Asia pacific journal of information systems

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

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

  • 강소라 (호서대학교 디지털비즈니스학부) ;
  • 김민수 (이화여자대학교 경영대학 경영학과) ;
  • 양희동 (이화여자대학교 경영대학 경영학과)
  • Published : 2006.06.30
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Abstract

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.

Keywords

References

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