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
Park, Sung Bum (Big Data Strategy Center, National Information Society Agency) Lee, Sangwon (Division of Information and Electronic Commerce, Wonkwang University) Chae, Seong Wook (Department of Business Administration, Hoseo University) Zo, Hangjung (Department of Business and Technology Management, Korea Advanced Institute of Science and Technology)
저널정보
한국경영정보학회 Asia pacific journal of information systems Asia pacific journal of information systems 제25권 제2호
발행연도
2015.1
수록면
265 - 288 (24page)

이용수

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

초록· 키워드

오류제보하기
IT convergence services, as the main stream of the digital age, are currently on their way to include the concept of Software as a Service (SaaS), where IT products and services are integrated as one. In particular, the recently introduced web-service-based SaaS is expected to be a more developed SaaS model. This new model provides greater influence on clients' job performances than its previous models, such as application service providers and the web-native phase. However, the effects of technology maturity on task performance have been overlooked in adoption and performance studies. Accordingly, this study introduces SaaS technology maturity as the exogenous technological characteristic influencing job performance. This study also examines the relationships among various SaaS-related performances according to the different levels of SaaS maturity. Results suggest that applying innovative technologies (such as SaaS), particularly when the technology reaches a certain level of maturity, is more helpful for managers in improving task-technology fit and job performance. This study makes an academic contribution by establishing and validating a performance model empirically with SaaS technology maturity perspectives.

목차

등록된 정보가 없습니다.

참고문헌 (87)

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