Vol. 5, No. 11, November 2024
E-ISSN: 2723 - 6692
P-ISSN: 2723 - 6595
http://jiss.publikasiindonesia.id/
Journal of Indonesian Social Sciences, Vol. 5, No. 11, November 2024 2867
The Impact of Cashless Payment Policies on Consumer Behavior
at Kesiangan Coffee, Batam City
Brightness Bill Boy N
Batam Tourism Polytechnic, Indonesia
Email: jerisaragi[email protected]m
Correspondence: [email protected]
*
KEYWORDS
ABSTRACT
Cashless Payment Policy;
Consumer Behavior; Linear
Regression Analysis
This research aims to analyze the effect of cashless payment policy
on consumer behavior at Kesiangan Coffee, Batam City. With the
increasing use of technology in various aspects of life, especially in
the payment sector, it is important to understand how cashless
policies affect consumer behavior. This study used a survey method
with questionnaires distributed to 100 respondents. Data analysis
was conducted using SPSS software, and it included validity,
reliability, and linear regression analysis. The results showed that
the R-value was 0.128 and the R Square was 0.165, indicating that
only 16.5% of the variation in the cashless payment policy could be
explained by consumer behavior. The validity and reliability test
results show that all research instruments are valid and reliable, but
the influence of consumer behavior on this policy is still relatively
low. This finding suggests that other more dominant factors, such as
technological infrastructure, level of security, and consumer
demographics, influence the acceptance of cashless payments.
Therefore, it is recommended that relevant parties, such as financial
institutions and the government, focus on education and
infrastructure development to increase the acceptance of this
payment system among the public. Further research is needed to
explore other factors that play a role in influencing cashless payment
policies, so that more effective strategies can be implemented to
encourage the use of this technology in various sectors.
Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Introduction
Technological developments in the financial sector have driven the transformation of payment
methods in various industries, including the hospitality and café industries (Buhalis et al., 2019;
Sriekaningsih, 2020). One of the significant changes is the adoption of cashless payment methods that
are increasingly popular among consumers. The cashless payment policy makes transactions faster,
more efficient, and more secure (Rui, 2023). This is driven by the increasing penetration of financial
technology (fintech) and digital payment systems in Indonesia. According to a report from Bank
Indonesia (2022), digital payment methods have increased by 38% over the past two years, especially
in big cities such as Batam.
Kesiangan Coffee, as one of the businesses in the F&B (Food and Beverage) sector in Batam City,
has implemented a cashless payment policy to facilitate customer transactions. This policy is expected
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to attract more customers and increase customer loyalty by prioritizing the convenience and security
of transactions. In this context, company policies can influence consumer behavior, including policies
in the payment methods applied. As stated by Setiawan (2023), the adoption of cashless payment
systems significantly impacts consumer purchasing behavior, where convenience and efficiency are
often the determining factors.
Cashless payment systems offer convenience for consumers and provide benefits for
businesses (Agrawal, 2021). In a study by Amalia (2023), it was explained that the implementation of
digital payment policies in cafes and restaurants in several major cities in Indonesia, including Batam,
was able to increase operational efficiency by 25% and reduce errors in financial management. With
the adoption of this policy, entrepreneurs can also utilize transaction data to analyze consumer
spending patterns and develop more effective marketing strategies.
However, not all consumers immediately enthusiastically accept cashless payment policies.
Some studies show resistance from certain groups, especially those less familiar with digital
technology. According to Prasetyo (2022), one of the challenges in implementing cashless policies is
the digital divide, where some consumers unfamiliar with technology find it difficult to use this
payment method. Understanding consumer behavior in response to new policies like this is
important.
Consumer behavior is one of the important aspects that companies must consider in
determining their business strategy (Chou et al., 2020). Kotler (2021) revealed that consumer
behavior is influenced not only by the products or services offered but also by external factors such
as company policies, including payment methods. Therefore, exploring how cashless payment
policies affect consumer behavior is important, especially in the F&B sector.
A study conducted by Sari (2023) in Jakarta showed that cashless payments contributed to
increased consumer satisfaction. The study found that consumers who use digital payment methods
are more likely to return to the same establishment because they find the transaction more
convenient and secure. This finding is relevant to Kesiangan Coffee's policy, which also focuses on the
adoption of cashless payments.
In Batam City, one of the economic and tourism centers in Indonesia, the trend of using cashless
payments is increasing. This is supported by adequate technology infrastructure and high
smartphone penetration. With its strategic location, Batam is a frequent destination for local and
international tourists, most of whom are already familiar with cashless payments in their home
countries. Therefore, adopting this policy is expected to meet the needs of more modern and digital-
savvy consumers.
Kesiangan Coffee, one of the most visited cafes in Batam, has taken an important step by
implementing a cashless policy as one of the strategies to improve efficiency and attract new
customers. However, the extent to which this policy impacts consumer behavior, especially in terms
of satisfaction, loyalty, and intention to return, still needs to be studied further. A better
understanding of the effect of this policy will help Kesiangan Coffee's management strategize more
effectively in the future.
This research is important because it provides an empirical view of the effect of cashless
payment policies on consumer behavior. With increasing competition in the F&B sector, companies
must proactively understand their consumers' preferences and behaviors. The results of this study
are expected to provide valuable insights for Kesiangan Coffee and other businesses in similar sectors.
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The main objective of this study is to examine the effect of cashless payment policy on consumer
behavior at Kesiangan Coffee. This research is also expected to provide relevant suggestions for
entrepreneurs in Batam on how the cashless policy can be optimized to attract more consumers and
increase customer loyalty.
Thus, this research will contribute significantly to the literature on consumer behavior in the
context of modern payment technology adoption and provide practical insights for businesses in
Batam City that are considering or have implemented cashless payment policies.
Research Methods
This research uses a quantitative approach with a descriptive design. Data was collected
through questionnaires distributed to 100 respondents, who are Kesiangan Coffee consumers who
have used cashless payments. Data analysis was carried out using regression techniques to see the
effect of cashless payment policies on consumer behavior.
Results and Discussion
Description of Respondents by Age
The results obtained from the respondent questionnaire based on the age of the respondent
can be seen in the table below:
Table 1. Age of Respondents
Description
Frequency
Percentage
<20 Years
20
20 %
20-30 Years
50
50 %
31-40 Years
20
20 %
>40 Years
10
10 %
Total
100
100 %
Source: Processed data, (2024)
Table 1 shows the gender distribution of the study's respondents. Of the 100 respondents, 40%
were male, and 60% were female. This indicates that most respondents are female, which may reflect
a demographic attraction or preference towards Kesiangan Coffee. Understanding this gender
composition is important for designing more effective marketing strategies that meet customer
needs.
Description of Respondents Based on Gender
The results obtained from the respondent questionnaire based on the gender of the respondent
can be seen in the table below:
Table 2. Gender of Respondents
Description
Frequency
Percentage
Male
40
40 %
Female
60
60 %
Total
100
100 %
Source: Processed data, (2024)
Table 2 summarizes the age distribution of respondents. Most respondents (50%) were in the
20-30 age group, indicating that Kesiangan Coffee is more popular among young consumers. The < 20
and 31-40 age groups accounted for 20%, while the > 40-year-old age group was only 10%.
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Knowledge of this age distribution can help management determine the right types of products,
promotions, and marketing strategies to attract more customers from different age groups.
Description of Respondents Based on Frequency of Visit to Kesiangan Caffe
The results obtained from the respondent questionnaire based on the frequency of visits to
Kesiangan Caffe can be seen in the table below:
Table 3. Frequency of visits to Kesiangan Caffe
Description
Frequency
Percentage
1-2 Times per Month
30
30 %
3-5 Times per Month
50
50 %
>5 Times per Month
20
20 %
Total
100
100 %
Source: Processed data, (2024)
This table shows the frequency of respondents' visits to Kesiangan Coffee. Most respondents
(50%) visit the cafe 3-5 times monthly, indicating good customer engagement. Around 30% of
respondents visit 1-2 times per month, while 20% visit more than 5 times per month. This data
suggests that the cashless payment policy may increase the frequency of visits and provides insight
for management to design loyalty programs or promotions for frequent customers.
Validity test
The following table presents the validity test results to evaluate the suitability of the items in
this research questionnaire. The validity test aims to ensure that each question can effectively
measure the variable under study: the effect of cashless payment policies on consumer behavior.
Through this analysis, we seek to ensure that the instruments used can provide valid and reliable data
to support the research results.
Table 4. Validity Testing Results of Cashless Payment Policy (X)
Statement
R count
R table
Description
X1
0,805
0.195
Valid
X2
0,659
X3
0,720
X4
0,575
X5
0,786
Source: SPSS Data Output version 26, (2024)
The table above shows the validity test results for the Cashless Payment Policy variable (X). All
statements (X1 to X5) have a calculated R-value greater than the R table (0.195), with the calculated
R-value ranging from 0.575 to 0.805. This shows that all statements are valid and can be used to
measure this study's cashless payment policy variable.
Table 5. Results of Consumer Behavior Validity Testing (Y)
Consumer Behavior (Y)
Statement
R count
R table
Description
Y1
0,817
0.195
Valid
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Y2
0,692
Y3
0,707
Y4
0,672
Y5
0,819
Source: SPSS Data Output version 26, (2024)
The table above shows the validity test results for the Consumer Behavior (Y) variable. All
statements (Y1 to Y5) have an R-value greater than the R table (0.195), with the R-value ranging from
0.672 to 0.819. Based on these results, all statements are declared valid and can be used to measure
consumer behavior variables in this study.
Reliability Test Results y
The reliability test was carried out to measure the consistency and reliability of the research
instruments used. Reliability shows the extent to which the instrument can provide consistent results
when used repeatedly under the same conditions. In this study, the reliability test was carried out
using Cronbach's Alpha coefficient to ensure that each statement in the questionnaire could
consistently measure the variables under study, namely cashless payment policies and consumer
behavior. A Cronbach's Alpha value higher than 0.6 indicates a reliable instrument.
Table 6. Reliability Testing Results
No.
Variables
Cronbach Alpha
Description
1
Cashless Payment Policy
0,756
Reliable
2
Consumer Behavior
0,793
Reliable
Source: SPSS Data Output version 26, (2024)
The table above presents the reliability test results using Cronbach's Alpha coefficient for the
Cashless Payment Policy and Consumer Behavior variables. The test results show that both variables
have a Cronbach's Alpha value above 0.6, with a value of 0.756 for the Cashless Payment Policy
variable and 0.793 for the Consumer Behavior variable. Based on this value, both variables are
declared reliable, which means that the instruments used in the questionnaire are reliable and
consistent in measuring each research variable.
Normality Test y
The normality test was carried out to determine whether the data obtained in this study were
normally distributed. In this study, the normality test used the Kolmogorov-Smirnov method. This test
compares the distribution of sample data with the theoretical normal distribution. If the significance
value (Sig.) is greater than 0.05, then the data is declared normally distributed, which means that the
normality assumption is met for further statistical analysis.
Table 7. Kolmograv Smirnov test
One-Sample Kolmogorov-Smirnov Test
Unstandardized Residual
N
100
Normal Parameters
a,b
Mean
.0000000
Std. Deviation
2.53372230
Most Extreme Differences
Absolute
.108
Positive
.108
Negative
-.074
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Test Statistic
.108
Asymp. Sig. (2-tailed)
.062
c
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
Source: SPSS output version 26, (2024)
The table above shows the results of the Kolmogorov-Smirnov normality test with the number
of respondents N = 100. The resulting Test Statistic value is 0.108, and the significance value (Asymp.
Sig. (2-tailed)) is 0.062. Since the significance value is greater than 0.05, this indicates that the residual
data is normally distributed. Thus, the normality assumption is met so that parametric statistical
analysis can be continued for further testing.
Multiple Linear Analysis Test
The following table presents the results of the linear regression analysis that tests the effect of
the independent variable on the dependent variable. In this study, the independent variable is
Consumer Behavior, and the dependent variable is Cashless Payment Policy. This analysis aims to
evaluate the extent to which changes in consumer behavior can affect the cashless payment policy
implemented.
Table 8. Multiple Linear Analysis Test
Coefficients
a
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
B
Std.
Error
Beta
1
(Constant)
17.416
1.964
8.866
.000
TOTAL_Y
.122
.095
.128
1.281
.001
a. Dependent Variable: TOTAL_X
Source: SPSS output version 26, (2024)
The table above shows the regression analysis results for the model that tests the effect of the
variable Consumer Behavior (TOTAL_Y) on the dependent variable Cashless Payment Policy
(TOTAL_X). The B coefficient for the constant is 17.416, which means that when Consumer Behavior
is zero, the predicted value of the Cashless Payment Policy is 17.416. The B coefficient for Consumer
Behavior of 0.122 indicates that every one-unit increase in Consumer Behavior will increase the
Cashless Payment Policy by 0.122 units. The Sig. value for Consumer Behavior is 0.001, which
indicates that its effect is statistically significant. In addition, the standardized Beta value is 0.128,
indicating a weak but positive influence of Consumer Behavior on Cashless Payment Policy.
Determination Test (R )
2
The R² determination test evaluates the proportion of variation in the dependent variable that
the independent variables in the regression model can explain. In this study, the R² value provides
information about the extent to which Consumer Behavior contributes to explaining variations in
Cashless Payment Policy to identify the strength of the relationship between the two variables.
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Table 9. Test Coefficient of Determination
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the
Estimate
1
.128
a
.165
.906
2.547
a. Predictors: (Constant), TOTAL_Y
Source: SPSS output version 26, (2024)
The table above presents the regression analysis results that measure the relationship between
the TOTAL_Y variable (Consumer Behavior) and the dependent variable. The R-value of 0.128
indicates a weak relationship between the two variables. Meanwhile, the R Square value of 0.165
indicates that only 16.5% of the variation in the Cashless Payment Policy can be explained by
Consumer Behavior. The Adjusted R Square value higher than R Square, 0.906, indicates a significant
adjustment. Std. The error of the Estimate of 2.547 indicates the size of the error in the model
prediction. Overall, the model shows that the contribution of Consumer Behavior to the Cashless
Payment Policy is quite low, indicating the need for further analysis to improve the accuracy of
predictions.
Discussion
The regression analysis results show that the relationship between Consumer Behavior and
Cashless Payment Policy is weak, with an R-value of 0.128. This indicates that consumer behavior
does not significantly influence the cashless payment policy implemented. The R Square value of
0.165 indicates that only 16.5% of the variation in the policy can be explained by consumer behavior.
This suggests that other factors are more dominant in determining this payment policy.
The validity and reliability tests of the instruments used in the study showed that all question
items were valid and reliable. Although the instrument has been tested, the effect obtained is still
relatively low. This indicates the need for further exploration of other variables that play a role in
cashless payment policies, such as government policies and technology adoption.
Research by Sari and Iskandar (2023) shows that the adoption of cashless payment technology
is influenced by consumer behavior and external factors such as technological infrastructure. Good
infrastructure availability contributes to higher adoption, showing the importance of government
support in digital infrastructure development.
On the other hand, consumer awareness of the benefits of cashless payments also affects their
acceptance. According to Putri and Wibowo (2022), education provided by financial institutions and
service providers is essential to increasing consumer understanding of these benefits. If consumers
do not understand this system's benefits and convenience, they will likely be reluctant to adopt it.
Security is also a major concern for consumers. Research by Rahayu and Supriyadi (2022)
revealed that data and transaction security concerns are major barriers to adopting cashless
payments. Therefore, service providers must improve security systems and assure consumers that
their transactions are safe.
Another obstacle faced is the diversity of consumer demographics. According to Sari and
Rahayu (2023), age and education affect the acceptance of cashless payment technology. Younger
consumers tend to adopt new technologies faster than older consumers. This emphasizes the need
for marketing strategies tailored to demographic characteristics.
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Internet penetration rate and smartphone usage are also important factors. Research by
Hidayah and Setiawan (2024) shows better cashless payment adoption rates in areas with good
internet access and high smartphone usage. This suggests developing a supportive digital
infrastructure to encourage further adoption.
Third-party involvement, such as fintech companies, also plays an important role. Research by
Wijaya and Prasetyo (2023) revealed that partnerships between banks and fintech companies can
increase consumer confidence in cashless payment services. By offering more innovative and easy-
to-use products, consumers will be more interested in switching to this payment method.
Overall, although there is a relationship between consumer behavior and cashless payment
policies, the contribution is relatively small. The results of this study suggest that to improve the
effectiveness of cashless payment policies, a multifaceted approach that includes education,
infrastructure improvement, and security enhancement is necessary. Further research should be
conducted to explore other factors that may influence this policy and find more effective ways to
increase the acceptance of cashless payments among consumers.
Conclusion
Based on the analysis's results, the relationship between consumer behavior and cashless
payment policy has an R-value of 0.128 and an R Square of 0.165. This indicates that only 16.5% of
the variation in cashless payment policies can be explained by consumer behavior, while other factors
influence the rest. Validity and reliability tests also show that the instruments used in this study are
valid and reliable.
To improve the effectiveness of cashless payment policies, it is recommended that related
parties, such as financial institutions and the government, focus on developing infrastructure and
educating the public about the benefits and security of this payment system. In addition, further
research should be conducted to explore other factors that influence the adoption of cashless
payments, such as technology penetration rates and consumer demographics. A more comprehensive
and data-driven strategy is needed to encourage the acceptance of cashless payments among the
public so that the objectives of using this technology can be achieved optimally.
Future research should focus on exploring the role of external factors such as technological
infrastructure, regulatory environment, and socio-cultural influences in determining the adoption of
cashless payment systems. Additionally, studies could investigate the effectiveness of targeted
educational programs in increasing consumer awareness and reducing barriers to adoption,
particularly for demographic groups less familiar with digital payment technologies.
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