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
박은주 (성신여자대학교) 이영주 (성신여자대학교)
저널정보
복식문화학회 복식문화연구 복식문화연구 제31권 제2호
발행연도
2023.4
수록면
173 - 192 (20page)

이용수

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

초록· 키워드

오류제보하기
This study conducted in-depth interviews with experts to implement Hanbok shows on metaverse, which can contribute to the succession and development of Hanbok design and to establish a platform that fits the reality of the Hanbok industry and consumers. In-depth interviews were conducted to collect opinions from experts, and the derived contents were divided and analyzed using an affinity diagram. Experts were positive about the use of the metaverse platform of the Hanbok show in terms of impact, accessibility, exposure, virtual fitting, issuance of NFTs, and promotion of Hanbok brands. As a result of verifying the validity of the four components of metaverse, experts highly evaluated the possibility of using Hanbok shows in the order of virtual reality, augmented reality, mirror world, and lifelogging. Visuality, influence, marketing efficiency in virtual reality, immersion in augmented reality, fantasy and artistic elements, expression, diversity, and abundant experiences were expected. The platform’s requirements emphasized realistic implementation equipment and technology, collaboration between Hanbok designers and producers, in addition to government support. Results of this study showed that appropriate target was analyzed to be in the 10–30s, and the appropriate price range was found to be able to sell at a discount of 40–80% compared to offline. This study provides useful implications for the service development of metaverse content, which will also be actively used in the Hanbok field, and can be used as basic data for reviving the Korean Hanbok industry and strengthening international competitiveness.

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