409 © 2025 Conscientia Beam. All Rights Reserved. Investigating factors influencing the continuity of financial technology usage: The case of Indonesia Henryanto Wijaya1 Carunia Mulya Firdausy2+ Indra Widjaja3 Hadi Cahyadi4 1,4Faculty of Economics and Business, Universitas Tarumanagara, Jakarta, Indonesia. 1Email: henryantow@fe.untar.ac.id 4Email: hadic@fe.untar.ac.id 2Faculty of Economics and Business, Universitas Tarumanagara, and National Research and Innovation Agency, Jakarta, Indonesia. 2Email: cmfirdausy@gmail.com 3Universitas Tarumanagara, Jakarta, Indonesia. 3Email: indraw9393@gmail.com (+ Corresponding author) ABSTRACT Article History Received: 5 December 2024 Revised: 29 January 2025 Accepted: 18 February 2025 Published: 4 March 2025 Keywords Digital financial literacy Fintech usage adoption Fintech usage continuity Perceived benefit Perceived ease of use Perceived risk Perceived usefulness Structural equation modeling. This study aims to investigate the factors that influence the continuity of fintech usage by taking Indonesia as a case. Factors that drive the continuity of fintech usage are perceived benefit, perceived risk, perceived ease of use, and perceived usefulness with fintech usage adoption as a mediating variable. Data was obtained from 343 fintech users located in Indonesia. These data were then analyzed by applying the Structural Equation Modelling (SEM). The results indicate that perceived benefit and usefulness positively and significantly affect the adoption and the continuity of fintech usage. However, the perceived risk and ease of use have no significant effect on the adoption and the continuity of fintech usage. Additionally, fintech usage adoption positively and significantly influences the continuity of fintech usage. Fintech usage adoption mediates the effects of perceived benefits and usefulness on fintech usage continuity but does not mediate the influence of perceived risk and ease of use on the continuity of fintech usage. The findings contribute to the knowledge of the perceived benefit and usefulness for users to adopt and continue fintech usage. The government needs to continue improving digital financial literacy to aware users of fintech. Contribution/Originality: This study differs from the previous studies advanced in the literature as we utilize fintech usage adoption as a mediating variable and examine the direct relationship between fintech usage adoption and the continuity of fintech usage. 1. INTRODUCTION Financial technology (fintech) refers to the integration of financial services with technological developments, facilitating consumer access to innovative financial solutions such as savings and investments, online payments, financial planning, peer-to-peer lending, mobile financial services and crowdfunding (Dorfleitner, Hornuf, Schmitt, & Weber, 2017; Knewtson & Rosenbaum, 2020; Liu, Chan, & Chimhundu, 2024; Mamonov, 2020; Schueffel, 2016; Shao, Zhang, Li, & Guo, 2019). This payment technology is essential for the advancement of financial inclusion and economic growth in the global world including in Indonesia (La Rocca, 2024; Mardiana, Faridatul, Herlindawati, Tiara, & Mardiyana, 2020; Razzaque, Cummings, Karolak, & Hamdan, 2020; Wang, Guan, Hou, Li, & Zhou, 2019; Wonglimpiyarat, 2011). Fintech services can facilitate access to financial services and promote greater economic inclusive participation (Lasmini & Zulvia, 2021; Muzdalifa, Rahma, Novalia, & Rafsanjani, 2018). Humanities and Social Sciences Letters 2025 Vol. 13, No. 2, pp. 409-427 ISSN(e): 2312-4318 ISSN(p): 2312-5659 DOI: 10.18488/73.v13i2.4116 © 2025 Conscientia Beam. All Rights Reserved. https://orcid.org/0009-0007-5460-1492 https://orcid.org/0000-0002-2428-8657 https://orcid.org/0009-0006-9840-0054 https://orcid.org/0000-0003-3163-8739 mailto:henryantow@fe.untar.ac.id mailto:hadic@fe.untar.ac.id mailto:cmfirdausy@gmail.com mailto:indraw9393@gmail.com https://www.doi.org/10.18488/73.v13i2.4116 Humanities and Social Sciences Letters, 2025, 13(2): 409-427 410 © 2025 Conscientia Beam. All Rights Reserved. The Indonesian Fintech Association (AFTECH) in 2023 indicated a growing demand for digital financial services in Indonesia, particularly among individuals aged 26 to 35 years (Asosiasi Fintech Indonesia, 2024). Notable companies in Indonesia offering fintech services include OVO, Gopay, Dana, Shopeepay, Linkaja, paylater, Doku, and Bareksa. These companies offer innovative solutions in financial transactions, payments, lending, investment, and other financial services, thereby modernizing the sector, generating new job opportunities, and attracting foreign investment (Kumar, Wong, Chauhan, Shubhankar, & Oetama, 2023; Nurhayani, Dongoran, Syah, & Sagala, 2024; Sekarningrum, 2022). Recognizing the above potential of fintech for the economy, the government of Indonesia (GOI) through the Financial Services Authority, locally called Otoritas Jasa Keuangan (OJK) created a supportive ecosystem including regulations and appointed the Indonesian Fintech Association (AFTECH) as the organizer of digital financial expansion (Irso, 2023; Otoritas, 2024). The task of this organization is to ensure the development of fintech to enhance financial inclusion, strengthen the financial sector and foster inclusive and sustainable economic growth (Otoritas, 2024). However, the present development of the fintech industry faces challenges such as data security and low financial literacy of its users. These challenges consequently affect consumers' and users' trust and the sustainable usage of fintech services (Sahroni, Santiago, & Redi, 2023). Data security is an important concern as it is essential to protect the integrity and confidentiality of consumers' financial information. Additional challenges encompass consumer protection, suitable regulation and disparities in technology access across various segments of society (Cahyadi, Tarigan, Masman, Trisnawati, & Wijaya, 2024). The recent data indicate that there is a decline in the fintech industry services. The total assets of peer-to-peer (P2P) lending services dropped by 5% in the fourth quarter of 2023. There was a 3.24% decline in the number of online loan accounts in November 2023 (Annur, 2024; Saputra, 2024). Global investments in fintech showed a sharp decrease of investment from US$ 88.8 billion (2022) to US$ 46.3 billion (2023) and the total number of transactions in fintech fell from 7,515 in 2022 to 4,547 in 2023 hitting the lowest levels since 2017 (Ruddenklau, 2024). These declining trends raise concerns about the future sustainability of fintech usage. Therefore, for this reason, there is an urgent need for further research particularly to analyze the factors behind these declines, identify the challenges faced by the industry and develop policies to ensure the sustainability and growth of the fintech sector. There have been many studies advanced in the literature investigating factors that affect fintech usage continuity. For instance, Jain and Raman (2023) found that the perceived benefits factor significantly influences the continuity of fintech usage. This finding was further confirmed by Alkadi and Abed (2023); Razzaque et al. (2020); Akturan and Tezcan (2012); Gao and Bai (2014); Hu, Ding, Li, Chen, and Yang (2019) and Ming and Jais (2022). The primary reason that perceived benefits affect the continued use of fintech is that users recognize fintech as offering economic advantages, facilitating seamless transactions and providing convenience. The economic advantage relates to the equilibrium between reduced financial expenses and the financial benefits derived from the utilization of fintech. A seamless transaction represents an improved process in which consumers engage in swift transactions facilitated by accessible and sophisticated financial service platforms, thereby integrating the fields of financial institutions and information technology (Alkadi & Abed, 2023; Razzaque et al., 2020). In addition to the perceived benefits, perceived risk factors, especially legal risks significantly influence the continued use of fintech. The perceived risk encompasses the possibility of data loss and the uncertainties linked to the adoption of new technology (Gefen, Srinivasan Rao, & Tractinsky, 2003; Hutapea & Wijaya, 2021; Li, Khaliq, Chinove, Khaliq, & Oláh, 2023; Tang, Ooi, & Chong, 2020; Zhang & Yu, 2020). According to Hutapea and Wijaya (2021); Li et al. (2023) and Tang et al. (2020) the categories of perceived risk associated with fintech are as follows: (1) security risk which pertains to the protection of personal data and transactions from threats such as hacking, data theft, or misuse. (2) Financial risk which concerns potential monetary losses arising from hidden costs, fraud, or transaction discrepancies. (3) Performance risk which relates to the service's inability to meet expectations, Humanities and Social Sciences Letters, 2025, 13(2): 409-427 411 © 2025 Conscientia Beam. All Rights Reserved. including system malfunctions or transaction problems. (4) Privacy risk which involves the possible misuse of personal information such as identity and transaction details. (5) Legal risk which is connected to uncertainties regarding regulations and legal protections for users of fintech services. Among these risk categories, financial and security risks have an adverse impact on the intent to consistently utilize fintech services (Abd Malik & Syed Annuar, 2019; Diana & Leon, 2020; Forsythe, Liu, Shannon, & Gardner, 2006; Gerlach & Lutz, 2019; Mufarih, Jayadi, & Sugandi, 2020; Putritama, 2019; Tanadi, Samadi, & Gharleghi, 2015). As a result, perceived benefits enhance retention whereas perceived risks, especially among female users, might reduce the intention (Nurlaily, Aini, & Asmoro, 2021). Customers tend to interact with a service when they perceive that the advantages outweigh the associated risks (Ryu, 2018). According to Bergmann, Maçada, de Oliveira Santini, and Rasul (2023) besides perceived benefits and perceived risks, the continuation of fintech is influenced by its perceived ease of use and perceived usefulness. However, these two factors influence the persistence of fintech when mediated by user satisfaction and trust. Furthermore, it was found that in Western countries, satisfaction plays a significant role in the continued use of fintech which is marked by high human development index levels and greater use of electronic payments. Among these two factors, the perceived ease of use is identified as the primary driver of continued fintech usage (Davis, 1989; Hu et al., 2019; Kanchanatanee, Suwanno, & Jarernvongrayab, 2014; Niu, Wang, & Zhou, 2022; Nugraha, Setiawan, Nathan, & Fekete-Farkas, 2022; Pambudi, Roswinanto, & Meiria, 2023). Studies that addressed the importance of perceived usefulness include the works of Bangkara and Mimba (2016); Davis (1985); Gao and Bai (2014); Hu et al. (2019); Jangir, Sharma, Taneja, and Rupeika-Apoga (2022) and Mufarih et al. (2020). Bangkara and Mimba (2016) and Mufarih et al. (2020) show that if users perceive fintech as user-friendly, they are more likely to continue using it. The perceived ease of use and perceived usefulness are essential factors influencing fintech users' decisions to continue utilizing fintech services. However, perceived benefits, risks, ease of use, and usefulness also affect the adoption of fintech usage. Studies that confirm a direct relationship between perceived benefits and fintech usage adoption include Davis (1985); Davis (1989); Gan and Wang (2017); Banna, Hassan, Ahmad, and Alam (2022); Hassan et al. (2022); Mascarenhas, Perpétuo, Barrote, and Perides (2021); Ryu (2018) and Sari (2022). While previous studies that validated the connection between the perceived risk and fintech services adoption were Ali, Raza, Khamis, Puah, and Amin (2021); Chan, Troshani, Rao Hill, and Hoffmann (2022); Diana and Leon (2020); Hassan et al. (2022); Abd Malik and Syed Annuar (2019) and Ming and Jais (2022). These studies confirmed that perceived risk can negatively affect the intent to adopt fintech. Furthermore, studies that showed the perceived ease of use is a crucial determinant in the adoption of fintech services were conducted by Sum Chau and Ngai (2010) and Akturan and Tezcan (2012) to name just two studies. However, the perceived ease of use significantly impacts the adoption of fintech services though its effect may be less pronounced compared to the perceived usefulness (Kesharwani & Singh Bisht, 2012; Shaw, 2014; Venkatesh & Davis, 2000). Next, studies that showed the perceived usefulness directly influence fintech adoption were undertaken by Purwantini and Anisa (2021) and Nugraha et al. (2022). Purwantini and Anisa (2021) pointed out that the practicality of a technology system substantially impacts an individual's choice to use it continuously. Users are more inclined to technology adoption when they perceive it and they will enhance their tasks efficiently. In the world of fintech, this entails accelerating transactions while mitigating the risk of inaccuracies. Based on the above previous studies, it can be confirmed that perceived benefit, perceived risk, perceived ease of use, and perceived usefulness influence the continuity of fintech usage. However, the previous studies have weaknesses in examining the effect of the fintech usage adoption on the fintech usage continuity. Additionally, the previous studies are not entirely conclusive in examining significant factors influencing the fintech usage adoption and the fintech usage continuity. Therefore, this study not only bridges the above research gap but more Humanities and Social Sciences Letters, 2025, 13(2): 409-427 412 © 2025 Conscientia Beam. All Rights Reserved. importantly highlights factors that need to be given attention in determining the fintech adoption and the continuity of fintech usage to mitigate the declining phenomenon of the development of the fintech industry. This study is ordered in the following structures: in section 2, we highlight the theoretical background that supports the proposed research model, variable relationships and hypothesis. In Section 3, we elaborate in detail on the source of data and methods of data analysis for evaluating the proposed framework. Section 4 addresses the results and discusses the results of the study derived from the analytical data analysis subject to research questions. Finally, we draw conclusions, policy implications and limitations of this study. 2. LITERATURE REVIEW 2.1. Theoretical Framework As discussed in the introduction, previous studies indicated that fintech usage continuity is directly related to perceived benefits, perceived ease of use, perceived risks, and perceived usefulness. These four factors are also directly related to the adoption of fintech usage (Bergmann et al., 2023). The adoption of fintech usage is closely linked to the fintech usage continuity (Hu et al., 2019; Kim, Kim, Lee, & Kim, 2019; Nurlaily et al., 2021; Putritama, 2019; Roh, Park, & Xiao, 2023; Ryu, 2018). The theoretical framework that supports these studies is the theory of Reasoned Action (TRA) advanced by Ajzen and Fishbein (1977) and the theory of the Technology Acceptance Model (TAM) highlighted by Venkatesh and Davis (2000). These studies accommodate these two basic theories since TRA explains how a person's behavior is determined by their intention to perform that behavior which in turn is influenced by two main factors, namely attitude towards behavior and subjective norm (Ajzen & Fishbein, 1977). TAM postulates that the acceptance of technology is predicted by the users' behavioral intention which is determined by the perception of technology's usefulness in performing the task and the perceived ease of its use (Venkatesh & Davis, 2000). Therefore, TRA and TAM are applied to examine variables in the research model. However, recent studies reveal that TRA and TAM have limitations (Ajibade, 2018). The TAM can elucidate individual adoption choices. However, it inadequately addresses the complexities involved in organizational adoption where elements such as regulatory compliance, operational integration and systemic risks are significant factors (Ajibade, 2018). Both theories fail to address social influences, facilitating conditions and behavioral uncertainty resulting in notable gaps when applied to complex fintech ecosystems (Saadah & Setiawan, 2024). These indicate the necessity for creating more comprehensive theoretical models that can more effectively consider individual and institutional factors in the continuity of fintech usage. 2.2. Variables Relationship and Hypothesis Development Studies that examined the influence of the perceived benefit of fintech adoption have been undertaken by Mascarenhas et al. (2021) and Ryu (2018). These studies suggest that the fintech users' benefits received from fintech services increased fintech usage adoption. These benefits include ease of transactions, cost efficiency, and improved financial accessibility. These findings correspond with the Technology Acceptance Model (TAM), asserting that greater perceived benefits could promote users' intentions and behaviors toward adopting fintech. These findings were also supported by Gan and Wang (2017); Hassan et al. (2022) and Sari (2022) since they found a positive correlation between perceived benefits and the intent to utilize digital applications. Following these studies, we hypothesize that H1: Perceived benefit positively and significantly affects the fintech usage adoption. The perceived ease of use is also a critical factor in the fintech service adoption influencing users’ interaction with the technology used (Sum Chau & Ngai, 2010). However, Venkatesh and Davis (2000) argued that although perceived ease of use is essential, its impact may differ compared to perceived usefulness. The perceived ease of use includes a straightforward payment method, accessible customer service, and simple transactions, which positively Humanities and Social Sciences Letters, 2025, 13(2): 409-427 413 © 2025 Conscientia Beam. All Rights Reserved. influence the intention to adopt fintech (Akturan & Tezcan, 2012; Sum Chau & Ngai, 2010). Thus, we anticipate that H2: Perceived ease of use positively and significantly affects the adoption of fintech usage. Perceived risk can adversely influence the intention to adopt fintech (Abd Malik & Syed Annuar, 2019; Ali et al., 2021; Chan et al., 2022; Diana & Leon, 2020; Hassan et al., 2022; Ming & Jais, 2022; Tang et al., 2020). These studies show that risks like data security issues and financial loss make consumers more aware and cautious, affecting their willingness to use fintech services. As a result, higher perceived risk usually leads to a lower intention to adopt these technologies. In light of this understanding, we assume that H3: Perceived risk negatively and significantly influences the adoption of fintech usage. Purwantini and Anisa (2021) further remarked that the success rate of a technology system significantly influences a person's decision to continue using it. Users are more likely to adopt technology that helps them complete tasks more efficiently. In fintech, this means enabling transactions while reducing time and lowering the risk of errors. The Technology Acceptance Model (TAM) states that perceived usefulness or the belief that a technology will enhance performance significantly influences the intention to use it (Davis, 1989). The study findings by Nugraha et al. (2022) show that the perceived usefulness directly affects the intention to adopt fintech. Research on consumer behavior indicates that people who see a system as beneficial are more likely to adopt fintech services (Akturan & Tezcan, 2012; Gao & Bai, 2014; Hu et al., 2019; Ming & Jais, 2022). Therefore, we hypothesize that H4: Perceived usefulness positively and significantly influences fintech usage adoption. The perceived benefit is crucial for the ongoing use of fintech services, as described by the Theory of Reasoned Action (TRA). This theory indicates that a positive view of perceived benefits, like transaction ease and economic gains enhance the intention to continue using the service. Research shows that perceived benefits, especially economic ones significantly influence the ongoing intention to use fintech services (Ajzen & Fishbein, 1977; Mascarenhas et al., 2021). Consequently, perceived benefit is crucial in influencing the intention and ongoing behavior of fintech users as delineated by TRA. Hence, we anticipate that H5: Perceived benefit positively and significantly affects fintech usage continuity. The Theory of Reasoned Action (TRA) elaborates that a person's intent to behave is determined by the following two primary factors: the attitudes toward the behaviors and the subjective norms. The perceived ease of use is linked to the attitude towards behavior in the TRA concept. Users who perceive fintech services as user- friendly are inclined to develop a favorable disposition towards these services. Thereby, it enhances their intention to keep utilizing them (Irimia-Diéguez, Velicia-Martín, & Aguayo-Camacho, 2023; Sheppard, Hartwick, & Warshaw, 1988). The study findings by Wilson, Alvita, and Wibisono (2021) revealed that there is a positive correlation between perceived ease of use and repurchase intention. This conclusion is confirmed further by supplementary research which indicates that users who regard technology as user-friendly (easily used) have more inclination to have greater perceived ease of use and engage with it again (Ali et al., 2021; Amin, Rezaei, & Abolghasemi, 2014; Aren, Güzel, Kabadayı, & Alpkan, 2013; Kim, Galliers, Shin, Ryoo, & Kim, 2012; Lee & Charles, 2021; Meilatinova, 2021; Visakha & Keni, 2022). Therefore, we hypothesize that H6: Perceived ease of use positively and significantly influences fintech usage continuity. The perceived risk substantially influences fintech usage continuity, as described by the Theory of Reasoned Action (TRA). Elevated perceived risks such as financial, legal, security, and operational risks, foster negative attitudes toward fintech services. Therefore, they diminish users' intention to continue utilizing them. Previous studies estimate that perceived risk undermines user trust and has a negative significant effect on the intent to use the continuity of fintech usage. Providers must mitigate the risks mentioned by implementing enhanced security measures, assurance of transparency and enhancement of user education to promote usage continuity (Ajzen & Fishbein, 1977; Mascarenhas et al., 2021; Purnama, Suryadi, & Andarwati, 2023). Therefore, we posit that Humanities and Social Sciences Letters, 2025, 13(2): 409-427 414 © 2025 Conscientia Beam. All Rights Reserved. H7: Perceived risk negatively and significantly influences the fintech usage continuity. The Theory of Reasoned Action (TRA) by Ajzen and Fishbein (1977) claims that users' attitudes towards continued use of fintech services are related to perceived usefulness. TRA suggests that a person's attitude toward behavior and subjective norms create behavioral intention which influences actual behavior. When users see fintech services as helpful, they tend to maintain a positive view of continued use. A positive attitude and factors like social influence and environmental pressure increase the intention to keep using fintech services. Perceived usefulness is important for creating positive attitudes that promote continued use of fintech services. Previous research by Wen, Prybutok, and Xu (2011) and Wilson (2019) confirmed this further indicating a positive significant effect of perceived usefulness on the repurchase intention and the continuity of fintech usage. Thus, we make another hypothesis. H8: Perceived usefulness positively and significantly influences the continuity of fintech usage. Fintech services are adopted based on their ongoing usage. The Theory of Reasoned Action (TRA) suggests that a person's intention to behave is shaped by their attitudes and the norms they perceive from others. Positive perceptions of the simplicity and benefits of fintech services with trust in social network support and encourage their initial adoption (Ajzen & Fishbein, 1977; Mahyarni, 2013; Nurlaily et al., 2021; Roh et al., 2023). TRA offers insights into the psychological and social determinants giving influence on initial adoption and continued utilization of fintech services (Ajzen, 1985; Chen, Chan, & Hashim, 2023; Nurlaily et al., 2021; Roh et al., 2023). Thus, we infer that H9: Fintech usage adoption positively and significantly affects fintech usage continuity. Fintech adoption significantly impacts the link between perceived benefits and ongoing fintech usage. The Theory of Reasoned Action (TRA) suggests that the intention to use technology is shaped by attitudes, subjective norms, and perceived control over behavior. Positive views on benefits can increase the intention to use fintech services, encouraging their continued use. Research shows that subjective norms and perceived behavioral control can predict intentions and behaviors regarding fintech usage. They assist service providers in creating strategies to enhance adoption and continued use (Ajzen, 1985). According to this, the next hypothesis is as follows: H10: Fintech usage adoption mediates the effect of perceived benefit on the continuity of fintech usage. Perceived ease of use is the comfort and confidence users have when using fintech services. Users are more likely to adopt fintech technology if they trust its use. This adoption results in ongoing use, as users perceive the technology as simple and advantageous over time. Studies indicate that how easily users find fintech services affect their intention to keep using them positively. It promotes adoption and ongoing use (Irimia-Diéguez et al., 2023; Nurhayani et al., 2024). The Theory of Reasoned Action (TRA) suggests that the intention to act is shaped by attitudes toward the action and subjective norms including the inclination to use fintech services (Ajzen, 1985; Ajzen & Fishbein, 1977). Based on this, the following hypothesis needs to be tested. H11: Fintech usage adoption mediates the perceived ease of use influence on the continuity of fintech usage. The Theory of Reasoned Action (TRA) emphasizes how subjective norms and attitudes influence behavioral intentions. Positive views on fintech benefits and supportive social norms can reduce the negative effects of perceived risk and encourage ongoing use. Perceived behavioral control which includes the ability to manage risks and confidence in fintech service security can enhance the intention to continue using fintech services despite perceived risks (Ajzen, 1985; Ajzen & Fishbein, 1977; Nurlaily et al., 2021). Then, the next hypothesis is made as follows: H12: Fintech usage adoption mediates the influence of perceived risk on the continuity of fintech usage. According to the Theory of Reasoned Action (TRA), the fintech services’ perceived usefulness or the recognition of their benefits is pivotal. TRA posits that behavioral intentions are shaped by personal attitudes towards the behavior and prevailing subjective norms involving perceptions of the usefulness of using fintech services. Users exhibiting a positive disposition and robust intention to adopt fintech are inclined to sustain long- Humanities and Social Sciences Letters, 2025, 13(2): 409-427 415 © 2025 Conscientia Beam. All Rights Reserved. term utilization of the service usage. This intention mediates the correlation between perceived usefulness and the continuity of fintech usage (Ajzen, 1985; Ajzen & Fishbein, 1977). Based on this, another hypothesis needs to be tested as follows: H13: Fintech usage adoption mediates the effect of perceived usefulness on the continuity of fintech usage. 2.3. Proposed Research Model Considering the above theoretical framework and variable relationships, the proposed conceptual model in this study is illustrated in Figure 1. Figure 1. The research (Conceptual) model. 3. METHODS 3.1. The Research Design The research design of this study briefly began by identifying the problem of fintech usage continuity and its urgency to conduct this study. After completing these parts, we then reviewed the previous empirical research to justify the variables and the model that were examined in the study. Then, we highlighted the research gap and the novelty of this study by comparing the variables used in this study with the variables used in the previous studies. These first steps aimed to justify the rationale of variables in the model examined in this study. The next step was data collection. However, before data were collected, we determined the unit analysis, the research location, the source of data, the sampling method, and the instrument to collect the data. Finally, we analyzed the data. In the data analysis, we employed two types of data analysis methods. First, by applying the descriptive analysis method to address the characteristics of the respondents sampled under the study. Second, by employing the Structural Equation Model (SEM). The rationale for applying SEM was that this method was able to estimate variables that have multiple relationships. Similarly, SEM can estimate the relationship between unobserved variables and manifest variables or indicator variables (Hair, Hult, Ringle, & Sarstedt, 2022). For more details, the steps were as follows: 3.2. Data Collection and Sampling Data was collected in the province of Jakarta. The reason to select this province was because Jakarta is the capital city of Indonesia and in this location fintech users and fintech services were dominant. We collected data Humanities and Social Sciences Letters, 2025, 13(2): 409-427 416 © 2025 Conscientia Beam. All Rights Reserved. from March 2024 to June 2024. The rationale for this duration was partly because we assumed that we would be able to collect respondents by online questionnaire during these four months. The unit of analysis of this study focused on users of fintech services, particularly OVO, Gopay, Dana, Shopeepay, Linkaja, and Paylater. These six fintech services were dominant in Jakarta. However, the number of the population of these six fintech users in Jakarta was unknown. As a result, we applied a non-probability sampling method to sample the fintech users of the six fintech services as respondents of this study. To determine the number of respondents sampled, we followed Hair, Black, Anderson, and Babin (2010) as they suggested that the number of samples ideally in SEM needs to be from 15 to 20 observations for each exogenous variable. As there were 4 exogenous variables, there should be at least 60 respondents. By noting that suggestion, we collected 343 respondents under this study to avoid untruthful and strategic bias given by the respondents when they responded to the online questionnaire administered on Google Forms. The online questionnaire was given to 343 respondents covered questions related to 6 demographic characteristics (i.e., gender, age, highest education level, type of fintech service used, and frequency of use) and 33 indicators of all variables under the survey (see Table 2). Furthermore, we used the Likert scale to measure indicators of each variable. This Likert scale used five response choices to indicate the agreement degree, trust or attitude of the respondents towards the given indicator statements or questions. Each respondent was asked to select an option that best reflects their opinions or attitude toward the statements or questions. We used a 1-5 Likert scale as follows: (1) strongly disagree that the respondent strongly disagree or has a negative attitude towards the statement or question posed. (2) Disagree that the respondent disagree or has a negative attitude towards the statement or question posed. (3) Neutral that respondent were neutral or did not have a specific attitude towards the statement or question posed. (4) Agree where respondents agree or have a positive attitude towards the statements or questions posed; and (5) strongly agree that the respondent exhibits strong agreement or has a very positive attitude towards the statement or question posed. 3.3. Variables Estimated and Method of Data Analysis Variables estimated consist of one dependent and four independent variables with one mediating variable. Fintech usage continuity serves as the dependent variable used in this study whereas the independent variables are perceived benefit, perceived ease of use, perceived usefulness, and perceived risks. The mediating variable used in this study is fintech usage adoption. This study selected variables for fintech usage continuity and adoption based on the TRA and TAM models as these variables are backed by empirical evidence in the previously discussed literature. The chosen variables form a model to examine the factors influencing the ongoing use of fintech with fintech adoption as a mediating variable. Table 2 shows the dimensions and indicators for each estimated variable. The method to analyze the data to estimate the research model was the Partial Least Squares Structural Equation Modelling (PLS-SEM) using Smart PLS 4.0 software (Hair et al., 2010). PLS-SEM with SmartPLS 4.0 is appropriate for this study's analytical needs. PLS-SEM effectively tests theoretical frameworks predictively and handles complex structural models with multiple constructs and relationships. SEM estimates complex cause-effect relationships with latent and observed variables making it useful for analyzing theoretical frameworks. PLS-SEM effectively balances explanation and prediction aligning with current research needs and making it a suitable choice for drawing significant empirical conclusions (Asra, Agung, Munawir, & Novi, 2022; Hair et al., 2022). There were six stages in applying the SEM analysis: (1) Defining individual constructs to have the measurement of model specification. (2) Formulating a measurement model to estimate loading factors by drawing a path diagram, measuring variables and constructing latent, and adding error terms. (3) Estimating construct reliability and variance extracted to know the reliability and validity of the goodness of fit model. (4) Formulating structural model. (5) Examining model validity by testing the hypothesis and structural relationship of variables Humanities and Social Sciences Letters, 2025, 13(2): 409-427 417 © 2025 Conscientia Beam. All Rights Reserved. and (6) drawing conclusion to confirm whether or not the data analysis is theoretically justified (Asra et al., 2022). The analysis was conducted using Smart PLS 4.0 with one-tailed testing of the hypothesis at a significance level of 0.05. The analysis of the inner model concentrated on the coefficient of determination (R2) and path coefficients (Hair et al., 2022). 4. RESULTS AND DISCUSSION 4.1. Results 4.1.1. Characteristics of Respondents The result of data analysis concerning the characteristics of respondents can be seen in Table 1. Based on gender, out of a total of 343 respondents, the majority are female (58%), while male account for 42%. Furthermore, based on age categories, Gen Z dominates with 68.2%. Whereas Gen Millennial is at 23.9% followed by Gen X at 6.4%, and Gen Baby Boomers at only 1.5%. In terms of education, most respondents hold a bachelor's degree (55.7%) while those with master and doctoral degrees account for 9.6% and 1.5%, respectively. The remaining 33.2% do not hold a bachelor's degree. In terms of fintech services, about 36.7 % of the respondents surveyed used GOPAY fintech service followed by OVO (27.4%), Shopeepay (23.6%), Dana (5.2%), Paylater (1.7%), and LinkAja (0.3%). The rest of the 5% of respondents used other categories of fintech services. Moreover, in terms of the frequency of using fintech services, nearly half of the respondents (49.6%) used these fintech services more than five times a week. About 16.6% of respondents used fintech services twice a week, 14.9% once a week, 11.4% three times a week, and 7.6% four times a week (see Table 1). Table 1. Characteristics of respondents based on gender, age, educational background, types of fintech services used, and the frequency of using fintech services. Description Category Total Percentage (%) Gender Male 144 42.0 Female 199 58.0 Total 343 100 Age Gen Z 234 68.2 Gen millennials 82 23.9 Gen X 22 6.4 Gen baby boomers 5 1.5 Total 343 100 Educational level Not a bachelor's degree 114 33.2 Bachelor degree 191 55.7 Master's degree 33 9.6 Doctorate 5 1.5 Total 343 100 Types of fintech services used Gopay 126 36.7 OVO 94 27.4 Shopeepay 81 23.6 Dana 18 5.2 LinkAja 1 0.3 Paylater 6 1.7 Others 17 5.0 Total 343 100 The frequency of using fintech services Once a week 51 14.9 Twice a week 57 16.6 Three times a week 39 11.4 Four times a week 26 7.6 More than five times a week 170 49.6 Total 343 100 Source: Calculated from questionnaires. Humanities and Social Sciences Letters, 2025, 13(2): 409-427 418 © 2025 Conscientia Beam. All Rights Reserved. Table 2. Outer loadings results related to the reliability test. Variables Dimensions Indicators Outer loading Composite reliability Cronbach's alpha Result Perceived benefit (PB) Economic benefit Cheaper price (PB1) 0.824 0.845 0.727 Reliable Save money (PB2) 0.834 Reliable Using multiple services at low cost (PB3) 0.754 Reliable Seamless transaction Use multiple services simultaneously (PB4) 1.000 0.840 0.778 Reliable Convenience Quick use (PB5) 0.838 0.891 0.816 Reliable Use anywhere and anytime (PB6) 0.828 Reliable Easily use (PB7) 0.899 Reliable Perceived ease of use (PEOU) Easiness Easily use compare to traditional payments (PEOU1) 1.000 0.872 0.777 Reliable Clean and understandable Clear and easy to grasp (PEOU2) 1.000 Reliable Easy to learn Easy to learn (PEOU3) 1.000 Reliable Perceived risk (PR) Financial risk Financial loss may occur (PR1) 0.850 0.866 0.767 Reliable Fraud may occur (PR2) 0.864 Reliable Financial loss may occur if not compatible with other services (PR3) 0.764 Reliable Performance risk Issue with credit status (PR4) 0.921 0.914 0.812 Reliable Incorrect payment (PR5) 0.914 Reliable Misuse of personal information (PR6) 0.854 0.918 0.866 Reliable Security risk Personal information not secure (PR7) 0.912 Reliable Unauthorized access to personal information (PR8) 0.899 Reliable Perceived usefulness (PU) Can meet the needs Meet my needs (PU1) 1.000 0.914 0.874 Reliable Being fast Save time (PU2) 1.000 Reliable Effectiveness Increase effectiveness (PU3) 1.000 Reliable Useful Overall useful (PU4) 1.000 Reliable Fintech usage adoption (FUA) Frequent use More often than traditional financial services (FUA1) 1.000 0.924 0.836 Reliable Continuance Current use and will continue to use (FUA2) 1.000 Reliable Experience Have a lot experience (FUA3) 0.931 Reliable Benefit from use fintech (FUA4) 0.922 Reliable Actual use Make many transactions using fintech (FUA5) 1.000 Reliable Fintech usage continuity (FUC) Consider to use Consideration in using fintech (FUC1) 1.000 0.901 0.833 Reliable Continue to use Willingness to use continuously (FUC2) 1.000 Reliable Will be recommended Will use in the future (FUC3) 1.000 Reliable Source: Calculated from questionnaires. Humanities and Social Sciences Letters, 2025, 13(2): 409-427 419 © 2025 Conscientia Beam. All Rights Reserved. 4.1.2. Model Measurement The results of the outer loading analysis to evaluate the reliability and validity of the indicators used to measure variables in the study are shown in Table 2. According to Table 2, all indicators in the outer model have composite reliability above 0.7. These results indicate that the reliability of each indicator is adequate for measuring its respective construct. Furthermore, the findings of the Average Variance Extracted (AVE) within the outer model are shown in Table 3. As determined by the Average Variance Extracted (AVE) for each construct presented, the findings from the validity assessment demonstrate that each construct accounts for over 50% of the variance in its respective indicators. The Average Variance Extracted (AVE) value for each construct exceeds 0.5. These results indicate that each indicator is valid. Table 3. Results of the average variance extracted (AVE) in the outer model. Variables Dimensions AVE Conclusion Perceived benefit (PB) Economic benefit 0.644 Valid Convenience 0.732 Valid Perceived ease of use (PEOU) Easiness 0.699 Valid Clear and understandable Valid Easy to learn Valid Perceived usefulness (PU) Can meet the needs 0.726 Valid Being fast Valid Effectiveness Valid Useful Valid Perceived risk (PR) Financial risk 0.684 Valid Performance risk 0.842 Valid Security risk 0.790 Valid Fintech usage adoption (FUA) Experience 0.859 Valid Fintech usage continuity (FUC) Intention to adopt 0.754 Valid Will adopt Valid Will recommend Valid The results of the Heterotrait-Monotrait (HTMT) ratio are shown in Table 4. According to Table 4, the HTMT value for each variable is below 0.9. This demonstrates the discriminant validity of each construct within the scope of this study. In other words, there is a significant level of difference between the constructs being studied. Table 4. Results of the Heterotrait-Monotrait ratio (HTMT) for the outer model. FUA FUC PB PEOU PR PU FUA FUC 0.790 PB 0.612 0.607 PEOU 0.527 0.533 0.676 PR 0.065 0.088 0.145 0.085 PU 0.754 0.754 0.705 0.647 0.056 The results of hypothesis testing are given in Table 5. According to Table 5, out of the 13 hypotheses, seven hypotheses are supported while six are not. This conclusion is derived from assessing the path coefficients and p- values or t-values obtained through the Smart PLS application. These seven hypotheses are H1, H4, H5, H8, H9, H10 and H13, while H2, H3, H6, H7, H11 and H12 do not support the hypothesis. The findings indicated that perceived benefit and usefulness positively and significantly affect the adoption of fintech usage. These two factors also significantly affect the continuity of fintech usage. However, perceived ease of use and perceived risk do not significantly affect the adoption of fintech usage and the continuity of fintech usage. Humanities and Social Sciences Letters, 2025, 13(2): 409-427 420 © 2025 Conscientia Beam. All Rights Reserved. Further, fintech usage adoption affects significantly the continuity of fintech usage. The fintech usage adoption also mediates the effects of perceived benefit and perceived usefulness on fintech usage continuity. However, fintech usage adoption does not mediate the effect of perceived ease of use and perceived risk on the continuity of fintech usage (see Table 5). Table 5. The estimated results of path coefficients, significance levels, and the conclusions of the hypothesis tests. No Hypothesis Path coefficients T statistics (|O/STDEV) p- values Conclusion H1 Perceived benefit positively and significantly affects the adoption of fintech usage. 0.168 2.846 0.002 Supported H2 Perceived ease of use positively and significantly affects the adoption of fintech usage. 0.078 1.237 0.108 Not supported H3 Perceived risk has a negative effect on fintech usage adoption. 0.010 0.229 0.410 Not supported H4 Perceived usefulness positively and significantly influences fintech usage adoption. 0.525 7.870 0.000 Supported H5 Perceived benefit positively and significantly affects fintech usage continuity. 0.087 1.803 0.036 Supported H6 Perceived ease of use has a positive effect on fintech usage continuity. 0.046 0.864 0.194 Not supported H7 Perceived risk negatively and significantly influences fintech usage continuity. -0.055 1.422 0.078 Not supported H8 Perceived usefulness positively and significantly influences the continuity of fintech usage. 0.277 4.384 0.000 Supported H9 Fintech usage adoption positively and significantly affects fintech usage continuity. 0.439 7.833 0.000 Supported H10 Fintech usage adoption mediates the effect of perceived benefit on fintech usage continuity. 0.074 2.762 0.003 Supported H11 Fintech usage adoption mediates the effect of perceived ease of use on fintech usage continuity. 0.034 1.185 0.118 Not supported H12 Fintech usage adoption mediates the effect of perceived risk on fintech usage continuity. 0.004 0.228 0.410 Not supported H13 Fintech usage adoption mediates the effect of perceived usefulness on fintech usage continuity. 0.230 5.534 0.000 Supported 4.2. Discussion According to Table 5, out of the 13 hypotheses, seven are supported while six are not. Factors that positively and significantly affect the adoption of fintech usage are perceived benefit and usefulness. These two factors also positively and significantly affect the continuity of fintech usage. These findings indicate that the present fintech services under the survey have not only given economic benefits (a cheaper price, saving money and low cost in using fintech services), seamless transaction, and convenience (quick use, use anywhere and anytime, and easy use) but also useful for fintech users’ respondents as they can meet the needs of users, being fast, effectiveness, and usefulness. This finding supports studies by Alkadi and Abed (2023); Razzaque et al. (2020); Akturan and Tezcan (2012); Gao and Bai (2014); Hu et al. (2019); Ming and Jais (2022); Purwantini and Anisa (2021) and Nugraha et al. (2022). Humanities and Social Sciences Letters, 2025, 13(2): 409-427 421 © 2025 Conscientia Beam. All Rights Reserved. The insignificant effects of perceived ease of use and perceived risk on the adoption of fintech usage and the continuity of fintech usage suggest at least three reasons. First, it may be because fintech users’ respondents ignored the risks and the importance of ease of use of fintech. Second, it may be because the fintech users’ respondents value the benefits and usefulness of fintech more than the risk and ease of use of fintech. Third, it may be due to the lack of knowledge related to the use of fintech services. The risk indicators that are highlighted in this context include financial risks, performance risks, and security risks. Whereas the ease-of-use indicators in this study context include easiness, clean and understandable and easy to learn. These findings are in contrast to the previous studies conducted by Gefen et al. (2003); Hutapea and Wijaya (2021); Li et al. (2023); Tang et al. (2020); Zhang and Yu (2020); Diana and Leon (2020)l Forsythe et al. (2006); Gerlach and Lutz (2019); Abd Malik and Syed Annuar (2019); Mufarih et al. (2020); Putritama (2019) and Tanadi et al. (2015) as they found the ease of using fintech has a significant influence on the adoption of fintech usage and the continuity of fintech usage. Similarly, the insignificant effect of perceived ease of use on the adoption of fintech services and the continuity of fintech usage does not support the study’s findings done by Sum Chau and Ngai (2010); Akturan and Tezcan (2012) and Venkatesh and Davis (2000). Furthermore, fintech usage adoption significantly affects the continuity of fintech usage. The fintech usage adoption also mediates the effects of perceived benefit and perceived usefulness on fintech usage continuity. These findings are in line with previous studies conducted by Davis (1985); Davis (1989); Gan and Wang (2017); Hasanul, Hassan, Ahmad, and Alam (2022); Hassan et al. (2022); Mascarenhas et al. (2021); Ryu (2018) and Sari (2022). These findings suggest two things. First, the continuity of fintech usage by users’ respondents are influenced or subject to frequent use, continuance, and experience as indicators of fintech adoption in this study. Second, it highlights the importance of the perceived benefit and usefulness of fintech for the users to adopt as well as to continue using fintech services. However, fintech usage adoption does not mediate the effect of perceived ease of use and perceived risk on the continuity of fintech usage. As noted previously, this may be because the fintech users’ respondents value the benefits and usefulness of fintech more than the risk and ease of use of fintech in adopting and continuing fintech usage. These findings do not support previous studies undertaken by Ali et al. (2021); Chan et al. (2022); Diana and Leon (2020); Hassan et al. (2022); Abd Malik and Syed Annuar (2019) and Ming and Jais (2022). Therefore, the perceived benefit and usefulness of fintech are the determinant factors leading to the adoption and the continuity of fintech usage by fintech users’ respondents under the survey. While perceived ease of use and perceived risks have no significant effects on the adoption and the continuity of fintech usage. The knowledge contribution and implications of these findings are as follows: First, the findings contribute to the knowledge of the importance of the perceived benefit and usefulness of fintech in comparison with the perceived ease of use and perceived risks for users to adopt and continue fintech usage. Second, the fintech services need to give more attention to adding more benefits and usefulness of fintech to encourage the consumers to adopt fintech on the one hand, and users to sustain the continuity of fintech usage on the other hand. Finally, the government needs to continue improving digital literacy and digital financial literacy to aware consumers and the users about the risks and ease of use of fintech. 5. CONCLUSION This study aimed to investigate the factors that influence the continuity of financial technology (fintech) usage by taking Indonesia as a case. Factors hypothesized to drive the continuity of fintech usage are perceived benefit, perceived risk, perceived ease of use and perceived usefulness with the adoption of fintech usage as a mediating variable. This research enhances knowledge of theories by incorporating and expanding upon established frameworks of the Theory of Reasoned Action (TRA) and the Technology Acceptance Model (TAM). Humanities and Social Sciences Letters, 2025, 13(2): 409-427 422 © 2025 Conscientia Beam. All Rights Reserved. The findings indicated that perceived benefit and perceived usefulness positively and significantly affect the adoption of fintech usage. These two factors also affect the continuity of fintech usage. However, perceived ease of use and perceived risk do not significantly affect the adoption of fintech usage and the continuity of fintech usage. The fintech usage adoption affects significantly the continuity of fintech usage. The fintech usage adoption also mediates the effect of perceived benefit and perceived usefulness on fintech usage continuity. However, the fintech usage adoption does not mediate the effect of perceived ease of use and perceived risk on the continuity of fintech usage. These findings confirm the theories of Reasoned Action (TRA) and the Technology Acceptance Model (TAM) but do not support the findings of the previous studies advanced in the literature particularly related to the effects of perceived ease of use and the perceived risks on the adoption of fintech and the continuity of fintech usage. The knowledge contribution and policy implications of these findings are as follows: First, the findings contribute to the knowledge of the importance of the perceived benefit and usefulness of fintech in comparison with the perceived ease of use and perceived risks for users to adopt and continue fintech usage. Second, the fintech services need to give more attention to adding more benefits and usefulness of fintech to encourage the consumers to adopt fintech on the one hand, and users to sustain the continuity of fintech usage on the other hand. Third, the government needs to continue improving digital literacy and digital financial literacy to aware consumers and users about the risks and ease of use of fintech. However, this study has certain limitations which are as follows: First, this study utilized a cross-sectional design relying on subjective self-reports obtained from fintech users from six fintech services located in Jakarta. Second, the sampling method used was by employing a non-probability sampling method to select 343 respondents. This sampling method cannot be generated for the whole of Indonesia. Third, the model developed was limited to variables of perceived benefits, perceived ease of use, perceived risk, perceived usefulness, the adoption of fintech, and the continuity of fintech usage. Fourth, the instrument used to collect the data relied heavily on the online questionnaire administered on Google Forms which may offer inaccurate or strategically biased responses given by the respondents. Therefore, caveats apply to interpret the estimated results of the study. Funding: This study received no specific financial support. Institutional Review Board Statement: The Ethical Committee of the Faculty of Economics and Business, Universitas Tarumanagara, Indonesia has granted approval for this study (Ref. No. 072-D/127/FE- UNTAR/I/2025). Transparency: The authors declare that the manuscript is honest, truthful and transparent, that no important aspects of the study have been omitted and that all deviations from the planned study have been made clear. This study followed all rules of writing ethics. Competing Interests: The authors declare that they have no competing interests. Authors’ Contributions: All authors contributed equally to the conception and design of the study. All authors have read and agreed to the published version of the manuscript. REFERENCES Abd Malik, A. N., & Syed Annuar, S. N. (2019). The effect of perceived usefulness, perceived ease of use, trust and perceived risk toward E-wallet usage. Insight Journal, 5(21), 183-191. Ajibade, P. (2018). Technology acceptance model limitations and criticisms: Exploring the practical applications and use in technology-related studies, mixed-method, and qualitative researches. Library Philosophy and Practice, 9. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control: From cognition to behavior. In (pp. 11-39). Berlin, Heidelberg: Springer Berlin Heidelberg. Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888-918. https://doi.org/10.1037/0033-2909.84.5.888 Akturan, U., & Tezcan, N. (2012). Mobile banking adoption of the youth market: Perceptions and intentions. Marketing Intelligence & Planning, 30(4), 444-459. https://doi.org/10.1108/02634501211231928 Ali, M., Raza, S. A., Khamis, B., Puah, C. H., & Amin, H. (2021). How perceived risk, benefit and trust determine user Fintech adoption: A new dimension for Islamic finance. Foresight, 23(4), 403-420. https://doi.org/10.1108/FS-09-2020-0095 https://doi.org/10.1037/0033-2909.84.5.888 https://doi.org/10.1108/02634501211231928 https://doi.org/10.1108/FS-09-2020-0095 Humanities and Social Sciences Letters, 2025, 13(2): 409-427 423 © 2025 Conscientia Beam. All Rights Reserved. Alkadi, R. S., & Abed, S. S. (2023). Consumer acceptance of fintech app payment services: A systematic literature review and future research agenda. Journal of Theoretical and Applied Electronic Commerce Research, 18(4), 1838-1860. https://doi.org/10.3390/jtaer18040093 Amin, M., Rezaei, S., & Abolghasemi, M. (2014). User satisfaction with mobile websites: The impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust. Nankai Business Review International, 5(3), 258-274. https://doi.org/10.1108/NBRI-01-2014-0005 Annur, C. M. (2024). February 1. The value of pinjol distribution in Indonesia drops in november 2023. Katadata databoks. Aren, S., Güzel, M., Kabadayı, E., & Alpkan, L. (2013). Factors affecting repurchase intention to shop at the same website. Procedia-Social and Behavioral Sciences, 99, 536-544. https://doi.org/10.1016/j.sbspro.2013.10.523 Asosiasi Fintech Indonesia. (2024). Berita terbaru. Retrieved from https://fintech.id/id/education-and-literacy/latest-news Asra, A., Agung, P. U., Munawir, A., & Novi, H. P. (2022). Analisis Multivariabel:suatu pengantar. Jakarta: Media Publikasi. Bangkara, R. P., & Mimba, N. (2016). Pengaruh perceived usefulness dan perceived ease of use pada minat Penggunaan internet banking dengan attitude toward using Sebagai variabel intervening. E-Jurnal Akuntansi Universitas Udayana, 16(3), 2408-2434. Banna, H., Hassan, M. K., Ahmad, R., & Alam, M. R. (2022). Islamic banking stability amidst the COVID-19 pandemic: The role of digital financial inclusion. International Journal of Islamic and Middle Eastern Finance and Management, 15(2), 310-330. https://doi.org/10.1108/imefm-08-2020-0389 Bergmann, M., Maçada, A. C. G., de Oliveira Santini, F., & Rasul, T. (2023). Continuance intention in financial technology: A framework and meta-analysis. International Journal of Bank Marketing, 41(4), 749-786. https://doi.org/10.1108/IJBM- 04-2022-0168 Cahyadi, H., Tarigan, R. P., Masman, R. R., Trisnawati, E., & Wijaya, H. (2024). Exploring the dynamics of fintech usage behavior moderated by customer characteristics in Indonesia. International Journal of Innovative Research and Scientific Studies, 7(3), 541–550. Chan, R., Troshani, I., Rao Hill, S., & Hoffmann, A. (2022). Towards an understanding of consumers’ FinTech adoption: The case of open banking. International Journal of Bank Marketing, 40(4), 886-917. https://doi.org/10.1108/IJBM-08-2021- 0397 Chen, C. F. Y., Chan, T. J., & Hashim, N. H. (2023). Factor influencing continuation intention of using fintech from the users’ perspectives: Testing of unified theory of acceptance and use of technology (UTAUT2). International Journal of Technology, 14(6), 1277–1287. https://doi.org/10.14716/ijtech.v14i6.6636 Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral Dissertation. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008 Diana, N., & Leon, F. M. (2020). Factors affecting continuance intention of FinTech payment among Millennials in Jakarta. European Journal of Business and Management Research, 5(4), 1-9. https://doi.org/10.24018/ejbmr.2020.5.4.444 Dorfleitner, G., Hornuf, L., Schmitt, M., & Weber, M. (2017). Fintech in Germany. Switzerland: Springer International Publishing. Forsythe, S., Liu, C., Shannon, D., & Gardner, L. C. (2006). Development of a scale to measure the perceived benefits and risks of online shopping. Journal of Interactive Marketing, 20(2), 55-75. Gan, C., & Wang, W. (2017). The influence of perceived value on purchase intention in social commerce context. Internet Research, 27(4), 772-785. https://doi.org/10.1108/IntR-06-2016-0164 Gao, L., & Bai, X. (2014). A unified perspective on the factors influencing consumer acceptance of internet of things technology. Asia Pacific Journal of Marketing and Logistics, 26(2), 211-231. https://doi.org/10.1108/APJML-06-2013-0061 https://doi.org/10.3390/jtaer18040093 https://doi.org/10.1108/NBRI-01-2014-0005 https://doi.org/10.1016/j.sbspro.2013.10.523 https://fintech.id/id/education-and-literacy/latest-news https://doi.org/10.1108/imefm-08-2020-0389 https://doi.org/10.1108/IJBM-04-2022-0168 https://doi.org/10.1108/IJBM-04-2022-0168 https://doi.org/10.1108/IJBM-08-2021-0397 https://doi.org/10.1108/IJBM-08-2021-0397 https://doi.org/10.14716/ijtech.v14i6.6636 https://doi.org/10.2307/249008 https://doi.org/10.24018/ejbmr.2020.5.4.444 https://doi.org/10.1108/IntR-06-2016-0164 https://doi.org/10.1108/APJML-06-2013-0061 Humanities and Social Sciences Letters, 2025, 13(2): 409-427 424 © 2025 Conscientia Beam. All Rights Reserved. Gefen, D., Srinivasan Rao, V., & Tractinsky, N. (2003). The conceptualization of trust, risk and their electronic commerce: The need for clarifications. Paper presented at the Proceedings of the 36th Annual Hawaii International Conference on System Sciences. Gerlach, J. M., & Lutz, J. K. (2019). Evidence on usage behavior and future adoption intention of fintechs and digital finance solutions. The International Journal of Business and Finance Research, 13(2), 83-105. Hair, J. F., Black, W. C., Anderson, R. E., & Babin, B. J. (2010). Multivariate data analysis (7th ed.). Upper Saddle River, New Jersey: Pearson Prentice Hall. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS- SEM). UK: SAGE Publications. Hasanul, B., Hassan, M. K., Ahmad, R., & Alam, M. R. (2022). Islamic banking stability amidst the COVID-19 pandemic: The role of digital financial inclusion. International Journal of Islamic and Middle Eastern Finance and Management, 7(1), 310– 330. Hassan, M. S., Islam, M. A., Sobhani, F. A., Nasir, H., Mahmud, I., & Zahra, F. T. (2022). Drivers influencing the adoption intention towards mobile fintech services: A study on the emerging Bangladesh market. Information, 13(7), 349. https://doi.org/10.3390/info13070349 Hu, Z., Ding, S., Li, S., Chen, L., & Yang, S. (2019). Adoption intention of fintech services for bank users: An empirical examination with an extended technology acceptance model. Symmetry, 11(3), 340. https://doi.org/10.3390/sym11030340 Hutapea, R. S., & Wijaya, E. (2021). Perceived risk, trust, and intention to use fintech service during the Covid-19 pandemic. Paper presented at the Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT ), 656–661. Irimia-Diéguez, A., Velicia-Martín, F., & Aguayo-Camacho, M. (2023). Predicting FinTech innovation adoption: The mediator role of social norms and attitudes. Financial Innovation, 9(1), 36. https://doi.org/10.1186/s40854-022-00434-6 Irso. (2023). Government encourages creation of conducive digital ecosystem. Indonesia: Kominfo.Go.Id. Jain, N., & Raman, T. (2023). The interplay of perceived risk, perceive benefit and generation cohort in digital finance adoption. EuroMed Journal of Business, 18(3), 359-379. https://doi.org/10.1108/EMJB-09-2021-0132 Jangir, K., Sharma, V., Taneja, S., & Rupeika-Apoga, R. (2022). The moderating effect of perceived risk on users’ continuance intention for FinTech services. Journal of Risk and Financial Management, 16(1), 21. https://doi.org/10.3390/jrfm16010021 Kanchanatanee, K., Suwanno, N., & Jarernvongrayab, A. (2014). Effects of attitude toward using, perceived usefulness, perceived ease of use and perceived compatibility on intention to use E-marketing. Journal of Management Research, 6(3), 1. https://doi.org/10.5296/jmr.v6i3.5573 Kesharwani, A., & Singh Bisht, S. (2012). The impact of trust and perceived risk on internet banking adoption in India: An extension of technology acceptance model. International Journal of Bank Marketing, 30(4), 303-322. https://doi.org/10.1108/02652321211236923 Kim, C., Galliers, R. D., Shin, N., Ryoo, J., & Kim, J. (2012). Factors influencing Internet shopping value and customer repurchase intention. Electronic Commerce Research and Applications, 11(4), 374-387. https://doi.org/10.1016/j.elerap.2012.04.002 Kim, K., Kim, K., Lee, D., & Kim, M. (2019). Identification of critical quality dimensions for continuance intention in mHealth services: Case study of onecare service. International Journal of Information Management, 46, 187-197. https://doi.org/10.1016/j.ijinfomgt.2018.12.008 Knewtson, H. S., & Rosenbaum, Z. A. (2020). Toward understanding FinTech and its industry. Managerial Finance, 46(8), 1043- 1060. https://doi.org/10.1108/mf-01-2020-0024 Kumar, S., Li, A., Wong, H., Chauhan, H., Shubhankar, S., & Oetama, I. (2023). Indonesia’s fintech industry is ready to rise boston consulting group. Retrieved from https://www.bcg.com/publications/2023/fintech-industry-indonesia-growth https://doi.org/10.3390/info13070349 https://doi.org/10.3390/sym11030340 https://doi.org/10.1186/s40854-022-00434-6 https://doi.org/10.1108/EMJB-09-2021-0132 https://doi.org/10.3390/jrfm16010021 https://doi.org/10.5296/jmr.v6i3.5573 https://doi.org/10.1108/02652321211236923 https://doi.org/10.1016/j.elerap.2012.04.002 https://doi.org/10.1016/j.ijinfomgt.2018.12.008 https://doi.org/10.1108/mf-01-2020-0024 https://www.bcg.com/publications/2023/fintech-industry-indonesia-growth Humanities and Social Sciences Letters, 2025, 13(2): 409-427 425 © 2025 Conscientia Beam. All Rights Reserved. La Rocca, M. (2024). Fintech: Finance, technologies, and the society. Digital Finance, 6(1), 1–2. https://doi.org/10.1007/s42521- 024-00111-6 Lasmini, R. S., & Zulvia, Y. (2021). Financial inclusion and its impact on the use of financial technology in the millennial generationl. Jurnal Inovasi Pendidikan Ekonomi, 11(1), 45-52. Lee, L., & Charles, V. (2021). The impact of consumers’ perceptions regarding the ethics of online retailers and promotional strategy on their repurchase intention. International Journal of Information Management, 57, 102264. https://doi.org/10.1016/j.ijinfomgt.2020.102264 Li, C., Khaliq, N., Chinove, L., Khaliq, U., & Oláh, J. (2023). Consumers’ perception of risk facets associated with fintech use: Evidence from Pakistan. SAGE Open, 13(4), 1-17. https://doi.org/10.1177/21582440231200199 Liu, Q., Chan, K.-C., & Chimhundu, R. (2024). Fintech research: Systematic mapping, classification, and future directions. Financial Innovation, 10(1), 24. https://doi.org/10.1186/s40854-023-00524-z Mahyarni, M. (2013). Theory of reasoned action and theory of planned behavior (A historical study of behavior). Jurnal El- Riyasah, 4(1), 13-23. https://doi.org/10.24014/jel.v4i1.17 Mamonov, S. (2020). The role of information technology in FinTech innovation: Insights from the New York city ecosystem. Paper presented at the In Responsible Design, Implementation and Use of Information and Communication Technology: 19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020, Skukuza, South Africa, April 6–8, 2020, Proceedings, Part I 19 (pp. 313-324). Springer International Publishing. Mardiana, S. L., Faridatul, T., Herlindawati, D., Tiara, & Mardiyana, L. O. (2020). The contribution of financial technology in increasing society’s financial inclusions in the industrial era 4.0. Earth and Environmental Science, 485(1), 1-7. Mascarenhas, A. B., Perpétuo, C. K., Barrote, E. B., & Perides, M. P. (2021). The influence of perceptions of risks and benefits on the continuity of use of fintech services. BBR. Brazilian Business Review, 18(1), 1-21. Meilatinova, N. (2021). Social commerce: Factors affecting customer repurchase and word-of-mouth intentions. International Journal of Information Management, 57, 102300. https://doi.org/10.1016/j.ijinfomgt.2020.102300 Ming, K. L. Y., & Jais, M. (2022). Factors affecting the intention to use e-wallets during the COVID-19 pandemic. Gadjah Mada International Journal of Business, 24(1), 82-100. Mufarih, M., Jayadi, R., & Sugandi, Y. (2020). Factors influencing customers to use digital banking application in Yogyakarta, Indonesia. The Journal of Asian Finance, Economics and Business, 7(10), 897-907. https://doi.org/10.13106/jafeb.2020.vol7.no10.897 Muzdalifa, I., Rahma, I. A., Novalia, B. G., & Rafsanjani, H. (2018). The role of fintech in increasing financial inclusion in MSMEs in Indonesia (Islamic finance approach). Jurnal Masharif Al-Syariah: Jurnal Ekonomi Dan Perbankan Syariah, 3(1), 1-24. https://doi.org/10.30651/jms.v3i1.1618 Niu, G., Wang, Q., & Zhou, Y. (2022). Education and FinTech adoption: Evidence from China. SSRN Electronic Journal, 1-41. Nugraha, D. P., Setiawan, B., Nathan, R. J., & Fekete-Farkas, M. (2022). FinTech adoption drivers for innovation for SMEs in Indonesia. Journal of Open Innovation: Technology, Market, and Complexity, 8(4), 208. https://doi.org/10.3390/joitmc8040208 Nurhayani, U., Dongoran, F. R., Syah, D. H., & Sagala, G. H. (2024). Fintech acceptance among MSMEs: A post-Covid 19 response. Jurnal Akuntansi dan Keuangan, 26(1), 56-66. https://doi.org/10.9744/jak.26.1.56-66 Nurlaily, F., Aini, E. K., & Asmoro, P. S. (2021). What determines generation Z continuance intention of fintech ? The moderating effect of gender. Paper presented at the Proceedings of the 3rd Annual International Conference on Public and Business Administration (AICoBPA). Doi:10.2991/aebmr.k.210928.055. Otoritas, J. K. (2024). Financial technology: OJK prepares regulations & digital economy development team. Sikapiuangmu.Ojk.Go.Id. Pambudi, I. A. S., Roswinanto, W., & Meiria, C. H. (2023). The influence of perceived ease of use, perceived usefulness, and perceived enjoyment on interest in continuing to use investment applications in Indonesia. Journal of Management and Business Review, 20(3), 482–501. https://doi.org/10.34149/jmbr.v20i3.577 https://doi.org/10.1007/s42521-024-00111-6 https://doi.org/10.1007/s42521-024-00111-6 https://doi.org/10.1016/j.ijinfomgt.2020.102264 https://doi.org/10.1177/21582440231200199 https://doi.org/10.1186/s40854-023-00524-z https://doi.org/10.24014/jel.v4i1.17 https://doi.org/10.1016/j.ijinfomgt.2020.102300 https://doi.org/10.13106/jafeb.2020.vol7.no10.897 https://doi.org/10.30651/jms.v3i1.1618 https://doi.org/10.3390/joitmc8040208 https://doi.org/10.9744/jak.26.1.56-66 https://doi.org/10.34149/jmbr.v20i3.577 Humanities and Social Sciences Letters, 2025, 13(2): 409-427 426 © 2025 Conscientia Beam. All Rights Reserved. Purnama, E. S., Suryadi, N., & Andarwati, A. (2023). The influence of perceived risk and perceived benefits on continuance intention to adopt fintech P2P lending mediated by trust in Indonesia. Journal of Business and Management Review, 4(10), 754-770. https://doi.org/10.47153/jbmr410.8522023 Purwantini, A. H., & Anisa, F. (2021). Fintech payment adoption among micro-enterprises: The role of perceived risk and trust. Jurnal Aset (Akuntansi Riset), 13(2), 375-386. https://doi.org/10.17509/jaset.v13i2.37212 Putritama, A. (2019). The mobile payment fintech continuance usage intention in Indonesia. Jurnal Economia, 15(2), 243-258. Razzaque, A., Cummings, R. T., Karolak, M., & Hamdan, A. (2020). The propensity to use FinTech: Input from bankers in the Kingdom of Bahrain. Journal of Information & Knowledge Management, 19(01), 2040025. https://doi.org/10.1142/S0219649220400250 Roh, T., Park, B. I., & Xiao, S. S. (2023). Adoption of AI-enabled Robo-advisors in Fintech: simultaneous employment of UTAUT and the theory of teasoned action. Journal of Electronic Commerce Research, 24(1), 29-47. Ruddenklau, A. (2024). Pulse of Fintech H2’23: Global analysis of fintech funding. Retrieved from https://assets.kpmg.com/content/dam/kpmg/xx/pdf/2024/02/pulse-of-fintech-h2-2023.pdf Ryu, H. S. (2018). Understanding benefit and risk framework of Fintech adoption: Comparison of early adopters and late adopters. Paper presented at the Proceedings of the Annual Hawaii International Conference on System Sciences, 3864–3873. doi.org/10.24251/hicss.2018.486. Saadah, K., & Setiawan, D. (2024). Determinants of fintech adoption: Evidence from SMEs in Indonesia. LBS Journal of Management & Research, 22(1), 55-65. https://doi.org/10.1108/lbsjmr-11-2022-0076 Sahroni, A., Santiago, F., & Redi, A. (2023). Legal guarantee of confidentiality of customer data in online loan business services. Interdiciplinary Journal and Hummanity, 2(2), 78-84. Saputra, F. (2024). Total aset fintech lending kuartal iv-2023 turun 5 %. kontan.co.id. Retrieved from https://keuangan.kontan.co.id/news/total-aset-fintech-lending-kuartal-iv-2023-turun-5-secara-kuartalan Sari, H. C. (2022). The impact of perceived risk, perceived benefit, and trust on customer intention to use Tokopedia apps. Jurnal Bisnis Strategi, 31(2), 145-159. Schueffel, P. (2016). Taming the beast: A scientific definition of fintech. Journal of Innovation Management, 4(4), 32-54. Sekarningrum, A. (2022). February the journey of Indonesian startups in the last 10 years and a list of companies Ekrut.Com,february. Retrieved from https://www.ekrut.com/media/startup-indonesia Shao, Z., Zhang, L., Li, X., & Guo, Y. (2019). Antecedents of trust and continuance intention in mobile payment platforms: The moderating effect of gender. Electronic Commerce Research and Applications, 33, 100823. https://doi.org/10.1016/j.elerap.2018.100823 Shaw, N. (2014). The mediating influence of trust in the adoption of the mobile wallet. Journal of Retailing and Consumer Services, 21(4), 449-459. https://doi.org/10.1016/j.jretconser.2014.03.008 Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15(3), 325–343. Sum Chau, V., & Ngai, L. W. (2010). The youth market for internet banking services: Perceptions, attitude and behaviour. Journal of Services Marketing, 24(1), 42-60. https://doi.org/10.1108/08876041011017880 Tanadi, T., Samadi, B., & Gharleghi, B. (2015). The impact of perceived risks and perceived benefits to improve an online intention among generation-Y in Malaysia. Asian Social Science, 11(26), 226-238. https://doi.org/10.5539/ass.v11n26p226 Tang, K. L., Ooi, C. K., & Chong, J. B. (2020). Perceived risk factors affect intention to use FinTech. Journal of Accounting and Finance in Emerging Economies, 6(2), 453-463. https://doi.org/10.26710/jafee.v6i2.1101 Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926 Visakha, M. D., & Keni, K. (2022). The impact of security and perceived ease of use on reuse intention of e-wallet users in Jakarta: The mediating role of e-satisfaction. Paper presented at the Proceedings of the 3rd Tarumanagara International Conference https://doi.org/10.47153/jbmr410.8522023 https://doi.org/10.17509/jaset.v13i2.37212 https://doi.org/10.1142/S0219649220400250 https://assets.kpmg.com/content/dam/kpmg/xx/pdf/2024/02/pulse-of-fintech-h2-2023.pdf https://doi.org/10.1108/lbsjmr-11-2022-0076 https://keuangan.kontan.co.id/news/total-aset-fintech-lending-kuartal-iv-2023-turun-5-secara-kuartalan https://www.ekrut.com/media/startup-indonesia https://doi.org/10.1016/j.elerap.2018.100823 https://doi.org/10.1016/j.jretconser.2014.03.008 https://doi.org/10.1108/08876041011017880 https://doi.org/10.5539/ass.v11n26p226 https://doi.org/10.26710/jafee.v6i2.1101 https://doi.org/10.1287/mnsc.46.2.186.11926 Humanities and Social Sciences Letters, 2025, 13(2): 409-427 427 © 2025 Conscientia Beam. All Rights Reserved. on the Applications of Social Sciences and Humanities (TICASH 2021), 655(Ticash 2021), 36–42. doi.org/10.2991/assehr.k.220404.007. Wang, Z., Guan, Z., Hou, F., Li, B., & Zhou, W. (2019). What determines customers’ continuance intention of FinTech? Evidence from YuEbao. Industrial Management & Data Systems, 119(8), 1625-1637. https://doi.org/10.1108/IMDS-01- 2019-0011 Wen, C., Prybutok, V. R., & Xu, C. (2011). An integrated model for customer online repurchase intention. Journal of Computer Information Systems, 52(1), 14-23. Wilson, N. (2019). The impact of perceived usefulness and perceived ease-of-use toward repurchase intention in the Indonesian e-commerce industry. Jurnal Manajemen Indonesia, 19(3), 241-249. Wilson, N., Alvita, M., & Wibisono, J. (2021). The effect of perceived ease of use and perceived security toward satisfaction and repurchase intention. Jurnal Muara Ilmu Ekonomi dan Bisnis, 5(1), 145-159. Wonglimpiyarat, J. (2011). The dynamics of financial innovation system. The Journal of High Technology Management Research, 22(1), 36-46. https://doi.org/10.1016/j.hitech.2011.03.003 Zhang, X., & Yu, X. (2020). The impact of perceived risk on consumers’ cross-platform buying behavior. Frontiers in Psychology, 11, 592246. https://doi.org/10.3389/fpsyg.2020.592246 Views and opinions expressed in this article are the views and opinions of the author(s), Humanities and Social Sciences Letters shall not be responsible or answerable for any loss, damage or liability etc. caused in relation to/arising out of the use of the content. https://doi.org/10.1108/IMDS-01-2019-0011 https://doi.org/10.1108/IMDS-01-2019-0011 https://doi.org/10.1016/j.hitech.2011.03.003 https://doi.org/10.3389/fpsyg.2020.592246