*Corresponding author Email: [email protected] P-ISSN : 2252-8997 Asia-Pacific Management and Business Application, 11, 3 (2023): 363-378 E-ISSN: 2615-2010 ARTICLE
Asia-Pacific Management and Business Application 11 (3) 363-378
©UB 2023 University of Brawijaya Malang, Indonesia http://apmba.ub.ac.id
Gaining User Satisfaction of KAI (Indonesian Railways Company)-Access: E‐Service Quality Dimensions as Antecedent Through E‐Trust
Andrieta Shintia Dewia Astri Wulandarib*
Agus Rahayuc Heny Hendrayatid
a,c,dManagement Doctoral Program, Universitas Pendidikan Indonesia; bMarketing Management Diploma Program, Telkom Applied Science School
Abstract
BUMN (Indonesian State Owned Company) companies participating in the development of the digital industry are PT. KAI (Indonesian Railways Companies). In 2014, PT. KAI launched an official mobile application to make it easier for users to find information about trains. Online shopping has become more popular as the internet and e-commerce continue to expand. In order to sell their wares online and stay ahead of the competition, businesses must provide reliable online services. The purpose of this research was to contribute to the literature by examining the link between e-service quality (efficiency, privacy, reliability, emotional benefits, and customer service), e-satisfaction, and e-trust. In this study using explanatory statistics, with SEM (Structural Equation Modeling) analysis techniques through data processing software SMART PLS 3.2.9. The researcher used a random sample method to collect data from 400 participants. The results of this research corroborate the existence of a positive connection between the two primary concepts of the measuring model under investigation: e-satisfaction and e-trust. E-trust is a prerequisite for e-satisfaction, and an app may make Indonesian customers happy if it provides them reasons to trust it. This study's findings indicate that a consumer's level of post-purchase happiness is significantly impacted by how they perceive their trust to have been treated. An improvement in the quality of e-services will have a positive effect on consumers, who will make more purchases in the future.
Keywords
E-Service Quality Dimensions; E-Trust, E-Satisfaction; KAI-Access.
Received: 23 February 2023; Accepted: 15 March 2023; Published Online: 30 April 2023
DOI: 10.21776/ub.apmba.2023.011.03.8
Introduction
More clients are purchasing online as the internet and e-commerce increase.
Companies use internet marketing to sell items via websites and acquire a competitive edge (Venkatesh et al., 2012;
Redjeki & Affandi, 2021). Many shops have added internet channels in recent years, becoming multi-channel (Frasquet et al., 2017; Kondo & Okubo, 2022). Service quality and e-service quality have become key marketing study subjects owing to their
influence on company finances (Kim and Lennon, 2017; Demir et al., 2021). Superior electronic services might provide a competitive edge (Yarimoglu, 2015; Lestari et al., 2020).
According to Google and Temasek, Indonesia's digital economy hit $40 billion in 2019, up from $8 billion in 2015, making it the fastest-growing in ASEAN. The Minister of Industry stated Indonesia needs and has potential in the digital economy, as seen by its volume and 49% annual growth (Lingga, 2019). PT. KAI is a BUMN company developing the digital sector. PT. KAI established a smartphone app in 2014 to provide train information. KAI Access is the app. This five-million-download software makes buying tickets online simpler (Tirto.id, 2019).
KAI Access has application difficulties during installation. The application server or functions often break. The program generally crashes after being updated or when traffic is strong. PT. KAI functionalities are inaccessible while the server is offline. KAI Access' flaws harm user happiness. This is clear from the numerous unfavorable reactions on social media, such as Instagram or Twitter, made directly to PT. KAI or reviews on different apps expressing displeasure (Franedya, 2019). In Figure 1.3, numerous consumers on the Appgroves application review site are dissatisfied; KAI Access received 63.6% unfavorable ratings.
On review websites, 63.6% of reviews are unfavorable. Since 2015, there have been app complaints.
Negative reviews include a user who doesn't obtain a purchased ticket, has trouble accessing the app, or can't cancel or reschedule when the KAI Access app is updated. Al Dweeri (2019) suggests that satisfaction may be assessed by several aspects, including online satisfaction (e- satisfaction). Efficiency, privacy, reliability, emotional benefits, and customer service.
This study indicated that efficiency, reliability, emotional benefits, and customer
service are significant in judging e-service quality, but still not in privacy. E-trust precedes e-satisfaction, and behavioral loyalty before attitudinal loyalty. This research evaluates efficiency, privacy, reliability, emotional benefits, and customer service connected to communication and responsibility. Which responsibilities given to users regarding the fulfillment of e-service quality.
KAI Access was developed to make railway ticket transactions simpler for customers, however challenges in its implementation render it inefficient. Borissova et al. (2020) defines efficiency as not wasting time, effort, or money. On August 13, 2019, PT. KAI customers had trouble booking rail tickets due to an application update. As a result, passengers who want to buy train tickets can only be served offline or manually. This causes customers to arrive early and wait, slowing down ticket sales (Hadi, 2019).
PT. KAI respects its users' privacy.
According to Anic et al. (2019), e-commerce privacy is the user's readiness to reveal personal information before purchasing or selling. This information must be protected so it's not abused. KAI Access questioned the application's privacy. In 2016, someone reverse-engineered the KAI Access program and uncovered various flaws. Email addresses, private addresses, identification numbers, and birth dates might be obtained by irresponsible parties. This is harmful when an account is hacked and the password is changed since there is no account authorization mechanism or warning to the original user. The API request URL doesn't have an SSL Certificate, therefore the data isn't secured, which is risky (Suandi, 2016).
LinkAja is an electronic payment option for KAI Access subscribers. In this payment method, direct debit payments may be made without entering the LinkAja pin, although this might hurt consumers. KAI Access user receives a notice stating an unknown person's LinkAja balance was used to purchase railway tickets. This happened without the account proprietors' awareness. Direct debit
Gaining User Satisfaction of KAI (Indonesian Railways Company)-Access... 365 helps reckless people. When someone's KAI
Access account is hacked, they may use LinkAja to pay. This is detrimental for users' security (Wardhana, 2019).
Parkurár et al. (2019) defines reliability as the company's capacity to supply proper and promised services to consumers. The company's services must satisfy customers.
Companies must offer dependable services, however the KAI Access application is unreliable since it's regularly offline.
Unusable features include login issues with KAI Access. The user has tried deleting cache data, logging in again, uninstalling and reinstalling the program, but nothing has worked. My Trip, which displays ordered rail tickets, doesn't operate correctly. When you pay, the order isn't shown. This confuses users, and the booking check function cannot be utilized thus users cannot see their own e- tickets.
As said, the fourth component is the emotional benefit of utilizing the software.
Emotional benefit is customer pleasure. User reaction improves with service quality (Tetanoe & Dharmayanti, 2014; Wang et al., 2019). Due to the application's limitations, KAI Access users express displeasure. App Store and Appgrooves have KAI Access customer reviews. Many individuals offer one star, the lowest rating. Some reviewers vent their fury and use harsh language to convey their unhappiness with the software.
In Appgrooves, people still expressed dismay or criticized KAI Access and offered negative reviews.
The last factor is customer service.
According to Følstad (2018) and Ashfaq et al.
(2020), customer service makes it easier for consumers to satisfy their interests.
Companies must also provide problem- solving services. PT. KAI has customer service, but what occurred with KAI problems? Problematic access users are
unsatisfied. The replies on PT. KAI's social media account look templated.
The research generally suggests that e- customer satisfaction will be impacted by how high the quality of the e-service is (Rita et al., 2019). Additionally, it was shown that consumer confidence in service providers is increased by the quality of electronic services (Kong et al., 2020). Additionally, e-trust was shown to be a significant predictor of online purchase (Çiftçi & Çizel 2020). However, there has also been discussion in recent years on the causative link between the causation of e-service quality, e-satisfaction, and e-trust.
Previous research has shown that e-service quality does not always affect e-satisfaction and e-trust.
This research investigates the causal link between dimensions of e-service quality (efficiency, privacy, reliability, emotional benefits, and customer service), e- satisfaction, and e-trust. The suggested model's e-service quality dimensions are based on four models. A detailed assessment of these e-services' quality will reveal their direct and indirect linkages. While service quality has been studied in many settings, e- retailing (Kumar et al., 2020) and eastern contexts have received less attention (Al- dweeri et al., 2017; Raza et al., 2020). E- service consumers are harder to impress and keep (Kao and Lin, 2016; Gupta et al., 2020).
This check will help determine their pleasure and trust. Increasing electronic service provider sales volume, market share, cross- selling, and client retention (Gera et al., 2017;
Van der Borgh et al., 2023). Based on the foregoing explanation, the researcher plans to undertake study titled "GAINING USER SATISFACTION OF KAI ACCESS: E- SERVICE QUALITY DIMENSIONS AS ANTECEDENT THROUGH E-TRUST".
The following figure is a model framework for this research.
Figure 1. Conceptual Research Model’s
Source: Processed by Researchers, 2022
Hypothesis Development
According to Al Dweeri et al. (2018), efficiency can affect e-trust. Efficiency relates to application information content, design, and information that is always updated so as to provide convenience in online transactions. When users feel facilitated, the level of e-trust will also increase.
H1: The efficiency of e-service quality has a positive and significant effect on the e-trust of users of the KAI Access application in Indonesia.
According to Al Dweeri et al. (2018), in terms of privacy the most visible aspect is the privacy policy of an application which explains how companies use and manage customer information to perform services in the application. Privacy is not a factor that is too influential in e-service quality or e- satisfaction of an application but rather online trust, but when trust can be influenced by privacy it will also affect e-satisfaction.
H2: Privacy from e-service quality has a positive and significant effect on the e-trust of KAI Access application users in Indonesia.
According to Al Dweeri et al. (2018), reliability is the most powerful factor influencing e-trust, because reliability relates to the perfection of the company in performing services starting from timeliness in providing services, presenting products according to what customers want quickly and precisely, and the company's ability to present service without making a mistake.
H3: The reliability of e-service quality has a positive and significant effect on the e-trust of users of the KAI Access application in Indonesia.
According to Al Dweeri et al. (2018), emotional benefits are related to feelings of pleasure when using applications, customers enjoy the purchase process in applications, and service customization. When customers get this when using or after using it, it means that customers go to online trust or e-trust.
H4: The emotional benefits of e-service quality have a positive and significant effect on the e-trust of KAI Access application users in Indonesia.
Quality of e-services may be evaluated in part by how well they interact with customers, as stated by Al Dweeri et al. (2018). Customer service can affect e-trust. Customer service relates to building relationships with consumers in providing services to meet consumer needs. When consumer needs can be met, the relationship with consumers will be tighter and the level of e-trust will be higher.
H5: Customer service from e-service quality has a positive and significant effect on the e- trust of KAI Access application users in Indonesia.
The ability to maintain client confidentiality and consistently provide the highest quality service or product is essential to building lasting relationships with those customers.
Effective customer service and genuine interest in the company's success are the
H2
H1
H3
Efficiency (X1) Privacy (X2)
E-Satisfaction (Z) E-Trust (Y) Emotional Benefit (X4)
Customer Service (X5) Reliability (X3)
H4
H5
H7
H6
Gaining User Satisfaction of KAI (Indonesian Railways Company)-Access... 367 cornerstones of a trustworthy relationship
(Chi et al., 2020). According to Rita et al.
(2019), companies doing business online should focus on building customers' confidence in them before trying to make them happy. E-trust is claimed to have an indirect effect on e-satisfaction, according to some researchers (Juwaini et al., 2022).
Pizzutti et al. (2022) propose that customer trust assessments before an exchange event affect post-purchase pleasure. E-trust predicts e-satisfaction in prior research (Trivedi & Yadav, 2020).
H6: E-trust has a positive and significant effect on the e-satisfaction of KAI Access application users in Indonesia.
Efficiency, privacy, reliability, emotional benefits, and customer service might impact e-satisfaction through e-trust, according to Al Dweeri et al. (2018). Increasing these e- service quality elements will boost e- satisfaction. Conceptual and practical definitions of e-satisfaction vary. Khan et al.
(2019) uses "feeling", Kaya et al., (2019) use
"affective reaction," while Çelik (2021) use
"experience", say a user will quit a website if it doesn't suit their demands. Customer happiness begins with a website's homepage.
Khan et al. (2019) found that e-service quality may increase customer satisfaction and competitive advantage in e-commerce.
H7: E-service quality has a positive and significant effect on e-satisfaction through e- trust of KAI Access application users in Indonesia.
Method
The results of this study can be used as material for consideration for company management and utilized as a foundation for future research. Practically, the results of this research can be used as input for PT. KAI as the owner of the KAI Access application and the company that will organize or issue its digital products. Theoretically, the results of this study will show how much impact efficiency, privacy, reliability, emotional benefits, and customer service have on the
trust (e-trust) and satisfaction (e-satisfaction) of KAI Access users in Indonesia.
This study employs quantitative research techniques since it makes use of numerical data and statistical computations and seeks to evaluate previously formulated hypotheses.
All Indonesian KAI Access users, the actual number of whom is unknown, comprise the study's population. Users of the KAI Access application in Indonesia who have used and transacted using the application make up the sample in this research. The Lemeshow formula may be used to calculate the sample size when the population in a research is unknown since it is not known in this case.
Because of the high degree of statistical confidence (95%) and low error rate (d=5%), the Lemeshow formula requires 385 people in this study to be included in the analysis;
nevertheless, the researchers decided to include more participants to bring the study's final sample size closer to 400.
PLS was utilized to analyze the data in this study. It is possible to describe the theoretical link between the study variables and to estimate latent variables with the aid of PLS.
Reliability and validity are ensured by using a measurement model, and causes are deduced using a theoretical framework (hypothesis testing with prediction model). In the context of a formal model, a latent variable is a linear combination of other variables. The weight estimate for producing latent variable score is influenced by both the internal model (a structural equation that links latent variables) and the exterior model (a measuring model that specifies indicators and constructions).
Results
SmartPLS, version 3.2.9, was used in the lab tests. A SmartPLS consists of two sub- models, a measurement model and a structural model, which are the outer and inner models, respectively.
Outer Model. Relationships between indicators and latent variables are specified
using the outer model. In order to ensure the accuracy of the measuring model (external model), it is crucial to assess the robustness of the indicators used. Testing was completed
out utilizing SmartPLS 3.2.9 software. The following graphic depicts the outer model used in this investigation.
Figure 2. Outer Model of SEM
Source: Data Processed by Researchers, 2022
When there is a high degree of correlation between the results of different concept- measuring instruments or concept- evaluation processes, we say that they have convergent validity. Convergent validity of the measurement model may be evaluated by looking at the relationship between the indicator score and the variable score. If the AVE (Average Variance Extracted) value of an indicator is more than 0.6, the measurement passes the convergent validity criterion (Chin, 1998 in Ghozali, 2014:39).
In addition to the validity test, each of the
existing variables was subjected to a reliability test. The reliability test determines how far a measurement on the same item may generate the same data (Hair et al., 2020). Both Composite Reliability and Cronbach's Alpha may be used in the reliability analysis of a Partial Least Square (PLS) model. A composite reliability value of 0.70 or higher, or a Cronbach alpha value of 0.60 or higher, is required before a variable may be regarded credible.
(Ghozali, 2014).
Gaining User Satisfaction of KAI (Indonesian Railways Company)-Access... 369 Table 1. Outer Model Test Results
Latent
Variable Questionnaire Indicator Items
Validity Test Reliability Test Loading
Factor Result Cronbachs Alpha
Composite
Reliability Result
Efficiency (X1)
Applications can make it easier for users to
find what is needed 0.810 Valid
0.926 0.945 Reliable
Can make transactions quickly 0.921 Valid
Can load pages quickly 0.911 Valid
Easy to use application 0.884 Valid
The application is well organized 0.869 Valid
Privacy (X2)
Can protect information related to behavior
in using the application 0.745 Valid
0.833 0.889 Reliable
The application does not share personal
information with other parties 0.788 Valid The application can protect the user's credit
card information 0.874 Valid
The application provides a symbol or message indicating that this application is safe to use
0.856 Valid
Reliability (X3)
The application provides services as
promised 0.849 Valid
0.932 0.946 Reliable
The application provides services in the form
of e-tickets with timely delivery 0.859 Valid The application delivers the appropriate
order quickly 0.849 Valid
The application sends products that have
been ordered 0.838 Valid
The application provides products according
to what has been offered 0.877 Valid
The application makes accurate promises
about product delivery 0.909 Valid
Emotional Benefit (X4)
There is a joyful feeling when using the
application 0.901 Valid
0.841 0.904 Reliable
There is a feeling of joy when using the
application 0.855 Valid
There is a feeling of pleasure when using the
application 0.856 Valid
Customer Service (X5)
Apps are ready and willing to respond to
consumer needs 0.791 Valid
0.877 0.910 Reliable
Customer service employees are always
willing to help consumers 0.844 Valid
Questions answered quickly 0.831 Valid
When the application has a problem, the application shows a good will to solve the problem
0.837 Valid After sales service on the application is very
good 0.788 Valid
E-Trust (Y)
I believe the app is safe and has reliable
features. 0.809 Valid
0.845 0.896 Reliable
I trust transactions made in the app. 0.870 Valid I believe the app keeps customers' financial
information safe. 0.816 Valid
I believe the app keeps customer's private
information safe. 0.811 Valid
E-Satisfaction (Z)
Customers are happy with the services
provided. 0.826 Valid
0.822 0.882 Reliable
Customers are satisfied with the decision to
make purchases through the application. 0.800 Valid Customers feel that making purchases
through the application is correct. 0.829 Valid Customers feel satisfied after making
purchases in the application. 0.775 Valid Source: Data Processed by Researchers, 2022
The reliability of the loading factor score derived from the study items is shown in Table 1. If the loading factor score you got was more than 0.7, then you're on to something real and might advance. Next, we'll look at the reliability rating we got.
Table 1 shows that evaluations of e-service quality (including efficiency, privacy, reliability, emotional benefits, and customer service), e-trust, and e-satisfaction, all exceed 0.7 on the Cronbarch's Alpha and Composite Reliability scales. The study's instruments were reliable as shown by their accuracy, precision, and consistency in the reliability tests conducted.
Inner Model. As a measure of goodness- of-fit, R-squared may be used to examine the internal consistency of a model.
Coefficients of determination (R) of 0.75, 0.50, and 0.25 showed the model's are robustness, moderateness, or weakness may be estimated using these values. In addition to the R-Squared value, the predictive significance of the PLS model may be assessed by removing the training data and running the model blind. Additionally, a t- test was used to analyze the latent variable's impact on the predictor. The t-test and the values of the parameter coefficients are then used to assess the effect and significance (Ghozali & Latan, 2015).
Figure 3 Inner Model of SEM
Source: Data Processed by Researchers, 2022
In this research, we assessed the degree of association between the variables using R- squared analysis the dependent variable and outside influences. It is generally accepted that the quality of a projected model
improves as the R-Square value attained in a study increases. An additional test was performed on the internal model (structural model) to determine influence and relevance by examining the parameter
Gaining User Satisfaction of KAI (Indonesian Railways Company)-Access... 371 coefficient values and the statistical
significance value (Ghozali & Latan, 2015).
The t-table value of 1.9659 and the results of the tests of hypotheses in this study (with
a 5% significance level for the two-tail test) are shown below.
Table 2. Inner Model Test (Hypothesis Test and Coefficient of Determination)
Relationship Path
Coefficient t-Statistics P Values
Critical
Value Conclusion R- Square Efficiency -> E-Trust 0.250 4.770 0.000 1,9659 Ho rejected,
H1 accepted
0.840 Privacy -> E-Trust 0.123 2.715 0.007 1,9659 Ho rejected,
H2 accepted Reliability -> E-Trust 0.259 4.527 0.000 1,9659 Ho rejected, H3 accepted Emotional Benefit -> E-Trust 0.115 3.240 0.001 1,9659 Ho rejected, H4 accepted Customer Service -> E-Trust 0.257 3.359 0.001 1,9659 Ho rejected, H5 accepted E-Trust -> E-Satisfaction 0.810 46.636 0.000 1,9659 Ho rejected,
H6 accepted 0.657 E-Service Quality -> E-Trust -
> E-Satisfaction 0.163 3.697 0.002 1,9659 Ho rejected, H7 accepted Source: Data Processed by Researchers, 2022
Causation may be determined using the t- value computed along the path linking the model variables (shown in Figure 3), where the upper bound of the t-value shows a substantial association with a value >
1.9659. Data analysis shows As can be seen in Table 2, the t-value for the whole hypothesis is more than 1.9659, hence it must be accepted.
The magnitude of the influence of the independent variables on the dependent variable can be seen from the calculation of the coefficient determination. Based on the calculation of the coefficient determination in e-trust, a value of 0.840 is obtained. This shows that the influence of the independent variables (efficiency, privacy, reliability, emotional benefits, and customer service) on the dependent variable (e-trust) has an effect of 84.0% and the rest is influenced by other factors of 16.0% which was not carried out in this study. Meanwhile, the combined 65.7% of e-satisfaction variables can be explained by e-trust and elements of e-service quality activities variables. While other factors around 34.4% not examined in this research account for the remainder.
Discussion
In the partial test (t), the efficiency variable has a significant and positive effect on the e-trust variable. This can be seen in the calculated t value (4.770) which is greater than t table. This research proves something similar to the research of Asfour & Haddad (2014) where the efficiency factor influences e-trust. Consistent with the findings of Hansen and Jonsson, we find that the efficiency of an e-service has an effect on consumers' happiness with and faith in online purchases related to our first dimension of e-service quality. Perhaps the students in our sample were already well- informed about the items before visiting the website, but neither the knowledge necessary to execute transactions nor that required to build a decent and beautiful design affected the happiness or confidence of buyers. While prior research has shown that efficiency does impact e-satisfaction and e-loyalty, our finding contradicts that evidence (e.g. Kao & Lin, 2016).
The second variable is privacy, where this variable has a positive and significant effect on the e-trust variable. This can be seen from the t count (2.715) which is greater
than the t table. This research proves something similar to the research of Al- Adwan & Al-Horani (2019). The reason for this finding can refer to users who have experience to be able to assess the security of an application due to a large amount of knowledge (Al-Adwan & Al-Horani 2019).
Second, privacy. Despite being a major factor in e-service quality, privacy and esatisfaction were unrelated. E-trust, however, had a good impact. This finding might suggest that privacy perceptions were more impactful on trust owing to risk and privacy concerns being a significant cause for the absence of electronic and mobile commerce (Al Masarweh et al., 2016). Due to the absence of safe electronic infrastructure, which limits electronic transactions on KAI Access application, KAI Access users are typically more worried about privacy and security than being happy. KAI Access application customers are more inclined to trust a website with these privacy precautions.
Researchers disagree on the importance of privacy while evaluating a website's offerings. According to the results, privacy positively influences consumer trust more than satisfaction: ensuring the protection of personal and financial data and the security of transactions positively affects the quality of services offered by a website and has an indirect effect on behavioural and attitudinal loyalty. Our analysis validates prior research on e-trust development (Xu et al., 2020), which found that a guarantee of privacy lessens consumer fears about illicit data exposure, leading to increased e-trust.
Next is reliability, where the variable has a positive and significant effect on the e-trust variable. This can be seen from the t count (4.527) which is greater than the t table. The results of this study are similar to the research of Shin (2021). This is because users already feel the service or quality that is owned by the KAI Access application, for example, such as having received the product according to the promised time and the suitability of the product because these things can increase user satisfaction.
Authors like Besalú & Pont-Sorribes (2021)
concur that reliability is the most crucial element when evaluating electronic services. Keeping one's word and providing the promised products or services on schedule are shown to increase e- satisfaction, e-trust, and behavioural and attitude loyalty. Delivery of purchased products in a timely manner was seen as favorably influencing e-trust and attitude loyalty, leading customers to speak well of the website and even suggest it to others.
The next variable is emotional benefit, this variable has a significant and positive effect on the e-trust variable. This can be seen in the t count (3.240) which is greater than t table. This study proves something similar to Al Dweeri's research (2018), which proves that emotional benefits affect e-trust.
Consistent with previous research, our findings suggest that a website's aesthetics, originality, emotional resonance, portrayal, and attractiveness all contribute to users' sense of pleasure and confidence in their online interactions with the site (Husain et al., 2022). These writers verify the importance of emotional advantage in determining both relationship longevity and propensity to buy. This is in line with our findings, however we did find that emotional appeal had a far larger impact on e-trust than on satisfaction.
Furthermore, customer service has a significant and positive effect on the e-trust variable. This can be seen in the t-value (3.359) which is greater than t-table. This study proves something similar to Al Dweeri's research (2018) which proves that customer service has an effect on e-trust.
Our research shows that it's crucial for KAI Access managers in Indonesia to demonstrate a readiness to react to customer requests and answer queries swiftly if they want to win their customers' confidence. In order to gain e-trust and e-satisfaction from their customers and, by extension, a competitive edge of online businesses should demonstrate a genuine desire to help them with any issues they may encounter during a purchase or thereafter. Despite the study's small sample size, these findings are
Gaining User Satisfaction of KAI (Indonesian Railways Company)-Access... 373 consistent with those of previous research,
including those by Rahayu (2021). We also discovered that satisfaction with customer service has a little effect on customers' propensity to remain loyal in both action and outlook. Additionally, this study's findings suggest that consumers are most happy when they get an emotional value from a service or product, and that confidence in the website's dependability is the most significant aspect in assuring repeat business.
Efficiency, privacy, reliability, emotional benefits, and customer service all have a significance value of less than 0.05, according to the data. Since e-trust is directly linked to e-satisfaction, we can rule out H0. The computed t value of 46.636 is more than the significance level of 1.9659, indicating that e-trust significantly affects e-satisfaction. The direction of the connection between the two variables is positive, as shown by the parameter coefficient value being positive (0.810). As a result, it's clear that users' levels of e-trust in the KAI Access application service might vary. The findings of this study corroborate previous studies by demonstrating a positive correlation between the two primary components of the measuring model: e-satisfaction and e-trust. KAI Access users are more likely to be happy with an online shopping experience if they have good reason to trust the site they are using. This study's findings corroborate those of Jamshidi & Rousta (2021), who hypothesized a causal link between consumers' trust assessments and their levels of pleasure after making a purchase.
In the hypothesis test by mediating variables, e-service quality variables consisting of efficiency (X1), privacy (X2), reliability (X3), emotional benefits (X4), and customer service (X5) simultaneously have a positive effect on variable e- satisfaction (Z) through the mediation of the e-trust variable (Y). This can be seen in the t count value of 3.697 > the t table value of 1.9659. In addition to the significance of 0.002 which means it is smaller than 0.05.
Customers' purchasing behavior will be positively affected in the future when they perceive an increase in the quality of service. They will be less likely to complain and more likely to praise the website, suggest it to others, or stick with it. This results in a favorable psychological consumer interaction with the website, which is thought to be crucial for long-term success of organizations. The empirical study's findings demonstrate how quality electronic services take the shape of a multidimensional structure that is built on a hierarchical structure, where the perception of quality is determined by distinct dimensions that are composed of a number of sub-dimensions (Kim & Tang, 2020).
Implications
Based on the respondent's assessment, the efficiency variable has the lowest statement regarding well-organized applications, so that the application is more well-organized, the application can be updated in appearance and its features that are more modern and more organized so that they are used more effectively. Regarding privacy, the statement that has the lowest statement regarding a message, symbol, or sign that the application is safe to use, should PT. PT.
KAI can evaluate how e-tickets are sent to users, whether there are frequent problems in the system or not. Next is the emotional benefit and the statement that has the lowest value is related to feeling happy when using the application. Preferably PT. KAI immediately improves services on the KAI Access application so that customers can have a happy feeling when using the KAI Access application. For example, by adding more servers or improving the quality of application servers, so that when application traffic is high, the application will not experience downtime. Furthermore, by increasing the quality of the application on a large scale, so that users can easily enter the application and the features contained in the application can be used properly, and there are no bugs experienced by users. In short, the application must have minimal distractions by paying attention to
the aspects previously mentioned, so that users feel happy. Lastly is the e-satisfaction variable and the statement that has the lowest point is related to satisfaction with the decision to purchase a product, PT. KAI can look back at the suggestions that have been described earlier so that users feel more satisfied in purchasing products on the KAI Access application.
Limitations
There are still numerous limitations in this study, thus it is anticipated that these limitations will be addressed in further research. In the future, more homes may get research questionnaires so that information from Indonesian respondents may be gathered. Given the amount of variables, it is anticipated that each variable may contain more than three questionnaire questions. It may be possible to compare and expand the study model via other e-service quality aspects or by include the dependent variable in future research.
Conclusions
This research shows that e-satisfaction and e-trust, two essential features of the aforementioned assessment approach, are strongly intertwined. Consumers in Indonesia may be happy if an app has given them reasons to trust them, since e-trust is a prerequisite for e-satisfaction. The outputs of this study support those of Al-dweeri et al. (2018), who hypothesized that customer trust assessments directly affect their post- purchase contentment. Customers' purchasing behavior will be positively affected in the future when they see an increase in the quality of the e-service. They will be less likely to complain and more likely to praise the applications, promote them, or express their delight. As a result, users develop a positive psychological trust in the applications, which is thought to be crucial for long-term economic success.
The results of the empirical research reveal a multidimensional structure, based on a hierarchical one, in which the quality of electronic services is perceived according to
different factors that are composed of a number of sub-dimensions.
Suggestions
Research shows that privacy and dependability are the factors with the smallest impacts on e-trust. The hope is that PT. KAI will be able to devote more resources to application privacy factors such as by socializing how user information is managed by the administrator. On the reliability factor, it is expected that PT. KAI as the owner of the application to further improve quality in terms of timeliness and product accuracy from what has been promised so that users feel more satisfied after using the KAI Access application. The variables used in this study are the effect of efficiency, privacy, reliability, emotional benefits and customer service on e- satisfaction. It is suggested for future researchers to examine other factors that influence online user satisfaction, such as information quality, responsiveness, site aesthetics, compensation, or system availability. In addition, future researchers are advised to use dependent variables other than e-satisfaction, for example e-loyalty, or repurchase intention. This suggestion is put forward in order to obtain more varied results and enrich existing theories.
Notes on Contributors
Astri Wulandari is a permanent lecturer at the Digital Marketing Diploma Study Program, Faculty of Applied Sciences, Telkom University. Graduated from Doctoral Program in Management Science Pasundan University in 2019. Currently, she mastering courses in Marketing Ethics Profession, Professionalism Development, Human Capital Management, Business Communication, Human Resource Management, Marketing Management, and Retail Management. Her main research areas are in the areas of marketing, business, entrepreneurship, and human resources.
Andrieta Shintia Dewi is a permanent lecturer at the Management Study Program,
Gaining User Satisfaction of KAI (Indonesian Railways Company)-Access... 375 Faculty of Economic and Business, Telkom
University. Graduated from Magister Program in Management Science Institute Management Telkom in 2010. Currently, she mastering courses in Financial Management, Capital Market, and Risk Management. Her main research areas are in the areas of Capital Market, Financial Literacy, and Behavioral Finance.
Prof. Agus Rahayu has a field of knowledge/expertise in Marketing Management Science. Currently a lecturer in the Department of Business Management Education, Indonesian, University of Education.
Heny Hendrayati is an experienced lecturers and researchers with a history of working in universities and have an interest in non-profit organizations. Also have an interest in the field of entrepreneurship research, especially related to MSMEs and Womenpreneurs, then have analytical, negotiation, and event management skills.
Apart from being a lecturer, she is also a business practitioner in the field.
References
Al Masarweh, M., Al-Masaeed, S., Al- Qaisi, L., & Hunaiti, Z. (2016). E- commerce adoption at customer level in Jordan: an empirical study of
Philadelphia general
supplies. International Journal of Advanced Computer Science and Applications, 7(11).
Al-Adwan, A. S., & Al-Horani, M. A.
(2019). Boosting customer e-loyalty:
An extended scale of online service quality. Information, 10(12), 380.
Al-dweeri, R. M., Moreno, A. R., Montes, F. J. L., Obeidat, Z. M., & Al-dwairi, K. M. (2018). The effect of e-service quality on Jordanian student’s e- loyalty: an empirical study in online retailing. Industrial Management &
Data Systems.
Al-dweeri, R. M., Obeidat, Z. M., Al-dwiry, M. A., Alshurideh, M. T., & Alhorani, A. M. (2017). The impact of e-service
quality and e-loyalty on online shopping: moderating effect of e- satisfaction and e-trust. International Journal of Marketing Studies, 9(2), 92-103.
Anic, I. D., Škare, V., & Milaković, I. K.
(2019). The determinants and effects of online privacy concerns in the context of e-commerce. Electronic Commerce Research and Applications, 36, 100868.
Asfour, H. K., & Haddad, S. I. (2014). The impact of Mobile Banking on enhancing customers' E-satisfaction:
An empirical study on commercial banks in Jordan. International Business Research, 7(10), 145.
Ashfaq, M., Yun, J., Yu, S., & Loureiro, S.
M. C. (2020). I, Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI- powered service agents. Telematics and Informatics, 54, 101473.
Besalú, R., & Pont-Sorribes, C. (2021).
Credibility of digital political news in Spain: Comparison between traditional media and social media. Social Sciences, 10(5), 170.
Borissova, D., Cvetkova, P., Garvanov, I.,
& Garvanova, M. (2020, October). A framework of business intelligence system for decision making in
efficiency management.
In International Conference on Computer Information Systems and Industrial Management (pp. 111- 121). Springer, Cham.
Chi, C. G. Q., Wen, B., & Ouyang, Z.
(2020). Developing relationship quality in economy hotels: the role of perceived justice, service quality, and commercial friendship. Journal of Hospitality Marketing &
Management, 29(8), 1027-1051.
Çelik, K. (2021). The effect of e-service quality and after-sales e-service quality on e-satisfaction. Business &
Management Studies: An International Journal, 9(3), 1137- 1155.
Çiftçi, Ş. F., & Çizel, B. (2020). Predictors of e-trust for Web-based travel
intermediaries: a survey on Istanbul visitors. Journal of Hospitality and Tourism Technology.
Demir, A., Maroof, L., Sabbah Khan, N. U.,
& Ali, B. J. (2021). The role of E- service quality in shaping online meeting platforms: a case study from higher education sector. Journal of Applied Research in Higher Education, 13(5), 1436-1463.
Følstad, A., Nordheim, C. B., & Bjørkli, C.
A. (2018, October). What makes users trust a chatbot for customer service? An exploratory interview study. In International conference on internet science (pp. 194-208).
Springer, Cham.
Franedya, R. 2019. “Sempat Server Down, Ini Penyebab Aplikasi KAI Access
Erorr.” tech.
https://www.cnbcindonesia.com/tech /20190903104521-37-
96712/sempatserver-down-ini- penyebab-aplikasi-kai-access-erorr (Januari 11, 2022).
Frasquet, M., Descals, A. M., & Ruiz- Molina, M. E. (2017). Understanding loyalty in multichannel retailing: the role of brand trust and brand attachment. International Journal of Retail & Distribution Management.
Gera, R., Mittal, S., Batra, D. K., & Prasad, B. (2017). Evaluating the effects of service quality, customer satisfaction, and service value on behavioral intentions with life insurance customers in India. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 8(3), 1-20.
Ghozali, I., & Latan, H. (2015). Partial Least Squares Concepts, Techniques and Applications using the SmartPLS 3.0 Program. Semarang: Issuing Board of Diponegoro University.
Gupta, P., Sachan, A., & Kumar, R. (2020).
Different stages of the e-service delivery system process: belief–
attitude–intention
framework. International Journal of Retail & Distribution Management, 48(7), 687-706.
Hadi, U. 2019. “Kembali ke Manual, Pemesanan Tiket KA Lokal Via KAI Access Trouble.” detik.
https://news.detik.com/berita-jawa- tengah/d-4663292/kembalike- manual-pemesanan-tiket-ka-lokal- via-kai-access-trouble (Oktober 18, 2019).
Hair Jr, J. F., Howard, M. C., & Nitzl, C.
(2020). Assessing measurement model quality in PLS-SEM using
confirmatory composite
analysis. Journal of Business Research, 109, 101-110.
Husain, R., Paul, J., & Koles, B. (2022). The role of brand experience, brand resonance and brand trust in luxury consumption. Journal of Retailing and Consumer Services, 66, 102895.
Juwaini, A., Chidir, G., Novitasari, D., Iskandar, J., Hutagalung, D., Pramono, T., ... & Purwanto, A.
(2022). The role of customer e-trust, customer e-service quality and customer e-satisfaction on customer e-loyalty. International Journal of Data and Network Science, 6(2), 477- 486.
Kao, T. W. D., & Lin, W. T. (2016). The relationship between perceived e- service quality and brand equity: A simultaneous equations system approach. Computers in Human Behavior, 57, 208-218.
Kaya, B., Behravesh, E., Abubakar, A. M., Kaya, O. S., & Orús, C. (2019). The moderating role of website familiarity in the relationships between e-service quality, e-satisfaction and e- loyalty. Journal of Internet Commerce, 18(4), 369-394.
Khan, M. A., Zubair, S. S., & Malik, M.
(2019). An assessment of e-service quality, e-satisfaction and e-loyalty:
Case of online shopping in Pakistan. South Asian Journal of Business Studies, 8(3), 283-302.
Kim, E., & Tang, L. R. (2020). The role of customer behavior in forming perceived value at restaurants: A multidimensional
Gaining User Satisfaction of KAI (Indonesian Railways Company)-Access... 377 approach. International Journal of
Hospitality Management, 87, 102511.
Kim, J. H., & Lennon, S. J. (2017).
Descriptive content analysis on e- service research. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 8(1), 18-31.
Kondo, F. N., & Okubo, T. (2022).
Understanding multi-channel consumer behavior: A comparison between segmentations of multi- channel purchases by product
category and overall
products. Journal of Retailing and Consumer Services, 64, 102792.
Kong, Y., Wang, Y., Hajli, S., &
Featherman, M. (2020). In sharing economy we trust: Examining the effect of social and technical enablers on millennials’ trust in sharing commerce. Computers in Human Behavior, 108, 105993.
Kumar, R., Sachan, A., & Dutta, T. (2020).
Examining the impact of e-retailing convenience dimensions on behavioral intention: The mediating role of satisfaction. Journal of Internet Commerce, 19(4), 466-494.
Lestari, S. D., Leon, F. M., Widyastuti, S., Brabo, N. A., & Putra, A. H. P. K.
(2020). Antecedents and consequences of innovation and business strategy on performance and competitive advantage of SMEs. The Journal of Asian Finance, Economics and Business, 7(6), 365-378.
Lingga, M. A. 2019. “Menperin:
Penguasaan Infrastruktur Jadi Kunci Daya Saing di Industri 4.0.” Kompas.
https://money.kompas.com/read/201 9/10/14/160300026/menperin- penguasaaninfrastruktur-jadi-kunci- daya-saing-di-industri-4.0 (Oktober 15, 2022).
Pizzutti, C., Gonçalves, R., & Ferreira, M.
(2022). Information search behavior at the post-purchase stage of the customer journey. Journal of the Academy of Marketing Science, 1-30.
Rahayu, K. S. (2021). E-ServQual on E- Trust, E-Satisfaction and Online
Repurchase Intention. Review of International Geographical Education Online, 11(4).
Raza, S. A., Umer, A., Qureshi, M. A., &
Dahri, A. S. (2020). Internet banking service quality, e-customer satisfaction and loyalty: the modified e-SERVQUAL model. The TQM Journal, 32(6), 1443-1466.
Redjeki, F., & Affandi, A. (2021).
Utilization of Digital Marketing for MSME Players as Value Creation for Customers during the COVID-19 Pandemic. International Journal of Science and Society, 3(1), 40-55.
Rita, P., Oliveira, T., & Farisa, A. (2019).
The impact of e-service quality and customer satisfaction on customer
behavior in online
shopping. Heliyon, 5(10), e02690.
Shin, D. (2021). The effects of explainability and causability on perception, trust, and acceptance:
Implications for explainable AI. International Journal of Human- Computer Studies, 146, 102551.
Suandi, T. 2016. “Mempertanyakan Keamanan Data Aplikasi KAI Access -Kompasiana.com.”
Mempertanyakan Keamanan Data Aplikasi KAI Access.
https://www.kompasiana.com/amp/te guhsuandi/mempertanyakan-
keamanandata-aplikasi-kai-
access_57edd34b8d7a613808e46895 (November 4, 2022).
Tetanoe, V. R., & Dharmayanti, D. (2014).
Pengaruh Experiential Marketing Terhadap Pembelian Ulang Dengan Kepuasan Pelanggan Sebagai Variable Intervening di Breadtalk Surabaya Town Square. 2(1), 1–12.
Tirto.id. 2019. “Terang Gelap Sejarah 74 Tahun Kereta Api Indonesia.” tirto.id.
https://tirto.id/terang-gelap-sejarah- 74-tahun-kereta-api-indonesia-eiQQ (Oktober 18, 2022).
Trivedi, S. K., & Yadav, M. (2020).
Repurchase intentions in Y generation: mediation of trust and e- satisfaction. Marketing Intelligence
& Planning.
Van der Borgh, M., Nijssen, E. J., &
Schepers, J. J. (2023). Unleash the power of the installed base:
Identifying cross-selling opportunities from solution offerings. Industrial Marketing Management, 108, 122-133.
Venkatesh, V., Thong, J. Y., & Xu, X.
(2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.
Wang, W. T., Ou, W. M., & Chen, W. Y.
(2019). The impact of inertia and user satisfaction on the continuance intentions to use mobile
communication applications: A mobile service quality perspective.
International Journal of Information Management, 44, 178-193.
Wardhana, H. 2019. “Bahaya Mengintai di Balik ‘Direct Debit’ LinkAja-KAI
Access.” KOMPASIANA.
https://www.kompasiana.com/wardh anahendra/5d7205f10d82302ca1564 862/bahaya-mengintai-di-balik- direct-debit-linkaja-kai-access (November 4, 2022).
Xu, F., Luo, X. R., & Hsu, C. (2020). Anger or fear? Effects of discrete emotions on employee’s computer-related deviant behavior. Information &
Management, 57(3), 103180.
