Syntax Literate: Indonesian Scientific Journal p–ISSN: 2541-0849 e-ISSN: 2548-1398

Vol. 9, No.11, November 2024

THE INFLUENCE OF FINANCIAL LITERACY AND DIGITAL LITERACY ON MOBILE BANKING ADOPTION

Varania Pambagyo Sabila¹, Hasnawati²

Universitas Trisakti, Jakarta, Indonesia^1,2

Email: [email protected]¹, [email protected]²

Abstract

This research examines the influence of Financial Literacy and Digital Literacy on Mobile Banking Adoption in Jabodetabek. This research data was obtained using a questionnaire in the form of a Google form and distributed via the WhatsApp friendship network and other social media such as TikTok and Instagram. The respondent criteria for this research are bank customers who are over 20 years old, have a mobile banking application, and actively use the mobile banking application for daily transactions. A total of 210 answers have been filled in and all answers have met the requirements for processing. This research observes that there is a significant influence of Financial Literacy and Digital Literacy on Mobile Banking Adoption. The dependent variables, namely Perceived Ease of Use, Perceived Usefulness, and Relative Advantage, have high explanatory power of the model. The independent variables Financial Literacy and Digital Literacy have a strong influence on the three dependent variables of this research, showing that Financial Literacy and Digital Literacy have a direct or positive influence on the use of Mobile Banking.

Keywords: Financial Literacy, Digital Literacy, Mobile Banking Adoption, Perceived Ease of Use, Perceived Usefulness, Relative Advantage

Introduction

The world is experiencing significant digitalization with the rapid advancement of technology and the rise of the Internet. The banking industry, like many other industries, recognized the advantages of the Internet and integrated it into their business practices, leading to the development of financial technology products and the emergence of electronic banking (Gounaris & Koritos, 2008). The use of various technologies in the financial services sector has brought significant changes to the banking industry (Pepur et al., 2024). Changes in people's consumption patterns towards digital have encouraged banks to accelerate the transformation process towards digital banking. In total, digital transactions worldwide from 2017–2021 grew by 118%, from USD 3.09 trillion in 2017 to USD 6.75 trillion in 2021 (Statista, 2021). In Indonesia itself, the development of digital transactions grew much higher, namely by 1,556 percent in the 2017–2020 period. Electronic money transactions reached IDR 786.35 trillion in 2021. This value increased by IDR 281.39 trillion (55.73%) compared to the previous year which was only IDR 504.96 trillion (Bank Indonesia, 2021).

The use of technology to deliver financial services provides innovative financial products and service models, increases access to finance, reduces transaction costs and improves the customer experience (Gomber et al., 2018; Pazarbasioglu et al., 2020). The most common digital distribution channel in the banking business is mobile banking (Nandru et al., 2023; Singh & Sharma, 2023). Literature shows that adopting financial technology services helps increase financial inclusion and improve consumers' financial well-being (Long et al., 2023).

Digital literacy, an individual's ability to effectively utilize digital devices such as smartphones and computers, access the internet, and use digital tools such as search engines and applications, plays an important role in this new digital paradigm (Pant & Agarwal, 2023). Digital literacy involves an understanding of how digital technologies work, including their hardware and software, as well as the ability to overcome common problems that may arise when using those technologies (Martin, 2008; Nawaz & Kundi, 2010). Digital literacy also includes an understanding of online security, including how to protect personal information, recognizing security threats such as viruses and phishing, and using secure passwords (OJK, 2023). Financial literacy, which has traditionally centered on retirement planning, must evolve to encompass the complex landscape of contemporary investment opportunities, including stock markets and fintech innovation (Pant and Agarwal, 2024). The literature defines Financial Literacy as possession of the knowledge to access and use mobile banking for banking services or purchasing goods and services (Mmari et al., 2024).

Several previous research results such as those conducted by Mmari, Horne, Appiah, and Gobind (2024) who examined The Role of Digital Literacy for Inclusive Banking in Tanzania stated that Digital Financial Literacy had a positive influence on the development of Digital Banking in Tanzania. Then further research conducted in Japan showed the results that Financial Literacy had a positive effect on Adoption of e-Payment Services and Usage Frequency of e-Money or Mobile Payment Apps (Long et al., 2023).

Furthermore, the results of research conducted by Peppur and Tvrdic (2024) in Croatia show that Personal Characteristics and Internet Banking Usage have a positive effect on Financial Literacy. Kaur, Suri, and Tyagi (n.d.) also conducted research entitled Factors Affecting The Adoption of Mobile Payment Service during The COVID-19 which was conducted in New Delhi, India which showed that Self-Efficacy, Personal Innovativeness, and Subjective Norm had a positive effect on Mobile Payment Adoption. Further research was conducted by Pant and Agarwal (2023) on financial literacy and digital literacy entitled Impact of Digital Financial Literacy on Financial Technology Adoption, Pant and Agarwal conducted research in India. The results of this research state that Financial Literacy and Digital Literacy have a positive effect on Fintech Adoption. This research takes the same discussion topic and conducts research in Indonesia.

Research Methods

This research focuses on the innovation experienced by banks and the resulting adoption of mobile banking which is influenced by financial literacy and digital literacy in Jabodetabek. This research uses quantitative research using questionnaires which focuses on collecting data from a certain sample or population. The object of this research is Mobile Banking Adoption as the dependent variable, while the independent variables used are Financial Literacy and Digital Literacy which can be explained using the following research model:

PEU1 = a + b1.FL + e

PU1 = a + b1.FL + e

RA1 = a + b1.FL + e

PEU2 = a + b1.DL + e

PU2 = a + b1.DL +e

RA2 = a + b1.DL + e

Operational Definition of Variables

Table 2. Operational Definition of Variables

No	Variable	Variable Definition
1	Mobile Banking Adoption (perceived ease of use)	The ease felt by customers in using the mobile banking application
2	Mobile Banking Adoption (perceived usefulness)	Benefits felt by customers in using the mobile banking application
3	Mobile Banking Adoption (relative advantage)	Benefits felt by customers in using the mobile banking application
4	Financial Literacy	Customer understanding of financial literature material
5	Digital Literacy	Customer understanding of digital literature material

Sample Determination Method

The population in this study are people aged over 20 years who are customers of private banks and state-owned banks that have mobile banking applications. This research uses convenience sampling, convenience sampling is a sampling technique for respondents based on how easy it is for the researcher or how many people are available to participate (Sugiyono, 2017).

Method of collecting data

The data collection method used in the research is using questionnaires and primary data. Primary data is data obtained directly from objects used for research. This questionnaire consists of several questions which are measured using a five-point Likert scale. The Likert scale is a data collection technique using a scale of 1-6 with the following explanation:

1 : Strongly Disagree

2 : Disagree

3 : Somewhat Disagree

4 : Quite Agree

5 : Agree

6 : Strongly Agree

Analysis Techniques

This research uses descriptive statistical analysis techniques and is processed with SPSS 26 software. Descriptive statistics are statistics used to analyze data by describing or illustrating the data concisely and clearly. Descriptive statistics is the presentation of data through tables or graphs to produce calculations of mode, median, mean (measurement of central tendency), calculations of data distribution through averages and standard deviations, maximum and minimum calculations (Sugiyono, 2017). The technique used is multiple linear regression and path analysis by carrying out validity and reliability tests first to check that each question indicator is valid and reliable. Validity test with a significance value <0.05 and reliability test with a Cronbach Alpha value >0.70 (Ghozali, 2018). Below are the indicators used to measure each variable.

Table 3. Statement Indicators

Variable	Indicator	Source
Financial Literacy (X1)	I understand bank products such as savings, deposits and loans	Pant & Agarwal (2024)
	I understand investment options such as pension funds, mutual funds, stock investments, etc
	I understand the risks associated with financial investments
	I set and regularly review my financial goals
	I set up my financial plan using my bank's app
	I have attended financial literacy training
Digital Literacy (X2)	I understand the features of smart devices such as mobile phones, laptops, etc	Pant & Agarwal (2024)
	I can install, set up, and use applications on my phone independently without help from others
	I understand cyber fraud and fraud when using the internet on mobile, leptop, etc
	The bank I use keeps me up to date on online scams and fraud when using online banking services
	I understand the risks of cyber fraud by using online banking applications
	I understand various fraud techniques in cyberspace (social engineering) such as "mamah asks for credit"
Mobile Banking Adoption (Perceived Ease of Use) (Y)	I didn't find any significant difficulties in using the new features of the online banking application on my smartphone	Pant & Agarwal (2024)
	Using online banking apps on smartphones, laptops, gives me flexibility
	The new features that mobile banking provides increase my use of banking apps on my phone
Mobile Banking Adoption (Perceived Usefulness) (Y)	I find the banking application on my cellphone useful for my transaction needs	Pant & Agarwal (2024)
	Using banking applications can increase efficiency and productivity
	I can easily use the bank's payment feature to make payments from other websites like e-commerce, travel bookings, etc
	My bank is integrated with various applications (Tokopedia, Shopee, OVO, Dana) through the VA (Virtual Account) facility
Mobile Banking Adoption (Relative Advantage) (Y)	I can save time by using banking apps compared to visiting a branch bank office	Pant & Agarwal (2024)
	I feel that the mobile banking that I use is relatively safer compared to other banks' mobile banking because it uses face recognition
	My bank provides the facility to talk directly with customer service by downloading certain applications (example: Halo BCA)
	My bank regularly introduces new online banking products and services and keeps me informed
	My bank keeps telling me about precautions to follow when using online banking
	Online banking minimizes my need to visit a bank branch
	I can withdraw cash from an ATM without having to use a debit/credit card by just using mobile banking

Results and Discussion

This research is quantitative research that uses a questionnaire as a data collection instrument. Data was collected from May 25, 2024 to June 8, 2024. In that period, 210 respondents were obtained. And all the data obtained meets the criteria so it can all be used. The data selection process is explained in table 4.

Table 4. Data Selection

No	Criteria	Amount of data
1	Number of Respondents	210
2	Respondents who have Mobile Banking	210
3	Total data that can be processed	210

Source: Results of data processing using SPSS 26

This section explains the demographics of respondents which describes the characteristics of respondents consisting of gender, age, education level, income/pocket money, domicile, and frequency of online shopping.

Table 5. Respondent Demographics

Respondent Characteristics	Frequency	Percentage
Gender
a. Man	74	35.2%
b. Woman	136	64.8%
Total	210	100.0%
Age
a. </= 20 Years	3	1.4%
b. 20.1 Years – 25 Years	78	37.1%
c. 25.1 Years – 30 Years	47	22.4%
d. 30.1 Years – 35 Years	13	6.2%
e. 35.1 Years – 40 Years	8	3.8%
f. 40.1 Years – 45 Years	16	7.6%
g. >45 Years	45	21.4%
Total	210	100.0%
Last education
a. SENIOR HIGH SCHOOL	28	13.3%
b. S1	166	79.0%
c. S2	13	6.2%
d. S3	3	1.4%
Total	210	100.0%
Income per Month
a. < IDR 1,000,000	8	3.8%
b. IDR 1,000,000 - IDR 5,000,000	34	16.2%
c. IDR 5,100.00 - IDR 10,000,000	98	46.7%
d. IDR 10,100,000 - IDR 15,000,000	31	14.8%
e. IDR 15,100,000 - IDR 20,000,000	19	9.0%
f. IDR 20,100,001 - IDR 25,000,000	6	2.9%
g. >25,000,000	14	6.7%
Total	210	100.0%
Domicile
a. Jakarta	91	43.3%
b. Bogor	19	9.0%
c. Depok	9	4.3%
d. Tangerang	30	14.3%
e. Bekasi	45	21.4%
f. Outside Jabodetabek	16	7.6%
Total	210	100.0%
Profession
a. Accountant / Finance	13	6.2%
b. Employee / Employee	88	41.9%
c. Auditor / Advisory / Consultant / Tax / Bank	42	20.0%
d. Teachers / Teaching Staff / Lecturers	11	5.2%
e. Contractor / Civil / Engineer / Design	6	2.9%
f. Retired / Housewife	32	15.2%
g. Student / Not Yet Working	10	4.8%
h. Businessman	8	3.8%
Total	210	100.0%
Source: Results of data processing using SPSS 26

Table 5 shows that the gender proportion of female respondents is twice that of male respondents. The majority of respondents were under 25 years of age with their last level of education being Bachelor's degree (79.0%) and income or pocket money below IDR 10,000,000 (46.7%). The majority of respondents who filled out this questionnaire live in Jakarta (43.3%). As many as 41.9% of respondents are civil servants or employees.

Figure 1. Percentage of Mobile Banking Used

Source: Google Form Responses Result

Figure 1 shows that the mobile banking most widely used by respondents is BCA at 77.1% followed by Mandiri at 34.3%, BNI at 19.5%, BSI at 11.4%, BRI at 9.5%, Permata as much as 5.7%, Jenius as much as 2.4%, and other mobile banking as much as 1% each.

Figure 2. Percentage of Mobile Banking Use

Source: Google Form Responses Result

Figure 2 shows that 82.4% of respondents had used the Mobile Banking application before the COVID-19 pandemic while another 17.6% used the Mobile Banking application after the COVID-19 pandemic.

Figure 3. Percentage of Mobile Banking Activity

Source: Google Form Responses Result

Figure 3 shows that the majority of respondents use the Mobile Banking application for Shopping Payment Transactions as much as 93.3%, followed by E-Money Top Up as much as 82.4%, Receiving a Salary as much as 71%, Routine Bill Payments as much as 60.5%, and for Credit Card Payments were 23.8%.

Hypothesis Results

The data collected has passed a quality test to see the seriousness of the respondents in answering questions and to see situational factors at the time the research was conducted. The test carried out was a validity test using Pearson Correlation < 0.05 and a reliability test using Cronbach's Alpha > 0.70. All question indicators for each variable have been proven valid because all significance values are below 0.05 and each variable has been proven reliable with Cronbach's Alpha values above 0.70. This research uses multiple regression to test the hypothesis using the coefficient of determination (adjusted R2), model feasibility test (F test), and partial test (t test).

Table 6. First Regression Results

Research Model: PEU1 = a + b1.FL + e
Variable	Prediction	Unstandardized Coefficients	t	Partial Test		Decision
		B	Std. Error	Sig.	Sig./2
(Constant)		8.344	0.696	11.985	<0.001
Financial Literacy (X1)	+	0.266	0.024	10.957	<0.001	<0.001
Adjusted R²	0.363
F Test	120.059
F Significance	<0.001
Dependent Variable Perceived Ease to Use (Y)

Source: Processed with SPSS 26

From table 6 it can be seen that the Adjusted R² value is 0.363. This means that 36.3% of the variation in the Perceived Ease of Use variable can be explained by the Financial Literacy variable. Meanwhile 63.7% was caused by other factors not included in this model. The significant F value shows <0.001, which means this model is fit. From the results of the partial t test, it was found that Financial Literacy influences Perceived Ease of Use. This can be seen from the significance value of t/2 which is smaller than 0.05.

Table 7. Second Regression Results

Variable	Prediction	Unstandardized Coefficients (B)	Std. Error	t	Sig.	Sig / 2	Decision
(Constant)		15.393	0.857	17.961	<0.001
Financial Literacy (X1)	+	0.241	0.030	8.052	<0.001	<0.001	H1 = Accepted
Adjusted R²	0.234
F Test	64.836
F Significance	<0.001
Dependent Variable		Perceived Usefulness (Y)

Source: Processed with SPSS 26

From table 7 it can be seen that the Adjusted R² value is 0.234. This means that 23.4% of the variation in the Perceived Usefulness variable can be explained by the Financial Literacy variable. Meanwhile 76.6% was caused by other factors not included in this model. The significant F value shows <0.001, which means this model is fit. From the results of the partial t test, it was found that Financial Literacy influences Perceived Usefulness. This can be seen from the significance value of t/2 which is smaller than 0.005.

Table 8. Third Regression Results

Variable	Prediction	Unstandardized Coefficients (B)	Std. Error	t	Sig.	Sig / 2	Decision
(Constant)		18.958	1.372	13.822	<0.001
Financial Literacy (X1)	+	0.595	0.048	12.442	<0.001	<0.001	H1 = Accepted
Adjusted R²		0.424
F Test		154.806
F Significance		<0.001
Dependent Variable		Perceived Usefulness (Y)

Source: Processed with SPSS 26

From table 8, it can be seen that the Adjusted R² value is 0.424. This means that 42.4% of the variation in the Relative Advantage variable can be explained by the Financial Literacy variable. Meanwhile 57.6% was caused by other factors not included in this model. The significant F value shows <0.001, which means this model is fit. From the results of the partial t test, it was found that Financial Literacy influences Relative Advantage. This can be seen from the significance value of t/2 which is smaller than 0.005.

Table 9. Fourth Regression Results

Variable	Prediction		Unstandardized Coefficients (B)	Std. Error	t	Sig.	Sig / 2	Decision
(Constant)			4.120	0.815	5.057	<0.001
Digital Literacy (X2)	+		0.374	0.026	14.530	<0.001	<0.001	H1 = Accepted
Adjusted R²			0.501
F Test			211.115
F Significance			<0.001
Dependent Variable		Perceived Usefulness (Y)

Source: Processed with SPSS 26

From table 9, it can be seen that the Adjusted R² value is 0.501. This means that 50.1% of the variation in the Perceived Ease of Use variable can be explained by the Digital Literacy variable. Meanwhile 49.9% was caused by other factors not included in this model. The significant F value shows <0.001, which means this model is fit. From the results of the partial t test, it was found that Digital Literacy influences Perceived Ease of Use. This can be seen from the significance value of t/2 which is smaller than 0.005.

Table 10. Fifth Regression Results

Variable	Prediction		Unstandardized Coefficients (B)	Std. Error	t	Sig.	Sig / 2	Decision
(Constant)			10.271	0.995	10.318	<0.001
Digital Literacy (X2)	+		0.380	0.031	12.077	<0.001	<0.001	H1 = Accepted
Adjusted R²			0.409
F Test			145.848
F Significance			<0.001
Dependent Variable		Perceived Usefulness (Y)

Source: Processed with SPSS 26

From table 10, it can be seen that the Adjusted R² value is 0.409. This means that 40.9% of the variation in the Perceived Usefulness variable can be explained by the Digital Literacy variable. Meanwhile 59.1% was caused by other factors not included in this model. The significant F value shows <0.001, which means this model is fit. From the results of the partial t test, it was found that Digital Literacy influences Perceived Usefulness. This can be seen from the significance value of t/2 which is smaller than 0.005.

Table 11. Sixth Regression Results

Variable	Prediction	Unstandardized Coefficients (B)	Std. Error	t	Sig.	Sig / 2	Decision
(Constant)		10.174	1.593	6.386	<0.001
Digital Literacy (X2)	+	0.815	0.050	16.202	<0.001	<0.001	H1 = Accepted
Adjusted R²		0.556
F Test		262.505
F Significance		<0.001
Dependent Variable	Perceived Ease to Use (Y)

Source: Processed with SPSS 26

From table 11, it can be seen that the Adjusted R² value is 0.556. This means that 55.6% of the variation in the Relative Advantage variable can be explained by the Digital Literacy variable. Meanwhile 44.4% was caused by other factors not included in this model. The significant F value shows <0.001, which means this model is fit. From the results of the partial t test, it was found that Digital Literacy influences Relative Advantage. This can be seen from the significance value of t/2 which is smaller than 0.005.

The results of testing the H1 hypothesis were successfully proven because the t test results were 5% greater. The results of this research are in line with research conducted by Pant and Agarwal (2024), Long, Morgan, and Yoshino (2023), Mmari, Horne, Appiah, and Gobind (2024) which shows that Financial Literacy has a significant effect on the ease of using mobile applications. banking.

H1: Financial Literacy has a significant effect on Mobile Banking Adoption (Perceived Ease of Use)

Furthermore, the results of testing the hypothesis H2 were also successfully proven because the t test results were greater than 5%, these results are in line with research conducted by Pant and Agarwal (2024) and Mmari, Horne, Appiah, and Gobind (2024) where Financial Literacy has a significant effect regarding the perceived benefits of using the mobile banking application.

H2: Financial Literacy has a significant effect on Mobile Banking Adoption (Perceived Usefulness)

The results of the H3 test were successfully proven because the t test results were greater than 5%, these results are in accordance with research conducted by Long, Morgan, and Yoshino (2023) and Pant and Agarwal (2024) where Financial Literacy has a significant effect on the benefits felt by the mobile banking application users.

H3: Financial Literacy has a significant effect on Mobile Banking Adoption (Relative Advantage)

Then the results for testing H4 were also successfully proven because the t test results were greater than 5%, these results were in accordance wita Pant and Agarwal (2024) and Mmari, Horne, Appiah, and Gobind (2024) where Digital Literacy has a significant effect on the convenience felt by customers when using mobile banking applications.

H4: Digital Literacy has a significant effect on Mobile Banking Adoption (Perceived Ease of Use)

Furthermore, the H5 test results were successfully proven because the t test results were greater than 5%, these results are in line with research by Kaur, Suri, and Tyagi (2024) and Pant and Agarwal (2024) where Digital Literacy significant influence on the perceived benefits of using the mobile banking application.

H5: Digital Literacy has a significant effect on Mobile Banking Adoption (Perceived Usefulness)

The H6 test results were also successfully proven because the t test results were greater than 5%, these results are in accordance with the research of Pant and Agarwal (2024), Mmari, Horne, Appiah, and Gobind (2024), Kaur, Suri, and Tyagi (2024), and Long, Morgan, and Yoshino (2023) where Digital Literacy has a significant effect on the benefits felt by mobile banking application users.

H6: Digital Literacy has a significant effect on Mobile Banking Adoption (Relative Advantage)

Conclusion

This research examines the influence of Financial Literacy and Digital Literacy on Mobile Banking Adoption (Perceived Ease of Use, Perceived Usefulness, and Relative Advantage). This research data was obtained by distributing a questionnaire in the form of a Google form and distributed via the WhatsApp, TikTok and Instagram applications. As many as 210 responses from the Google form were filled in and all answers met the requirements for processing. The results of this research show that Financial Literacy and Digital Literacy have a significant effect on Mobile Banking Adoption (Perceived Ease of Use, Perceived Usefulness, and Relative Advantage). This research found that customers who have an understanding of financial literacy and digital literacy experience more benefits and ease in using mobile banking applications and are also greatly helped with their daily transactions. These findings can be useful for mobile banking customers who still do not understand how to operate the mobile banking application or the features in the mobile banking application.

This research has several limitations, the first is the use of questionnaires as a way to collect data. Questionnaires have limitations in terms of guaranteeing the honesty and seriousness of respondents in answering questions. The second limitation is that the majority of respondents are 20 – 30 years old so they cannot represent other generations of age and income. Based on research limitations, further research can be carried out by distributing the questionnaire more widely so that all generations can participate in filling out the research questionnaire form. So it can reflect more real conditions today.

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Copyright holder:

Varania Pambagyo Sabila, Hasnawati Hasnawati (2024)

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Syntax Literate: Jurnal Ilmiah Indonesia

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