Abstract
Purpose
This study explores the relationship between financial literacy and quality of life (QoL). The study further examines the mediating effect of fintech adoption and the moderating effect of leisure on the relationship between financial literacy and QoL.
Design/methodology/approach
Using convenience sampling, 345 respondents participated in a cross-sectional survey. To test the moderated mediation hypotheses, the PROCESS macro was used.
Findings
The results reveal the mediating effect of fintech adoption on the relationship between financial literacy and QoL, highlighting the importance of digital literacy in an increasingly digitalized society. Moreover, leisure moderates the mediating relationship. Individuals with high leisure are more likely to perceive the uncertainties and risks associated with new technology optimistically – an observation supported by existing literature on the relationships among leisure, perceived freedom, and internal locus of control.
Practical implications
Financial literacy must incorporate digital literacy in order to utilize innovative technology for more efficient financial management. Additionally, having a sense of control over life outcomes can lead to well-being.
Originality/value
Previous research on fintech adoption is mostly related to financial inclusion for the unbanked population in underprivileged rural areas. Here, fintech usage by the general public is the focus. The study also reveals the significance of leisure, as those who have high financial literacy are more likely to adopt fintech when they have more freedom in their lives, which leads to higher QoL.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2021-0633.
Keywords
Citation
Kakinuma, Y. (2022), "Financial literacy and quality of life: a moderated mediation approach of fintech adoption and leisure", International Journal of Social Economics, Vol. 49 No. 12, pp. 1713-1726. https://doi.org/10.1108/IJSE-10-2021-0633
Publisher
:Emerald Publishing Limited
Copyright © 2022, Emerald Publishing Limited
1. Introduction
Financial literacy has economic significance in today's world: one needs good financial literacy to make informed decisions in financial planning, wealth accumulation, investment, borrowing, and retirement savings. These financial management skills are key to life satisfaction and well-being in life – in other words, quality of life (QoL) (Bowling and Windsor, 2001; Xiao et al., 2009). Financial literacy directly influences wealth creation (Behrman et al., 2012), stock market participation (Van Rooij et al., 2011), retirement planning (Lusardi and Mitchell, 2007), and debt management (Chotewattanakul et al., 2019), leading to improved well-being. However, several scholars argue that the relationship between financial literacy and QoL is complex and indirect (Amonhaemanon and Isaramalai, 2020; Pahlevan Sharif et al., 2020).
Financial literacy is vital for rapidly aging countries. An extended retirement period requires well-planned savings to ensure well-being during retirement. This study was conducted in Thailand, the first developing economy to enter a super-aged society. By 2035, more than 20% of its population will be aged 65 years or older (Chittinandana et al., 2017). With a state pension system that is limited and underdeveloped, Thai households have to save for retirement without expecting government support. Many financial products are available today, but the propensity of the citizens to take advantage of them depends on their financial literacy (Ketkaew et al., 2022). Thus, it is important to access financial literacy in the country to guide the formulation of appropriate policy. Since 2013, the Bank of Thailand (BOT) has conducted financial literacy surveys based on a framework adapted from the Organization for Economic Cooperation and Development (OECD). Three main components were considered: financial literacy, financial behavior, and financial attitude. The COVID-19 pandemic raised public awareness of the importance of long-term financial planning as unexpected events can deteriorate financial stability. The latest survey in 2020 indicated that Thai households have improved their financial skills since the 2018 survey with a score well above the OECD average (The Nation, 2021). Even then, the survey surprisingly revealed that only 39% of the respondents had sufficient funds for three month's worth of expenses in case of an emergency (Banchongduang, 2021). Most Thai people do not have emergency funds and are unprepared for unexpected situations. Financial difficulties arising from unforeseen events lead to stress and anxiety, worsening the QoL. Although the central bank's study suggests that Thais' financial skills have improved, they need to improve their understanding of, and attitude toward financing planning. Indeed, a recent study conducted in a rural area of Thailand suggests that financial attitude positively influences the well-being of Thai households (Thongrak et al., 2021).
This study aims to explore the relationship between financial literacy and QoL, with fintech adoption as a mediator and leisure as a moderator. Here, fintech adoption and leisure are investigated as integral components to improve the QoL of financially literate individuals. Previous studies on fintech focus on factors related to the intention to use (Daragmeh et al., 2021) and financial inclusion for unbanked citizens in developing regions (Ezzahid and Elouaourti, 2021). Incorporating Kass-Hanna et al. (2022) argument that financial literacy needs to be redefined to include digital literacy, this study considers fintech adoption as an indicator of digital literacy. Here, its mediating role on the pathway from financial literacy to QoL is tested. This study was conducted during the COVID-19 pandemic when fintech adoption had a special context in daily life. Contactless payments enabled by fintech can mitigate the risk of contracting the COVID-19, ensuring users' health. Moreover, the pandemic was a catalyst for becoming digitally literate (Mansour, 2022) as lockdown measures by the Thai government immobilized its citizens.
Previous studies on leisure have mostly focused on its direct effect on QoL (Iwasaki, 2007). Leisure in this study represents the availability of free time in daily life rather than an activity-based concept, and its moderating role in the financial literacy-fintech adoption-QoL link is examined. This study chooses leisure as a key moderator because it represents individuals' time availability and personal traits that affect fintech adoption. The literature suggests that leisure represents the degree of perceived freedom and internal locus of control. Those with high leisure value perceived freedom (Ellis and Witt, 1986), and there is a high correlation between perceived freedom and internal locus of control (Verme, 2009). Several studies (Schreier and Prügl, 2008; Hsia, 2016; Taffesse and Tadesse, 2017) indicate those with high locus control are more likely to adopt new technologies. Thus, leisure influences one's decision to adopt fintech.
The contributions of this study are threefold: First, using a proprietary dataset, this study presents evidence that financial literacy alone does not lead to a better QoL. The relationship is indirect and intricate, and a positive link is feasible with the mediating and moderating factors. Second, fintech adoption significantly mediates the relationship between financial literacy and QoL, highlighting the importance of digital literacy in today's increasingly digitalized society. Third, this study reveals a significant moderating role of leisure on fintech adoption. Individuals with high leisure time optimistically perceive the uncertainties and risks associated with new technologies. Their internal locus of control makes them believe that adopting innovative technology rewards them with positive outcomes, resulting in a higher QoL.
The remainder of this paper is organized as follows. Section 2 reviews related literature and develops the hypotheses. Section 3 describes the data and the methodology used in this study. Section 4 presents the results and discusses the implications. Section 5 presents conclusions, research limitations, and suggestions for future work.
2. Literature review and hypothesis development
2.1 Financial literacy and quality of life
Many researchers have proclaimed the benefits of solid financial literacy. Financial literacy contributes to economic and financial stability and helps manage financial resources effectively (Adil et al., 2021). She et al. (2022) indicate that financial knowledge positively leads to better financial behavior and well-being. On the other hand, a lack of financial literacy brings undesirable consequences such as excess borrowing (Sevim et al., 2012) or investment scams (Mohd Padil et al., 2022). Financial security in later life and retirement increases independence and control over one's life, leading to less anxiety and better mental health. Indeed, Lusardi et al. (2017) find that financial knowledge accounts for 30–40% of retirement wealth inequality. Thus, this study postulates that:
There is a positive relationship between financial literacy and QoL.
2.2 The mediating role of fintech adoption
Some studies suggest that higher financial literacy may not automatically improve QoL. However, it does so through media such as attitude and behavior (Amonhaemanon and Isaramalai, 2020) or financial security (Pahlevan Sharif et al., 2020). With the proliferation of smartphones and the development of fintech, financial services are increasingly digitalized. Kass-Hanna et al. (2022) argue that it is crucial for traditional financial literacy to align with worldwide fintech development by integrating digital financial literacy. Similarly, Jünger and Mietzner (2020) identify financial literacy as critical to the adoption of fintech products and services.
The COVID-19 outbreak has made the utilization of fintech a natural choice over traditional face-to-face transactions from a personal health risk management perspective. Daqar et al. (2021) find that fintech perceptions and behavior among consumers help reduce the spread of COVID-19 by capitalizing on contactless payments. Easing the fear of viral infection through use of fintech should improve QoL. Fintech enables users to avoid visiting bank branches, using ATMs, or making payments in cash. This gives fintech adopters some protection from infection during the pandemic.
Based on the literature reviewed above, this study proposes the mediating role of fintech adoption on the link between financial literacy and QoL.
There is a positive relationship between financial literacy and fintech adoption.
There is a positive relationship between fintech adoption and QoL.
Fintech adoption mediates the relationship between financial literacy and QoL.
2.3 The moderating role of leisure
In this research, leisure is defined as the availability of free (Shaw, 1984) and unobligated time (Bedini and Phoenix, 2004). Free time is a luxury in today's daily life, with people immersing themselves in their professions. Retail financial services are an essential infrastructure in people's daily lives, but waiting in a long queue at a bank branch to make simple transactions is not exciting. Fintech allows people to save time by giving them banking capability at their fingertips. Perceived usefulness in an often-cited technology acceptance model TAM (Davis et al., 1989) is a significant attribute for fintech adoption in numerous studies (Shaikh et al., 2020; Singh et al., 2020). Discretionary time availability is a core element of leisure (Esteve et al., 1999), so people with less leisure time are more likely to adopt fintech because of its perceived benefits of saving time.
Leisure in this study also represents personal traits. Perceived freedom is an essential criterion for leisure (Ellis and Witt, 1986). Verme (2009) find a significant relationship between perceived freedom and the internal locus of control, a personal trait in which individuals believe that they can control their lives. Several scholars (Schreier and Prügl, 2008; Hsia, 2016; Taffesse and Tadesse, 2017) have found that those with high locus control are more likely to adopt new technologies. Adopting new technology is associated with risks and uncertainty, and those with a high internal locus of control voluntarily seek relevant information on the new technology to reduce risks. Leisure in this study broadly represents the degree of perceived freedom and internal locus of control, which presumably influence one's decision to adopt fintech.
A large body of literature indicates that leisure contributes to QoL regardless of country or culture (Michalos, 2005; Ritsner et al., 2005). Leisure plays an integral role in subjective well-being and offers opportunities to meet life values and needs (Brajša-Žganec et al., 2011). Thus, leisure can be a moderating factor in enhancing QoL, such as spiritual well-being (Heintzman and Mannell, 2003) and reduced life stress (Iso-Ahola and Park, 1996). This study tests leisure's moderating effect on the paths from financial literacy to fintech adoption and to QoL. Based on the literature reviewed above, this study proposes the following hypotheses:
Leisure moderates the relationship between financial literacy and fintech adoption.
Leisure moderates the relationship between financial literacy and QoL.
Figure 1 shows the proposed moderated mediation model and hypotheses. This model explains the relationship between financial literacy and QoL. The model examines how fintech adoption mediates the relationship and how leisure affects the paths from financial literacy to fintech adoption and QoL. In model estimation, we control for demographic factors.
3. Data and methodology
We conducted an online cross-sectional survey using convenience sampling. The target respondents are residents of Thailand, aged 20 years or older, living in and outside Bangkok. The respondents were informed that the survey is voluntary, and that their anonymity was guaranteed. Data were collected with an online survey via social media platforms such as Facebook and LinkedIn. The structured questionnaire consisted of five sections: 1) questions on the sociodemographic characteristics of the respondents, 2) The second to fifth sections measured their financial literacy, fintech adoption, QoL, and leisure using a five-point Likert scale. From the initial 359 responses obtained, after omitting incomplete responses, 345 responses were used in the analysis.
3.1 Respondent profile
Table 1 reports the respondents' sociodemographic characteristics. The majority of the respondents were female (n = 222, 64.4%), younger than 40 years old (n = 251, 72.7%), and residing in Bangkok (n = 210, 60.9%). The most distinct characteristic of the sample is that they are highly educated, with at least a bachelor's degree (n = 278, 80.6%). Although bachelor's degrees have become a minimum requirement for white-collar positions in Thailand (Grohmann, 2018), this may pose a bias. To address this issue, we controlled for demographic factors, including educational level in the statistical tests of the hypotheses. The largest income group were earning THB15,000–30,000 per month (n = 109, 31.6%). According to the Bank of Thailand (2021), the average monthly salary for holders of bachelor's degrees is THB23,054 in the first quarter of 2021. More than half of the respondents had net worths below THB300,000 (n = 182, 52.8%).
3.2 Measures
3.2.1 Financial literacy
Five multiple-choice questions from Van Rooij et al. (2011) were used to evaluate participants' basic financial knowledge on compound interest, time value of money, inflation, and nominal and real interest rates. The maximum financial literacy score was 5 and the minimum score was 0. Cronbach's alpha was 0.57. A reliability coefficient of 0.5 or higher indicates internal consistency (Bowling, 1997).
3.2.2 Quality of life
Quality of life was measured using the Satisfaction with Life Scale (Diener et al., 1985). The five positively-worded statements on life were rated on a five-point scale from “strongly agree” to “strongly disagree.” An example of a statement is, “If I could live my life over, I would change almost nothing.” The possible score ranges from 25 to 5, with a higher score representing a better quality of life. Cronbach's reliability was 0.82.
3.2.3 Leisure
The measurement of leisure was developed by Shaw (1984). The five statements on the availability of time associated with enjoyment, relaxation, freedom of choice, motivation, and lack of evaluation, were rated on a five-point scale from “strongly agree” to “strongly disagree.” An example of a statement is, “I can freely choose activities that I am motivated to do.” The possible score ranges from 25 to 5, with a higher score representing greater availability of free time. Cronbach's alpha was 0.86.
3.2.4 Fintech adoption
Fintech adoption was measured by actual use of fintech services. Most prior studies on fintech adoptions are based on the intention to use (Daragmeh et al., 2021). However, as the utility of fintech services is realized only through actual use rather than mere intention, this study focuses on the actual usage of fintech. Fintech adoption was measured using the frequency of fintech service use. The respondents were asked how frequently they used (1) digital banking, (2) digital payment, or (3) digital transfer (Morgan and Trinh, 2020). Usage frequency was scored on a 5-point scale: 5 for usage of more than once a week; 4 for once a week; 3 for once a month; 2 for less than once a month; and 1 for never having used the fintech function.
3.3 Data analysis
The present study employs Hayes's (2018) PROCESS macro to assess the moderated mediation model. The proposed model specifies financial literacy as the independent variable, QoL as the dependent variable, fintech adoption as the mediator, leisure as the moderator, and gender, age, education, residence, income, and assets as the control variables in Model 8 of PROCESS macro (Hayes, 2018). The bootstrapping technique with 1,000 sample replications at a 95% confidence level yields robust standard errors for the parameter estimates. Advantages of PROCESS macro include avoiding sample size and degree of freedom restrictions (Hair et al., 2010) and providing accurate statistical inferences without complicated programming (Hayes et al., 2017). PROCESS differs from other methods such as structural equation modeling (SEM) in the estimation approach. PROCESS is regression-based and estimates the parameters of each equation separately. On the other hand, covariance-based maximum likelihood (ML)-SEM and component-based partially least squares (PLS)-SEM approach the entire system of equations simultaneously. Hayes et al. (2017) conclude that although PROCESS and SEM have different estimation methods and theories, differences in the results are insignificant and essential conclusions are not influenced by the choice of PROCESS or SEM.
The proposed moderated mediation model is estimated with the following equations (Igartua and Hayes, 2021):
4. Results and discussion
Table 2 shows the descriptive statistics and correlations among the variables in this study. The mean score for financial literacy was 2.833, with a relatively wide standard deviation of 1.452. Given that respondents are highly educated individuals (more than 80% of them have at least a bachelor's degree), the different levels of financial knowledge among the samples pose challenges to the conventional educational system in improving citizens' financial understanding. Financial literacy is significantly correlated with fintech adoption. Financial literacy and QoL are not significantly correlated, but leisure had a significant positive relationship with QoL.
Table 3 shows the results of the moderated mediation model. Fintech adoption functions as a mediator in the relationship between financial literacy and QoL. Leisure moderates the link between financial literacy and fintech adoption as well as between financial literacy and QoL. The effects of gender, age, education, residence, income, and assets were controlled for connections with fintech adoption and QoL. We found that the relationship between financial literacy and QoL is not significant (β = 0.032, p > 0.05); thus, H1 is not supported. Financial literacy alone does not increase QoL. A possible explanation for the failure to support H1 lies in financial behavior. Amonhaemanon and Isaramalai (2020) assert that financial behavior, measured by the degree to which individuals have saved or made investment decisions after comparing information or considering information from trusted sources, is the most important factor in enhancing QoL. Financial literacy, to put it in another way, can be mere knowledge, yet it is a consequential action that matters in life.
Financial literacy is not directly related to fintech adoption (β = −0.208, p > 0.05), indicating that H2 is not supported. A recent study by Setiawan et al. (2021) reveals that financial literacy is less important than user innovativeness when adopting fintech. User innovativeness – the willingness to experiment with new technologies (Lu et al., 2005) – is strengthened by the optimization of the external information (Yun et al., 2020). This user innovativeness factor justifies H5, the positive moderation of leisure on the path from financial literacy to fintech adoption. Individuals with high leisure are the internals who are more innovative, proactive, and risk-taking (Miller et al., 1982), an equivalent defining criterion for user innovation. The impact of perceived risks and uncertainty is significant when individuals make financial decisions (Murari et al., 2021). Nonetheless, the combination of financial knowledge and internal locus of control overcomes the barrier to accepting innovative financial technologies.
Fintech adoption significantly affects QoL (β = 0.078, p < 0.05), supporting H3. The result indicate that digital literacy is a critical element of financial literacy in today's increasingly digitalized society. Those who have adopted fintech are digitally literate, and they have broader access to new information and knowledge acquired and shared through digital channels such as blogs and social media. Fintech adoption results from continuous learning because individuals need a willing attitude and flexibility to learn modern technology. Continuous self-improving learning enhances the knowledge and skills to improve QoL (Laal et al., 2014).
Table 4 reports the pathways between financial literacy and QoL via fintech adoption at different levels of leisure. The conditional indirect effect is weakly significant, and only at a high level of leisure with a mean plus one standard deviation (β = 0.012, p < 0.10). The conditional indirect effect is not significant at a mean level or lower. Thus, H4, the mediation effect of fintech adoption, is supported given that the moderation effect of leisure is at a high level. Table 3 indicates leisure moderates the relationship between financial literacy and fintech adoption— a significant positive effect (β = 0.082, p < 0.05), supporting H5. In other words, H4 is supported by the collaboration between H3 and H5. Figure 2 graphically presents the mediating relationship between financial literacy and QoL through fintech adoption for varying levels of leisure. It indicates that financial literacy does not affect fintech adoption when leisure is low, whereas there is a linear relationship between financial literacy and fintech adoption when the leisure level is high. Figure 2 also illustrates that when leisure is low, fintech adoption is relatively high regardless of financial literacy. This reflects the behavior of people who are immersed in their busy daily lives and utilize fintech to save time (Setiawan et al., 2021). However, the level of fintech adoption with low leisure is not significant for a better QoL. The moderation effect is only significant when leisure is high. In other words, the interaction between high financial literacy and high leisure induces higher fintech adoption, leading to a higher QoL. This moderated mediation effect of fintech and leisure signifies the value of active learning in improving QoL. Financial literacy provides economic benefits, but financially literate individuals must actively seek new information and adjust to a constantly changing society. Leisure comes into play when adopting an unfamiliar product or service. Individuals with high leisure deal with uncertainty associated with new technology by searching for relevant data and evidence. The knowledge and experience gained through technology adoption lead to greater personal human capital and well-being.
Leisure has a strong significant positive relationship with QoL (β = 0.590, p < 0.001), but its moderating effect on the relationship between financial literacy and QoL is insignificant (β = −0.024, p > 0.05). Thus, H6 is not supported. Financial behavior explains the failure to support H6. Individuals with high leisure tend to be the internals. People with high internal control ascribe their results to themselves, and their sense of responsibility is sometimes excessive (Davis and Davis, 1972). Mutlu and Özer (2022) conclude that when financially literate individuals have a high internal locus of control with high responsibility and anxiety, their self-responsibility level rises even further. This results in a more complicated financial decision-making process, which leads to a deterioration of financial behavior.
For the control variables, we found that younger respondents (β = −0.157, p < 0.05) and levels of higher education (β = 0.395, p < 0.05) have a significantly higher tendency to adopt fintech, and women have a higher QoL (β = 0.170, p < 0.05).
5. Conclusion
This study provides novel evidence on the indirect relationship between financial literacy and QoL, highlighting the mediating effect of fintech adoption and the moderating effect of leisure on the relationship. The utilization of financial technology is a key to a better life in today's increasingly digitalized society. The novelty of this study is that it focuses on fintech usage by the general public, as most previous research on fintech adoption is related to financial inclusion for the unbanked population in underprivileged rural areas. In addition, the study reveals the significance of leisure, as those who have high financial literacy are more likely to adopt fintech when they have high perceived freedom, which leads to higher QoL.
The implications of this study are that fintech usage should be promoted as a fundamental life skill at the same level as financial literacy. Financial literacy is no longer mere numerical skills and knowledge of the capital market; it needs to incorporate digital literacy to utilize innovative technology for more efficient financial management. As the digitalization of financial services continues in the finance industry, users need to equip themselves with adequate digital knowledge as an essential life skill. Policymakers have attempted to implement financial education programs for the public, but such programs need to update the content in line with today's digitalized society. New evidence suggests that digital financial literacy positively affects financial behavior and decision-making (Andreou and Anyfantaki, 2021). Furthermore, digital literacy increases the awareness of financial scams and fraud, which are often solicited online. Digital literacy is not only a skill to maneuver electric devices but also to manage, integrate, and process information. Thus, policymakers should recognize digital literacy as a catalyst that leads to a more secure and stable society.
Another implication is that a sense of control over life outcomes can lead to well-being. Based on the existing literature on the link between leisure, perceived freedom, and internal locus of control, this study shows that individuals with high leisure are more likely to perceive the uncertainties and risks associated with new technology optimistically. Those with an internal locus of control possess a strong belief in the relationship between effort and rewards, and seek more information to use the new technology more effectively (Tseng and Hsia, 2008). Chang et al.(2009) agree that problem-solving skills enhance well-being. Education programs for citizens, especially young students, targeting the improvement of digital financial literacy as well as the acquisition of internal locus of control are encouraged for the benefit of society. The limitations of this study include the effect of COVID-19 on individuals' behavior. COVID-19 was a catalyst for change (Mansour, 2022), and the new normal situation during the pandemic inescapably affected their fintech usage. Stay-at-home and work-from-home policies imposed by local authorities and private firms might have affected their leisure, because these policies generally increased free time. A relevant question for future research would be whether nonpayment fintech services can improve the relationship between financial literacy and QoL. New fintech services such as peer-to-peer lending, robo-advisors, and insurtech are gaining momentum among tech-savvy households. The synergy that financial and digital literacy create for better well-being can be further explored.
Figures
Socio-demographic of the respondents
| Variable | N | % | Variable | N | % |
|---|---|---|---|---|---|
| Gender | Residence | ||||
| Male | 115 | 33.3 | Bangkok Metropolitan Area | 210 | 60.9 |
| Female | 222 | 64.4 | Outside Bangkok | 135 | 39.1 |
| Prefer not to say | 8 | 2.3 | Metropolitan Area | ||
| Age | Income | ||||
| 20–29 | 144 | 41.7 | THB0-15,000 per month | 92 | 26.7 |
| 30–39 | 107 | 31.0 | THB15,000–30,000 | 109 | 31.6 |
| 40–49 | 51 | 14.8 | THB30,001–50,000 | 83 | 24.1 |
| 50–59 | 35 | 10.2 | THB50,001–100,000 | 43 | 12.5 |
| 60 or older | 8 | 2.3 | THB100,001 or higher | 18 | 5.2 |
| Education | Asset | ||||
| Elementary school | 10 | 2.9 | Less than THB300,000 | 182 | 52.8 |
| High school | 29 | 8.4 | THB300,001–500,000 | 51 | 14.8 |
| Vocational school | 28 | 8.1 | THB500,001–1,000,000 | 42 | 12.1 |
| Bachelor degree | 215 | 62.3 | THB1,000,000–3,000,000 | 29 | 8.4 |
| Master degree or higher | 63 | 18.3 | THB3,000,000 or more | 41 | 11.9 |
| Total | 345 | ||||
Summary statistics and correlation
| Variable | Mean | SD | Financial literacy | Fintech adoption | Leisure |
|---|---|---|---|---|---|
| Financial literacy | 2.833 | 1.452 | – | ||
| Fintech adoptation | 4.591 | 0.976 | 0.220*** (0.00) | – | |
| Leisure | 3.409 | 0.901 | 0.063 (0.24) | −0.054 (0.31) | – |
| QoL | 3.219 | 0.856 | −0.023 (0.668) | −0.001 (0.99) | 0.558*** (0.00) |
Note(s): The table reports the summary statistics and the Pearson correlation matrix between the variables. The p-values are shown in the brackets. *** denotes the significant level at 0.1%
Results of moderated mediation model
| Path | Standardized coefficient | p-value |
|---|---|---|
| Moderated mediation model | ||
| Financial literacy → Fintech adoption | −0.208 | 0.126 |
| Leisure → Fintech adoption | −0.327* | 0.015 |
| Financial literacy × Leisure→ Fintech adoption | 0.082* | 0.046 |
| Financial literacy → QoL | 0.032 | 0.778 |
| Fintech adoption → QoL | 0.078* | 0.041 |
| Leisure → QoL | 0.590*** | 0.000 |
| Financial literacy × Leisure→ QoL | −0.024 | 0.475 |
| Control variables | ||
| Gender (Female) → Fintech adoption | 0.004 | 0.970 |
| Age → Fintech adoption | −0.157** | 0.004 |
| Education → Fintech adoption | 0.395*** | 0.000 |
| Residence (outside Bangkok) → Fintech adoption | 0.061 | 0.538 |
| Income → Fintech adoption | 0.031 | 0.558 |
| Asset → Fintech adoption | 0.005 | 0.906 |
| Gender (Female) → QoL | 0.170* | 0.029 |
| Age → QoL | 0.054 | 0.163 |
| Education → QoL | −0.081 | 0.092 |
| Residence (outside Bangkok) → QoL | 0.031 | 0.699 |
| Income → QoL | 0.044 | 0.322 |
| Asset → Fintech QoL | 0.059 | 0.072 |
Summary of indirect effects at different levels of leisure
| Different levels of the moderator leisure on the indirect effect | Coefficient | p-value | LLCI | ULCI |
|---|---|---|---|---|
| Low Leisure (mean minus one SD = −1) | −0.001 | 0.986 | −0.008 | 0.009 |
| Mean Leisure | 0.006 | 0.154 | −0.001 | 0.015 |
| High Leisure (mean plus one SD = +1) | 0.012♦ | 0.082 | −0.001 | 0.025 |
Note(s): CI = 95% confidence level for indirect effect between financial literacy and QoL via fintech adoption. If CI does not include zero, the indirect effect is considered statistically significant at 5% level. ♦Denotes the significant level at 10%
Measurement questions are available at: https://drive.google.com/file/d/13KRvIj9kCYhYBKd9DCaW5WO9W-aERgZO/view?usp=sharing.
References
Adil, M., Singh, Y. and Ansari, M.S. (2021), “How financial literacy moderate the association between behaviour biases and investment decision?”, Asian Journal of Accounting Research, Vol. 7 No. 1, pp. 17-30, doi: 10.1108/ajar-09-2020-0086.
Amonhaemanon, D. and Isaramalai, S. (2020), “Boosting financial literacy: its role in enhancing quality of life”, ABAC Journal, Vol. 40 No. 1, pp. 85-108.
Andreou, P.C. and Anyfantaki, S. (2021), “Financial literacy and its influence on internet banking behavior”, European Management Journal, Vol. 39 No. 5, doi: 10.1016/j.emj.2020.12.001.
Banchongduang, S. (2021), “Survey Shows low but rising financial literacy”, Bangkok Post, available at: https://www.bangkokpost.com/business/2205727/survey-shows-low-but-rising-financial-literacy.
Bank of Thailand (2021), “Average wage classified by level of education”, available at: https://www.bot.or.th/App/BTWS_STAT/statistics/BOTWEBSTAT.aspx?reportID=666&language=ENG.
Bedini, L.A. and Phoenix, T.L. (2004), “Perceptions of leisure by family caregivers : a profile”, Therapeutic Recreational Journal, Vol. 38 No. 4, pp. 366-381.
Behrman, J.R., Mitchell, O.S., Soo, C.K. and Bravo, D. (2012), “How financial literacy affects household wealth accumulation”, American Economic Review, Vol. 102 No. 3, pp. 300-304, doi: 10.1257/aer.102.3.300.
Bowling, A. (1997), Research Methods in Health, Open University Press, Buckingham.
Bowling, A. and Windsor, J. (2001), “Towards the good life: a population survey of dimensions of quality of life”, Journal of Happiness Studies, Vol. 2 No. 1, doi: 10.1023/A:1011564713657.
Brajša-Žganec, A., Merkaš, M. and Šverko, I. (2011), “Quality of life and leisure activities: how do leisure activities contribute to subjective well-being?”, Social Indicators Research, Vol. 102 No. 1, doi: 10.1007/s11205-010-9724-2.
Chang, E.C., D'Zurilla, T.J. and Sanna, L.J. (2009), “Social problem solving as a mediator of the link between stress and psychological well-being in middle-adulthood”, Cognitive Therapy and Research, Vol. 33 No. 1, doi: 10.1007/s10608-007-9155-9.
Chittinandana, D., Kulnartsiri, N., Pinthong, J. and Sawaengsuksant, P. (2017), “Aging population: global perspectivess”, available at: https://www.bot.or.th/Thai/ResearchAndPublications/DocLib_/AgingPopulation.pdf.
Chotewattanakul, P., Sharpe, K. and Chand, S. (2019), “The drivers of household indebtedness: evidence from Thailand”, Southeast Asian Journal of Economics, Vol. 7 No. 1, pp. 1-40.
Daqar, M.A., Constantinovits, M., Arqawi, S. and Daragmeh, A. (2021), “The role of fintech in predicting the spread of covid-19”, Banks and Bank Systems, Vol. 16 No. 1, doi: 10.21511/bbs.16(1).2021.01.
Daragmeh, A., Lentner, C. and Sági, J. (2021), “FinTech payments in the era of COVID-19: factors influencing behavioral intentions of ‘Generation X’ in Hungary to use mobile payment”, Journal of Behavioral and Experimental Finance, Vol. 32, p. 100574, doi: 10.1016/j.jbef.2021.100574.
Davis, W.L. and Davis, D.E. (1972), “Internal-external control and attribution of responsibility for success and failure”, Journal of Personality, Vol. 40 No. 1, doi: 10.1111/j.1467-6494.1972.tb00653.x.
Davis, F.D., Bagozzi, R.P. and Warshaw, P.P. (1989), “User acceptance of computer technology : a comparison of two theoretical models”, Management Science, Vol. 35 No. 8, pp. 982-1003, doi: 10.1287/mnsc.35.8.982.
Diener, E., Emmons, R.A., Larsem, R.J. and Griffin, S. (1985), “The satisfaction with life scale”, Journal of Personality Assessment, Vol. 49 No. 1, doi: 10.1207/s15327752jpa4901_13.
Ellis, G.D. and Witt, P.A. (1986), “The leisure diagnostic battery: past, present, and future”, Therapeutic Recreation Journal, Vol. 20 No. 4, pp. 31-47.
Esteve, R., Martin, J.S. and Lopez, A.E. (1999), “Grasping the meaning of leisure: developing a self-report measurement tool”, Leisure Studies, Vol. 18 No. 2, doi: 10.1080/026143699374961.
Ezzahid, E. and Elouaourti, Z. (2021), “Financial inclusion, mobile banking, informal finance and financial exclusion: micro-level evidence from Morocco”, International Journal of Social Economics, Vol. 48 No. 7, doi: 10.1108/IJSE-11-2020-0747.
Grohmann, A. (2018), “Financial literacy and financial behavior: evidence from the emerging Asian middle class”, Pacific Basin Finance Journal, Vol. 48, doi: 10.1016/j.pacfin.2018.01.007.
Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. and Tatham, R.L. (2010), Multivariate Data Analysis, Vol. 7th ed., Prentice-Hall, Upper Saddle River, NJ.
Hayes, A.F. (2018), “Introduction to mediation, moderation, and conditional process analysis”, A Regression-Based Approach, 2nd ed., The Guilford Press.
Hayes, A.F., Montoya, A.K. and Rockwood, N.J. (2017), “The analysis of mechanisms and their contingencies: PROCESS versus structural equation modeling”, Australasian Marketing Journal, Vol. 25 No. 1, pp. 76-81, doi: 10.1016/j.ausmj.2017.02.001.
Heintzman, P. and Mannell, R.C. (2003), “Spiritual functions of leisure and spiritual well-being: coping with time pressure”, Leisure Sciences, Vol. 25 Nos 2-3, doi: 10.1080/01490400306563.
Hsia, J.W. (2016), “The effects of locus of control on university students' mobile learning adoption”, Journal of Computing in Higher Education, Vol. 28 No. 1, doi: 10.1007/s12528-015-9103-8.
Igartua, J.J. and Hayes, A.F. (2021), “Mediation, moderation, and conditional process analysis: concepts, computations, and some common confusions”, Spanish Journal of Psychology, Vol. 24 No. 6, doi: 10.1017/SJP.2021.46.
Iso-Ahola, S.E. and Park, C.J. (1996), “Leisure-related social support and self-determination as buffers of stress-illness relationship”, Journal of Leisure Research, Vol. 28 No. 3, doi: 10.1080/00222216.1996.11949769.
Iwasaki, Y. (2007), “Leisure and quality of life in an international and multicultural context: what are major pathways linking leisure to quality of life?”, Social Indicators Research, Vol. 82 No. 2, doi: 10.1007/s11205-006-9032-z.
Jünger, M. and Mietzner, M. (2020), “Banking goes digital: the adoption of FinTech services by German households”, Finance Research Letters, Vol. 34, doi: 10.1016/j.frl.2019.08.008.
Kass-Hanna, J., Lyons, A.C. and Liu, F. (2022), “Building financial resilience through financial and digital literacy in South Asia and Sub-Saharan Africa”, Emerging Markets Review, Vol. 51, doi: 10.1016/j.ememar.2021.100846.
Ketkaew, C., Van Wouwe, M., Jorissen, A., Cassimon, D., Vichitthamaros, P. and Wongsaichia, S. (2022), “Towards sustainable retirement planning of wageworkers in Thailand: a qualitative approach in behavioral segmentation and financial pain point identification”, Risks, Vol. 10 No. 1, pp. 1-30, doi: 10.3390/risks10010008.
Laal, M., Laal, A. and Aliramaei, A. (2014), “Continuing education; lifelong learning”, Procedia - Social and Behavioral Sciences, Vol. 116, doi: 10.1016/j.sbspro.2014.01.889.
Lu, J., Yao, J.E. and Yu, C.S. (2005), “Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology”, Journal of Strategic Information Systems, Vol. 14 No. 3, doi: 10.1016/j.jsis.2005.07.003.
Lusardi, A. and Mitchell, O.S. (2007), “Baby Boomer retirement security: the roles of planning, financial literacy, and housing wealth”, Journal of Monetary Economics, Vol. 54 No. 1, doi: 10.1016/j.jmoneco.2006.12.001.
Lusardi, A., Michaud, P.C. and Mitchell, O.S. (2017), “Optimal financial knowledge and wealth inequality”, Journal of Political Economy, Vol. 125 No. 2, doi: 10.1086/690950.
Mansour, H. (2022), “How successful countries are in promoting digital transactions during COVID-19”, Journal of Economic Studies, Vol. 49 No. 3, pp. 435-452, doi: 10.1108/JES-10-2020-0489.
Michalos, A.C. (2005), “Arts and the quality of life: an exploratory study”, Social Indicators Research, Vol. 71 No. 1, doi: 10.1007/s11205-004-8013-3.
Miller, D., Kets de Vries, M.F.R. and Toulouse, J.-M. (1982), “Top executive locus of control and its relationship to strategy-making, structure, and environment”, Academy of Management Journal, Vol. 25 No. 2, doi: 10.5465/255988.
Mohd Padil, H., Kasim, E.S., Muda, S., Ismail, N. and Md Zin, N. (2022), “Financial literacy and awareness of investment scams among university students”, Journal of Financial Crime, Vol. 29 No. 1, pp. 355-367, doi: 10.1108/JFC-01-2021-0012.
Morgan, P.J. and Trinh, L.Q. (2020), “FinTech and financial literacy in Vietnam”, ADBI, Working Paper Series (No.1154).
Murari, K., Shukla, S. and Adhikari, B. (2021), “Do psychological social and financial perceptions of post-retirement life and demography influence the retirement planning behaviour?”, International Journal of Social Economics, Vol. 48 No. 11, pp. 1545-1566, doi: 10.1108/IJSE-08-2020-0581.
Mutlu, Ü. and Özer, G. (2022), “The moderator effect of financial literacy on the relationship between locus of control and financial behavior”, Kybernetes, Vol. 51 No. 3, pp. 1114-1126, doi: 10.1108/K-01-2021-0062.
Pahlevan Sharif, S., Naghavi, N., Sharif Nia, H. and Waheed, H. (2020), “Financial literacy and quality of life of consumers faced with cancer: a moderated mediation approach”, International Journal of Bank Marketing, Vol. 38 No. 5, doi: 10.1108/IJBM-10-2019-0355.
Ritsner, M., Kurs, R., Gibel, A., Ratner, Y. and Endicott, J. (2005), “Validity of an abbreviated Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-18) for schizophrenia, schizoaffective, and mood disorder patients”, Quality of Life Research, Vol. 14 No. 7, doi: 10.1007/s11136-005-2816-9.
Schreier, M. and Prügl, R. (2008), “Extending lead-user theory: antecedents and consequences of consumers' lead userness”, Journal of Product Innovation Management, Vol. 25 No. 4, doi: 10.1111/j.1540-5885.2008.00305.x.
Setiawan, B., Nugraha, D.P., Irawan, A., Nathan, R.J. and Zoltan, Z. (2021), “User innovativeness and fintech adoption in Indonesia”, Journal of Open Innovation: Technology, Market, and Complexity, Vol. 7 No. 3, p. 188, doi: 10.3390/joitmc7030188.
Sevim, N., Temizel, F. and Sayilir, Ö. (2012), “The effects of financial literacy on the borrowing behaviour of Turkish financial consumers”, International Journal of Consumer Studies, Vol. 36 No. 5, doi: 10.1111/j.1470-6431.2012.01123.x.
Shaikh, I.M., Qureshi, M.A., Noordin, K., Shaikh, J.M., Khan, A. and Shahbaz, M.S. (2020), “Acceptance of Islamic financial technology (FinTech) banking services by Malaysian users: an extension of technology acceptance model”, Foresight, Vol. 22 No. 3, doi: 10.1108/FS-12-2019-0105.
Shaw, S.M. (1984), “The measurement of leisure: a quality of life issue”, Loisir et Societe, Vol. 7 No. 1, doi: 10.1080/07053436.1984.10715172.
She, L., Rasiah, R., Turner, J.J., Guptan, V. and Sharif Nia, H. (2022), “Psychological beliefs and financial well-being among working adults: the mediating role of financial behaviour”, International Journal of Social Economics, Vol. 49 No. 2, pp. 190-209, doi: 10.1108/ijse-07-2021-0389.
Singh, S., Sahni, M.M. and Kovid, R.K. (2020), “What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model”, Management Decision, Vol. 58 No. 8, doi: 10.1108/MD-09-2019-1318.
Taffesse, A.S. and Tadesse, F. (2017), “Pathways less explored-locus of control and technology adoption”, Journal of African Economies, Vol. 26, doi: 10.1093/jae/ejx013.
The Nation (2021), “More Thais getting smarter with their money, BOT survey shows”, available at: https://www.nationthailand.com/business/40008144.
Thongrak, N., Chancharat, S. and Kijkasiwat, P. (2021), “Financial literacy: does it improve well-being? A case study of farmers in Khon Kaen, Thailand”, Environmental, Social, and Governance Perspectives on Economic Development in Asia, International Symposia in Economic Theory and Econometrics), pp. 117-129, doi: 10.1108/S1571-03862021000029A022.
Tseng, A.H. and Hsia, J.W. (2008), “The impact of internal locus of control on perceived usefulness and perceived ease of use in e-learning: an extension of the technology acceptance model”, Proceedings of the 2008 International Conference on Cyberworlds, CW 2008. doi: 10.1109/CW.2008.109.
Van Rooij, M., Lusardi, A. and Alessie, R. (2011), “Financial literacy and stock market participation”, Journal of Financial Economics, Vol. 101 No. 2, doi: 10.1016/j.jfineco.2011.03.006.
Verme, P. (2009), “Happiness, freedom and control”, Journal of Economic Behavior and Organization, Vol. 71 No. 2, doi: 10.1016/j.jebo.2009.04.008.
Xiao, J.J., Tang, C. and Shim, S. (2009), “Acting for happiness: financial behavior and life satisfaction of college students”, Social Indicators Research, Vol. 92 No. 1, doi: 10.1007/s11205-008-9288-6.
Yun, J.H.J., Zhao, X., Jung, K.H. and Yigitcanlar, T. (2020), “The culture for open innovation dynamics”, Sustainability, Vol. 12 No. 12, p. 5076, doi: 10.3390/su12125076.
Acknowledgements
The author would like to thank Pichchaporn Kalassukkawat, Ornipa Chanakarn, and Tanaporn Phurinan for helping distribute questionnaires and collect data.