Satisfied and Loyal Customers: Unveiling the Role of Bank Service Quality

Rahmatullah Alfikri^1,*, Bella Puspita Rininda², Rahmi Nadiar³, Marliza Noor Hayatie⁴, Try Edi Suwarno⁵

^1,2,3,4,5 Polytechnic State of Tanah Laut, Pelaihari, Indonesia

ABSTRACT: With customer satisfaction serving as the mediating variable, investigating and assessing the connection between customer loyalty and bank service quality is the goal of this study. This research is focused on civil servants who use consumer products. The sample size is determined using the formula proposed by Ferdinand (2014), resulting in 110 respondents selected through purposive sampling. This research utilizes primary data collected through questionnaires. Data analysis in this work is done using Structural Equation Modeling, which provides Path Analytic capabilities. The path analysis used in this research is Partial Least Squares (PLS), using Smart-PLS software. The study’s conclusions show that customer satisfaction is impacted by bank service quality; Bank Service Quality also affects customer loyalty; satisfaction impacts customer loyalty; and indirectly, Bank Service Quality influences customer loyalty through the interaction of customer satisfaction, which as an intervening variable. Based on the Bank Service Quality Model, this study comes to the conclusion that customer satisfaction and loyalty are impacted by bank service quality.

KEYWORDS: Bank Service Quality, Satisfaction, Loyalty

1. INTRODUCTION

Banking institutions rely on trust as a fundamental principle for their operations and stability. Trust is the fundamental element of everyday banking operations, including funding, lending, and providing services (Putera, 2020). As information intermediaries, banks depend on maintaining trust and confidence to function efficiently (Basaran & Bagheri, 2020). Trust has a significant impact on credit access for small and medium-sized enterprises (SMEs), as it can bridge the information gap caused by asymmetries between banks and borrowers (Kautonen et al., 2020). It has been found in research that there is a positive correlation between trust and credit access for SMEs, particularly when formal information to assess creditworthiness is insufficient (Kautonen et al., 2020). However, further investigation is needed to understand how banks incorporate qualitative factors like trust into lending decisions and whether trust between borrowers and lenders is symmetric (Kautonen et al., 2020). Overall, trust plays a crucial role in maintaining public confidence, facilitating credit access, and ensuring the stability of the banking system.

Multilateral development banks are instrumental in promoting economic growth and connectivity in developing countries. They act as development agents through strategic, developmental, and financial dimensions (Creutz, 2023). The African Development Bank (AfDB) also fosters Pan-African development through its unique characteristics and lending style nya (Nyadera et al., 2022). Development banks, in particular, serve as essential instruments in public policy in peripheral countries, capable of driving sustainable structural changes and acting counter-cyclically (Feil & Feijó, 2021). In Indonesia, the establishment of a land bank aims to address land procurement challenges for national development (Danendra & Mujiburohman, 2022). The banking industry, especially in India, has evolved to include various agency tasks beyond traditional banking services, with technology playing a significant role in enhancing operations and customer experience (Shakyawar & Shakya, 2023).

1. Bank Kalsel, is maintaining its banking services by offering various types of credit, including investment loans, working capital loans, and consumer loans. One of the current competitive challenges in banking lies in the offerings of credit facilities, both in terms of the features of these credit types and the comfort and benefits perceived by prospective customers. As the population increases, so does the demand for services, particularly in the context of rising prices, which affects household consumption needs. Bank Kalsel’s ownership is under Provincial Government of South Kalimantan. This adds value to its banking operations, as Bank Kalsel has been appointed as the regional cash holder, with regional cash funds deposited at the bank for the payment of salaries to Regional Civil Servants (ASN).

The fixed monthly income received by customers is the basis for calculating consumer loan repayments. Civil servant who receive their salaries through Bank Kalsel represent a strength and advantage in the consumer credit business, which includes multipurpose products, enhanced multipurpose loans, and extended multipurpose loans for civil servant. This is advantageous because it allows for direct deductions from their salaries for monthly repayment obligations automatically upon salary disbursement. Additionally, this convenience alleviates the need for civil servant to make monthly payments to the bank for their credit obligations.

Regional development banks in Kalimantan play a crucial role in the local economy. Bank Kalsel aims to enhance customer satisfaction through service quality, product value, and facilities (Muhtadi et al., 2020). The performance of banking services is influenced by transformational leadership, managerial development, organizational commitment, and work motivation (BAstAri et al., 2020). In South Kalimantan, third-party funds positively affect economic growth, whereas credit and investment have a negative but significant impact (Saudah & Nuryadin, 2022). Consumer credit is the largest segment, with the highest portfolio amounts and the most significant number of accounts (NOA). The substantial distribution of consumer credit indicates that this segment is the primary focus of Bank Kalsel’s Main Branch in Banjarmasin, with a target of achieving 10% annual growth in consumer loan accounts. Meeting this target poses a challenge for PT. Bank Kalsel Main Branch Banjarmasin, necessitating an improvement in service quality to ensure customer satisfaction and loyalty toward the products offered.

To attract potential customers to choose consumer credit products, these loans must feature distinctive attributes that provide additional value. Examples of consumer credit features include interest rates, fees, insurance, collateral, percentage deductions, penalties, payment methods, withdrawal processes, security, speed, and flexible loan terms. Fluctuations in the number of customers indicate the level of loyalty toward the products offered by PT. Bank Kalsel Main Branch Banjarmasin. Research on consumer credit products highlights several factors influencing customer interest and decision-making. Knowledge, product features, and promotions significantly impact customers’ interest in saving at the bank (Munandar & Onsardi, 2021). Customer awareness of products, costs, and considerations of halal lifestyle choices play a vital role in selecting savings accounts (Toha & Aini, 2021). For consumer loans, product, price, location, promotion, physical evidence, people, and process are all part of the marketing mix, with the process variable having the most considerable impact (Athar, 2021).

The primary business process of banking is the disbursement of credit to the public, as credit represents the core banking activity that generates the most profit. Each bank’s credit products have distinct features and provide different added values. To create value addition, it is essential to incorporate supporting variables beyond the inherent features of the product, such as service quality and customer satisfaction. Effectively managing these variables will create a sense of comfort for customers, leading them to choose and remain loyal to the product.

The assessment of service quality is a routine task conducted by the management of Bank Kalsel to realize its value proposition, “Faithfully Serving, Progressing Together.” Bank Kalsel received many awards in 2023, as a result of their commitment. The numerous awards in various fields, particularly in service quality, reflect the management’s commitment to maintaining and improving service standards, thereby enhancing customer loyalty toward Bank Kalsel through customer satisfaction with the products and services provided.

2. RESEARCH METHOD

2.1. Type and Location of Research

According to Ghozali (2018), the present investigation is classified as explanatory research, which aims to clarify the relationships among the variables under investigation. In order to solve issues and increase knowledge, explanatory research aims to investigate and clarify the relationships between variables or phenomena using a scientific method (Sari et al., 2023). According to Arikunto et al. (2010), studies that employ correlation approaches seek to ascertain the degree of association between variables. Customer loyalty (Y) is the dependent variable, satisfaction (Z) is the intervening variable, and bank service quality (X) is the independent variable. The purpose of this study is to evaluate the correlations between these three variables. Customers of Banjarmasin’s Bank Kalsel Main Branch participate in the study.

2.2. Unit of Analysis

In this study, the unit of analysis is customers of consumer credit as well as customers who have previously or are currently utilizing consumer credit services at Bank Kalsel Main Branch in Banjarmasin.

2.3. Population and Sample

The definition of a population is a fundamental concept in ecology and research, with varying interpretations depending on the context. In ecological studies, populations can be defined based on demographic and evolutionary processes, considering factors such as genetic drift and effective population size (Hare & Rudstam, 2022). For research purposes, clearly defining the population structure is essential, particularly for novice researchers and doctoral students. This includes determining the unit of analysis, subgroups within the population, and sample characteristics (Casteel & Bridier, 2021). Understanding the demographics of a population is crucial for estimating risk factors and access to services. Key aspects include age and gender structure, distribution, demographic levels, life expectancy, and population growth. Various sources of demographic information exist, such as censuses, death certificates, and demographic monitoring systems (Vaughan et al., 2021). The population in this study consists of 5,636 civil servants (known as ASN) utilizing consumer products at Bank Kalsel Main Branch in Banjarmasin. The number of credit accounts (NOA) totals 8,860, with 5,636 civil servants as borrowers, indicating that approximately 3,224 civil servant have loans with more than one NOA per civil servant (based on data from 2021).

Non-probability sampling is the sampling technique utilized in this study. (Ferdinand, 2014) outlines sample guidelines concerning the use of structural equation modeling (Structural Equation Model), to ensure accurate analysis, it’s recommended to have a sample size of 5 to 10 times the number of indicator variables. This study comprises 11 indicators (BSQ = 6 indicators, Satisfaction = 1 indicator, and Loyalty = 4 indicators), resulting in a required sample size of 10 x 11 indicators = 110 customers who have utilized consumer credit at Bank Kalsel, meeting the criterion of having experienced more than one instance of consumer credit facilities.

3. RESULT AND DISCUSSION

3.1. Convergent Validity

A loading factor that is positive and more than 0.7 is necessary for an indicator to be validated. The loading factor value, which is a measure of the corresponding variable, determines the weight of each indication or item. These indicators represent the most potent (dominant) measures of the variable, according to high loading factors. Additionally, the Variance Inflation Factor (VIF) test is utilized to check for homoscedasticity or multicollinearity issues in the data. The VIF values below 10 indicate that there are no indications of multicollinearity in any of the variables. Below is a list of the VIF test results:

Table 1. VIF Value

Source: Output from SmartPLS (v.3.2.9) Data processed on 2024

3.2. Discriminant Validity

Cross-loading is necessary to examine the square root of the Average Variance Extracted (AVE) for every construct and the relationships between it and other constructs in the model, especially when the standard value exceeds 0.07. When each construct’s square root of the AVE is greater than the correlation values with other constructs in the model, this is regarded as good discriminant validity.

Table 2. Fornell-Larcker Criterion (AVE) Value

Source: Output from SmartPLS (v.3.2.9) Data processed on 2024

The findings suggest that all variables have good discriminant validity since their construct values are higher than those of other variables within each respective construct.

3.3. Reliability

Cronbach’s alpha and Composite reliability are used to assess reliability in PLS. The Composite reliability value above 0.7 is a necessary factor in determining how reliable a construct is, and above 0.6 is a recommended Cronbach’s alpha value. Table 3 provides the Cronbach alpha and Composite reliability values below:

Table 3. Reliability Test

Source: Output from SmartPLS (v.3.2.9) Data processed on 2024

Table 3 above shows that all research variables have composite reliability values above 0.7 and Cronbach’s Alpha values above 0.6. The findings indicate that each variable is highly reliable and meets the Cronbach’s Alpha and composite reliability requirements. To perform additional analysis, it is necessary to examine the model’s fit. This involves assessing the inner model to determine the correlations between constructs, significance values, and the R-squared value of the research model, as shown in Figure 1.

Figure 1. Structural Model (Inner Model)

Source: Output from SmartPLS (v.3.2.9) Data processed on 2024

3.4. R Square

In Ghozali & Latan’s 2015 study (Ghozali & Latan, 2015), it was found that a strong model has an R Square value of 0.67, a moderation model has a value of 0.33, and a weak model has a value of 0.19. The Adjusted R Square value is a result of the R Square value being adjusted using the standard error. When evaluating the extent to which an exogenous construct may explain an endogenous construct, the Adjusted R Square is a more dependable metric than the R Square. Table 4 illustrates the R square test’s outcome.

Table 4. Results of the R Square Testing

Source: Output from SmartPLS (v.3.2.9) Data processed on 2024

The R-Square value for the Satisfaction variable is 0.514, which shows that the Bank Services Quality variable can explain 51.4% of the Satisfaction variable, while other variables not included in this study explain 48.6%. The Bank Services Quality and Satisfaction variables account for 75.0% of the Loyalty variable’s R-Square value of 0.750, with other variables not included in this study accounting for the remaining 25%.

3.5. F Square

The F Square test is conducted to analyze the degree of influence of latent variables, determining whether the effect is small, medium, or large at the structural level. The criteria for F Square are as follows:

1. A small effect of the exogenous variable on the endogenous variable is indicated if F2 = 0.020.
2. A medium effect of the exogenous variable on the endogenous variable is indicated if F2 = 0.150.
3. A significant impact of the exogenous variable on the endogenous variable is indicated if F2 = 0.350.

Table 5. F Square Test

Source: Output from SmartPLS (v.3.2.9) Data processed on 2024

Based on the data in the table above, it can be determined that:

1. The Bank Service Quality variable affects the Satisfaction variable with an F Square value of 1.057, indicating a high level of influence.
2. The Bank Services Quality variable affects the Loyalty variable with an F Square value of 0.300, indicating a medium level of influence.

The Satisfaction variable affects the Loyalty variable with an F Square value of 0.566, indicating a high level of influence.

3.6. Hypothesis Testing

The structural model is tested using PLS software. The output images and values found in the output path coefficients serve as the foundation for directly evaluating the hypothesis. As seen in Table 6, a significant impact of the exogenous variable on the endogenous variable is indicated if the p-value is less than 0.05 (significance threshold = 5%), which is the condition for directly testing the hypothesis.

Table 6. Total Effects

Source: Output from SmartPLS (v.3.2.9) Data processed on 2024

1. Bank Services Quality is Predicted to Affect Satisfaction

The first hypothesis test, which predicts that satisfaction will be impacted by Bank Services Quality, shows a positive original sample value of 0.717, indicating a positive link between BSQ and contentment. The t-statistic value of 9.869 is more than the t-table value of 1.981, and the p-value of 0.000 is less than 0.05. These findings imply that satisfaction is highly impacted by the quality of bank services. Therefore, it is believed that the quality of bank services is predicted to have a positive and significant impact on customer satisfaction.

Research consistently shows that the quality of bank services positively influences customer satisfaction and financial performance. Service quality is characterized by reliability, responsiveness, assurance, and empathy, have been shown to significantly impact customer satisfaction. Furthermore, high-quality service is crucial for meeting customer needs and maintaining competitiveness (Sugiarto & Octaviana, 2021). Customer satisfaction, in turn, enhances loyalty and improves the financial performance of banks (Ijara, 2020; Mjaku, 2020). The relationship between service quality and financial performance can be direct or indirect, mediated by customer satisfaction and loyalty (Ijara, 2020). In the context of the COVID-19 pandemic, banks have adapted their service strategies to maintain customer satisfaction while adhering to health and safety protocols (Rumiyati & Syafarudin, 2021). Overall, these studies emphasize the critical role of service quality in driving customer satisfaction and ultimately enhancing bank performance.

2. Bank Services Quality is Predicted to Affect Loyalty

According to the results of the second hypothesis test, which predicts that loyalty will be impacted by Bank Services Quality, there is a positive correlation between BSQ and loyalty, with an original sample value of 0.393. The t-statistic value of 4.903 is more than the t-table value of 1.981, and the p-value of 0.000 is less than 0.05. These findings suggest that loyalty is strongly impacted by the quality of bank services. As a result, the idea that the quality of bank services is expected to have a favorable and noteworthy impact on loyalty is accepted.

This research indicates that the quality of bank services positively influences customer loyalty, both directly and indirectly. Service quality has been shown to significantly impact loyalty, perceived value, and corporate image (Jahan et al., 2020). This effect is also positive across all dimensions in the Jordanian commercial banking sector (Al-Slehat, 2021). However, one study found that service quality indirectly influences loyalty through customer satisfaction (Supriyanto et al., 2021). Customer satisfaction and trust have been identified as mediating factors between service quality and loyalty (Al-Slehat, 2021; Yudi & Ruswanti, 2021). These findings emphasize the importance of service quality in developing sustainable, customer-centric marketing strategies for banks (Jahan et al., 2020). To enhance customer loyalty, banks should focus on tangible aspects and customer satisfaction (Al-Slehat, 2021). Overall, maintaining high service quality is crucial for banks to retain customers and gain a competitive advantage in an increasingly competitive and technologically advanced environment.

3. Satisfaction is Predicted to Affect Loyalty

The final hypothesis test, which suggests that loyalty is predicted to be impacted by satisfaction, yielded an original sample value of 0.540, suggesting that loyalty and satisfaction are positively correlated. The t-statistic of 6.361 and the p-value of 0.000 are more than the t-table value of 1.981. These findings suggest that loyalty is strongly impacted by satisfaction. As a result, the hypothesis that satisfaction is expected to have a favorable and noteworthy impact on loyalty is approved.

Customer satisfaction plays a crucial role in influencing customer loyalty in banking, as evidenced by several aligned studies. Research by Chikazhe et al., (2021) and Al-Slehat, (2021) shows that customer satisfaction has a direct positive effect on loyalty. Additionally, customer satisfaction serves as a mediator between service quality and loyalty (Kumar & Mokha, 2022; Supriyanto et al., 2021). Service quality and corporate image partially mediate the relationship between satisfaction and loyalty (Chikazhe et al., 2021). While one study found that service quality does not directly influence loyalty (Supriyanto et al., 2021), another reported a positive impact of banking service quality on loyalty (Al-Slehat, 2021). Electronic Customer Relationship Management (E-CRM) also positively influences loyalty, with customer satisfaction partially mediating this relationship (Kumar & Mokha, 2022). Demographic factors such as gender, age, education, and income do not moderate the effect of satisfaction on loyalty (Chikazhe et al., 2021). These findings emphasize the importance of focusing on customer satisfaction, service quality, and corporate image to enhance customer loyalty in the banking sector.

4. Bank Service Quality is Predicted to Affect Loyalty Through Satisfaction

An original sample value of 0.387 indicates a positive link between BSQ and loyalty through satisfaction, according to the results of the fourth hypothesis test, which suggests that the quality of bank services is predicted to have an impact on loyalty via satisfaction. The t-statistic of 5.198 and the p-value of 0.000 are more than the t-table value of 1.960. These findings suggest that customer satisfaction with bank services has an impact on loyalty. Therefore, it is believed that the quality of bank services is predicted to have a positive and significant impact on customer satisfaction and loyalty.

The research indicates that the quality of bank services positively influences customer loyalty, often mediated by customer satisfaction. Service quality has a significant positive impact on customer satisfaction, which in turn affects loyalty (Al-Slehat, 2021; Supriyanto et al., 2021). While some studies indicate that service quality has a direct effect on loyalty, others find this relationship to be indirect, mediated by satisfaction (L. Aprilia et al., 2020; Supriyanto et al., 2021). Trust also plays a role in this relationship, with service quality positively influencing trust, which subsequently impacts loyalty (N. E. Aprilia, 2021). However, these findings are not entirely consistent across studies. For instance, L. Aprilia et al., (2020) found that service quality does not significantly affect satisfaction and loyalty. Despite some variations, the overall trend suggests that improving banking service quality can enhance customer satisfaction and, consequently, increase loyalty, underscoring the importance of service quality in the banking sector.

4. CONCLUSION
5. Bank Service Quality has a significant impact on customer satisfaction at Bank Kalsel Main Branch in Banjarmasin. It is proven that the better the service quality provided, the higher the level of customer satisfaction.
6. Bank Service Quality also significantly influences customer loyalty at Bank Kalsel Main Branch in Banjarmasin. This demonstrates that high-quality services can encourage customers to remain loyal to the bank’s services.
7. Customer satisfaction positively affects loyalty. In other words, customers who are satisfied with the services provided by the bank tend to show a higher level of loyalty.
8. Bank Service Quality affects customer loyalty both directly and indirectly through satisfaction. This indicates that good service quality can enhance customer loyalty, especially when customers feel satisfied with the services received.

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