Purpose The purpose of this paper is to examine (a)symmetric features of task-technology-performance characteristics that are most relevant to fit, satisfaction and continuance intention of using apps in mobile banking transactions. Design/methodology/approach Exploratory factor analysis was used with maximum likelihood extraction and Varimax rotation on a separate sample of 183 mobile banking apps users prior to the main data collection. The theoretical model was tested applying a factor-based structural equation modelling approach to a sample of 250 experienced mobile banking apps users. Findings The study unveiled that the task and performance characteristics are more relevant compared to technology characteristics when doing transactions via apps. In addition, the findings uncovered that user satisfaction and continuous intention to use apps stem from the degree of fit in online transactions. The findings of moderation analysis highlighted that users in the lower income group are more concerned about the performance characteristics of banking apps, and there are no differences across age and gender groups. Surprisingly, technology characteristic has a nonlinear nature and this study shows potential boundary conditions of technology characteristics in degree of fit, user satisfaction and continuance intention to use apps. Practical implications Findings from the conditional probabilistic queries reveal that with 83.3 per cent of probability, user satisfaction is high when using apps for banking transactions, if the levels of fit, task, performance and technology characteristics are high. Furthermore, with 72 per cent of probability, continuance intention to use apps is high, if the levels of performance and task characteristics are high. Originality/value Contributing to task-technology fit theory, this study shows that performance characteristics need to be aligned with task and technology characteristics in order to have better fit when using apps for online banking transactions.
Stored only when both papers are in the corpus — 25 citations exist upstream.
Imported from OpenAlex (CC0) — nothing here is generated.