ISSN 2809-929X (Prin.
ISSN 2809-9303(Onlin.
Journal of Social Commerce Vol.
5 No.
4, 2025 (Page: 501-.
DOI: https://doi.
org/10.
56209/jommerce.
The Influence of Convenience.
Risk, and Security on Usage Decisions of Digital Bank to the People of Surabaya City Regita Bintari Prameswari1.
Lia Nirawati1 1Universitas Pembangunan Nasional "Veteran" Jawa Timur Article History Keywords Usage Decisions Digital Banking Applications Convenience Risk JEL Classification G21.
G20.
D12.
M15.
O33 Abstract The increasing use of digital banking applications encourages the need for an in-depth understanding of the factors that influence usage decisions.
This study aims to analyze the influence of convenience, risk, and security on the decision to use SeaBank digital banks on the people of Surabaya City.
The research method used was quantitative by collecting data using questionnaires to 271 respondents who used the SeaBank application in the Surabaya area.
The data analysis technique used multiple linear regression analysis.
The results of the study show that simultaneously the variables of convenience, risk, and safety have a significant effect on the decision to use.
Partially, convenience, risk, and safety have a significant positive effect on usage decisions.
The implications of the findings can be a guideline for digital banking service providers to improve the quality they have.
Focusing on these factors is expected to form the basis for the development of more effective strategies in optimizing the user experience in the world of digital banking.
Introduction The development of information and communication technology in the digital era has driven fundamental changes in various sectors, including banking.
Services that previously relied on physical branch offices are now switching to internet-based digital services and mobile devices.
According to De Leon in Harahap .
, a digital bank is a financial institution that specifically provides banking services through online platforms such as mobile applications and websites, without the presence of a physical office.
These changes are triggered by the increasing use of smartphones, widespread internet access, and a shift in consumer preferences towards accessible and convenient services (AL-Zoubi et al.
, 2023.
Shah & Mehta, 2023.
Kumar et al.
, 2023.
oECn et al.
, 2.
In Indonesia, the digital banking sector is experiencing very rapid growth.
These developments encourage the creation of a positive competitive climate between financial institutions, provide a variety of choices for customers, while spurring improvement in service quality and 1Corresponding Author: Regita Bintari Prameswari.
Email: 21042010206@student.
Address Jl.
Rungkut Madya.
Gn.
Anyar.
Kec.
Gn.
Anyar.
Surabaya.
Jawa Timur 60294 Copyright A 2025.
Journal of Social Commerce is licensed under Creative Commons Attribution-ShareAlike 0 International License .
ttp://creativecommons.
org/licenses/by-sa/4.
Celebes Scholar pg Journal of Social Commerce innovation in the national banking industry (Zhao et al.
, 2019.
Famiyeh et al.
, 2018.
Attah et , 2.
The following is the projected data of digital bank users in Indonesia:
Figure 1.
Graph of Digital Bank Users in Indonesia Source: databoks.
Referring to the projections from the Finder.
com financial website quoted through .
, the number of digital bank users in Indonesia shows significant growth.
In 2021, around a quarter .
%) of Indonesia's adult population already has a digital bank account, equivalent to approximately 47.
7 million people.
This figure is expected to increase to 31% or around 59.
9 million users in 2022.
In fact, it is projected that in 2026, the percentage will rise to 39%, or around 74.
8 million digital banking service users (Yulianti.
The following is digital bank data known to the Indonesian public (July 2.
Figure 2.
Digital Bank Data Known to Indonesian Audiences Source: info.
According to the results of populix's research, the graph shows data about digital bank brands known to consumers in Indonesia.
The data is displayed in 3 categories using the form of percentage, namely TOM (Top of Mind/First Mentio.
or in other words which brand first comes to consumers' minds when asked about digital banks, the second category is total spontaneous mentions, and total awareness (Suhanto et al.
, 2023.
McCarthy-Jones, 2.
From this data, it can be seen that Seabank is the most well-known digital bank, with 95% of respondents knowing the brand.
In second place.
Jago and Blu by BCA are known by 94% and 85% of respondents, respectively.
At the bottom.
OCTO Mobile is the least known brand, with Regita Bintari Prameswari & Lia Nirawati Celebes Scholar pg Journal of Social Commerce only 37% of respondents knowing about the brand.
This fact signifies fierce competition in the digital banking industry.
In the midst of these developments, competition between digital banking service providers is becoming increasingly fierce.
The emergence of various new digital banks as well as innovations from conventional banks require every service provider to understand the factors that influence usage decisions by consumers (Dauda & Lee, 2.
The decision to use, according to Kotler & Keller (Wahyuningsih, 2.
, is an activity after deciding to use a product or application, a person will go through several stages before actually using it.
They will assess whether the product suits their needs, and then decide whether to use it or not.
It's like choosing from a wide range of options available.
In the context of digital banks, usage decisions are an important indicator of the success of the service in retaining customers and attracting new users.
Technical factors such as convenience, risk, and security are key elements that influence how users decide to use digital bank services.
Davis in Awwal .
states that ease of use reflects the extent to which users believe that a system or technology can be operated easily without facing significant difficulties.
Risk, according to Pebriantie .
, is the uncertainty faced by consumers when they cannot be sure of the outcome of the purchase decision of a product.
Security, according to Hoehle et al.
, is the perception of protection when conducting digital transactions, which is increasingly important in the midst of cyber threats such as phishing and malware (BPPTIK, 2.
In understanding technology adoption behavior.
Davis .
introduced the Technology Acceptance Model (TAM) which emphasizes two main constructs: perceived ease of use and perceived usefulness as determinants of technology acceptance (Suhendry, 2.
In the context of digital banks, users will be more likely to use the app if they find it easy to operate and feel significant benefits.
Quoting from research (Authar Barik Elsyam, 2.
This model was first introduced by Lui & Jamieson .
by combining risk perception and trust perception as additional variables that affect technology acceptance.
The risk perception used refers to the user's concern over the uncertainty and potential losses that may occur during the use of technology, such as transaction errors, loss of funds, and personal data leakage (Jarvenpaa et al.
, 1999.
Stone & Gronhaug, 1993.
Beldad et al.
, 2011.
Chellappa & Paylo.
Budiharseno & Kim, 2.
Meanwhile, the perception of trust refers to the belief of users that digital systems can operate reliably, safely, and according to expectations (Pavlou.
This model is relevant for analyzing decisions to use digital bank services, which in addition to considering convenience and benefits, are also influenced by security factors and risk perception.
SeaBank, which is integrated with the Shopee ecosystem, offers savings services, deposits, free interbank transfers, e-wallet top-ups, bill payments, and QRIS (Truong, 2.
This advantage makes it popular in big cities like Surabaya.
However, high competition requires SeaBank to continuously improve convenience, manage risk, and strengthen security to remain Therefore, this study aims to analyze the influence of convenience, risk, and security on the decision to use digital banking services, with a case study on SeaBank application users in Indonesia.
The results of the study are expected to not only provide a deeper understanding of the factors influencing usage decisions, but also provide recommendations for the development of SeaBank application strategies and features.
Improved convenience, risk management, and security are expected to be a strategic foundation to strengthen SeaBank's position in the increasingly competitive digital banking industry.
Regita Bintari Prameswari & Lia Nirawati Journal of Social Commerce Celebes Scholar pg Methods This study uses a quantitative approach with the main objective of analyzing the influence of Convenience.
Risk, and Security on the Decision to Use Seabank Digital Bank.
This approach was chosen because it is able to provide an objective explanation of the relationship between variables through numerical and measurable data.
The research data was collected through an online questionnaire or Google Form which was distributed to the people of Surabaya City as a research population.
Each question item was compiled using a five-point likert scale, ranging from strongly disagree .
to strongly agree .
, to describe the respondents' level of approval of each research indicator.
The total number of respondents who participated in this study was 271 people.
The sampling technique used is purposive sampling, because the researcher sets special criteria so that the selected respondents are truly relevant to the research context.
These criteria include the respondent is an active customer of SeaBank and have made at least two financial transactions using the SeaBank application on various types of services.
The purposive sampling method was chosen because it was considered the most appropriate to obtain data from users who have direct experience and a real understanding of the digital bank services being studied.
The theoretical basis in this study refers to Technology Acceptance Model (TAM) introduced by Davis .
This model explains that a person's acceptance of a technology is influenced by two main perceptions, namely perceived usefulness .
erceived benefit.
and perceived ease of use .
ase of us.
Both aspects determine the extent to which users are willing to accept and use technology in their activities.
Furthermore, the TAM model has evolved into the Trust and Risk Integrated Technology Acceptance Model (TRITAM), which integrates the elements of trust and risk into the technology acceptance framework.
The TRITAM model assumes that user behavior in the digital context is influenced not only by the perception of convenience and benefit, but also by the level of trust in the security of the system as well as the perception of risks that may arise.
Therefore, this study adopts TAM and TRITAM as a theoretical basis to explain the relationship between ease, risk, and security to the decision to use SeaBank.
The combination of these two models provides a more comprehensive conceptual basis, so it is expected to be able to deepen understanding of the factors that shape user behavior in adopting digital banking This research is testing the following hypothesis:
H1: Convenience.
Risk, and Security simultaneously have a significant effect on the Decision to Use SeaBank Digital Bank.
H2: Convenience has a significant effect on the Decision to Use SeaBank Digital Bank.
H3: Risk has a significant effect on the Decision to Use SeaBank Digital Bank.
H4: Security has a significant effect on SeaBank's Digital Bank Use Decision.
Variable Operations The determination of operational definitions is carried out to ensure the compatibility between theoretical concepts and empirical measurements.
The indicators of each variable in this study were adapted and modified from relevant previous research, such as Davis .
to TAM.
Featherman & Pavlou .
to perceived riskand Suh & Han .
to perceived trust and Table 1.
Operational Definition Variable Ease Indicators X1.
X1.
X1.
Information Easy to use Easy to reach The system is clear and understood Regita Bintari Prameswari & Lia Nirawati Journal of Social Commerce Celebes Scholar pg Risk Security Decision Use X2.
X2.
X2.
X3.
X3.
X3.
X3.
X3.
X4.
X4.
X4.
X4.
X4.
Presence of certain risks Suffer losses Thinking that it is risky Privacy Integrity Password Electronic Identity Document (Certificat.
Fingerprints (Biometri.
and TOTP Problem management Information search Alternative evaluation Usage decisions Post-use behavior The operational explanation of the variables is described as follows:
Ease X1.
1 : The product or service should be designed to be easy to use, so that users can immediately understand how to use it without the need to learn for a long time.
X1.
2 : The product or service must be easily accessible from various devices and places, so that the user feels comfortable when he wants to use it.
X1.
3 : The information and instructions provided must be clear and easy to understand, so that the user is not confused when using the system.
Risk X2.
1 : The extent to which the user is aware of the risks when using the SeaBank application.
X2.
2 : How concerned the user is about potential financial or data loss.
X2.
3 : The extent to which the user thinks that using SeaBank is risky.
Security X3.
1 : SeaBank application's ability to protect users' personal information from being accessed by unauthorized parties.
X3.
2 : SeaBank's system ability to maintain the integrity of user data to remain authentic and unchanged during the transaction process.
X3.
3 : The level of security that the user feels based on the complexity and reliability of the password when accessing the SeaBank application.
X3.
4 : The use of official digital identity to ensure the authenticity and security of users in using SeaBank services.
X3.
5 : Implementation of dual authentication via fingerprint and one-time TOTP code to improve the security of user account access.
Usage Decisions X4.
1 : The extent to which customers are aware of the need for practical financial services and encourage them to consider SeaBank.
X4.
2 : To what extent the customer finds out information about SeaBank before deciding to use it.
X4.
3 : To what extent customers compare SeaBank with other digital banking applications before choosing.
X4.
4 : To what extent do customers decide to use SeaBank as a digital banking solution? X4.
5 : The extent to which the customer has shown satisfaction or intention to continue using and recommending SeaBank after trying.
Regita Bintari Prameswari & Lia Nirawati Journal of Social Commerce Celebes Scholar pg Data Analysis Procedure The data collected from the questionnaires were analyzed through a sequence of statistical procedures designed to ensure measurement quality and to test the proposed relationships between variables.
The analysis began with an examination of respondent characteristics to describe the profile of SeaBank users in Surabaya City.
This stage focused on summarizing demographic and usage-related information, including domicile, gender, age, occupation, income range, and transaction frequency, in order to contextualize the behavioral patterns of the respondents.
The quality of the measurement instruments was evaluated to ensure that each indicator accurately represented the intended construct.
Item-level analysis was conducted to assess whether each statement consistently reflected its corresponding variable.
Indicators that demonstrated adequate association with their respective constructs were retained for further In addition, internal consistency was examined to confirm that the indicators within each variable functioned cohesively as a single measurement dimension.
This step ensured that the data used for inferential analysis were both valid and reliable.
After confirming the adequacy of the measurement instruments, the analysis proceeded to examine the relationships between the independent variables and the dependent variable.
The study employed an explanatory analytical approach to evaluate how Convenience.
Risk, and Security were associated with Usage Decisions.
This analysis allowed the study to assess both the collective influence of the three independent variables and the individual contribution of each variable to usage decisions.
The simultaneous effect of Convenience.
Risk, and Security was evaluated to determine whether these factors jointly influenced the decision to use SeaBankAos digital banking services.
In parallel, the partial effects were examined to identify the relative strength and direction of each variableAos influence when considered independently.
This approach enabled a nuanced interpretation of user behavior by distinguishing general patterns from variable-specific effects.
The analysis assessed the extent to which variations in usage decisions could be explained by the proposed factors.
This step provided insight into the explanatory power of the research model and clarified the proportion of user decision-making behavior accounted for by Convenience.
Risk, and Security, while acknowledging the presence of other influencing factors beyond the scope of the study.
Results and Discussion The statistical results show that the data obtained from SeaBank users exhibit consistent and stable patterns across all measured variables.
Responses demonstrate sufficient variability while remaining coherent, indicating that respondents were able to assess convenience, risk, security, and usage decisions based on actual experience with the application.
The measured indicators display meaningful contributions to their respective constructs, and no irregular response patterns were observed.
Presentation of Research Results Data Classification of Respondents Based on Domicile Table 2.
Frequency Distribution of Respondents' Domicile Domicile East Surabaya
West Surabaya
South Surabaya
North Surabaya
Frequency Percentage 35,5% 14,8% Regita Bintari Prameswari & Lia Nirawati Journal of Social Commerce Celebes Scholar pg
Central Surabaya
Total
11,8%
100,00%
Source: Author's research, 2025 Based on table 2, the majority of respondents came from East Surabaya as many as 96 people .
5%), followed by West Surabaya 65 people .
%) and North Surabaya 40 people .
8%).
Respondents from South Surabaya were recorded at 38 people .
%), while Central Surabaya was 32 people .
8%).
Overall, the distribution of respondents was relatively evenly distributed in the five main areas of Surabaya City, with the largest concentration being in East Surabaya.
Classification of Respondents by Gender Table 3.
Frequency Distribution of Respondents' Gender Gender Frequency Man Woman Total Percentage 41,3% 58,7% 100,00% Source: Author's research, 2025 Based on table 3 data, the majority of respondents are women, which is 159 people or 58.
of the total respondents.
Meanwhile, male respondents amounted to 112 people or 41.
This illustrates that women's participation in this study is higher than that of men.
Classification of Respondents by Age Table 4.
Frequency Distribution of Respondents' Ages Age 17-23 years old 24-30 years 31-37 years old >37 years old Total Frequency Percentage 62,7% 28,4% 8,1% 0,7% 100,00% Source: Author's research, 2025 Based on table 4, the respondents' age data shows that most of the respondents are .
with a total of 271 years old.
Classification of Respondents by Occupation Table 5.
Distribution of Respondents' Work Frequency Work Student Self-Employed Workers Civil Servants Student Private Sector Workers Housewives Professional Workers Total Frequency Percentage 60,5% 26,6% 7,7% 1,8% 1,5% 1,1% 0,8% 100,00% Source: Author's research, 2025 Regita Bintari Prameswari & Lia Nirawati Journal of Social Commerce Celebes Scholar pg Based on table 5 of employment data, the majority of respondents were students as many as 164 people .
5%), followed by self-employed people 72 people .
6%) and civil servants 21 people .
7%).
The rest consisted of students, private employees, housewives, and professional workers with a percentage below 2%.
The dominance of students is in line with the characteristics of active users of digital services such as SeaBank.
Classification of Respondents by Income Range Table 6.
Frequency Distribution of Respondents' Income Ranges Revenue Range .
er mont.
<IDR 1,000,000 IDR 1,000,000 Ae IDR 2,500,000 IDR 2,500,000 Ae IDR 5,000,000 >IDR 5,000,000 Not Filling in the Income Range Total Frequency Percentage 30,3% 32,8% 18,9% 0,8% 100,00% Source: Author's research, 2025 Based on table 6 regarding the income range of the respondents, it shows that most of the respondents are in the income category of less than IDR 1,000,000 as many as 82 respondents .
3%), followed by the income group of IDR 1,000,000 Ae IDR 2,500,000 as many as 89 respondents .
8%).
This is in line with the majority of respondents who are professional as students, so their income tends to be in the low category.
There were as many as 2 respondents who chose not to fill in income information.
Nevertheless, all respondents still met the research criteria, namely being SeaBank customers and having made transactions more than twice using the application.
Respondent Classification Based on Number of Transactions (Per Mont.
Table 7.
Distribution of Frequency of Number of Transactions (Per Mont.
of Respondents Number of Transaction 1 Ae 3 times 4 Ae 6 times 7 Ae 9 times 10 Ae 12 times >12 times Total Frequency Percentage 33,6% 12,9% 9,6% 15,9% 100,00% Source: Author's research, 2025 Based on table 7, data on the number of respondents' transactions on the SeaBank application in one month shows that the majority of respondents, namely 91 people .
6%), make transactions 1-3 times per month.
Then, as many as 78 respondents .
%) made transactions 4-6 times per month.
Furthermore, there were 35 respondents .
9%) who made transactions 7-9 times, and 26 respondents .
6%) made transactions 10-12 times a month.
Meanwhile, 43 respondents .
9%) were recorded to be active in transactions more than 12 times per month.
This transaction pattern is also influenced by the income level of the respondents, most of whom are below Rp 2,500,000 per month, with the majority of professions being students who generally have more limited financial activities.
Regita Bintari Prameswari & Lia Nirawati Journal of Social Commerce Celebes Scholar pg Validity Test Table 8.
Validity Test Indicators X1.
X1.
X1.
X2.
X2.
X2.
X3.
X3.
X3.
X3.
X3.
Y1.
Y1.
Y1.
Y1.
Y1.
r count Sign r Table 0.
Information Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Source: Data Processing Process with SPSS Program, 2025 Based on table 8, it shows that all of the indicators obtained ycycaycuycycuyc a result of > ycycycaycaycoyce 0.
So, the conclusion that can be drawn is that all data in this study is recognized as valid.
Reliability Test Table 9.
Reliability Test Variable Facilities (X.
Risk (X.
Security (X.
Usage Results (Y.
Cronbach's Alpha () Information Reliable Reliable Reliable Reliable Source: Data Processing Process with SPSS Program, 2025 Based on table 9, it shows that all indicators obtained Cronbach's Alpha () > a critical limit of Therefore, all variable items are declared reliable.
Multiple Linear Regression Analysis Test Table 10.
Multiple Linear Regression Analysis Test Results Unstandardized Coefficients Std Coefficients Std.
Error Beta (Constan.
Ease Risk Security Type Sig.
Source: Data Processing Process with SPSS Program, 2025 Based on table 10, the equation can be seen below:
Y = 0 1X1 2X2 3X3 4X4
Regita Bintari Prameswari & Lia Nirawati Journal of Social Commerce Celebes Scholar pg Y= 8.
Based on the regression equation, the following analysis process can be carried out below: .
The constant (CA) of 8.
588 indicates that if all independent variables, namely Ease (X.
Risk (X.
, and Security (X.
are in a constant .
condition, then the base value of the Usage Decision (Y) is 8.
588 units.
The regression coefficient of the Ease variable (X.
which means that every one-point increase in Ease will increase the Usage Decision by 0.
points, assuming the other variables are fixed.
The regression coefficient of the Risk variable (X.
264 indicates that a one-unit increase in Risk perception will also increase the Use Decision by 0.
264 points, when the other variables remain unchanged.
The regression coefficient of the Security variable (X.
329 indicates that a one-point increase in Security will impact an increase in Usage Decisions by 0.
329 points, assuming the other independent variables are constant.
Coefficient of Determination (R.
Table 11.
Results of Coefficient Determination Type R Square Adjusted R Square Std.
Error of the Estimate Source: Data Processing Process with SPSS Program, 2025 Based on table 11, the results of regression analysis can be explained, the R quare value of 271 is obtained.
This shows that 27.
1% of the variation in the Use Decision as a dependent variable can be explained by the independent variables used in the model, namely Ease.
Risk, and Security.
Meanwhile, the remaining 72.
9% .
% - 27.
1%) were influenced by other factors outside the regression model used in this study.
Test F Table 12.
F Test Result Type Regression Residual Total Sum of Squares Mean Square Sig.
Source: Data Processing with SPSS Program, 2025 Based on table 12, it is known that the significance value .
< 0.
05 and the value of .
> .
so that it can be concluded that simultaneously the variables Ease (X.
Risk (X.
, and Safety (X.
simultaneously have a significant effect on the Decision of Use (Y).
T test Table 13.
Test Results t Type Unstandardized Coefficients Std.
Error (Constan.
Ease Risk Security Standardized Coefficients Beta Sig.
Source: Data Processing Process with SPSS Program, 2025 Regita Bintari Prameswari & Lia Nirawati Journal of Social Commerce Celebes Scholar pg Based on table 13, the results of the t-test are explained as follows: .
The Ease variable (X.
< 0.
05 and the value of .
> 1.
it can be concluded that H0 is rejected and H1 is accepted, meaning that partially the Ease variable (X.
has a significant effect on the Usage Decision variable (Y).
The Risk Variable (X.
< 0.
05 and the value .
> 1.
Thus, it can be concluded that H0 is rejected and H1 is accepted, meaning that the Risk variable (X.
has a significant effect on the Consumption Decision variable (Y).
The Ease variable (X.
< 0.
05 and the value .
> 1.
Thus, it can be concluded that H0 is rejected and H1 is accepted, meaning that the Security variable (X.
has a significant effect on the Usage Decision variable (Y).
Understanding User Decisions in Digital Banking Contexts The results of this study indicate that convenience, risk, and security jointly play a meaningful role in shaping usage decisions in the context of SeaBank digital banking services.
This finding reinforces the growing consensus in technology adoption research that user behavior in digital finance is not driven by isolated considerations but by an integrated evaluative process.
Users simultaneously assess how easy a system is to use, how much uncertainty it entails, and how well it protects their personal and financial information.
In this sense, the present findings do not merely replicate earlier models but situate them within the lived experiences of active digital banking users.
The significant positive influence of convenience on usage decisions is consistent with foundational and contemporary studies on technology acceptance.
Davis .
originally argued that ease of use reduces cognitive burden and increases the likelihood of system acceptance, a claim that has been repeatedly supported and extended by later scholars such as Venkatesh & Davis .
and Venkatesh et al.
In the context of digital banking, convenience extends beyond interface simplicity and becomes embedded in usersAo daily financial practices.
The present findings suggest that SeaBank users value seamless navigation, clarity of transaction procedures, and accessibility across situations, which in turn strengthens their decision to continue using the application.
This supports the view that convenience remains influential not only at the initial adoption stage but also in sustaining long-term usage behavior among users who are already familiar with digital technologies.
The positive relationship between perceived risk and usage decisions requires a more nuanced reading when engaged with existing studies.
Early research on perceived risk often emphasized its inhibiting role, suggesting that higher risk perceptions discourage technology use (Stone & Gronhaug, 1993.
Featherman & Pavlou, 2.
However, more recent studies indicate that risk does not uniformly function as a deterrent, particularly in contexts where users possess prior experience and sufficient information (Pavlou, 2001.
Wahyuni & Dahmiri, 2.
In this study, the perception of risk among SeaBank users appears to reflect awareness rather than anxiety.
Users recognize potential vulnerabilities inherent in digital transactions, yet this awareness does not translate into avoidance.
Instead, it coexists with continued usage, suggesting that risk is cognitively evaluated and weighed against perceived benefits and safeguards.
This finding supports the argument that in mature digital environments, risk perception may signify informed engagement rather than resistance.
Security was found to have the strongest influence on usage decisions, underscoring its central role in digital banking behavior.
Prior studies have consistently emphasized that perceived security forms the foundation of user trust, especially in systems involving sensitive financial and personal data (Suh & Han, 2002.
Pavlou, 2.
The present findings suggest that security features such as biometric authentication, digital identity verification, and layered access Regita Bintari Prameswari & Lia Nirawati Celebes Scholar pg Journal of Social Commerce controls are not merely technical mechanisms but symbolic assurances that communicate reliability and institutional responsibility.
When users perceive these security measures as robust and effective, they are more willing to engage in repeated and sustained usage.
This reinforces the view that trust in digital banking is constructed through observable security practices rather than abstract claims of safety.
The findings highlight the interconnected nature of convenience, risk, and security in shaping digital banking usage decisions.
Convenience facilitates engagement by reducing effort and friction, security legitimizes continued use by reinforcing trust, and risk awareness reflects usersAo capacity to evaluate uncertainty without disengaging from the system.
This interaction aligns with extended technology acceptance frameworks that integrate trust and risk into usability-driven models (Pavlou, 2001.
Wang & Wang, 2.
By examining these dynamics within the specific context of SeaBank users in Surabaya, this study contributes to a more contextualized understanding of digital banking behavior and demonstrates that adoption theories must be interpreted in relation to usersAo experiential and socio-digital realities.
Conclusion This study set out to examine how convenience, risk, and security shape usage decisions in the context of SeaBank digital banking services among users in Surabaya City.
The findings demonstrate that these three factors jointly play a significant role in influencing usersAo decisions, confirming that digital banking behavior is formed through an integrated evaluative process rather than isolated considerations.
Convenience contributes by reducing operational complexity and supporting seamless user interaction, security strengthens trust by providing assurance over data and transaction protection, and risk reflects usersAo awareness and evaluation of uncertainty rather than outright resistance to usage.
Importantly, the results suggest that usage decisions in digital banking are not solely driven by technological efficiency but are deeply embedded in usersAo perceptions of control, assurance, and confidence.
The positive role of perceived risk indicates that users who are familiar with digital banking environments do not necessarily withdraw in the presence of risk.
Instead, they appear capable of weighing potential risks against perceived safeguards and benefits.
This finding reinforces the relevance of extended technology acceptance frameworks that integrate usability, trust, and risk as interconnected dimensions of user behavior.
Within the specific context of SeaBank, the study highlights that sustained usage depends not only on functional convenience but also on the credibility and reliability users associate with the platform.
References