Extending the Task-Technology Fit Theory with a Skill Fit Construct: A Case Study of a Transaction Control Log and Accounting System

Abstract

Numerous studies have employed the Task-technology fit (TTF) theory to examine the impact of information systems used for training. While some of these studies reported positive outcomes, others presented mixed results on the impact of the systems improving users' performance in problem solving and learning. One possible explanation for these inconsistencies is likely caused by additional factors beyond the task and technology characteristics emphasized in TTF. This research is a preliminary study to enhance understanding of TTF and its impact on system usage and work performance. The study argues that task-technology alignment should also consider users' skills and the fit between the task and technology. Therefore, this research explores the effects of task characteristics, technology characteristics, and users' skills on system usage and work performance. Data from 210 participants of the Revenue Department of Thailand was analyzed using a two-way factorial multivariate analysis (Factorial MANOVA) to assess the impact of Task-technology-skill fit (TTSF) on system usage and work performance. Additionally, a simple regression analysis was conducted to examine the effect of system usage on work performance. The findings indicated that the fit among tasks, technology, and skills significantly impacts system usage and work performance. However, the system usage does not directly affect work performance. This study proposed a factorial design to depict the task-technology-skill fit, the first to introduce this integrated framework.