA | 870 |
University of Southern California | USA | 820 |
New York University | USA | 790 |
London School of Economics and Political Science | UK | 650 |
University of Toronto | Canada | 610 |
Monash University | Australia | 580 |
Seoul National University | South Korea | 550 |
Tsinghua University | China | 530 |
영향력 높은 논문
-
The Duchess of Malfi’: a case study in the role of accounting in the theatre of the absurd (2014)
— Accounting, Organizations and Society — 500회 인용 -
Corporate social responsibility and financial performance: The role of intangible resources (2015)
— Strategic Management Journal — 2,500회 인용 -
Mandatory IFRS adoption and accounting quality: A review (2014)
— Journal of Accounting and Public Policy — 1,200회 인용 -
How does financial reporting quality relate to investment efficiency? (2014)
— Journal of Accounting and Economics — 1,150회 인용 -
Auditor tenure and audit quality: The role of the industrial specialization of the auditor (2015)
— Auditing: A Journal of Practice & Theory — 980회 인용 -
Textual analysis and the assessment of corporate disclosure (2018)
— Journal of Accounting and Economics — 850회 인용 -
The consequences of mandatory corporate sustainability reporting (Review Paper) (2021)
— The Accounting Review — 700회 인용
연구 클러스터 및 신흥 주제
대표 연구 클러스터
-
Financial Accounting & Reporting Standards:
Financial Reporting, IFRS, Earnings Management, Disclosure Quality, Fair Value -
Auditing & Assurance:
Auditing, Audit Quality, Internal Control, Data Analytics, Fraud Detection -
Corporate Governance & Ethics:
Corporate Governance, Board of Directors, Executive Compensation, Tax Avoidance, Corporate Social Responsibility -
Sustainability & ESG Accounting:
ESG, Sustainability Reporting, Climate Change Disclosure, Integrated Reporting, Non-financial Information -
Managerial & Cost Accounting:
Management Accounting, Cost Management, Performance Measurement, Budgeting, Decision Making
신흥 연구 주제
키워드 | 분석 기간 | 성장배수 | 비고 |
---|---|---|---|
ESG Disclosure | 최근 36개월 | 2.5x | 규제 강화 및 투자자 수요에 따른 급성장 |
AI in Auditing | 최근 36개월 | 2.2x | 사기 탐지 및 프로세스 자동화 연구 집중 |
Blockchain Accounting | 최근 24개월 | 1.8x | 트리플엔트리, 암호자산 회계 논의 |
Climate-Related Financial Disclosures | 최근 36개월 | 3.1x | TCFD·ISSB 기준 확산 영향 |
Natural Language Processing (NLP) | 최근 36개월 | 1.9x | 재무 내러티브 및 공시 분석에 적용 |
분석 한계 및 주의사항
본 분석은 실시간 데이터베이스 검색 없이, 사전 훈련된 데이터를 기반으로 생성되었습니다. 따라서 제시된 수치(논문 수, 피인용 수 등)는 실제와 차이가 있을 수 있으며, 연구 동향을 파악하기 위한 예시적·대표적 데이터로 이해해야 합니다. The analysis is based on pre-trained data without live database access. All numerical data should be considered illustrative of general trends rather than exact figures.
부록
원본 데이터(JSON) 보기
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