Continuance intention in financial technology: a framework and meta-analysis

Abstract

Purpose: Although many studies have sought to address the topic of continuance intention among Fintech customers, the reported findings are fragmented. Therefore, the present study proposes a research model that integrates the main constructs involved in Fintech continuance intention. Design/methodology/approach: The current study uses a meta-analytic-based correlation analysis of effect sizes, meta-regression analysis and meta-analytic structural equation modeling, with 247 effect sizes in 69 studies involving 26,140 respondents. Findings: The results reveal continuance intention is driven by satisfaction and trust, with ease of use and usefulness being antecedents of satisfaction and trust. The authors also found evidence to show satisfaction partially mediates the relationship between ease of use and continuance intention and that trust fully mediates the relationship between ease of use and continuance intention and partially mediates the relationship between usefulness and continuance intention. In addition, the authors found that in Western countries, with higher Human Development Index levels and greater of use of electronic payment, satisfaction has more impact on continuance intention. Practical implications: From a theoretical standpoint, this meta-analytic study has implications for the literature on Fintech by offering an empirical generalization on the strength of the antecedents of Fintech continuance intentions and by testing possible moderators in a wide range of countries and studies. In other words, this study’s goal is to broaden the scope of the research. Regarding managerial implications, it is important to listen to user opinions regarding the positive and negative points of their experience with these technologies and take them into consideration when planning improvements. Additionally, the analysis shows the importance of using data from user interaction with technology, obtained, for example, through big data analytics, whereby companies can see how users behave, how much time they spend accessing certain functions and which technological features they use most, and thus seek to improve whatever is needed. Originality/value: This meta-analytic study advances the understanding of Fintech continuance intentions. Using the proposed approach, it is possible to generate accurate estimates of the effect size of each analyzed antecedent as the meta-analytic method jointly evaluates the results produced by a wide variety of studies performed in different contexts, allowing more accurate conclusions to be drawn.