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
박영현 (경남대학교) 정준식 (경남대학교)
저널정보
한국해양비즈니스학회 해양비즈니스 해양비즈니스 제50호
발행연도
2021.12
수록면
1 - 24 (24page)

이용수

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

초록· 키워드

오류제보하기
The data opportunities of big data service finance are summarized into three main categories. The anomaly forecast scenario, the future scenario, and the current forecast scenario have reached that point, this scenario has not been successful, has not been completed, has reached this point. The higher management has it, and there is a possibility of success in systems thinking, marketing strategies, etc. Next, future scenarios will be able to cope when they are no longer able to cope. So far, more stages have been reached and even more levels have been reached. Domestic shipping companies have been implementing automation, remote control, real-time cargo management, and ship location tracking while maintaining the existing IT business system. Data sharing and accessibility are still poor, and there is a shortage of related experts. Although the domestic shipping industry is building an ICT system, it is maintaining the system of the past ERP level, which does not reflect current technological trends. In the shipping sector, the application of technology is delayed compared to onshore manufacturing facilities, and there is still a perception that the benefits or added value of the introduction of ICT technology in shipping are not of much help to the factors of increase in volume and shippers. The use of big data can be utilized as a decision-making and solution tool for users based on prediction and analysis of various scenarios. It is believed to enable the transformation of Accordingly, it will be possible to utilize big data in more diverse forms in the shipping and logistics field, and it is believed that unstructured data will play a major role in interpreting and explaining existing structured data.

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