Components Affecting Intention to Use Digital Banking Among Generation Y and Z: An Empirical Study from the Philippines

Abstract

Amid the Covid pandemic surge last year, customers and businesses started embracing digital transactions. Digital banking, as an answer to the cash-less-contact-less way of doing financial transactions, was highly convenient during the pandemic, especially in the Philippines. This position examines the Gen Y and Gen Z in the Philippine case and its willingness to encourage digitalization of the financial sector. This study aimed at evaluating the intention to use digital banking services using the factors (1) ease of use; (2) perceived usefulness; (3) perceived risk; (4) trust; (5) convenience. A total of 226 respondents were selected by random sampling method and linear regression was used to analyse the collected data. Analysis of the results show that the components (1) perceived ease of use; (2) perceived usefulness; (3) perceived risk; (4) trust; (5) convenience had a significant effect on intention to use digital banking while the demographics - gender, age, monthly income, and educational attainment do not have any significance on the intention to use digital banking. The relevance of the study can be used for marketing and financial strategies to increase the intention to use digital banking and to contribute to the enhancement of technology acceptance concerning digital banking.

1. Introduction

With the advances in technology and the digitalization of business processes in the financial services industry, physical and virtual environments are rapidly converging (Jünger & Mietzner, 2020). There are innumerable instances of technology creating and breaking lives and businesses – one of these is in the banking business (Sardana & Singhania, 2018). The banking sector digitalization is inextricably linked with the development of the Internet and IT technologies (Votintseva et al., 2019). The intrusion of digital technology into the sphere of banking has brought about a paradigm shift in banking – creating what is now referred to as Digital Banking (Sardana & Singhania, 2018). All traditional banking operations and financial services are being transitioned into a digital environment through digital banking (Nguyen, 2020). According to Ananda et al. (2020), “digital banking is the process of digitization of all banking activities that were available only inside a bank branch to its customers”. Consumers can either inquire about account balance, transfer money, pay bills, order checks, load accounts, invest or maintain their accounts all at the same time using the same digital interface (Mendoza et al., 2020). It provides faster, easier and more efficient services to the customers that lead to customer satisfaction (Ananda et al., 2020).

In Asia, internet users continue to increase from 764.4 million in 2009 to 2.7 billion as of June 2021 (Internet World Stats, n.d.). This significant increase has been linked to affordable smartphones and mobile data plans (Digital in 2018, n.d., De Leon, 2019). Banks used this data and shifted to Digital Banking. In the UK banks had reduced branch numbers and strengthened their Digital Banking strategy (Mbama & Ezepue, 2017).

In the Philippines, banks started to engage in electronic banking as early as 2000 following the trend of financial technology “fintech” integration (Mendoza et al., 2020). The government, through its financial regulating body, Bangko Sentral ng Pilipinas (BSP), accepted this innovation as part of the financial inclusion, thereafter drafting guidelines for the provision of electronic banking services amongst banks (BSP Circular No. 240, 2000). It was reported that though there is a significant internet usage and awareness of online payment methods amongst Filipinos, 46% of those with accounts and using the internet remains indecisive about electronic transactions due to various behavioural components such as cost, convenience, security, and reliability of service (Mendoza et al., 2020). According to De Leon (2019), digital banking advancement, in the Philippines, has been slow and only 28% use digital banking. However, during the pandemic, consumers were forced to use digital banking (Agur et al, 2020). Mbama and Ezepu (2017) mentioned that “bank’s marketing and financial management models are changing” which makes the banks hardly understand its customers. It has now become a focal and collective concern amongst the banking institutions to entice more customers to use internet banking and strengthen the customer-provider relationship (Mendoza et al., 2020).

This study will further investigate the components affecting the intention to use digital banking by Filipino customers. This study will provide insights for the banking industry on the most influential components to use digital banking and use it to their advantages and future improvements even in a global crisis in the industry.

2. Literature Review

Digital Banking—a new concept in electronic banking, aims to enrich standard online and mobile banking services by integrating digital technologies, for example, strategic analytics tools, social media interactions, innovative payment solutions, mobile technology, and a focus on user experience (Balasubramanian, 2018). Digital Banking is seen as an evolution from what was previously referred to as e-banking or online banking, with more focus on customer experience (Megargel et al., 2018). According to Ananda et al (2020), digital banking will drive future banking transactions due to the digitalization and e-governance initiative of the banks and the government. Many studies have been conducted about the intention to use digital banking platforms, however, in the case of the Philippines, researchers may improve the limitations in the studies till now by increasing the sample size, administering the research using different survey methods and sampling techniques (De Leon, 2019).

2.1. Perceived Usefulness

The perceived usefulness was revered to have a substantial influence on behavioural intention to use mobile banking (Wibella et al., 2018). Perceived usefulness is among the key factors in the adoption of innovative technology as it increases customer satisfaction and loyalty. In the study of Nguyen (2020), perceived usefulness had favourable effects on intention to use the service. Ananda et al. (2020) & Wen Ni (2020) revealed that perceived usefulness is the single most significant decisive factor in the adoption of digital banking. Whereas in the study of Mufarih et al. (2020), perceived usefulness does not have a significant effect on attitude toward using or intention to use digital banking.

H1: Perceived usefulness has a substantial impact on intention to use digital banking.

2.2. Perceived Ease of Use

In the study of Ananda et al. (2020) perceived ease of use and other variables do not have a significant impact on the adoption of digital banking services. However, according to Nguyen (2020) perceived ease of use affects customers’ views and attitudes towards the service. While Wibella et al. (2018) & Wen Ni (2020) revealed that there is a positive relationship between perceived ease of use with intention of adopting digital banking services.

H2: Perceived ease of use has a substantial impact on intention to use digital banking.

2.3. Perceived Risk

Perceived risk had a significant component of intention to use in terms of internet banking adoption (Chauhan et al., 2019). It was reported to have a significant negative influence on consumers’ intentions to use innovative technology. A high level of perceived risks often leads to a negative attitude towards the service, which means that poor perceptions of the information or transaction security when using digital banking services will make customers to have a bad attitude towards the service (Nguyen, 2020).

H3: Risk has a substantial impact on intention to use digital banking.

2.4. Trust

As trust is one of the critical antecedent factors, banks must establish a safe financial environment for clients to use their services (De Leon, 2019). Trust may be based on real knowledge, opinions, or faith (Ramli et al., 2021). Customers who sense a high level of trust inclination are more likely to form trust and use mobile banking. Trust inclination positively influences behavioural intention to use mobile banking (De Leon, 2019). Sharma & Sharma, (2019) implied that a higher level of trust and better service quality in mobile banking will help in retaining old customers and attracting new and potential customers.

H4: Trust has a substantial impact on intention to use digital banking.

2.5. Convenience

Convenience is a combination of time and space utilities (Williams, 2021). Nguyen (2020) revealed that convenience does not affect the intention to use digital banking services. Williams (2021) found out that convenience has a minor negative influence on digital banking. Meanwhile, an increase in convenience helps increase customers’ intention to use (Nguyen, 2020).

H5: Convenience has a substantial impact on intention to use digital banking.

2.6. Demographic Profile

Onyia and Tagg (2011), revealed that demographic factors such as gender, level of education and employment status affect the intention to use internet banking. According to Gupta & Bansal (2011), gender affects the perception of using digital banking. De Leon (2019) pointed out that demographic factors such as age, gender, educational attainment, and monthly income work as managing variables in intention to use digital banking.

H6: Demographic Profile has a substantial impact on intention to use digital banking.

2.7. Research Framework

The Technological Acceptance Model is an adaptation of the Theory of Reasoned Action (TRA) to the field of IS. TAM posits that perceived usefulness and perceived ease of use determine an individual’s intention to use a system with the intention to use serving as a mediator of actual system use. Researchers have simplified TAM by removing the attitude construct found in TRA from the current specification (Venkatesh et. al., 2003) (Nguyen, 2020). Attempts to extend TAM have generally taken one of three approaches: by introducing factors from the related models, by introducing additional or alternative belief factors, and by examining antecedents and moderators of perceived usefulness and perceived ease of use (Nguyen, 2020). In a recent paper, Gefen and Larsen (2017) demonstrated that TAM’s construct relationships primarily emerge from semantic relationships between its questionnaire items. A Theory explaining their findings is described as the Semantic theory of survey response.

The operational framework in Figure 1 as obtainable above consists of independent variables and dependent variables. Independent variables are situated on the left corner which are perceived usefulness, perceived use, perceived risk, and trust, convenience, and demographic profile have a direct impact. These are the determinants that the user considers towards the intention to use digital banking for Gen Y and Z.

Figure 1: Operational Framework of the Study

3. Research Methodology

3.1. Research Method

The quantitative methodology allows for the discovery of respondents on the components affecting the intention to use digital banking by gathering perceptions of surveys in a state university in the Philippines – among College Business Administration Graduate Studies (CBAGS) students. Specifically, this research examined how a range of survey practices are influenced by the users.

3.2. Research Design

A descriptive – causal study is undertaken to be able to describe the characteristics of the variables. The researchers used an online survey, Google form, to gather data from the students to conduct hypothesis testing to explain the nature of each component affecting the relationship of the intention to use digital banking. To interpret the raw data, it was cleaned and transformed into an Excel file to be able to run the said data in the Jamovi application.

3.3. Sampling Design

A Probability sampling design was used in this study to ensure that the respondents in the population have a known and equal chance of being selected as respondents. Out of 545 students, 226 are the actual respondents with 95% confidence level and 5% of marginal error.

The demographic profile of the respondents showed that the percentage of female participants was higher than that of males with 124 counts with 54.90% while 102 counts with 45.10% of the total respondents. There were 192 of the respondents with the majority of them (84.96%) aged between 18–37 years, 30 of the respondents (13.30%) were aged between 38–53 years and only 4 respondents or 1.80% had an age of 54 and above. Since the population of the study was students of CBAGS, 161 of the respondent’s highest educational attainment was a bachelor’s degree (71.20% of the respondents) while 65 respondents or 28.80% are post-graduate studies. For the monthly income of the respondents, total of 18 respondents or 8.00% were earning Php10,000.00 and below, 164 respondents or 72.60% were earning monthly ranging from Php 10,001.00–Php50, 000.00, 36 respondents or 15.90% were earning monthly within ranges of Php50,001.00–Php100,000.00 and 8 respondents or 3.50% were earning above Php 101,000.00.

3.4. Research Instrument

An online survey questionnaire was done in this study which consisted of demographic factors and the constructs – perceived usefulness, perceived ease of use, perceived risk, trust in the service and convenience. The demographic profile consisted of age, gender, educational attainment, and monthly income, all derived from the study of De Leon (2019). All the items in the construct are to be measured by Likert 5-point scale in which: 1 – strongly disagree and 5 – strongly agree and was adopted from the article from Nguyen (2020).

3.5. Statistical Treatment of Data

Linear regression analysis was used to locate the degree of various variables. The technique for testing the relationship between two variables are correlation and linear regression. Correlation quantifies the strength of the linear relationship between a pair variable whereas in linear regression the relation is in the form of an equation, Kumari et al. (2018).

4. Results

The data passed all the assumption checks – the mean of intention to use digital banking had a favourable response for indicators INT1 (\(\bar{x}\) = 4.57) and INT3 (\(\bar{x}\) = 4.54) and neutral for indicator INT2 (\(\bar{x}\) = 4.29). For further analysis, a test of normality across individual indicators was employed. Data gathered revealed negative skewness for the individual indicators INT1= -1.80, INT2 = -0.900, INT3 = -1.49 with general skewness of -1.46. Values are less than or within the range of +1 and -1 which is the normal value. Kurtosis of the indicators valued at INT1 = 4.29, INT2 = 0.212, INT3 = 2.24 with 3.08 general kurtosis, which are less than and within the normal range of +3 and -3. The results show that the values indicate normal symmetry normality test since the p value is 0.016 which is less than the level of significance (0.05), the data above is normally distributed test for independence and shows that Durbin – Watson d = 1.97 is between the two critical values of 1.5 < d < 2.5, therefore there is no first order linear autocorrelation in the data, and test of linearity revealed the Perceived Usefulness has a tolerance of 0.453 (VIF = 2.21), Perceived Ease of Use has a tolerance of 0.454 (VIF = 2.20), Trust has tolerance of 0.484 (VIF = 2.07), Perceived Risk has a tolerance of 0.806 (VIF = 1.24), Convenience has a tolerance of 0.424 (VIF = 2.36), Gender has a tolerance of 0.944 (VIF = 1.06) Age has tolerance of 0.764 (VIF = 1.31) Educational Attainment has a tolerance of 0.969 (VIF = 1.03) and Monthly Income has tolerance 0.817 (VIF = 1.22). Since the tolerance of the independent variables is greater than 0.1 (or VIF < 10), it can be derived that the independent variables are correlated and the researcher continued to run the data using the regression analysis.

Table 1 shows the regression analysis of perceived usefulness has an impact on the intention to use digital banking of the respondents. It can be observed on the table that the PU1 usefulness in saving money has a p value of 0.003, PU2 usefulness in time saving has p value of < 0.001, the PU3 usefulness in access to services has p value of 0.011 and PU4 usefulness of digital banking has a p value of 0.002 which is less than the assigned level of significance. When looking at the construct, the adjusted R² can predict 43.1% of the variation in perceived usefulness with the impact on intention to use the digital banking and the level of significance has a result of < 0 .001 hence the researcher rejects the conjecture.

Table 1: Perceived Usefulness, Perceived Ease of Use and Perceived Risk to Intention to Use

*Level of Significance is < 0.05. *PU1: usefulness in saving money, PU2: usefulness in time saving, PU3: usefulness in access to services, PU4: usefulness of digital banking. *PEU1: ease of use on how to use, PEU2: ease of use on process, PEU3: ease of use on duration, PEU4: ease of use. *RIS1-risk in providing bank information, RIS2-risk in using digital banking, RIS3- risk in providing personal information, RIS4- risk in signing up online, RIS5: risk vs personally going to the bank.

With the p value of < 0.001 of the construct perceived usefulness with 43.1% predictable reliability, we can derive from the result that usefulness in saving money, in time saving, in access to service and overall usefulness of digital banking are significant components in the customer’s intention to use digital banking. This confirms the study of Ananda et al., (2020) and Nguyen, 2020) that usefulness had positive effects on intention to use the service. It is important to enhance the sense of the usefulness of users through media platforms so that customers may completely comprehend the benefits of using digital banking (Nguyen, 2020).

Perceived ease of use has an impact on the intention to use digital banking of the respondents. It can be observed that the PEU1 has a p-value 0.026 (β = 0.1370) and PU4 has a p-value of < 0.001 (β = 0.3120) which are within the significance level. While the PEU2 has p value of 0.149 (β = 0.0919) and the PEU3 has p value of 0.088 (β = 0.1140) which less than the assigned level of significance. Therefore, when looking at the construct, the adjusted R² can predict 43.8% of variation in perceived ease of use with the impact on intention to use the digital banking and the level of significance has a result of < 0 .001 hence the researcher rejects the conjecture.

With p value of < 0.001 conjecture for perceived ease of use is rejected. Results of the study also indicate that ease of use on how to use digital banking and general ease of use of digital banking is a significant factor on consumers’ intention to use digital banking. A study by Wen Ni (2020) states that perceived ease of use is among the two components that can enhance the branchless digital banking acceptance among Generation Y in Malaysia. Perceived ease of use has been identified as an important factor positively influencing the attitude of customers regarding technology-enabled banking services (Kaur et al., 2021). More specifically individual’s ability to use computers and technology positively influences the adoption of technology (Kaur et al., 2021). The result indicates that clients who believe that the applications which are easy to use are likely to be adopted in digital banking. (De Leon, 2019). Therefore, we conclude by the statements above that perceived usefulness is a significant component in intention to use digital banking.

Perceived risk has an impact on the intention to use digital banking of the respondents. It can observe on that the RIS1 has a p-value 0.002 and the RIS3 has p value of 0.001, which is less than the assigned level of significance. On the other hand, the RIS2 is insignificant (p-value 0.906 with β = 0.00561), RIS4 is insignificant (p-value = 0.638 with β = -0.03014) and RS5 with p value of 0.231 and β = -0.05670. Therefore, when looking at the construct, the adjusted R² can predict 19.1% of variation in Perceived risk with the impact on intention to use digital banking.

The risk in providing bank information and risk in providing personal information is a significant component on intention to use digital banking while risk in signing up online and personally going to bank negatively impact intention to use digital banking. This result confirms the claim of the study Nguyen (2020) that a high level of perceived risk often leads to a negative attitude towards the service, which means that poor perceptions of the information or transaction security when using digital banking services will make customers have a bad attitude towards the service. Perceived Risk was also found to be a significant predictor of intention to use in terms of internet banking adoption; it was reported to have a significant negative influence on consumers’ intentions to use innovative technology (Chauhan et al., 2019).

Table 2 shows the regression analysis of trust to intention to use digital banking. We can derive from the table that TRU1 with p value 0.005 (β = 0.1698) and TRU4 with p value of 0.007 (β = 0.1940) are significant, while TRU2 with p value 0.211 (β = 0.0872), TRU3 with p value 0.420 (β = 0.0543) are less than the significance level. Therefore, when looking at the construct, the adjusted R² can predict 27.8% of variation in Trust with the impact on intention to use digital banking and the level of significance has a result of < 0 .001, hence the researcher rejects the conjecture.

Table 2: Trust and Convenience to Intention to Use

*Level of Significance is < 0.05.

TRU1-trust in app, website, TRU2-trust in bank, TRU3-trust in service, TRU4-trust in perceived benefit. CON1: convenience due to internet connection, CON2: convenience to time, CON3: convenience of accessibility, CON4: convenience of service between providers.

The results of the study indicate that trust in us app website and trust in perceived benefit has a significant component in intention to use digital banking while trust in bank and trust in the service is not a deciding factor in intention to use digital banking. This confirms the result of the various studies of Kaur (2021) and Nguyen (2020). One of the major hurdles in adopting the innovative digital banking channel is the lack of customers’ trust (Kaur et al., 2021). Hence banks need to build the trust of customers by providing them personalized banking services by identifying the different segments of customers and offering them the right channel mix (Kaur et al., 2021).

Convenience has an impact on the intention to use digital banking of the respondents. It can be observed that CON1 with p value of 0.021, CON2 has a p-value < .001, the CON3 has p value of 0.005 and CON4 has a p-value of 0.011 which is less than the assigned level of significance. When looking at the construct the adjusted R² can predict 52.3% of variation in Convenience with the impact on intention to use digital banking and the level of significance has a result of < .001 hence the researcher rejects the conjecture. Results prove that convenience is a significant factor on intention to use digital banking. Convenience due to internet connection, due to convenience to time, due to accessibility and service between providers are common components and is significant in intention to use digital banking. This conforms with the study that states that online convenience is the key to providing effective online services (Jebarajakirthy & Shankar, 2021). In the study of Nguyen (2020), convenience does not imply the intention to use digital banking services. However, the result can be interpreted by the Kano theory which states that utility services using high technology like digital banking, convenience is considered a must structure (Nguyen, 2020).

Table 3 shows the regression analysis of Gender, Age, Educational Attainment, and monthly income has an impact on intention to use digital banking of the respondents. It can be observed that the Age 18–37 has a p-value 0.017, the Age 38–53 has p-value of < 0.001and ages 54 and above has p-value of 0.004 which is less than the assigned level of significance. On the other hand, Gender is insignificant (p-value 0.229 with β = 0.0952). Educational Attainment is insignificant (p-value = 0.283 with β = 0.0931). When looking at the construct the adjusted R² can predict 11.5% of variation in overall demography with the impact on intention to use the digital banking and the level of significance has a result of < 0 .001, hence the researcher rejects the conjecture.

Table 3: Demographic to Intention to Use

*Level of Significance is < 0.05.

Gender and educational attainment are not significant in the intention to use digital banking. This outcome may be because the educational attainment and higher education of the respondents are the same. In the study of De Leon(2019), there are various results on the components that influence the adoption of digital banking. As shown in Table 3, age 18–37 has a p-value 0.017, Age 38–53 has p value of < 0.001 and ages 54 and above has a p-value of 0.004 which is less than the assigned level of significance, therefore, there are significant differences in behavioural intention to use mobile banking due to age. The study shows that younger individuals are more inclined to use digital banking (De Leon, 2019). The findings of this study support the studies by Koksal (2016) and Sharma (2017). We can derive from the table that an income of Php 10,000 and below has lower behavioral intention than those receiving an income of Php 10,001–50,000 (Koksal, 2016). The income group with Php 100,001 and above has higher behavioural intention than the rest of the income groups (Koksal, 2016). The result on customers with higher monthly income having a higher behavioral intention to use digital banking is similar to the studies by (Koksal, 2016; De Leon, 2019).

5. Conclusion and Limitations

This study traverses the components affecting the intention to use digital banking. From the constructs of Perceived usefulness (PU), perceived ease of use (PEU), perceived risk (RIS), Trust (TRU) convenience (CON), the demographic data such as period of age, gender, educational and monthly income of the site was reliable to intention to use (INT) digital Banking. In conclusion, the usefulness in saving money, time saving, and usefulness in access to services and usefulness of digital banking, in general, are significant components of intention to use digital banking. The study’s findings also show that customer willingness to use digital banking is influenced by how easy it is to use digital banking and how easy it is to use digital banking in general. The danger of providing bank information and personal information has a substantial influence on the intention to use digital banking, whereas the risk of signing up online and going to the bank in person has a negative impact on the intention to use digital banking. The study’s findings also show that trust in the app’s website and faith in the claimed benefit of use in digital banking are important factors in selecting whether to use it, but trust in the bank and trust in the service are not the deciding components. The convenience of internet access, convenience of time, accessibility, and service between providers are all important factors in deciding whether to utilize digital banking. While age and monthly income are factors in using digital banking, gender and educational attainment do not significantly affect the intention to use the service. Hence that survey conducted on the period of the pandemic year 2021 that the deciding factor of the respondents even though the economy affects the global crisis (Jucá & Fishlow, 2021).

The result implies that respondents are willing to use the digital banking. This study can also be used for the betterment of financial services; especially digital banking and results can be used as a marketing strategy to encourage the use of digital banking. In this time of pandemic when going physically to the bank has been a struggle; use of digital banking is highly encouraged. The advancement of digital banking in these conditions is inevitable. Respondents can also benefit from this study. In choosing the components that influence the intention to use digital banking, they can easily compare services of different financial institutions on the best offered services.

This study is based on five components, future researchers may reconcile other variables on creating the intention to use in digital banking. Since the perceived risk in signing up online and risk in personally going to the bank has a negative effect on intention to use the service, the researchers recommend further studies in line with the perceived risks. The researchers also recommend conducting studies with respondents who are more diverse in terms of age and educational attainment.

Future research may explore and consider valuable variables in solidifying intention to use digital banking. This study examined the intention to use digital banking using various constructs using different theories in the Philippine settings. Testing in different settings and with highly diverse respondents is highly recommended.

The scope and limitation of the study was no way to override the development of the recurring technology in the market rather how the customer affects in using the digital banking as a platform of mediating transaction to banking protocols. Also, it will not affect the enhancement of the different banks’ platform of digital banking, rather it will make it convenient for the customers to use it for digital banking. This study had certain limitations like, its focus was limited to the rating of the components affecting the intention to use digital banking on their stressors namely role conflicts, and physical settings of the research at the Polytechnic University of the Philippines – College of Business Administration Graduate School Sta. Mesa Campus. The study used an online survey platform (Google Forms) which put restrictions on the time frame in answering the questionnaire and the opinion of the respondents may or may not be inclined to bias since the survey was conducted during the COVID 19 pandemic.