Intention to Adopt Fintech Services among Entrepreneurs and Student of Entrepreneurship in Kuala Lumpur
Zaiton Osman1*, Phang Ing1, Izyanti Awg Razli1, Wong Fu Rick1
1 Faculty of Business, Economics and Accountancy, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia
*Corresponding Author: [email protected]
Accepted: 15 December 2020 | Published: 28 December 2020
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Abstract: Fintech is inevitable as the dynamic change in technology is continuously progressing. The pandemic of Covid-19 has forced entrepreneurs to change their norm of conducting business by inculcating fintech product and services as part of their business operation. This study investigates the intention to adopt fintech services among entrepreneurs and students of entrepreneurship in Kuala Lumpur. 213 data were collected from the respondent in Kuala Lumpur via purposive sampling and the data were analyse using SmartPls version 3.3.2. The findings showed that security concern, perceived enjoyment, government support have significant positive influence on the intention to adopt fintech services among entrepreneurs and students of entrepreneurship in Kuala Lumpur. The findings however showed that age does not play any moderation role in enhancing the relationship between security concern, perceived enjoyment, and government support towards the intention to adopt fintech services.
Keywords: Intention to Adopt, Fintech Services, Entrepreneurs, Entrepreneurship Students ___________________________________________________________________________
This work was supported by the Skim Penyelidikan Bidang Keutamaan, Universiti Malaysia Sabah [SBK0398-2018]
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1. Introduction
Digital technologies have replaced traditional technologies with higher effectiveness and efficiency level that provides incredible results for many business transaction and personal purposes. Financial technology (fintech) is a kind of digital technology integrating various forms of technology including blockchain, robo-advisors, crowdfunding, big data, peer-to-peer (P2P) lending and intelligent investment consulting in financial sector.
Past researchers have defined fintech as the improved technology-based products and services that provide new financial solutions, which are faster, cheaper, easier, and more accessible.
(Abu Amuna, Abu-Naser, Al Shobaki, and Abu Mostafa, 2019). Another study defined fintech as the use of new technology and innovation to compete in the marketplace of financial institutions and intermediaries – is the result of fast funding and online applications which has lowered costs for their clients (Fenwick, McCahery, and Vermeulen, 2017). Subsequently, Financial Stability Board defined it as technologically enabled financial innovation that could result in new business models, applications, processes, or products with an associated material effect on financial markets and institutions and the provision of financial services. Another similar definition by Gomber, Koch, and Siering (2017) defined fintech as internet-based
technologies such as cloud computing or mobile Internet with established business activities of the banking industry. In a nutshell, this study defined fintech is digitalised and technology- enabled financial product and services that is offered by financial institution worldwide in an effort to reduce cost, increased efficiency and wider accessibility.
Entrepreneur characteristics include a set of knowledge, skills, abilities and behaviors that a person must possess until he becomes an entrepreneur. Some of these traits are inherited and some are acquired by learning and training. Empirical evidence showed that entrepreneurs in general are innovative, risk-takers who work long hours, have high self-confidence, possessed excellent managerial and communication skills, and adapt to changes in technology (El Talla, Abu Naser, Abu Amuna, & Al Shobaki, 2017). Having excellent attributes enable an entrepreneur to be successful and a bright future for fintech in Malaysia is a push factor for a better growth in its industry. Opportunity to excel in fintech industry for entrepreneur are wider as people are moving away from retail outlets into online, mobile, or social media banking (Schinckus, 2019). A report by Price Waterhouse Coopers (PWC) in 2016 stated that in 2015 and the first half of 2016, about 11% (US$345 billion) of total venture capital funding in Southeast Asia went to fintech. With Southeast Asia growing economies and have a relatively large unbanked population, this is undoubtedly an attractive market for the new business entrant. The similar report also stated that 42% of Malaysian financial institutions think that their customers are ready to embrace Fintech (PWC, 2016). Subsequently, a 2017 World Bank report projected that Malaysia would have a strong continuous growth (12.5%) in the fintech industry until 2023. Financial institutions have been the first to embrace this, with 66 per cent of Malaysian banks aiming to transform their approach to becoming more digital-focused by 2020 (Schinckus, 2019). As of April 2019, there were close to 200 start-ups in Malaysia in a range of fintech areas, including payments, lending, and blockchain (IMF, 2020). Collaboration between bank and financial technology companies are able to improve financial services to entrepreneurs where application program interface (APIs) technology is able to transmit information at a more convenience pace between entrepreneurs and bank or financial institutions with seamless communications. In the same instance, the technology also conduces in expanding number and breadth of products and services offered by bank or financial institutions. This effort will not only enhance the user’s experience but also improve the effectiveness and efficiency of banks and financial institutions.
In addition, Malaysia has over 1 million SMEs with 98% of total businesses and the major obstacles faced by these SMEs are lack of business connections, limited awareness on business and financial tools, access to funding, education and lack of internet presence in a world of fully digital (Hussin, 2020). PWC (2016) also reported that large numbers of financial institutions concerned about the threat fintech poses to businesses including regulatory uncertainty and information security. Governments should encourage a culture of entrepreneurship by supporting business initiatives, business incubators and business accelerators. Government organisations may enhance or hinder the success of entrepreneurship by determining the level of risk to them. On the other hand, leadership behavior is influenced by the laws and procedures of the country. To achieve success, entrepreneurship requires a supportive ecosystem of interrelated factors ranging from infrastructure to access to financial services. Decision-making institutions play a very important role in the entrepreneurial ecosystem (Al Shobaki, Abu Naser, Abu Amuna, & El Talla, 2018; El Talla, Abu Naser, Abu Amuna, & Al Shobaki, 2017).
The millennials entrepreneurs are usually more techno-savvy as compared to any other age cohort. However, the millennials are financial less capable in engaging with fintech as
compared with the other age cohort. The millennials are often overlooked but as time goes by, they will become the target market of the banks due to improved financial capacity overtime.
Technologies are expected to continue progress and embed and integrate into our daily life, thus the demand of millennials towards better experience is getting stronger. Hence, it is crucial to examine the intention to adopt fintech services by the different age cohort of entrepreneurs as it will be able to help banks to meet the different needs of SMEs in the future.
Innovations of fintech services had impacted people’s daily life such as mobile payment and e-wallets, insurance, cryptocurrencies, and other personal finance applications which leads to effortless and scalable financial transactions. There were a lot of studies has been carried out throughout the years where the researchers focus on the specific fintech services such as cryptocurrencies and e-wallet and rarely conduct in-depth research on empirical extension in Technology Acceptance Model (TAM) framework in Fintech from demand side. (Hu, Ding, Li, Chen and Yang, 2019). By conducting in-depth research on the intention to adopt Fintech services by entrepreneurs and students of entrepreneurship through TAM thereby expanding the applicability of traditional TAM models. The results are expected to be able to provides valuable data and information for banks and financial institutions to revise their business strategies and goals to improve quality of services and increased efficiency.
Although penetration level of fintech services is on an increasing growth, there is some evidence among the consumer with lack of fintech knowledge that makes it difficult to instil confidence in adopting fintech services (Aziza, 2019). Elderly bank users might face difficulties to adopt fintech services and lack of self-confidence and motivation to understand its mechanism developed frustration among the people especially the old ones (Wang, Bolling, Mao, Reichstadt, Jeste, Kim, & Nebeker,2019). Subsequently, security concern seems to be the central issue in not adopting to fintech services. The main adoption barriers are risk issues such as financial (e.g., loss of financial outcome and extra fee), regulation (e.g., legal uncertainty for adoption), security and privacy (e.g., vulnerability of security technologies), and operational (e.g., inadequate processes or systems of Fintech companies) concerns (Ryu, 2018). Another security concern surrounding the adoption of fintech services is cybercrime.
Uncontrollable cybercrime might lead to financial disruption in financial industry. According to the research of Dupont (2019) cybercriminals had infiltrate to financial institutions’ system and steal valuable information in addition launched the attacks to the digital assets of financial institutions because of the motivation from financial gains. In the study of Mee and Schuermann (2018), it stated that the cyberattacks will have direct impacts to banks or financial institutions especially on the confidence of customer towards banks and financial institutions security level. As SMEs’ confident slowly deteriorating, panic and confuse, they start to withdraw and stop using the services and eventually the bank will start losing its customers and hence, affecting the banks operations and profitability. Meanwhile, risk of technology failure will also affect customer’s intention to adopt fintech services. The transformation from traditional financial services to digitise financial services forces heavy reliance on technology infrastructure with less personal interaction. Interaction is crucial factor in determining a variety of affective and behavioural outcomes such as satisfaction, attitude, decision making and involvement (Coyle & Thorson, 2001; Fortin & Dholakia, 2005; Stewart & Pavlou, 2002).
Hence, lack of online communication could be the crucial factor that hinders bank users in adopting fintech services. Additional challenges to fintech growth in Malaysia, for both financial institutions and new fintech businesses, include a shortage of talent in key tech areas like data analytics and machine learning, regulatory burdens, and access to funding (Shoffman, 2020). Bank user will have less confidence towards fintech sector due to the unfairness by government to fintech services that fintech founders unable to access the financial support by
government such as government-backed investment funds which will lead to financial crisis (Makoni, 2020). In response to the above challenges, this study would like to investigate the intention to adopt fintech services among bank users’ in Kuala Lumpur. Specifically, this study examines the influence of users’ security concern (SC), perceived enjoyment (PE) and government support (GS) towards intention to adopt fintech in Kuala Lumpur.
2. Literature Review
Definition of Fintech And Technological Acceptance Model (TAM)
According to Buckley, Arner, & Barberis (2016), they indicated that the financial technology (fintech) is technology-driven financial solutions where fintech is not only focus to specific sectors or business models such as financing sector and peer-to-peer (P2P) lending, but also focus on the entire scope of products and services that provides from the financial services industry. Furthermore, fintech defined as a type of financial innovation from the act of creating and later universalised new financial instruments and new financial technologies, institutions and market that consist of institutional, product and process of innovation (Hussain, 2015;
Varga, 2017). Financial technology as a service sector that adopt the mobile-centred IT technology to improve the efficiency of financial system (Kim, Park & Choi, 2016). According to McAuley (2015), he indicated that fintech refers to an economic industry which composed of companies that adopt the technology to improve the efficiency of financial systems.
Technology Acceptance Model (TAM) is developed by Davis (1989) which able widely adopt in different fields. For instance, sociology, marketing, agriculture, education, and information technology sector. According to Venkatesh & Bala (2008), the researchers stated that in information system and technology adoption, TAM is a highly predictive model.
Intention towards the adoption of Fintech
Intention towards the adoption of fintech refers to the readiness or willingness of an individual to use the financial technology services. In the study of Chong, Choo, Yip, Chan, Teh and Ng (2019), Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) was used to examine the adoption intention of the changes in technology in daily transactions in Malaysia and the findings indicate that there are positive influence on the intention towards the adoption of fintech services. In the study of Wen (2016), the researcher adopts six independent variables to investigate the rate of adoption of fintech services in Finland. Meanwhile, Hu et al. (2019), adopted user innovativeness, brand image, perceived ease of use, government support and perceived risk with improved Technology Acceptance Model (TAM) to examine the intention towards the adoption of fintech services and result reveal that perceived risk and perceived ease of use do not have significant impact on the intention of user to adopt fintech services. Furthermore, a study by Abrahão, Moriguchi and Andrade (2016) investigate the adoption behavioural intention of Brazilian towards new technology and found a significant relationship between behavioural intention and intention to adopt new technology.
Security Concern
Security concern refers to the ability and willingness to keep monetary information confidential during the transmission and storage to prevent security breaches (Taherdoost, 2017). Consumer and SMEs main concern on security issue is on the technology providers protection policy in the case of loss of private monetary information (Taherdoost, 2018). Study done by Ogbanufe and Kim (2018), found that cybercrime as the obstacle to fintech services where people feel insecure of the security threat and confidentiality of personal data as the fundamentals in settling and processing financial transactions. Furthermore, according to Singh (2014),
unbanked transactions (online/mobile banking) would be electronic only if there were sufficient security and convenience. Negative perception generated via the event of loss of personal confidential information has impeded the intention of adoption of technologies including fintech services (Ogbanufe and Kim, 2018). Similar result was supported by Laforet and Li (2005) that revealed security is important to Chinese respondents as compared to ease of use and convenience of mobile banking. In addition, a positive relationship between security concern and intention to adopt Fintech was found by Chong et al. (2019). The importance of trustworthiness of new technologies in order to secure personal data of users is of utmost priority among consumers (Zhou, 2013). However, there were some studies argued that security concern is not the important in determining the adoption of fintech services. Chau and Ngai (2010) shown that attitude of young people aged 16 to 29 towards mobile banking were determined by their experiences and not security concern. They had more positive behavioural intentions towards adoption of internet banking system. Hence, the study proposed the hypothesis below:
H1: There is a significant positive relationship between security concern and intention to adopt fintech services.
Perceived Enjoyment
According to Chuang, Chun and Hsiao (2016), perceived enjoyment is an intrinsic gain from the experience of new information technology where psychologically satisfied, by which increase interest to adopt fintech services. Besides, from the study of Chen, Chen, Yeh and Tsaur (2016), perceived enjoyment is one of the important influence factors towards the adoption of fintech services in Taiwan due to the consumer willing to experience from trying a new technology, feeling joyful and cheerful while the new information technology perceived to be enjoyable and useful. Subsequently, perceived enjoyment has a positive influence on the intention to adopt Plastc Card, a new payment solution where consumer able to enjoy the intelligent of new payment solution with great feelings such as happy, pleasant and satisfy (Wen, 2016). Furthermore, in the study of Boonsiritomachai and Pitchayadejanant (2017) in Thailand, the intention of user to adopt mobile banking services among generation Y is influenced by perceived enjoyment towards mobile banking services due to its motivation and increased number of individuals who preferred and enjoyed using the mobile banking services that brings joyful and pleasant experience. According to Pousttchi and Dehnert (2018), that there is a significant influence of perceived enjoyment on the fintech services among the consumer from Germany, United States of America (USA) and United Kingdom (UK) due to the digitalisation of retail banking which embed joy, fun and user friendly. Hence, the study proposed the hypothesis below:
H2: There is a significant positive relationship between perceived enjoyment and intention to adopt fintech services.
Government Support
One of the biggest drivers of Fintech adoption among users is government support. Due to the good reputation and sufficient funds that government own, it can help to promote and encourage financial institutions to develop and produce Fintech products or services that are highly reliable and credible. Hu et al. (2019) found that government support had positive impact on users’ attitude toward the adoption of Fintech services. The government support can be in terms of investment in communication network construction and secured networking which indirectly will draw consumers in accepting Fintech products and services (Hu et al., 2019). For instance, government’s intention to provide appropriate technological infrastructure is the key driver for internet banking (Jaruwachirathanakul & Fink, 2005). In the research done by Marakarkandy, Yajnik & Dasgupta (2017), found that government support had a positive
effect on trust of online banking products. According to Guild (2017), fintech has the potential to expand financial services to hundreds of millions of people who are currently unable to access them if fintech development is in tandem with complementary government policies and regulations. Hence, the study proposed the hypothesis below:
H3: There is a significant positive relationship between government support and intention to adopt fintech services.
Age Group and Intention to Adopt Fintech Services
In the previous studies of intention to adopt and early adoption of fintech services, demographic variables such as age group and gender is used as control (Gulamhuseinwala, Bull and Lewis, 2015; Morgan and Trinh, 2 020). The study of the adoption of fintech services by household in German, there is a lower probability of switching to fintech for older respondents and this confirms the common perception that younger people have a greater affinity for digital innovations (Jüngera and Mietzner, 2020). Meanwhile, Choudrie and Vyas (2014) and Choudrie, Junior, McKenna, and Richter (2018) find similar results for the adoption of mobile banking services by older adults in the UK. They report that the likelihood of using mobile technology by older generations is rather low but increases with continuous access to mobile devices, internet connection, the support of their family and friends, and privacy. In the study published by EY Global Financial Services Institute in 2015, the use of FinTech skews toward younger, higher-income groups. This study reported that in every four respondents aged 25 to 34 has used at least two FinTech products in the last six months. In comparison, for each cohort above age 44, the proportion of FinTech users is below the average of all users. As for non- user, the younger group are far more likely than older group to try fintech product in the future (Gulamhuseinwala, Bull and Lewis, 2015). Subsequently, in another study conducted to analyse the fintech and financial literacy in Vietnam found that the proportion of younger people (i.e., those aged less than 30 years old) using fintech services is much higher than that among older people, and the differences are rather large, especially between those aged less than 30 years old and those more than 60 years old (Morgan and Trinh, 2020). Hence, this study proposed as a moderating variable and the hypothesis below:
H4: Age group moderates the relationship between security concern, perceived enjoyment, and government support towards intention to adopt fintech services.
Findings and Discussion
Data for the study is collected via online survey and are distributed through WhatsApp group and social media platform such as Facebook and Instagram. The sample are purposively selected among entrepreneurs and students of entrepreneurship in Kuala Lumpur. The data is collected for a period of 9 weeks from 8th July 2020 until 15th September 2020 and the usable data is analysed using SmartPLS version 3.
The descriptive analysis as tabulated in table 1 below shows that out of 213 respondents, 77 (36.2%) are males 136 (63.8%) females. In the age cohort segment, there is only 2 cohort of age in this study ie., baby boomer and Generation X which comprises of 31 (14.6%) respondents are baby boomer which aged between 56 to 76 years old and 182 (85.4%) respondents are Gen X which aged between 41 to 55 years old. Subsequently, 177 (83.1%) respondents are entrepreneurs and only 36 (16.9%) respondents are student of entrepreneurs.
Among the 213 respondents, 128 (60.1%) respondents are bachelor holder, 35 (16.4%) respondents are diploma holder, 4 (1.9%) respondents are master’s degree holder or higher degree. Besides, there are 132 (62%) respondents earned less than RM 2000, 55 (25.8%) respondents earned monthly income between RM 2000 to RM 6000, 16 (7.5%) respondents
earned RM 6000 to RM 10000, and 10 (4.7%) respondents earned income more than RM10000 monthly.
Table 1: Descriptive Analysis
Variables Categories Frequency Percentage (%)
Gender Male 77 36.2
Female 136 63.8
Age Baby Boomers (between 56 -76
years old) 31 14.6
Gen X (between 41 - 55 years old) 182 85.4 Employment
Status
Student 36 16.9
Self Employed 177 83.1
Education Status
SPM/STPM 46 21.6
Diploma 35 16.4
Bachelor 128 60.1
Master or more 4 1.9
Monthly Income
Less than RM2000 132 62
RM2000 - RM6000 55 25.8
RM6001 - RM10000 16 7.5
More than RM10000 10 4.7
Construct validity
Construct validity testifies to how well the results obtained from the use of the measure fit the theories around which the test is designed (Sekaran and Bougie, 2010) and can be assessed through convergent and discriminant validity. The proposed significant cut-off value for loadings is at 0.5 (Hair, Black, Babin and Anderson, 2010). As such, if any items which have a loading of higher than 0.5 on two or more factors then they will be deemed to be having significant cross loadings. From Table 2, it can observe that all the items measuring a particular construct have loading higher than 0.5 on its constructs confirming construct validity.
Table 2: Construct Validity Intention to Adopt
Fintech Age Government
Support
Perceived Enjoyment
Security Concern
AI1 0.701
AI2 0.669
AI3 0.704
AI4 0.680
AI5 0.768
AI6 0.747
AI7 0.729
Age 1
GS1 0.805
GS2 0.790
GS3 0.876
PE1 0.840
PE2 0.808
PE3 0.841
SC1 0.672
SC2 0.617
SC3 0.787
SC6 0.611
Convergent validity
The convergent validity tested the degree to which multiple items to measure the same concept are in agreement. As suggested by Hair et al. (2010) factor loadings, composite reliability, and average variance are extracted to assess convergence validity. The loadings for all items should exceed the recommended value of 0.5 (Hair et al. 2010). Composite reliability values (see Table 3), which depict the degree to which the construct indicators indicate the latent, construct ranged from 0.848 to 1.000 which exceeded the recommended value of 0.7 (Hair et al. 2010).
The average variance extracted (AVE) measures the variance captured by the indicators relative to measurement error, and it should be greater than 0.50 to justify using a construct (Barclay, Higgins and Thompson, 1995). The average variance extracted, were in the range of 0.500 and 1.000.
Table 3: Measurement Model Assessment
Model Constructs Measurement Items Loadings Composite Reliability (CR)a
Average Variance Extracted
(AVE)b
Intention to Adopt Fintech Services
AI1 0.701
0.879 0.5110
AI2 0.669
AI3 0.704
AI4 0.680
AI5 0.768
AI6 0.747
AI7 0.729
Age Age 1 1 1
Government Support
GS1 0.805
0.864 0.680
GS2 0.790
GS3 0.876
Perceived Enjoyment
PE1 0.840
0.869 0.688
PE2 0.808
PE3 0.841
Security Concern
SC1 0.672
0.768 0.500
SC2 0.617
SC3 0.787
SC6 0.611
Criteria: Composite Reliability >0.708 (Hair et al., 2017), (Hair et al., 2017) AVE> 0.5 (Hair et al., 2017), (Hair et al., 2017).
Discriminant validity
The discriminant validity of the measures (the degree to which items differentiate among constructs or measure distinct concepts) was assessed by examining the correlations between
the measures of potentially overlapping constructs. Items should load more strongly on their constructs in the model, and the average variance shared between each construct and its measures should be greater than the variance shared between the construct and other constructs (Compeau, Higgins and Huff, 1999). From table 4 below, the squared correlations for each construct are less than the average variance extracted by the indicators measuring that construct indicating adequate discriminant validity. In total, the measurement model demonstrated adequate convergent validity and discriminant validity.
Table 4: Fornell-Larcker Criterion
Age Government
Support
Intention to Adopt Fintech
Perceived Enjoyment
Security Concern
Age 1.000
Government Support 0.129 0.825 Intention to Adopt
Fintech 0.175 0.507 0.715
Perceived Enjoyment 0.045 0.620 0.494 0.830
Security Concern -0.012 0.566 0.552 0.652 0.675
Diagonals (in bold) represent the average variance extracted while the other entries represent the squared correlations
Another assessment of discriminant validity used in this study is Heterotrait-monotrait (HTMT) test. Table 5 below shows the HTMT output and as suggested by Gold, Malhotra and Segars, (2001) and Henseler, Ringle and Sarstedt, (2015), the value of HTMT for each construct in this research is lower than 0.9. Thus, all the construct in this research do not have discriminant validity problem. Overall, the reliability and validity tests conducted on the measurement model are satisfactory. All reliability and validity tests are confirmed, and this is an indicator that the measurement model for this study is valid and appropriate to be used to estimate parameters in the structural model.
Table 5: Heterotrait-monotrait (HTMT) Criterion
Age Government
Support
Intention to Adopt Fintech
Perceived Enjoyment
Security Concern
Age
Government Support 0.146
Intention to Adopt
Fintech 0.199 0.621
Perceived Enjoyment 0.104 0.811 0.596
Security Concern 0.040 0.826 0.750 0.873
Criteria: Discriminant validity is established at HTMT0.85 / HTMT0.90
Hypotheses testing
The path analysis is performed to test the hypotheses in this study. Figure 1 and Table 5 present the results. It shows that security concern has positive significant influence on intention to adopt fintech services (β=0.362). Similarly, perceived enjoyment (β=0.143), government support (β=0.188) and age (β=0.135) also have positive significant influence on intention to adopt fintech service. However, this study found that age does not moderate the relationship between security concern (β=-0.067), perceived enjoyment (β=-0.026) and government support (β=-0.057) towards intention to adopt fintech services.
Table 6: Results of Path Analysis Path Coefficient Standar
d Beta Standard
Error T-
Value P
Values Decision 𝑓² R² VIF Q²
Security Concern ->
Intention to Adopt 0.362 0.079 4.601 0.000 Supported 0.111
0.406 1.983
0.189 Perceived Enjoyment ->
Intention to Adopt 0.143 0.071 2.020 0.044 Supported 0.016 2.103
Government Support ->
Intention to Adopt 0.188 0.072 2.593 0.010 Supported 0.032 1.834
Age -> Intention to Adopt 0.135 0.050 2.710 0.007 Supported 0.029 1.056 Moderator 1: Security
concern -> Intention to
Adopt -0.067 0.066 1.007 0.315 Not
Supported 0.005 1.782
Moderator 2: Perceived enjoyment -> Intention to
Adopt -0.026 0.067 0.392 0.696 Not
Supported 0.001 1.903
Moderator 3: Government support -> Intention to
Adopt -0.057 0.101 0.568 0.570 Not
Supported 0.002 2.042
Lateral Collinearity: VIF 3.3 or higher (Diamantopoulos & Sigouw, 2006) R2 ≥ 0.26 consider Substantial (Cohen, 1989)
F2 ≥ 0.26 consider Substantial (Cohen, 1989) Q2 > 0.278 consider medium (Hair et al., 2017)
A 500 re-sample of bootstrapping procedure was run to generate the t-values to assess if the direct relationships are significant. T-values were used to determine the significance of the hypotheses in the study. Based on the above results in table 6 and figure 1 show that security concern (t-values=4.601 and p-values=0.000), perceived enjoyment (t-values=2.020 and p- values=0.044), government support (t-values=2.593 and p-values=0.010) and age (t- values=2.710 and p-values=0.007) have positive significant relationship on intention to adopt fintech services among respondents in Kuala Lumpur. However, this study found that age does not moderate the relationship between security concern (t-values=1.007 and p-values=0.315), perceived enjoyment (t-values=0.392 and p-values=0.696) and government support (t- values=0.568 and p-values=0.570) towards intention to adopt fintech services.
Variance inflation factor (VIF) statistic is used to determine if the formative indicators were too highly correlated. A traditional rule of thumb posits that multicollinearity is a concern if the VIF is higher than 10; however, for formative measures, scholars suggest that VIF values greater than 3.3 indicate high multicollinearity (Diamantopoulos and Siguaw, 2006). The finding shows that the maximum value of VIF in this study is 2.103 which is below the threshold of 3.30 and proved that there is no multicollinearity issue. R2 indicate the variance explained in each of the endogenous constructs. A R2 of 0.406 in this study indicates that intention to adopt fintech services is explained by 40.6% of security concern, perceived enjoyment, and government support. R2 in this study has a moderate predictive accuracy in explaining its endogenous constructs (Henseler, Ringle and Sinkovics, 2009; Hair, Ringle and Sarstedt, 2011). In addition to evaluating the R2 values of all endogenous constructs, the change in the R2 value when a specific predictor construct is omitted from the model can be used to evaluate whether the omitted construct has a substantive impact on the endogenous constructs.
The findings show that omission of all independent variables (ƒ2 values - excluding perceived enjoyment) has small effect on intention to adopt fintech services (Cohen, 1988). However, this study also found that the omission of perceived enjoyment (ƒ2 value equal to 0.016) has no effect to intention to adopt fintech services. Another means to assess the model’s predictive accuracy is the Q2 value (Geisser, 1974; Stone, 1974). Cross validated redundancy explores
the predictive relevance of the PLS path model (Wold, 1982). The finding shows a Q2 value of 0.189 which indicated a medium predictive relevance of the endogenous constructs.
Figure 1: Results of Path Analysis
3. Discussion and Conclusion
The objective of this study is to investigate the influence of security concern, perceived enjoyment, and government support towards intention to adopt fintech services. In addition, this study would also like to examine whether age group moderates the relationship between security concern, perceived enjoyment, government support and intention to adopt fintech services. The finding shows that security concern, perceived enjoyment, government support and age confirmed to have a significant influence on the intention to adopt fintech services in Kuala Lumpur. The result of positive significant relationship between security concern and intention to adopt fintech services is supported by the previous studies as the consumers believed that with a solid security in place, cybercrime (Ogbanufe and Kim, 2018) such as personal data breaching, loss of personal information (Ogbanufe and Kim, 2018) and identity theft will not be able to penetrate the banking system and this will provide a sense of confidence and safety (Laforet and Li, 2005; Singh, 2014). This also showed that customers who had the intention to adopt fintech services will only act on their intention if they find that the security installed is secured and trustworthy (Chong et al., 2019; Zhou, 2013). Banks and other financial institution should make huge investment in the online security with various measures.
Perceived enjoyment showed to have a significant positive relationship with the intention to adopt fintech services by entrepreneurs and students of entrepreneurship. The respondents in this study fall in the age cohort of baby boomers and Generation X, which are widely known as hard-working and opportunist generation (Wiley, 2020) which is few of the many positive traits of entrepreneurs, hence the advancement of technology has forced them to learn and quickly adapt to the changes. As the entrepreneurs willing to try new technology, feeling joyful and perceived the new technology as enjoyable and useful, they have a higher intention to adopt new technology (Chen, Chen, Yeh and Tsaur, 2016). This is supported by Chuang, Chun and
Hsiao (2016), perceived enjoyment is an intrinsic gain from the experience of new information technology where psychologically satisfied, by which increase interest to adopt fintech services. As an example, a study by Wen (2016) found that customer is more willing to adopt the intelligent new payment solution of Plastc Card if the new fintech product provide great feelings such as happiness, pleasant and satisfaction. Entrepreneurs would be more than willing to invest and subscribe to such product of fintech if the product will indirectly increase its customers’ pool. According to Pousttchi and Dehnert (2018), that there is a significant influence of perceived enjoyment on the fintech services among the consumer from Germany, United States of America (USA) and United Kingdom (UK) due to the digitalisation of retail banking which embed joy, fun and user friendly.
In this study, government support also shows a significant influence on the intention to adopt fintech services. This finding is in line with the work of Hu et al. (2019), they believe that government encouragement and promotion will drive the interest of individual entrepreneurs to adopt and move towards fintech services (Marakarkandy, Yajnik & Dasgupta, 2017). At the same instance, the initiatives rendered by government in terms of IT infrastructure and facilities (Jaruwachirathanakul & Fink, 2005) will also enhance the development of fintech at the national level and indirectly will encourage banks to establish rock-solid ground for fintech services. These efforts will later persuade existing bank users including individual entrepreneurs to adopt and shift to fintech services. With the improved IT infrastructure and facilities, banks and financial institution can broaden their flagship to promote fintech services to even far-reaching clients and not only to those central in the city (Guild, 2017). In addition, with the prudent rules and policy on fintech service, the government is able to monitor fintech transactions and activities, hence provide greater security for bank users. Banks and financial institutions able to collaborate with government to enhance and strengthen their services in the perspective of use, security, speed, user’s innovativess and convenience in order to fullfil the needs and wants of individual entrepreneurs to increase the adoption intention of entrepreneurs and student of entreprenuership towards fintech services.
Despite the significant positive relationship between age and intention to adopt fintech services, this study found that age group does not moderate the relationship between security concern, perceived enjoyment, government support and intention to adopt fintech services. Even though younger age is more technology savvy and they are have greater attraction with technology (Jüngera and Mietzner, 2020; Choudrie and Vyas, 2014; Choudrie, Junior, McKenna, and Richter, 2018; Morgan and Trinh, 2020), this result show no moderation role played by age group. This result confirmed with the previous study that age has a direct influence towards intention to adopt fintech services among entrepreneurs and students of entrepreneurship in Kuala Lumpur. This study would also like to suggest multiple dimensions of study to be carried out in the future in order to have a comprehensive, concentrate and accurate result of the interaction between the adoption intention of bank users towards fintech services and the variables.
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