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