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AIS Transactions on Human-Computer Interaction

Abstract

Task-technology fit theory proposes that the match between tasks and technologies, known as task-technology fit, has a positive relation with technology use and performance. Researchers have recently extended task-technology fit theory by conceptualizing task-technology misfit, which describes instances in which technology provides too few (too little) or too many (too much) features to perform a task. We link this newly expanded theory, which we label expanded task- technology fit (E-TTF) theory, with the technology acceptance model (TAM). We conducted a study and found that task- technology fit and too little significantly related to the variables in the TAM and that each ultimately had an indirect effect on use. In contrast, too much did not significantly relate to any variable in the TAM. These results support that E-TTF theory explains meaningful variance in the TAM, which suggests that integrating these theories is important for understanding technology use. Likewise, these results emphasize the importance of the multidimensional conceptualization that the E-TTF theory proposes. Too little (too few features) predicted outcomes beyond task- technology fit and meaningfully improved our model’s predictive abilities. In contrast, too much’s (too many features) relationships lacked significance, which emphasizes the need to distinguish types of task-technology misfit. Therefore, our study provides benefits for research on E-TTF theory, the TAM, and their integration.

DOI

10.17705/1thci.00184

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