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
질문

논문 기본 정보

자료유형
학술저널
저자정보
장진열 (인천대학교) 송상화 (인천대학교)
저널정보
한국SCM학회 한국 SCM 학회지 한국SCM학회지 제22권 제1호
발행연도
2022.5
수록면
53 - 66 (14page)
DOI
10.25052/KSCM.2022.5.22.1.53

이용수

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

이 논문의 연구 히스토리 (2)

초록· 키워드

오류제보하기
With the growth of the global economy, along with the rapid spread of mobile devices, e-commerce and COVID-19, transactions between shippers and logistics service companies and domestic import and export trades have shown a drastic increase. Platforms merging from the 4th industrial revolution have allowed Small and Medium Enterprises (SME) logistics service companies to participate as equal bidding service providers in Business-to-Business (B2B) logistics field. However, SME logistics services have experienced difficulties in accessing and utilizing the B2B logistics platforms because of the existing trading practices, such as information asymmetry and closures led by existing large corporations in the logistics industry. Therefore, it is necessary for the SME to study the factors that influence users’ decision to use the platform when securing its competitiveness in the logistics field. Since it is difficult to reflect a company’s relationship characteristics of B2B transactions with existing Technology Acceptance Models(TAMs), it is extended by adding fair trade and risk factors to study the technology acceptance behavior of users. The studies show that social influence, price efficiency and fair trade are the crucial variables for the users’ decision to use the platform. It also demonstrates that fair trade, in correlation to risk, has the significant impact on users’ acceptance of the platform. Based on the results of this study, it is beneficial if a company designs a platform structure from the perspective of fair trade and risks when developing a B2B platform in the future.

목차

1. 서론
2. 선행 연구
3. 연구모형
4. 실증연구
5. 결론
REFERENCES

참고문헌 (46)

참고문헌 신청

함께 읽어보면 좋을 논문

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

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2022-324-001347698