A Meta-Regression of Task-Technology Fit in Information Systems Research
Document Type
Article
Publication Date
8-2022
Abstract
Task-technology fit (TTF) is of considerable importance in information systems research. TTF predicts individuals’ perceptions, intentions, and behaviors as well as performance impacts due to technology use. While TTF is expected to have positive effects, empirical results have been mixed. This study hypothesizes that the variation in the effects of TTF may be attributed to study characteristics. Using a meta-regression of 104 findings in 100 studies, this study shows that the variation in TTF effects is explained by type of respondents, type of dependent variable, and type of TTF variable. Specifically, students reported positive effects of TTF on other variables more often than non-students, TTF had positive effects on behavioral variables less frequently than perceptual variables, and TTF had positive effects on other variables less frequently when it was computed and not measured. These imply that TTF should be directly measured, associated with perceptions rather than behaviors, and contextualized to specific types of technologies and users.
Repository Citation
Jeyaraj, A.
(2022). A Meta-Regression of Task-Technology Fit in Information Systems Research. International Journal of Information Management, 65, 102493, 13.
https://corescholar.libraries.wright.edu/infosys_scm/80
DOI
doi.org/10.1016/j.ijinfomgt.2022.102493