Exploring the determinants of FinTech adoption and intention to use in Jordan: The impact of COVID-19

Abstract This study explores FinTech adoption in Jordan during and post-COVID-19 pandemic by integrating and extending the TAM and UTAUT theories to predict behavioral intention to use FinTech. Six predictors were hypothesized to test their impact on behavioral intention: perceived usefulness, perceived ease of use, social influence, personal innovativeness, financial risks, and privacy risks. while using COVID-19 lockdowns as a moderator. Using structural equation modeling (SEM) on a sample of 296 respondents, the data analysis results indicated that the proposed variables, including the predictors and the moderator, accounted for 38.4% of the variation in behavioral intention to use FinTech. Which clearly shows the important impact of COVID-19 on increasing the adoption of technologies and especially FinTech’s in the Jordanian context. The empirical findings revealed that perceived usefulness and personal innovativeness had the most significant impact on behavioral intention. In contrast, privacy risks had no significant impact on behavioral intention. Besides, this study empirically demonstrated the impact of COVID-19 lockdowns as a moderator. The impact of COVID-19 lockdowns significantly moderated the relationship between perceived usefulness, perceived ease of use, personal innovativeness, and financial risks with behavioral intention. The result of this study contributes to both theory and practice by adding to the existing literature on FinTech adoption using new determinants that might drive behavioral intention to use FinTech services.

variables, including the predictors and the moderator, accounted for 38.4% of the variation in behavioral intention to use FinTech.Which clearly shows the important impact of COVID-19 on increasing the adoption of technologies and especially FinTech's in the Jordanian context.The empirical findings revealed that perceived usefulness and personal innovativeness had the most significant impact on behavioral intention.In contrast, privacy risks had no significant impact on behavioral intention.Besides, this study empirically demonstrated the impact of COVID-19 lockdowns as a moderator.The impact of COVID-19 lockdowns significantly moderated the relationship between perceived usefulness, perceived ease of use, personal innovativeness, and financial risks with behavioral intention.The result of this study contributes to both theory and practice by adding to the existing literature on FinTech adoption using new determinants that might drive behavioral intention to use FinTech services.

Introduction
Financial technology, or simply FinTech, is gaining more and more attention in the business world due to the great opportunities that this innovative integration of financial services and information technology will bring.In fact, FinTech is disrupting the financial industry by taking advantage of the advancement of the internet and ubiquitous communication, representing a key part of the fourth Industrial Revolution (Khuong et al., 2022;Le, 2021).FinTech is characterized by its services, ease of use, and high standards of transparency (Al-Okaily et al., 2021;Almulla et al., 2021), as well as the range of its products, such as mobile banking, e-wallets, peer-to-peer lending, crowdfunding, blockchain, cryptocurrencies, and Robo-advisors (Goldstein et al., 2019;Shaikh et al., 2023), which are changing the financial landscape and representing a huge opportunity for consumers and businesses.
Traditional FinTech services include online and mobile banking, while emerging FinTech services from non-bank financial institutions include mobile wallets, mobile payments, and crowdfunding.FinTech is a new financial system that uses technology to improve financial activities, financial services, and social welfare.FinTech offers faster transaction rates, no wait times, 24/7 customized services, better information transparency, increased flexibility, and no physical boundaries.Financial technology allows mobile financial transactions (Chawla & Joshi, 2019).FinTech helps people access finance, pay bills, transfer funds, and buy online.Thus, FinTech services are gaining importance across the financial sector.FinTech innovations can improve financial products, lower costs, create new businesses, and create a more inclusive and robust financial system.
In fact, individuals can now pay for products and transfer funds using their portable devices due to the rapid expansion of smartphone usage and technological advancements in portable devices (Al-Mamary, 2022b;Brem et al., 2021;Jung et al., 2020).Mobile banking is a service that enables users to do banking transactions without debit/credit access cards, such as tracking money, obtaining alerts, transferring money swiftly, reviewing balances, and more (Shahid et al., 2022).Mobile wallets are also part of the FinTech solutions (Chalik & Faturohman, 2022).The pathway of mobile wallets can broaden the delivery of conventional financial services to neglected parts of society that are unreached by traditional channels (Shaikh et al., 2023).Thus, due to the importance of FinTech, many researchers have investigated FinTech adoption in an effort to explore the different factors that may drive or deter people's intention and behavior to adopt FinTech services (e.g., Setiawan et al., 2021;Xie et al., 2021).Senyo and Osabutey (2020) state that FinTech innovations have been hailed as game-changers for financial inclusion, but they still need to be widely accepted and used.Flavián et al. (2020) suggest studying FinTech adoption from different angles.However, a review of FinTech adoption research found very few studies, most of which were conducted in advanced economies (Thusi & Maduku, 2020).Moreover, to date and to our knowledge, no definitive recent studies could identify factors determining FinTech adoption and usage.In fact, despite the great opportunities that FinTech is bringing, people are still reluctant to use it, which hinders both individual and business growth.However, the 2020 COVID-19 pandemic has made FinTech services relevant for social isolation, lockdowns, and other pandemic conditions.
In this research, we aim to study and explore the adoption of FinTech services such as mobile banking (e.g., Arabi Mobile, JKB Mobile, and other banks) and mobile wallets (e.g., Zain Cash, Orange Money, and other mobile wallets available in Jordan) among Jordanians during and after the COVID-19 pandemic.
Furthermore, this study explored six indicators to establish a viable framework for evaluating behavioral intention to utilize FinTech in Jordan.The paper also conceptualizes how the COVID-19 epidemic may affect FinTech adoption in Jordan.This study uses a conceptual model to evaluate how COVID-19 lockdowns moderate the link between predictors and behavioral intention to utilize FinTech products like mobile banking and mobile wallet in Jordan.This study fills a gap in the literature on FinTech adoption in Jordan by examining factors that influence users' behavioral intention to adopt FinTech services, notably during and after COVID-19.To further knowledge by offering a robust framework that incorporates and expands two well-established theories regarding technology usage and acceptability (Ng et al., 2023).

Hypotheses development
In the past few years, FinTech has grown to provide a diverse range of innovative financial services.Hence, exploring the determinates of FinTech adoption has increased significantly and having a theoretical basis is necessary since it enhances the rationale for the study to comprehend determinants affecting FinTech adoption in the Jordanian context.This research derives its theoretical framework from the literature on technology adoption models and theories and builds on Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) frameworks.TAM to predict behavioral intentions to adopt new technologies based on perceived usefulness and perceived ease of use and UTAUT to incorporate the social influence construct to build a more comprehensive conceptual model.By integrating both TAM and UTAUT model while incorporating three additional factors: personal innovativeness, financial risk, and privacy risk, and accounting for COVID-19 as a moderator, we expect to see more accurate and comprehensive results and analysis.In fact, this combination of perceived usefulness, perceived ease of use, social influence, personal innovativeness, and components of perceived risk with TAM and UTAUT has been found to significantly enhance the validity of the model and increase its predictive strength in explaining the variance in behavioral intention to adopt new technologies (Al-Mamary, 2022a;Al-Mamary et al., 2023;Chauhan et al., 2019;Slade et al., 2015).The technology acceptance model, or TAM, developed by Fred Davis in 1986, is a commonly accepted adaptation of the theory of reasoned action to elucidate a method through which a user accepts and uses technology.The model proposes two core constructs: perceived usefulness and perceived ease of use, which are determinants of attitude toward using technology, where the attitude reflects a user's appraisal of the technology.Besides that, the TAM framework offers a base for tracking the effect of external factors on beliefs, attitudes, and intentions toward using new technology.In the TAM theory, perceived usefulness and perceived ease of use are fundamental causes for adopting new technology, explaining the behavioral intention to accept and use the new technology.It was affirmed that perceived usefulness and perceived ease of use are of significant importance for technology acceptance and usage behavior (Davis et al., 1989), substantially affecting attitudes toward technology adoption (Taherdoost, 2018).The TAM framework assumes that users' perceptions of the innovation's usefulness and easiness would play a significant role in determining their attitudes toward the intention to adopt it (Giovanis et al., 2019).Furthermore, Venkatesh et al. (2003) introduced the unified theory of acceptance and use technology, or UTAUT, which is a framework aimed to unify the models and theories on behavioral intention and usage behavior into a coherent theoretical model of technology acceptance that incorporates the main components of eight well-established theories and models, namely the theory of reasoned action, the technology acceptance model, the theory of planned behavior, the diffusion of innovation theory, Determinants of Technology Acceptance and the social cognitive theory, among others (Feng et al., 2021;Venkatesh et al., 2003).UTAUT proposes four fundamental constructs: performance expectancy, effort expectancy, social influence, and facilitating conditions, which are significant predictors of behavioral intention and usage behavior (Chawla & Joshi, 2019), and it postulated that these four constructs could anticipate the intent of persons to adopt a technology (Jung et al., 2020).According to the UTAUT framework, performance expectancy, effort expectancy, and social influence are significant predictors of behavioral intention, whereas behavioral intention and facilitating conditions are significant predictors of usage behavior (Giovanis et al., 2019).Furthermore, UTAUT was created because it was deemed fundamental for a comprehensive model encompassing diverse characteristics related to studying emerging technology and comprehending determinants that cause its acceptance and usage by users.Therefore, the following conceptual model presented in Figure 1 was derived based and will be tested.Davis (1989, p. 320) defined perceived usefulness as "the degree to which a person believes that using a particular system would enhance his or her job performance."According to the technology acceptance model, the perceived usefulness of technology affects attitudes and behavioral intentions, ultimately resulting in acceptance and use of the given technology (Siamagka et al., 2015).Perceived usefulness constitutes one of the essential core constructs of TAM and a significant determinant in adopting technological innovations (Liébana-Cabanillas et al., 2020).Undoubtedly, users could accept a new technology if they believe it would help them meet a specific need (Shankar & Datta, 2018).Moreover, in digital technologies, it could be expected that people are more inclined to accept and adopt a new technology that gives them additional benefits, such as productivity, minimal effort, and time efficiency.Sharma (2017) stated that perceived usefulness is the most important and frequently used predictor of technology adoption, including FinTech.In addition, perceived usefulness implies that a user anticipates that FinTech will increase their transactional efficiency (Lin et al., 2020).A satisfactory perception of usefulness in completing financial transactions using FinTech might positively drive users' usage intention and more beneficial than traditional methods  2021), Agarwal and Prasad (1998), Davis et al. (1989).(Patel & Patel, 2018).Once users feel that FinTech will assist them in making transactions more quickly and conveniently, they are more inclined to adopt it since they assume that doing so will save them time and effort (Kalinic & Marinkovic, 2015;Kalinic et al., 2019).According to Suhartanto et al. (2019), If FinTech services offer the usefulness as anticipated, adoption is probable, but if they do not, adoption is unlikely.Accordingly, this leads to suggest the following hypothesis:

Perceived usefulness
H1a. Perceived usefulness has a statistically significant effect on behavioral intention to use FinTech at a significance level of α ≤ 0.05.

Perceived ease of use
Perceived ease of use is notably essential when users are inexperienced with technology, resulting in increased mental effort and difficulties in understanding complicated information and stimulation.Malaquias and Hwang (2019) indicated that even with a prospective belief in the usefulness of technology, users might express concern about whether or not the technology is too difficult to use.If there is little difficulty in functioning a technology, positive attitudes toward intentions and behavior might evolve to use that technology.According to Suhartanto et al. (2019), a person is more likely to adopt less complicated technology than one that is more complex.In fact, simplicity of new technology can also increase usage intention and behavior and users are more likely to adopt a technology if it's easy to use and has a clear interface (Giovanis et al., 2019).User-friendly technology is usually more appealing.According to previous research, digital technology use is often influenced by perceived ease of use (Kar, 2020).
Perceived ease of use is the level to which users would be at ease and endeavor to learn how to use FinTech (Hu et al., 2019).A user might feel the ease of using FinTech if it is user-friendly, easy to understand and navigate, and does not require excessive effort (Bashir & Madhavaiah, 2015).In fact, perceived ease of use in financial technology entails the time, effort, and comprehension services which are uncomplicated and thus leads to increase user's adoption (Leong et al., 2020).Nevertheless, users will not accept FinTech if they find it challenging to use, despite the numerous benefits of this innovation (Hassan & Wood, 2020).Hence, the current research will test the following hypothesis: H1b. Perceived ease of use has a statistically significant effect on behavioral intention to use FinTech at a significance level of α ≤ 0.05.

Social influence
The basic idea of social influence is that a person can be influenced by his social network especially when considering the use of new and disruptive technologies, and they can be affected by the advice others give (Singh et al., 2020).According to Giovanis et al. (2019), individuals often seek the advice from their surroundings, and this can directly affect their intention to adopt new technologies.Al-Saedi et al. (2020) assumed that social influence is the most significant and crucial variable in adopting new technology.Different previous studies on FinTech adoption indicated that the behavior of users is affected by those relatively close to them, namely family, friends, colleagues, and peers, who would always influence their attitudes and preferences toward using a particular type of FinTech services (Patel & Patel, 2018).In fact, we argue that because FinTech is still a relatively novel concept, individuals would generally look for the viewpoints of others who have used it and may be motivated to use FinTech services (Oliveira et al., 2016).Jordan used as a case in this study, we argue that it is acceptable to think that others, like family members, friends, colleagues, or social groups, might significantly influence intentions and behavior to adopt FinTech services.Accordingly, these assumptions result in forming the following hypothesis: H1c.Social influence has a statistically significant effect on behavioral intention to use FinTech at a significance level of α ≤ 0.05.

Personal innovativeness
Personal innovativeness describes the degree to which a person is receptive to experiencing and experimenting with new technologies (Slade et al., 2015).Individuals with a higher level of innovativeness are likely to accept new technology (Singh et al., 2020).In fact, innovative people are more reasonable in accepting new challenges, and consequently, they tend to have a higher level of trust in the latest technologies (Rouibah et al., 2016).According to Hong (2019), the more willing users are to dig into new digital technologies, the higher the assumption that the user can use the technology as desired.Generally, FinTech is a disruptive technology, and it would be more valuable and attractive to users with genuinely innovative characteristics (Yoon et al., 2020).Hence it is logical to assume that people who exhibit an attitude of innovativeness would embrace FinTech before others (Leong et al., 2020).Thus, according to Liébana-Cabanillas et al. ( 2020), personal innovativeness can seriously impact how people perceive FinTech.In addition, as FinTech services are relatively new and innovatively distinct from traditional services, it is highly thought that personal innovativeness will play a positive and substantial part in their usage intention (Patil et al., 2020).
Therefore, the following hypothesis will be tested H1d.Personal innovativeness has a statistically significant effect on behavioral intention to use FinTech at a significance level of α ≤ 0.05.

Financial risks
Financial risk has been studied for decades as an integral component associated with consumer behavior in offline and online marketplaces representing a significant aspect for adopting digital services (Featherman & Pavlou, 2003;Zhao et al., 2019).Financial risk is the possibility of incurring monetary losses due to acquiring a poor digital service or digital fraud (Trinh et al., 2020) comes in different from malfunctions, scams, and transactional problems (Harris et al., 2016;Pal et al., 2020).In fac, financial risk reflects users' anxiety over the safety of their transactions in using FinTech (Roy et al., 2016).Thus, financial risk can be a key issue that might discourage individuals from adopting FinTech innovations.According to Yang et al. (2015), the exchange of funds between accounts in FinTech may raise serious concerns over the theft of financial information, such as account credentials, and the consequent threat of losing money.As well, financial risk can arise from FinTech malfunction, user error, or cybercrime, leading people naturally to abandon these services (Senyo & Osabutey, 2020;Siddik et al., 2023).Hence financial risks involved with FinTech may limit the adoption of FinTech services.Therefore, the following hypothesis is suggested: H1e. Financial risk has a statistically significant effect on behavioral intention to use FinTech at a significance level of α ≤ 0.05.

Privacy risks
Privacy risk as a fundamental facet of perceived risks representing as a possible loss of control over personal information leading to unexpected harm caused by sensitive information becoming compromised through digital transactions and may involve a likely loss of confidentiality of personal information (Alzaidi & Agag, 2022;Awad et al., 2023;Featherman & Pavlou, 2003;Johnson et al., 2018;Zhao et al., 2019).In recent years, the expansion of digital services has given rise to privacy concerns among individuals such as personal data collection and subsequent illegal usage of this data by unauthorized parties (Hsu & Lin, 2016).As the digital world evolves and digital services expand rapidly, more privacy risks are emerging and users become more and more concerned about protecting their private information (Zhang et al., 2018).Thus, it is reasonable to presume that fears of exploiting personal information may seriously affect individuals to accept using digital technologies, including FinTech (Pal et al., 2020).In fact, according to Yang et al. (2015), privacy risk is a big worry for users when it comes to adopting FinTech, as FinTech usage requires much personal information and these transactions may contain private data.Accordingly, the following hypothesis is developed: H1f. Privacy risk has a statistically significant effect on behavioral intention to use FinTech at a significance level of α ≤ 0.05.

The impact of COVID-19 lockdowns as a moderator
The COVID-19 pandemic has been one of the most significant occurrences of the last few decades, with massive social and economic effects on a global basis dominating humanity and resulting in restrictions and measures including global lockdowns and physical distancing (Cruz-Cárdenas et al., 2021).Hence, digitalization became a vital and viable option in times of lockdowns leading to an explosion in the usage of digital technologies changing consumer behavior (Boot et al., 2021;Raza et al., 2020).During the COVID-19 epidemic, FinTech have been in high demand throughout making financial services more accessible and convenient for communities (Daragmeh et al., 2021;Yan et al., 2021).In fact, empirical research has shown that the COVID-19 pandemic has played a significant role in increasing the behavior toward adopting FinTech (Abdul-Rahim et al., 2022;Ahmad et al., 2023;Daragmeh et al., 2021;Fu & Mishra, 2022).
However, very little is known about the impact of COVID-19 lockdowns in Jordan on the adoption of FinTech solutions and very few studies had examined the effect of the COVID-19 pandemic on FinTech acceptance among individuals in Jordan.Therefore, it would very important to understanding the impact of COVID-19 lockdowns as a moderator on intentions and behavior to adopt FinTech in Jordan.Thus, the current study proposes six hypotheses as follows: H2a.The impact of COVID-19 lockdowns has a statistically moderating effect on the relationship between perceived usefulness and behavioral intentions to use FinTech at a significant level of α ≤ 0.05.
H2b.The impact of COVID-19 lockdowns has a statistically moderating effect on the relationship between perceived ease of use and behavioral intention to use FinTech at a significant level of α ≤ 0.05.
H2c.The impact of COVID-19 lockdowns has a statistically moderating effect on the relationship between social influence and behavioral intention to use FinTech at a significant level of α ≤ 0.05.
H2d.The impact of COVID-19 lockdowns has a statistically moderating effect on the relationship between personal innovativeness and behavioral intention to use FinTech at a significant level of α ≤ 0.05.
H2e.The impact of COVID-19 lockdowns has a statistically moderating effect on the relationship between financial risk and behavioral intention to use FinTech at a significant level of α ≤ 0.05.
H2f.The impact of COVID-19 lockdowns has a statistically moderating effect on the relationship between privacy risk and behavioral intention to use FinTech at a significant level of α ≤ 0.05.

Behavioral intention and usage behavior
Behavioral intentions to accept new technology precede the adoption and usage of that technology.Hence, understanding the determinants of behavioral intentions to use new technology is fundamental for analyzing the adoption of that technology (Singh et al., 2020).Researchers hypothesize that intention may reflect a variety of behavioral elements that affect people to get involved in a behavior (Patil et al., 2020), while usage behavior is regarded as a direct result of behavioral intention and is indicative of a person's readiness to undertake a particular action (Sharma et al., 2020).Different empirical studies in the recent literature have observed a positive relationship between behavioral intentions and usage behavior toward FinTech services (e.g., Senyo & Osabutey, 2020;Thusi & Maduku, 2020).Yet, in contrast, Singh et al. (2020) found no significant relationship between behavioral intention and FinTech usage.Therefore, the current research hypothesizes that behavioral intention to use FinTech can significantly affect FinTech usage.Therefore, the following hypothesis is presented: H3.Behavioral intention to use FinTech has a statistically significant effect on FinTech usage behavior at a significance level of α ≤ 0.05.

Methodology
This research applied a quantitative approach based on a cross-sectional study using a questionnaire survey to obtain data.A five-point Likert scale that ranges from one (Strongly disagree) to five (Strongly agree) was used to measure all items.The study applied convenience sampling technique and used Google forms to distribute the questionnaire starting from 18 November 2022 to 4 December 2022.The questionnaire was also distributed through multiple tools and platforms, including email, WhatsApp, Facebook, and LinkedIn.The questionnaire was sent to individuals in Jordan older than 18 years old who use FinTech applications such as mobile banking and mobile wallets have been the target population.The goal of the study was revealed to these voluntarily participating study participants.These participants were also informed that their participation was anonymous and that they could abandon the study at any time during the study (Podsakoff et al., 2003).
Only 310 surveys out of 384 circulated were completed.Ultimately, 296 submissions from the number of 310 were verified for processing.The data collected was analyzed using descriptive analysis in SPSS, and structural equation modeling (SEM), path analysis, and confirmatory factor analysis (CFA) were performed using AMOS software.

Demographic analysis
Table 1 presents the demographic information of the participants, showing that males constituted the majority of respondents, accounting for approximately 54.7%, while females comprised 45.3%.The largest age range was between 25 and 34 years old, accounting for almost 48% of participants, while 18 to 24 years old accounted for 32.4%.Moreover, about 67.9% of the respondents had a bachelor's degree as their highest level of education.The majority of the participants were employed in the private sector, and 24% were still attending college.Additionally, the data indicates that 86.8% of the participants live in Amman, whereas the remaining reside in other governorates.
As shown in Table 2, the participants were asked three questions about the usage of FinTech applications.However, the results shows that mobile banking is the most popular FinTech application, with around 55.4% of respondents using it, and 39.2% of participants revealed that they use both mobile banking and mobile wallet.Additionally, most participants reported using FinTech applications daily or at least 2 to 3 times per week.While 50 percent of respondents have been using FinTech applications for less than two years, the remaining 50 percent have adopted FinTech applications for over two years.

Reliability and validity
When analyzing reflective outer models, researchers must check both the reliability and validity by employing composite reliability to evaluate the internal consistency reliability of the constructs' measures, and the second part of assessing reflective indicators is the evaluation of validity (Hair et al., 2014).Hence, before performing structural equation modeling (SEM) to test hypotheses, the researchers assessed the reliability and validity of the data.Using the average variance extracted (AVE), a measure of convergent validity with Composite reliability (CR), the results shown in Table 3 shows that convergent validity and composite reliability were achieved based on the values of AVE and CR for all variables and equal to or higher than 0.70 as recommended in previous literature.

Results of hypotheses testing
In testing H1 hypothesis, we examined the direct path relation between the independent factors and the dependent variable using structural equation modeling (SEM).Table 4 shows these results while Table 5 shows the results of H1 hypothesis testing.
As exhibited in the tables above, the hypothesis (H1a) was accepted.This result concluded that perceived usefulness positively affected behavioral intention to use FinTech at a P-Value less than 0.001.The same findings were discovered in testing hypothesis (H1d), which indicated that personal innovativeness positively impacted behavioral intention to use FinTech at P-Value less than 0.001.Hypotheses (H1b and H1c) were accepted where P-Value was less than 0.05.Also, the hypothesis (H1e) was accepted, and this result confirmed that financial risks negatively impacted behavioral intention to use FinTech.While the hypothesis (H1f) was rejected, where P-Value was .338,this result revealed that privacy risks had no significant impact on users' behavioral intention to use FinTech.Furthermore, in this model, the R-squared value was 0.259, indicating that perceived usefulness, perceived ease of use, social influence, personal innovativeness, financial risks, and privacy risks explained 25.9% of the variation in behavioral intention to use FinTech in Jordan.
Now to test H2 hypothesis, the moderating variable was included in examining the path relation between the independent factors and the dependent variable using structural equation modeling (SEM).Table 6 shows these results while Table 7 shows the results of H2 hypothesis testing.
Based on the findings shown in the tables above, there were four hypotheses (H2a, H2b, H2d, and H2e) accepted.These results confirmed that the impact of COVID-19 lockdowns moderated the relationships between perceived usefulness and behavioral intention to use FinTech, perceived ease of use and behavioral intention to use FinTech, personal innovativeness and behavioral intention to use FinTech, and financial risks and behavioral intention to use FinTech.At the same time, the hypothesis (H2c) was rejected, which indicated that the moderating effect of the impact of COVID-19 lockdowns on the relationship between social influence and behavioral intention to use FinTech was not significant.Also, the hypothesis (H2f) was not accepted since there was no significant relationship between privacy risk and behavioral intention to use FinTech.Furthermore, after adding the moderating variable to this model, the R-squared value was 0.384, meaning that 38.4% of behavioral intention to use FinTech is explained by the independent variables and the moderating variable.
Finally, to test H3 hypothesis and assess the influence of behavioral intention on usage behavior, simple regression analysis was used and can be found in Table 8.
As can be seen in Table 8 the results show that behavioral intention to adopt FinTech had a significant impact on FinTech usage behavior, with a P-value less than 0.001 and a Beta value of 0.638.Consequently, leading to the acceptance of hypothesis (H3).

Discussion
As FinTech in growing in popularity worldwide, encouraging people in Jordan to change their behavior from traditional ways of doing financial transactions to using FinTech services is not a simple task (Alalwan et al., 2018).In this study determinants of FinTech adoption in Jordan was explored using a sound theoretical model which was developed based on TAM and UTAUT theories.Structural equation modeling (SEM) was employed to test the theoretical model hypotheses.There were three parts of the hypotheses, denoted H1, H2, and H3.H1 is comprised of six hypotheses that examine the direct impact of perceived usefulness, perceived ease of use, social influence, personal innovativeness, financial risks, and privacy risk, on behavioral intention to use FinTech.H2 featured six additional hypotheses to measure the impact of COVID-19 lockdowns as a moderator on the relationship between predictors and behavioral intention to use FinTech.Lastly, H3 was used to test the relationship between behavioral intention to use FinTech and FinTech usage behavior.These results showed the positive impact of perceived usefulness, perceived ease of use, social influence, and personal innovativeness on behavioral intention to use FinTech.While the impact of privacy risks on behavioral intention to use FinTech was insignificant.Moreover, this empirical study verified the positive impact of COVID-19 lockdowns as a moderator on the behavioral intention to use FinTech applications.Likewise, the relationship between users' behavioral intention to use FinTech and their actual use of FinTech was proved.Thus, the hypothesis (H3) was confirmed.Interestingly, the conceptual model demonstrated considerable explanatory power with all predictors and the moderating variable in estimating behavioral intention to use FinTech applications, where R 2 = 0.384.
The findings revealed that perceived usefulness has the most substantial relationship with behavioral intention to use FinTech and in line with earlier research (e.g., Chawla & Joshi, 2019;Daragmeh et al., 2021;Leong et al., 2020;Liébana-Cabanillas et al., 2020;Singh et al., 2020) has found.This finding suggests that individuals in Jordan are more likely to adopt FinTech services if they perceive their usefulness.Similarly, the impact of perceived ease of use on behavioral intention to use FinTech is key to the adoption of FinTech services.This result was consistent with prior empirical studies (e.g., Shaikh et al., 2022Shaikh et al., , 2020;;Singh & Srivastava, 2020).This result suggests that simple and user friendly FinTech services can foster FinTech adoption among people in Jordan.
Similarly, the results were aligned with a majority of recent studies that have demonstrated the positive impact of social influence on behavioral intention to use FinTech services (e.g., Jung et al., 2020;Liébana-Cabanillas et al., 2020;Patil et al., 2020;Singh & Srivastava, 2020;Yan et al., 2021) suggesting the importance of positive opinions on others Fintech users in Jordan.As well, personal innovativeness played a significant role in predicting behavioral intention to use FinTech services with direct and positive influence on behavioral intention to use FinTech (e.g., Giovanis et al., 2019;Jun et al., 2018;Liébana-Cabanillas et al., 2020).
Financial risks revealed a negative impact on users' behavioral intention to use FinTech services (e.g., Agárdi & Alt, 2022) indicating how individuals in Jordan are concerned about losing their money due use of FinTech services, and this uncertainty inhibits their behavioral intention to use FinTech.Interestingly, the empirical findings showed the huge positive impact of COVID-19 lockdowns on FinTech adoption in Jordan.In fact, COVID-19 moderated positively all four determinants of behavioral intention to use FinTech and strengthening the relationship between perceived ease of use and behavioral intention, by change in P-value from 0.037 to 0.005 for instance.However, the impact of COVID-19 lockdowns did not moderate the relationship between social influence and behavioral intention.Similarly, the impact of COVID-19 lockdowns did not moderate the relationship between privacy risks and behavioral intention because privacy risks did not affect behavioral intention.
Finally, the empirical results demonstrated how behavioral intention to use FinTech had a significantly positive impact on the actual usage behavior of FinTech which comes in line with earlier recent empirical studies that have observed a significant relationship between behavioral intentions and usage of FinTech services (Senyo & Osabutey, 2020;Thusi & Maduku, 2020).
In Summary, we believe that not only in Jordan but other countries in the developing world, policymakers, and developers need to employ these empirical findings to foster the expansion of the FinTech industry.In fact, Fintech users must remain assured that they can get exposure to dependable, convenient infrastructures that will empower them to use FinTech applications.As well, assistive techniques like live discussion or robots to create constant guidance that promotes reasons for adopting FinTech while providing the right legislations that can stimulate the expansion of the FinTech industry which can also promote security and lower risks.

Conclusion
This research explored the factors that affects the intentions and behavior of FinTech in Jordan based on a sound conceptual model that was derived from previous theories in the existing literature.Later, 296 valid responses were used to analyze 13 hypotheses using different statistical techniques.The results of the first phase in which six hypotheses were tested to determine the impact of predictors on behavioral intention to use FinTech services showed that perceived usefulness, perceived ease of use, social influence, personal innovativeness, and financial risks significantly impacted the behavioral intention to use FinTech.In the second phase we tested six additional hypotheses to assess the impact of COVID-19 lockdowns as a moderator on the relationship between predictors and behavioral intention.The empirical findings showed that the impact of COVID-19 lockdowns moderated the relationship between perceived usefulness, ease of use, personal innovativeness, and financial risks with the behavioral intention to use FinTech.However, COVID-19 lockdowns as moderator showed no impact on social influence and privacy risk.Finally, the study's findings demonstrated how users' behavioral intention significantly affected their actual use of FinTech.In conclusion, we believe that these results can help policy makers and technology providers develop more relevant technologies and policies that can boost FinTech acceptance and adoption not only Jordan abut in many developing countries.