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논문검색

업무-기술적합(TTF) 영향에 대한 다차항 회귀분석과 반응표면 방법론적 접근: 그룹지원시스템(GSS)의 경우

원문정보

Polynomial Regression Analysis and Response Surface Methodology in Task-Technology Fit Research: The Case of GSS (Group Support Systems)

강소라, 김민수, 양희동

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

This study takes a quantitative approach to the influence of TTF (Task-Technology Fit) on the individual's use and performance of GSS (Group Support Systems), while traditional studies on TTF have taken the experimental approach to explore the characteristic fit between diverse tasks and technologies. We have the following two research inquires: Are the IS use and performance maximized when information technologies are provided by the exact amount of demand?; and, Does TTF at the high level between task and IT produce better IS use (or performance) than at the low level? To investigate these issues, we use the polynomial regression analysis and response surface methodology of Edwards (1993) instead of traditional direct measure of TTF. This method measures the degree of desired and actual level of information technologies in conducting tasks, and traces the dynamic changes of dependent variables (IS use and performance) according to the variances of each independent variable. Our results conclude that user's IS use and performance are maximized when information technologies are actually provided by no more or less than the desired level. We also found that TTF at the high level promotes better IS use and performance than TTF at the low level.

목차

I. 서론
 II. 이론적 배경
  2.1 업무기술 적합(Task-Technology Fit, TTF)
  2.2 그룹 지원 시스템(Group Support System)
 III. 연구모형과 가설
 IV. 조사방법론
  4.1 개념의 조작적 정의와 측정
  4.2 자료의 수집, 연구방법 및 구성
 V. 연구가설의 검증
  5.1 구성개념의 신뢰성 및 타당성 검증
  5.2 분석 결과
 VI. 토론 및 결론
 참고문헌
 <부록> 설문 항목

저자정보

  • 강소라 Sora Kang. 호서대학교 디지털비즈니스학부
  • 김민수 Min-Soo Kim. 이화여자대학교 경영대학 경영학과
  • 양희동 Hee-Dong Yang. 이화여자대학교 경영대학 경영학과

참고문헌

자료제공 : 네이버학술정보

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