<![CDATA[The rapid advancement of financial technology has positioned electronic money (e-money) as a critical innovation in modern payment systems, making the alignment between technological capabilities and user requirements essential for successful adoption. This study conducts a systematic literature review to examine the application of Task–Technology Fit (TTF) theory in e-money and digital payment research published between 2020 and 2025, with the aim of synthesizing empirical evidence and identifying theoretical and methodological gaps in the existing literature. Following the systematic review protocol proposed by Kitchenham and Charters, a comprehensive search was conducted in the Scopus database using predefined keywords related to TTF and fintech, yielding 1,424 articles that were subsequently filtered through inclusion and exclusion criteria to obtain 26 primary studies. Quality assessment was performed using five predefined criteria, and data extraction addressed five research questions concerning TTF model types, research focus, theoretical integration, methodological approaches, and knowledge gaps. The findings indicate that 80.8% of the reviewed studies employed extended or hybrid TTF models integrated with behavioral theories, particularly UTAUT/UTAUT2 and TAM. Most studies focused on technology adoption, followed by utilization and fit-related analyses, with quantitative approaches dominating the literature and SEM-PLS emerging as the most frequently used analytical technique. Geographically, research was concentrated in European countries, notably the United Kingdom, the Netherlands, and Switzerland, with a marked increase in publications observed in 2024. Despite the robustness of TTF in explaining e-money adoption, the review identifies persistent gaps related to contextual factors such as digital literacy and trust, limited cross-cultural perspectives, and a lack of longitudinal and experimental designs, highlighting the need for stronger theoretical integration and broader methodological approaches to advance fintech adoption research across diverse socio-economic contexts.]]>
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