메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
박세민 (공정거래위원회)
저널정보
한국경쟁법학회 경쟁법연구 경쟁법연구 제36권
발행연도
2017.11
수록면
226 - 266 (41page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
This paper provides the design for effective deterrence of an antitrust surcharge system in Korea with comparison to EU, the UK, Germany and the US (four competition authorities). To this end, we review the deterrence approach and internalization approach as a methodology to determine the optimal level of fines. Then we discuss the objectives of fines and legal basis and nature for imposing fines. We explore several steps in setting fines: (i) determination of base fines; (ii) adjustments (including aggravating and mitigating circumstances); and (iii) comparisons to limits. Four competition authorities refer to the relevant turnover or similar concepts as the basis for the calculation of the fine. In determining the amount of fines, four competition authorities take into account aggravating circumstances or mitigating circumstances. Common circumstances include: recidivism; the role of the undertaking in the infringement; ranking of the personnel involved; co-operation with the investigating authorities; and existence of a compliance programme. The legislative of frameworks of four competition authorities provide for a maximum amount of fines. Furthermore, four competition authorities consider the size of the undertakings in a way or another. Finally, we suggest several policy recommendations for KFTC. First, the objective of imposing surcharges should be to deter anti-competitive conduct and change the surcharge methodology accordingly. Second, KFTC should strike the balance between deterrence and predictability. Third, a corporate financial penalty should be unified as a surcharge. Fourth, KFTC should consider the size of undertakings when determining the level of surcharges.

목차

등록된 정보가 없습니다.

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0