INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026  
The Effect of Mobile Service Quality on Continuance Intention  
Mediated by Perceived Value and Customer Satisfaction Among  
Users of the Mytelkomsel App in Banda Aceh  
Nurul Shahira Ramadhani1, Syarifah Evi Zuhra2, Sayed Mahdi3  
Department of Management, Faculty of Economics and Business, Syiah Kuala University  
DOI: https://doi.org/10.51583/IJLTEMAS.2026.150600150  
Received: 27 June 2026; Accepted: 02 July 2026; Published: 17 July 2026  
ABSTRACT  
This study aims to examine the effect of mobile service qualityon continuance intention in the MyTelkomsel  
application, with perceived value and customer satisfaction as mediating variables. Data were collected through  
an online questionnaire distributed to 200 respondents who are users of the MyTelkomsel application in Banda  
Aceh, using a non-probability sampling technique with purposive sampling method. The results of the analysis  
indicate that mobile service qualityhas a positive and significant direct effect on continuance intention, perceived  
value, and customer satisfaction. Perceived value does not have a positive and significant direct effect on  
continuance intention and therefore does not mediate the relationship between mobile service qualityand  
continuance intention. Meanwhile, customer satisfaction has a positive and significant direct effect on  
continuance intention and partially mediates the relationship between mobile service qualityand continuance  
intention.  
Keyword: mobile service quality, perceived value , customer satisfaction, continuance intention, MyTelkomsel  
INTRODUCTION  
Indonesia has now entered an era of transformation characterized by increasingly rapid, uncertain, and complex  
changes. To survive in these conditions, the ability to adapt supported by digital technology has become essential  
for both individuals and organizations to survive and develop sustainably (Olivia & Kezia Marchyta, 2022). The  
internet plays a crucial role in supporting connectivity during the digital transformation process (Bumbungan,  
2025). In line with the increasing use of the internet, businesses that leverage mobile applications are  
experiencing growth and have expanded into nearly every aspect of life (Al-Debei et al., 2022). Companies and  
brands across various industries are better positioned if they can develop their own applications to meet customer  
needs (Sari, 2024). Application development by companies not only helps businesses remain relevant but also  
strengthens customer relationships, which ultimately fosters loyalty (Sharma, 2022).  
As one of the largest telecommunications companies in Indonesia, Telkomsel has launched the MyTelkomsel  
app as a self-service customer care solution. Customers can easily plan and select the services they want in a  
short amount of time. Currently, the MyTelkomsel app offers various key features, including account  
management, purchases and payments, entertainment, Telkomsel Points, customer service, health features, and  
lifestyle features (Telkomsel, 2025). MyTelkomsel continues to introduce various innovations to optimize the  
app’s functionality as a digital service platform. Currently, the MyTelkomsel app has been downloaded over 100  
million times, with a rating of 4.1 on Google Play and 4.7 on the App Store. Furthermore, user engagement and  
the app’s effectiveness are not only measured by the number of downloads and ratings but can also be analyzed  
through monthly active users (MAU) and total time spent in-app (Azzahra & Kusumawati, 2023).  
The collected data shows that the number of MyTelkomsel monthly active users increased from 6 million in  
2020 to 30 million in 2021, then rose to 32 million in 2022 and 35 million in 2023. In 2024, the number of MAUs  
rose again to 46 million and reached 58 million in 2025. Although it has shown an upward trend every year, this  
number of active users remains significantly lower than the total number of app downloads which has exceeded  
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100 million as well as Telkomsel’s total subscriber base. This situation indicates that not all users who have  
downloaded the app intend to continue using it on an ongoing basis. Although the app offers various  
conveniences, in practice, there are still numerous user complaints regarding app performance, such as errors,  
slow loading times, and the complexity of features. These issues suggest that the app’s service quality has not  
yet fully met user expectations, which could potentially affect users’ intention to continue using the app.  
Continuance intention is a behavior that emerges after the initial adoption phase, reflecting users’ intent to  
continue using the system (Limayem et al., 2007). Continuance intention is closely related to user experience  
(Jo, 2024). When the user experience is positive, customer satisfaction increases and retention is maintained,  
which ultimately helps reduce customer churn (Situmorang et al., 2025). The MyTelkomsel app was selected as  
the research subject because it exhibits an undesirable phenomenon related to the perceived quality of the app’s  
service, which affects users’ intention to continue using the app.  
Mobile service quality reflects the extent to which an app is able to meet the needs and requirements of its target  
users (Zhou et al., 2021). Previous research on apps has shown that service quality is a key factor that determines  
organizational performance while also influencing market share and profitability (Kar, 2021). However, the  
influence of mobile service quality on continuance intention is not always direct but occurs through users’  
cognitive and affective evaluation processes (Al-Debei et al., 2022). To assess this, this study uses perceived  
value as a form of cognitive evaluation and customer satisfaction as a form of affective evaluation, both of which  
are positioned as mediating variables.  
Perceived value is understood as consumers’ assessment of the value of products and services by comparing the  
benefits received with the sacrifices made (Zeithaml, 1988). Customers who assess that the service quality of a  
product or service has met or even exceeded their expectations tend to feel more satisfied and have an intention  
to continue using that service (Sharma, 2016). Furthermore, customer satisfaction reflects users’ evaluations  
while using an information system (Bhattacherjee, 2001). High levels of satisfaction are closely linked to higher  
levels of continuance intention (Chen & Demirci, 2019).  
Previous studies on mobile service quality, perceived value, customer satisfaction, and continuance intention  
still have limitations, indicating a significant research gap. Most have focused only on mobile banking apps (Inan  
et al., 2023), mobile shopping (Kim et al., 2021), or mobile government (Wang et al., 2020), while research on  
telecommunications-based apps remains limited.  
The use of the MyTelkomsel app, which is largely situational, poses a unique challenge in increasing users’  
continuance intention compared to other apps used daily. Therefore, this study aims to analyze how mobile  
service quality influences continuance intention, with perceived value and customer satisfaction serving as  
mediating variables, among users of the MyTelkomsel app in Banda Aceh.  
Objectives of the Study  
The primary objective of this study is to examine the relationship between service quality, perceived value,  
customer satisfaction, and continuance intention among users of the MyTelkomsel app in Banda Aceh. The  
specific objectives are:  
1. To determine the effect of mobile service quality s on continuance intention among users of the  
MyTelkomsel app in Banda Aceh .  
2. To determine the effect of mobile service quality on perceived value among MyTelkomsel app users in  
Banda Aceh.  
3. To determine the effect of mobile service quality on customer satisfaction among MyTelkomsel app  
users in Banda Aceh.  
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4. To determine the effect of perceived value on continuance intention among MyTelkomsel app users in  
Banda Aceh.  
5. To determine the effect of customer satisfaction on continuance intention among MyTelkomsel app users  
in Banda Aceh .  
6. To determine whether perceived value mediates the effect of mobile service quality on continuance  
intention among MyTelkomsel app users in Banda Aceh.  
7. To determine whether customer satisfaction mediates the effect of mobile service quality on continuance  
intention among MyTelkomsel app users in Banda Aceh.  
Research Questions  
Based on the objectives of the study, the following research questions arise:  
1. How does mobile service quality influence continuance intention among MyTelkomsel app users in  
Banda Aceh?  
2. How does mobile service quality influence perceived value among MyTelkomsel app users in Banda  
Aceh?  
3. How does mobile service quality affect customer satisfaction among MyTelkomsel app users in Banda  
Aceh?  
4. How does perceived value influence continuance intention among MyTelkomsel app users in Banda  
Aceh?  
5. How does customer satisfaction influence continuance intention among MyTelkomsel app users in Banda  
Aceh?  
6. How does mobile service quality influence continuance intention through perceived value among  
MyTelkomsel app users in Banda Aceh?  
7. How does mobile service quality influence continuance intention through customer satisfaction among  
MyTelkomsel app users in Banda Aceh?  
Research Hypotheses  
The following hypotheses were formulated to guide the study.  
H1 : Mobile service quality influences continuance intention  
H2 : Mobile service quality influences perceived value  
H3 : Mobile service quality influences customer satisfaction  
H4 : Perceived value influences continuance intention  
H5 : Customer satisfaction influences continuance intention  
H6 : Mobile service quality influences continuance intention through perceived value  
H7 : Mobile service quality influences continuance intention through customer satisfaction  
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LITERATURE REVIEW  
Continuance Intention  
Continuance intention is a user’s intention to continue using a system after initial use (Bhattacherjee, 2001).  
Continuance intention is a form of post-adoption behavior, that is, behavior that emerges after the initial adoption  
stage (Limayem et al., 2007). This variable can be understood as the degree to which a consumer intends to  
adopt a specific attitude or behavior. In line with this view, (Wu, 2017) defines continuance intention as an  
individual’s perception of the likelihood that they will continue to use a system or application in the future. Thus,  
continuance intention serves as a bridge between past usage experiences and actual future behavior.  
Perceived value  
Perceived value is understood as a consumer’s evaluation of a product’s value by comparing the benefits received  
with the sacrifices made in using a service (Zeithaml, 1988). Monroe (1990) (as cited in Al-Debei et al., 2022)  
states that perceived value is a trade-off between the costs and sacrifices perceived by the consumer and the  
perceived quality or benefits of the product or service. This concept emphasizes that the perception of value is  
formed through the consumer’s rational assessment of the service used.  
Customer satisfaction  
Customer satisfaction is an overall assessment of a user’s affective and cognitive responses regarding the extent  
to which their needs are met while using an information system (Bhattacherjee, 2001). From a marketing  
perspective, according to Kotler & Keller (2012), consumer satisfaction is a person’s feeling of pleasure or  
disappointment that arises after comparing their perceptions of the performance or results of the product they  
purchased with their expectations. Consumers will feel satisfied if the product or service they receive meets or  
exceeds their expectations; conversely, they will feel disappointed if the product or service’s performance falls  
short of their expectations. Furthermore, research by Fungai (2017) reveals that customer satisfaction is also  
defined as the number of customers or the percentage of the total customer base who, based on their assessment,  
exceed the satisfaction goals set by a company regarding its products or services.  
Mobile Service Quality  
Service quality is a multidimensional concept that has attracted widespread attention for research, particularly  
in the fields of marketing and information systems (Al-Debei et al., 2022). In the context of the mobile business,  
service quality can be defined as the functionality of mobile services and applications that are capable of meeting  
the needs and requirements of the target users (Zhou et al., 2021). Additionally, research conducted by Obinna  
C & Osarenkhoe (2018) defines service quality as the gap between the service performance perceived by  
customers and their expectations regarding that service.  
Stimulus-Organism-Response Theory  
The stimulus-organism-response (S-O-R) theory is a conceptual framework used to analyze consumer behavior,  
comprising three main components: stimulus, organism, and response (Jacoby, 2002). In the stimulus-organism-  
response model, the environment and information are positioned as stimuli that influence an individual’s internal  
processes, both cognitive and affective aspects (organism), which ultimately drive behavioral intentions (Bigne  
et al., 2020). The S-O-R model has been widely used in various studies and contexts within the field of  
information systems (Al-Debei et al., 2022; Chopdar & Balakrishnan, 2020). In the context of this study, the S-  
O-R model serves as the most appropriate theoretical foundation; the stimulus (S) represents mobile service  
quality. Furthermore, the organism (O) reflects internal conditions that include cognitive aspects, namely,  
perceived value, as well as affective aspects, namely, customer satisfaction. Finally, the formation of a specific  
behavioral outcome, which in this study takes the form of continuance intention, constitutes the response (R).  
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Figure 1 Research Framework  
RESEARCH METHOD  
Population and Sample  
In the context of this study, the population under investigation consists of users who have previously used the  
MyTelkomsel app in Banda Aceh. In this study, the researcher employed a non-probability sampling technique,  
specifically purposive sampling. According to Hair et al. (2018), sample size depends on the number of  
indicators contained in all the variables under consideration. The sample size should be equivalent to the number  
of indicators multiplied by a factor of 5–10. The total number of question indicators is 25. In this study, the  
researcher used a sample size of 8, so:  
n
= 8 × the number of indicators used  
= 8 × 25 indicators  
= 200 respondents  
Data Collection Techniques  
Based on the data collection method applied in this study, this research can be categorized as a survey study, in  
which a questionnaire serves as the primary instrument for data collection. The weight of each respondent’s  
answer is measured using a Likert scale.  
Analysis Method  
The data analysis method used in this study is SEM-PLS analysis. In this study, the data were processed and  
analyzed using SmartPLS software. This software was used to process and adjust statistical data; the PLS-SEM  
equation model was used because it is more suitable in the context of theory development and prediction.  
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RESEARCH RESULTS AND DISCUSSION  
Respondent Characteristics  
The characteristics of the respondents nhistudycan be seen in the following table:  
Table 1. Respondent Characteristics  
200  
200  
Source: Field Survey, 2026  
Research Instrument Testing  
Measurement Model Test (Outer Model)  
Table 2. Indicator Reliability Test  
Indicator  
Continuation Intention Customer  
Mobile Service Quality  
Perceived value  
satisfaction  
0.858  
0.891  
0.819  
0.905  
0.853  
0.916  
0.908  
0.919  
CI1  
CI2  
CI3  
CI4  
CI5  
CS1  
CS2  
CS4  
0.624  
0.767  
0.758  
0.735  
0.818  
0.761  
0.765  
0.828  
MSQ1  
MSQ3  
MSQ4  
MSQ5  
MSQ6  
MSQ7  
MSQ8  
MSQ9  
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0.744  
0.784  
0.848  
0.866  
0.906  
0.839  
0.899  
MSQ10  
MSQ11  
MSQ12  
PV1  
PV2  
PV3  
PV4  
Based on the table above, it appears that not all indicators meet the criteria for indicator reliability, namely having  
an outer loading value greater than 0.708 to indicate that each indicator is able to explain its construct well. There  
are two indicators that still have values below the required threshold. Indicators MSQ 1 and MSQ 2 appear to  
have values below 0.70, at 0.624 and 0.641, respectively, and thus do not meet the specified threshold. However,  
these two indicators can still be retained as long as they do not compromise the content validity of the measured  
variables. Thus, all variables in this study have met the requirements for the indicator reliability test, allowing  
the analysis to proceed to the next stage.  
Table 3. Internal Consistency Reliability Test  
Composite Reliability  
Composite  
Reliability (rho_c  
0.937  
0.939  
0.931  
Variable  
Cronbach’s Alpha  
(rho_a)  
0.918  
0.903  
0.903  
0.934  
Continuance Intention  
Customer satisfaction  
Perceived value  
0.916  
0.902  
0.901  
0.930  
Mobile Service Quality  
0.940  
From the table above, Cronbach’s alpha and composite scores are greater than 0.70 and do not exceed 0.95,  
meaning that all constructs in this study have good internal reliability and are consistent in measuring their  
respective constructs.  
Table 4. Convergent Validity Test  
Variable  
Average Variance Extracted (AVE)  
Continuance Intention  
Customer satisfaction  
Perceived value  
0.749  
0.836  
0.771  
0.591  
Mobile Service Quality  
The table above shows that all variables in this study demonstrate good convergent validity. This is indicated by  
AVE values greater than 0.50, meaning that all constructs in this study are valid and the variables are able to  
explain the variance of their respective indicators.  
Table 5. Discriminant Validity Test  
Variable  
HTMT  
0.861  
0.900  
0.847  
0.788  
0.886  
0.871  
Mobile Service Quality <-> Continuance Intention  
Mobile Service Quality <-> Perceived Value  
Mobile Service Quality <-> Customer Satisfaction  
Perceived Value <-> Continuance Intention  
Customer Satisfaction <-> Continuance Intention  
Perceived Value <-> Customer Satisfaction  
From the table above, it can be seen that all HTMT values have met the specified threshold, namely that the  
average correlation between constructs is below the required limit of <0.90. Thus, the discriminant validity in  
this study can generally be considered to have been met.  
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Structural Model Test (Inner Model)  
Table 6. Coefficient of Determination Test (R2 )  
R-square  
Adjusted R-square  
Continuance Intention  
Customer satisfaction  
Perceived value  
0.714  
0.632  
0.682  
0.710  
0.630  
0.681  
From the table above, the effect size values areR2 . All three values fall into the moderate category, so it can be  
concluded that the endogenous variance in this study can largely be explained by the exogenous variables.  
Table 7. Effect Size Test (f2 )  
Mobile  
Service  
Quality  
Customer  
satisfaction  
Continuance Intention  
Perceived Value  
Continuance Intention  
Customer satisfaction  
Mobile service quality  
Perceived value  
0.254  
0.154  
0.000  
1.716  
2.147  
From the table above, it can be seen that the value for customer satisfaction on continuance intention is 0.254,  
and the f² value for mobile service quality on continuance intention is 0.154. These fall into the moderate  
category, indicating a fairly strong or moderate influence of each variable on continuance intention. On the other  
hand, the relationship between mobile service quality and customer satisfaction shows an f² value of 1.716, and  
the relationship between mobile service quality and perceived value also has an f² value of 2.147, both of which  
are classified as very large, indicating a very strong and dominant influence. Meanwhile, the relationship  
between perceived value and continuance intention has an f² value of 0.000, which falls into the very small or  
insignificant category.  
Table 8. Predictive Relevance Test (Q2 )  
(퐐ퟐ )  
Continuance Intention  
Customer satisfaction  
Perceived value  
0.530  
0.523  
0.519  
From the table above, it can be seen that the Q² values for continuance intention (0.530), customer satisfaction  
(0.523), and perceived value (0.519) indicate that the model has a strong level of predictive relevance. This  
means that the model in this study has excellent predictive accuracy, where the mobile service quality variable  
is able to consistently predict the continuance intention variable through the mediation of perceived value and  
customer satisfaction.  
Direct Hypothesis Testing  
Table 9. Path Coefficients  
Original  
sample  
(o)  
Sample  
mean (M)  
Standard  
deviation  
(STDEV)  
T-statistic  
P-values  
Note  
Variable  
Mobile service quality ->  
Intention to continue  
Mobile service quality ->  
Perceived value  
0.409  
0.416  
0.083  
4.935  
0.000  
Significant  
0.826  
0.795  
0.826  
0.794  
0.028  
0.034  
29.347  
23.119  
0.000  
0.000  
Significant  
Significant  
Mobile service quality ->  
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Customer satisfaction  
Perceived value ->  
Continuance intention  
Customer satisfaction ->  
Continuance intention  
0.003  
0.479  
0.003  
0.474  
0.085  
0.092  
0.041  
5.221  
0.967  
0.000  
Not Significant  
Significant  
Based on the table above, the test results indicate that mobile service quality has a significant effect on  
continuance intention, with a T-statistic value of (4.935) > 1.96 and a p-value of (0.000) < 0.05. Therefore, it  
can be concluded that mobile service quality has a significant direct effect on continuance intention among users  
of the MyTelkomsel app in Banda Aceh.  
Next, regarding the effect of mobile service quality on perceived value, the t-statistic value was (29.347) > 1.96  
and the p-value was (0.000) < 0.05. Therefore, it can be concluded that mobile service quality has a significant  
direct effect on perceived value among users of the MyTelkomsel app in Banda Aceh.  
Furthermore, the test results showed the effect of mobile service quality on customer satisfaction, yielding a t-  
statistic value of (23.119) > 1.96 and a p-value of (0.000) < 0.05. Thus, it can be concluded that mobile service  
quality has a significant direct effect on customer satisfaction among MyTelkomsel app users in Banda Aceh.  
In contrast to the previous results, the effect of perceived value on continuance intention yielded a t-statistic  
value of (0.041) < 1.96 and a p-value of (0.967) > 0.05. It can therefore be concluded that perceived value does  
not yet have a significant direct effect on continuance intention among MyTelkomsel app users in Banda Aceh.  
Finally, the test results show that the effect of customer satisfaction on continuance intention is significant, with  
a t-statistic value of (5.221) > 1.96 and a p-value of (0.000) < 0.05. Thus, it can be concluded that customer  
satisfaction has a significant direct effect on continuance intention among users of the MyTelkomsel app in  
Banda Aceh.  
Table 10. Specific Indirect Effect  
Original  
sample  
(o)  
Sample  
mean  
(M)  
Standard  
deviation  
(STDEV)  
T-statistic  
P-values  
Note  
Variable  
Mobile service quality ->  
Not  
Significant  
Perceived value  
-> Continuance 0.003  
0.002  
0.375  
0.070  
0.072  
0.041  
5.280  
0.968  
0.000  
intention  
Mobile service quality → Customer  
satisfaction → Continuance intention  
0.381  
Significant  
Based on the indirect effect table, the test results for the effect of mobile service quality on continuance intention  
via perceived value yielded a T-statistic of (0.041) < 1.96 and a p-value of (0.968) > 0.05. Therefore, it can be  
concluded that mobile service quality does not have a significant effect on continuance intention via perceived  
value among users of the MyTelkomsel app in Banda Aceh.  
Furthermore, the test results show the effect of mobile service quality on continuance intention through customer  
satisfaction, yielding a T-statistic value of (5.280) > 1.96 and a p-value of (0.000) < 0.05. Thus, it can be  
concluded that mobile service quality has a significant effect on continuance intention through customer  
satisfaction among users of the MyTelkomsel app in Banda Aceh.  
CONCLUSION  
Based on the discussion of the research results presented in the previous section, the following conclusions can  
be drawn:  
1. Mobile service quality has a positive and significant effect on continuance intention.  
2. Mobile service quality has a positive and significant effect on perceived value.  
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3. Mobile service quality has a positive and significant effect on customer satisfaction.  
4. Perceived value has no significant effect on continuance intention.  
5. Customer satisfaction has a positive and significant effect on continuance intention.  
6. Perceived value does not mediate the relationship between mobile service quality and continuance  
intention.  
7. Customer satisfaction partially mediates the effect of mobile service quality on continuance intention.  
Based on the results presented, there are several recommendations for future research to obtain better results:  
1. Future research in the field of post-adoption of information systems is advised to explore other variables  
that may influence users’ continuance intention toward digital applications, such as trust, perceived  
usefulness, user experience, perceived enjoyment, and habit, which have strong potential to drive  
continuance intention.  
2. Telkomsel is advised to continue improving mobile service quality on the MyTelkomsel app. A key  
priority should be enhancing the app’s system stability to minimize errors and technical glitches that  
users still frequently experience. Additionally, the system’s response to user input and the app’s ability  
to handle customer complaints must be continuously optimized to ensure a more comfortable and  
consistent user experience.  
3. Although perceived value does not influence continuance intention, Telkomsel still needs to provide  
added value that is more relevant to users. This can be achieved through the development of features that  
support daily digital activities, personalized service programs, and promotional offers tailored to user  
needs.  
4. MyTelkomsel is advised to improve customer satisfaction by maintaining consistent service quality,  
providing responsive customer service, and offering promotions and services that align with user needs.  
5. MyTelkomsel is advised to continue boosting users’ continuance intention by improving the app’s  
quality. This is because users show a strong tendency to increase their usage frequency when the app’s  
quality improves. Additionally, a strategy is needed to encourage the use of the app in daily activities so  
that it is not only used when needed but also becomes part of users’ routines.  
6. This study was conducted exclusively among MyTelkomsel app users in Banda Aceh; therefore, the  
results cannot be generalized to users in other regions who may have different characteristics, usage  
behaviors, income levels, and digital service preferences. Future research could expand the model to  
include different regions and user characteristics.  
7. MyTelkomsel app users are advised to make more optimal use of the various digital service features  
available on the app, not just limiting themselves to purchasing data packages and checking data quotas.  
Utilizing other features, such as digital customer service, redeeming points, promotions, and  
entertainment services, can help users maximize their experience and increase the perceived benefits of  
using the app.  
REFERENCES  
1.  
Al-Debei, M. M., Dwivedi, Y. K., & Hujran, O. (2022). Why would telecom customers continue to use  
mobile value added services? Journal of Innovation and Knowledge, 7(4).  
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