Impact of service quality dimensions on customer satisfaction in priority sector lending
Leema Roseline Arul Doss1
Gayathri Jayapal2*
Suganya Ganesan3
Justin Nelson Michael4
1,2Department of Commerce and Financial Studies, Bharathidasan University, India. |
AbstractPriority Sector Lending (PSL) is a financial inclusion strategy that encourages banks to support vital industries for stimulating economic expansion. This study aims to analyse how different service quality parameters affect customer satisfaction. The 339 people who used PSL for agricultural and educational loans provided responses. Path analysis using Structural Equation Modelling (SEM) was used to assess the impact of the five dimensions on customer satisfaction. The results of the path analysis revealed that only reliability, responsiveness and tangibility have significantly impacted customer satisfaction. There exists an opportunity for improvement in the extent to which bankers demonstrate assurance and empathy during the loan processing phase of the priority sector lending scheme. The study provides valuable insights for employees and customers alike, shedding light on the nature of the services rendered and received. Furthermore, the results of this research can inform policy makers in making decisions aimed at promoting the delivery of outstanding customer service. |
Licensed: |
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Keywords: JEL Classification: |
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Received: 17 March 2023 |
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| (* Corresponding Author) |
Funding: This study received no specific financial support. |
Competing Interests: The authors declare that they have no competing interests. |
1. Introduction
The banking industry is widely regarded as a crucial player in the economic development of any country, owing to its central role in providing finance to priority sectors such as agriculture, small and medium enterprises, and education, which are fundamental to overall economic growth. While the provision of financial services is critical, customer satisfaction for these services is equally important. As per the definition put forth by Parasuraman, Zeithaml, and Berry (1988), service quality is characterized as the disparity between a customer's expected level of service and their actual perception of the service received. To assess service quality, respondents are required to provide feedback on both their expectations and perceptions. In the banking industry, service quality plays a pivotal role in shaping customer satisfaction and loyalty. Singh, Srivastava, and Sinha (2017) revealed that in the banking sector, service quality strongly predicted both customer satisfaction and loyalty, with higher levels of perceived service quality associated with reliability. Existing literature suggests that various dimensions of service quality, including reliability, responsiveness, assurance, empathy, and tangibility, impact customer satisfaction. Reliability pertains to the accuracy and dependability of services provided by the bank, while responsiveness refers to the promptness with which the bank assists its customers. Assurance relates to the knowledge and courtesy of bank employees, instilling trust and confidence in customers. Empathy refers to the bank's ability to understand and address customer needs, while tangibility concerns the appearance of the bank's facilities, equipment, personnel, and communication materials. Several studies have investigated the relationship between service quality dimensions and customer satisfaction in the context of priority sector lending. Izogo and Ogba (2015) found that reliability, responsiveness, assurance, and empathy were significant predictors of customer satisfaction in the automobile repair services sector. Uddin, Hossain, and Islam (2019) identified reliability, responsiveness, and empathy as critical dimensions of service quality influencing customer satisfaction in the small and medium enterprise sectors. Therefore, it is imperative for banks to comprehend the service quality dimensions that impact customer satisfaction in the priority sector lending segment, in order to formulate effective strategies that enhance service quality and ultimately improve customer satisfaction and loyalty.
2. Review of Literature
2.1. Customer Satisfaction
Priority sector lending is a crucial aspect of the banking industry in developing countries, as it targets the underprivileged sections of society. Several studies have explored customer satisfaction with priority sector lending and the factors influencing it. Access to credit is the most important element impacting consumer satisfaction with priority sector lending. Satish (2021) found that easy access to credit was positively related to customer satisfaction on priority sector lending. The study also revealed that timely disbursement of loans and minimal documentation requirements were critical drivers of customer satisfaction. Another factor influencing customer satisfaction on priority sector lending is the interest rate. Patro and Baral (2019) found that a lower interest rate was positively related to customer satisfaction on priority sector lending. The study also found that customers were more satisfied when banks offered customized interest rates based on their creditworthiness. The service quality of the banks influences customer satisfaction on priority sector lending. Mandal (2016) found that customer satisfaction on priority sector lending was positively related to the quality of service provided by banks. The study also found that personalized services and effective communication were critical drivers of customer satisfaction. Moreover, the transparency of lending practices and the level of information provided to customers also influence customer satisfaction on priority sector lending. Kandwal and Pathania (2017) found that customers were more satisfied when banks provided clear information on the terms and conditions of loans and the eligibility criteria. Finally, the social impact of priority sector lending also influences customer satisfaction. Saha and Biswas (2017) found that customers were more satisfied when banks demonstrated a commitment to the social welfare of the community through their priority sector lending practices. In conclusion, customer satisfaction on priority sector lending is influenced by various factors, including access to credit, interest rates, quality of service, transparency of lending practices, and social impact. Banks need to understand these factors and strive to provide high-quality services to enhance customer satisfaction and loyalty in the priority sector lending segment. Sudhahar and Selvam (2007) confirmed that tangibles, reliability, responsiveness, assurance, and empathy are the five dimensions of service quality for Indian retail banking customers. The devised scale, according to the authors, showed high predictive ability for forecasting customer satisfaction and was valid and trustworthy. Sudhahar and Selvam (2006) found that service quality significantly impacts customer satisfaction and loyalty.
2.2. Service Quality
The issue of service quality has garnered significant scholarly attention within the banking sector, with numerous studies investigating its impact on customer satisfaction in the context of priority sector lending. In a recent empirical investigation, Saeed and Abu (2020) conducted a study to examine the influence of service quality dimensions on customer satisfaction within the framework of priority sector lending. The findings revealed that all of these dimensions exhibited a significant effect on customer satisfaction, with reliability emerging as the most salient factor. Similarly, Kumar and Singh (2021) conducted a study to explore the association between service quality and customer satisfaction in the microfinance segment, which holds crucial importance as a constituent of priority sector lending. The study found that dimensions such as responsiveness, empathy, tangibility, and reliability significantly influenced customer satisfaction in the microfinance segment. Furthermore, the literature has also delved into the impact of service quality on customer loyalty in the context of priority sector lending. For instance, Chitnis and Kothari (2019) conducted an empirical investigation that examined the relationship between service quality dimensions and customer loyalty within the priority sector lending segment. The findings of the study revealed that these dimensions exerted a positive influence on customer loyalty in the segment. Additionally, the role of technology in enhancing service quality in the realm of priority sector lending has been a subject of inquiry. Kaur, Ali, Hassan, and Al-Emran (2021) conducted a study that explored the impact of digital technology adoption on service quality within the banking sector. The study concluded that the adoption of digital technology significantly improved service quality and customer satisfaction in the segment.
Finally, the importance of employee behavior and competence in delivering high-quality service in priority sector lending has also been highlighted. Mukherjee, Saha, and Sengupta (2019) conducted a study that found that employee competence and behavior significantly influenced service quality and customer satisfaction in the priority sector lending segment. In conclusion, the present body of research highlights the critical role of service quality in determining customer satisfaction and loyalty in priority sector lending. To enhance service quality, banks need to focus on improving reliability, responsiveness, empathy, tangibles, and assurance. Additionally, adopting digital technology and fostering employee competence and behavior can help improve service quality in the priority sector lending segment.
2.3. Service Quality Dimensions and Customer Satisfaction
Service quality has been widely acknowledged as a significant factor in the service industry, particularly in the banking sector. Extensive research has been conducted to identify the dimensions of service quality that significantly impact customer satisfaction and loyalty. The commonly studied dimensions are reliability, responsiveness, assurance, empathy, and tangibility. In the banking sector, reliability is of paramount importance as customers expect error-free and timely services. Parasuraman, Zeithaml, and Berry (1985) found that reliability was the most critical service quality dimension influencing customer satisfaction. Similarly, responsiveness is crucial in the banking sector, where customers often require immediate assistance. Caruana (2002) revealed that responsiveness was a significant predictor of customer satisfaction. Assurance, which relates to the trust customers place in banks with their finances, is also essential. Sureshchandar, Rajendran, and Anantharaman (2002) found that assurance significantly influenced customer satisfaction. Empathy, which pertains to the service provider's ability to understand and address customers' needs, is also significant in the banking sector. Rahman and Al Mamun (2021) revealed that empathy was a significant predictor of customer satisfaction. Finally, tangibility, which encompasses the appearance of the service provider's facilities, equipment, personnel, and communication materials, is critical. Hsu and Chen (2018) found that tangibility was a crucial service quality dimension that influences customer’s satisfaction.
2.3.1. Relationship between Assurance and Customer Satisfaction
Parasuraman et al. (1985) define assurance as the capacity of employees to instill confidence and trust in clients through their knowledge, courtesy, and conduct. A key element in assessing an employee's aptitude, knowledge, and demeanour as well as their capacity to develop and sustain relationships of trust with clients is the degree of assurance in service quality. (Parasuraman et al., 1985). In a study of selected public sector banks in India, Kant and Jaiswal (2017) found that assurance and image were positively and significantly related to customer satisfaction. Assurance emerged as the most significant factor influencing customer satisfaction with banking services (Selvakumar, 2015). The study revealed that banks’ assurances, which included considering customers’ recommendations and opinions, safeguarding transactions, and possessing adequate knowledge, exceeded customers’ expectations. Numerous researchers have confirmed the positive and significant effect of assurance on customer satisfaction (Munusamy, Chelliah, & Mun, 2010; Shanka, 2012). Building on the literature reviewed above, the following hypothesis is proposed:
H1: Assurance has a positive effect on customer satisfaction in Priority Sector Lending.
2.3.2. Relationship between Reliability and Customer Satisfaction
Ennew, Waite, and Waite (2013) defined reliability as the extent to which customers can rely on a company when they promised to deliver good service. This implies that reliability is associated with the ability to provide services accurately and consistently, as noted by Parasuraman et al. (1985). A reliable service provider ensures that it delivers what it has committed to its clients, that is resulted in increased customer satisfaction, as suggested by Selvakumar (2015). Previous research has established the significant impact of reliability on customer satisfaction in the financial services sector, as evidenced by studies conducted by Shanka (2012); Peng and Moghavvemi (2015) and Selvakumar (2015). Drawing from the above-mentioned literature, the following hypothesis is formulated:
H2: Reliability has a positive influence on customer satisfaction in Priority Sector Lending.
2.3.3. Relationship between Empathy and Customer Satisfaction
Parasuraman et al. (1985) posited that providing attentive, personalized attention to each client is a critical aspect of service quality in the banking sector. Ennew et al. (2013) underlined the need of empathy in handling consumer concerns, which necessitates a thorough comprehension of the problem. Ananth, Ramesh, and Prabaharan (2011) found that there is often a significant gap between customers' expectations and their perception of the quality of services provided, and recommended that banks bridge this gap by providing superior service to retain existing customers and attract new ones. From the prior studies, it is evident that empathy plays a crucial role in enhancing customer satisfaction in the banking sector (Peng & Moghavvemi, 2015; Selvakumar, 2015; Shanka, 2012) . Building on this research, the following hypothesis is proposed:
H3: Empathy positively influences customer satisfaction in Priority Sector Lending.
2.3.4. Relationship between Tangibility and Customer Satisfaction
Tangibility, as defined by Parasuraman et al. (1985),refers to the outside look of buildings, furnishings, staff, and communication equipment that enables clients to clearly see the service being provided. Previous research has shown that tangible components of the service facility, such as machinery and equipment, empathetic customer service, reliable and secure customer support, and online banking, have a positive impact on the service quality delivery, leading to a higher perceived value (Peng & Moghavvemi, 2015). Furthermore, studies conducted by Kant and Jaiswal (2017) and Shanka (2012) have revealed a positive and significant relationship between tangibility and customer satisfaction. Building upon this existing literature, the present study posits the hypothesis as stated below:
H4: Tangibility positively influences customer satisfaction in Priority Sector Lending.
2.3.5. Relationship between Responsiveness and Customer Satisfaction
Parasuraman et al. (1985) assert that the responsiveness aspect of service quality is contingent upon the organization's preparedness and ability to provide clients with prompt and efficient service. This entails a willingness to assist customers and extend benefits, as highlighted by Khan, Lima, and Mahmud (2021). Krishnamurthy, Mani, Sivakumar, and Sellamuthu (2010) identified responsiveness as a significant predictor of overall satisfaction with banking services. Similarly, Khan et al. (2021) established a significant positive correlation between the responsiveness of banking service quality and customer satisfaction. In relation to Priority Sector Lending, the following theory was created based on the earlier studies:
H5: Responsiveness has a positive impact on customer satisfaction in Priority Sector Lending.
2.4. Theoretical Framework
Based on the existing theory and literature, the present study aims at customer satisfaction by focusing on the service quality dimensions such as reliability, responsiveness, empathy, tangibles, and assurance as shown in Figure 1.
| Source: | Parasuraman et al. (1988). |
3. Methodology
3.1. Data Collection
In the primary survey, agriculture and education loan borrowers of banks under the priority sector lending scheme were considered as the sample unit of the study. The questionnaire items were constructed and adapted from the existing intensive literature review. In this present research, the satisfaction level of customers toward the service quality provided by the banks is measured on a five-point Liker Scale (1=Strongly Disagree to 5=Strongly Agree). The researcher circulated 700 questionnaires, with responses received from 426, the research dropped out 87 incomplete responses on the whole and the final sample was 339. Table 1 shows the demographic classification of the respondents. The majority of the respondents are from rural areas. The majority of the respondents are female. The bulk of the population falls within the age range of 21 to 30. Hindus make up the majority in terms of faith. If marital status is taken into account the majority are unmarried. 41 % of the respondents are Post Graduates. Thus, while analysing the service quality of priority sector loans, the financial excluded categories, such as respondents from rural areas and women, are taken into account. Since the education loan is considered, the major beneficiaries namely young post graduates are considered as sample respondents.
3.2. Reliability and Validity
The two most crucial features of any measurement process are reliability and validity. Reliability is the belief that the measuring tool will provide the same numerical value when the measurement is repeated on the same object. The Cronbach alpha coefficient is often used by researchers to determine the scale's internal consistency. Cronbach's alpha value of 0.70 or above can be considered a good test of scale reliability.
Table 2 ensures the reliability and validity of the measurement model, wherein composite reliability was utilized as an alternative to the conventional Cronbach's alpha, based on previous literature (Bagozzi & Yi, 1988; Hair Jr, Sarstedt, Ringle, & Gudergan, 2017; Tenenhaus, Vinzi, Chatelin, & Lauro, 2005) . The table shows that, with values above the suggested threshold of 0.6, all reflective latent variables have high levels of internal consistency dependability. Chin (1998) and Höck and Ringle (2006). A composite reliability value of >=0.6 is considered acceptable to confirm model adequacy (Chin, 1998; Höck & Ringle, 2006), while a value of >=0.8 is considered good (Hair Jr et al., 2017). The obtained values in the present study confirm the composite reliability of the construct study. Furthermore, to support construct validity, convergent validity was assessed by examining the Average Variance Extracted (AVE) values, which were found to exceed the acceptable threshold of 0.5 as recommended by Bagozzi and Yi (1988), Chin (2010), and Hair Jr et al. (2017). In addition, discriminant validity was confirmed by calculating the square root of AVE for each latent variable, which was found to be greater than the other correlation values among the latent variables, in accordance with the criterion established by Fornell and Larcker (1981).
| Variables | Particulars | No. of respondents |
Percentage to total |
| Area of residence | Rural | 168 |
49.6 |
| Urban | 110 |
32.4 |
|
| Semi-Urban | 61 |
18.0 |
|
| Gender | Male | 158 |
46.6 |
| Female | 179 |
52.8 |
|
| Transgender | 2 |
0.6 |
|
| Age | Less than 20 years | 31 |
9.1 |
| 21 – 30 Years | 187 |
55.2 |
|
| 31 – 40 Years | 89 |
26.3 |
|
| 41 – 50 Years | 27 |
8.0 |
|
| Above 50 years | 5 |
1.5 |
|
| Category | Hindu | 199 |
58.7 |
| Muslim | 45 |
13.3 |
|
| Christian | 91 |
26.8 |
|
| Others | 4 |
1.2 |
|
| Marital status | Married | 134 |
39.5 |
| Unmarried | 189 |
55.8 |
|
| Widows | 7 |
2.1 |
|
| Widower | 3 |
0.9 |
|
| Separated | 6 |
1.8 |
|
| Educational qualification | School level | 47 |
13.9 |
| Graduate | 96 |
28.3 |
|
| Post graduate | 139 |
41.0 |
|
| Technical / Diploma | 24 |
7.1 |
|
| Professional degree | 33 |
9.7 |
Particulars |
Outer loadings |
Cronbach's alpha |
Composite reliability (rho_a) |
Composite reliability (rho_c) |
Average variance extracted (AVE) |
Ass 1 |
0.859 |
0.864 |
0.867 |
0.917 |
0.787 |
Ass 2 |
0.922 |
||||
Ass 3 |
0.880 |
||||
Reli 1 |
0.910 |
0.845 |
0.845 |
0.906 |
0.764 |
Reli 2 |
0.864 |
||||
Reli 3 |
0.846 |
||||
Emp 1 |
0.873 |
0.843 |
0.844 |
0.905 |
0.762 |
Emp 2 |
0.846 |
||||
Emp 3 |
0.898 |
||||
Tan 1 |
0.846 |
0.842 |
0.850 |
0.905 |
0.761 |
Tan 2 |
0.926 |
||||
Tan 3 |
0.844 |
||||
Res 1 |
0.875 |
0.852 |
0.854 |
0.910 |
0.771 |
Res 2 |
0.859 |
||||
Res 3 |
0.899 |
||||
CS 1 |
0.874 |
0.936 |
0.936 |
0.948 |
0.722 |
CS 2 |
0.817 |
||||
CS 3 |
0.836 |
||||
CS 4 |
0.851 |
||||
CS 5 |
0.849 |
||||
CS 6 |
0.861 |
||||
CS 7 |
0.857 |
4. Results and Discussion
The discriminant validity of the dimensions of service quality and customer satisfaction was assessed using the Fornell-Larcker criterion, as presented in Table 3. The diagonal values in the matrix represent the square root of the Average Variance Extracted (AVE), indicating the accuracy of measurement for each construct by its respective indicators.
The off-diagonal values, on the other hand, represent the correlations between the constructs. Overall, the results demonstrate that the constructs exhibit adequate discriminant validity, as the AVE values for each construct are higher than the corresponding inter-construct correlations. Notably, responsiveness and customer satisfaction had the greatest correlation coefficient in the matrix (0.778), demonstrating a substantial link between these dimensions.
The next highest correlation coefficient is 0.776, observed between empathy and tangibility, while the lowest correlation is 0.685, observed between assurance and customer satisfaction. In terms of individual construct reliability, all constructs surpass the recommended threshold of 0.7, with values ranging from 0.715 to 0.887, suggesting high internal consistency within each construct. Collectively, the Fornell-Larcker criterion provides empirical evidence of the discriminant validity of the service quality and customer satisfaction constructs, supporting the notion that these constructs are distinct and can be independently measured.
| Particulars | Assurance |
Reliability |
Empathy |
Tangibility |
Responsiveness |
Customer satisfaction |
| Assurance | 0.887 |
|||||
| Reliability | 0.715 |
0.874 |
||||
| Empathy | 0.733 |
0.743 |
0.873 |
|||
| Tangibility | 0.718 |
0.745 |
0.776 |
0.873 |
||
| Responsiveness | 0.723 |
0.737 |
0.738 |
0.747 |
0.878 |
|
| Customer satisfaction | 0.685 |
0.743 |
0.691 |
0.753 |
0.778 |
0.849 |
| Particulars | Assurance |
Reliability |
Empathy |
Tangibility |
Responsiveness |
Customer satisfaction |
| Ass 1 | 0.859 |
0.639 |
0.653 |
0.635 |
0.615 |
0.605 |
| Ass 2 | 0.922 |
0.670 |
0.667 |
0.652 |
0.678 |
0.636 |
| Ass 3 | 0.880 |
0.591 |
0.630 |
0.622 |
0.630 |
0.579 |
| Reli 1 | 0.653 |
0.910 |
0.613 |
0.666 |
0.633 |
0.662 |
| Reli 2 | 0.615 |
0.864 |
0.655 |
0.639 |
0.650 |
0.637 |
| Reli 3 | 0.606 |
0.846 |
0.679 |
0.647 |
0.649 |
0.648 |
| Emp 1 | 0.646 |
0.659 |
0.873 |
0.697 |
0.661 |
0.611 |
| Emp 2 | 0.604 |
0.619 |
0.846 |
0.612 |
0.584 |
0.586 |
| Emp 3 | 0.668 |
0.665 |
0.898 |
0.720 |
0.684 |
0.612 |
| Tan 1 | 0.606 |
0.642 |
0.634 |
0.846 |
0.620 |
0.660 |
| Tan 2 | 0.685 |
0.678 |
0.716 |
0.926 |
0.696 |
0.706 |
| Tan 3 | 0.582 |
0.628 |
0.681 |
0.844 |
0.637 |
0.600 |
| Res 1 | 0.666 |
0.642 |
0.633 |
0.648 |
0.875 |
0.682 |
| Res 2 | 0.606 |
0.646 |
0.638 |
0.620 |
0.859 |
0.647 |
| Res 3 | 0.634 |
0.655 |
0.673 |
0.697 |
0.899 |
0.719 |
| CS 1 | 0.594 |
0.670 |
0.644 |
0.705 |
0.670 |
0.874 |
| CS 2 | 0.622 |
0.675 |
0.641 |
0.643 |
0.672 |
0.817 |
| CS 3 | 0.588 |
0.614 |
0.572 |
0.639 |
0.652 |
0.836 |
| CS 4 | 0.557 |
0.597 |
0.548 |
0.615 |
0.680 |
0.851 |
| CS 5 | 0.588 |
0.637 |
0.568 |
0.632 |
0.675 |
0.849 |
| CS 6 | 0.567 |
0.598 |
0.578 |
0.626 |
0.651 |
0.861 |
| CS 7 | 0.550 |
0.619 |
0.550 |
0.613 |
0.623 |
0.857 |
Table 4 presents the cross-loadings for service quality and customer satisfaction. The cross-loadings indicate the extent to which each of the items in the service quality constructs and the customer satisfaction construct is related to each other. The results show that all of the items load significantly onto their respective constructs, indicating good construct validity.
In terms of the service quality construct, the cross-loadings show that all three items for Assurance (Ass) have significant loadings on the assurance construct, with loadings ranging from 0.859 to 0.922. Similarly, all three items for Reliability (Reli), Empathy (Emp), Tangibility (Tan), and Responsiveness (Res) also have significant loadings on their respective constructs, with loadings ranging from 0.846 to 0.926. In terms of the customer satisfaction construct, the cross-loadings show that all seven items (CS1-CS7) have significant loadings on the customer satisfaction construct, with loadings ranging from 0.817 to 0.874. These results indicate that the items in the customer satisfaction construct are measuring the same underlying construct. Overall, the cross-loadings suggest that the items in the service quality and customer satisfaction constructs are reliable and valid measures of their respective constructs.
| Particulars | Saturated model |
Estimated model |
| SRMR | 0.057 |
0.057 |
| d_ULS | 0.817 |
0.817 |
| d_G | 0.586 |
0.586 |
| Chi-square | 1301.548 |
1301.548 |
| NFI | 0.805 |
0.805 |
| Note: | PLS-SEM – Partial least squares structural equation modelling; SRMR – Standardized root mean square residual; ULS - Unweighted least squares; NFI – Bentler-bonett normed fit index. |
SRMR is used to confirm the goodness of fit in PLS-SEM which helps in avoiding model misspecification (Henseler et al., 2014). Conventionally when the SRMR value is lesser than 0.08, the model is considered a good fit (Hu & Bentler, 1998). A conservative value of less than 0.10 (Hu & Bentler, 1999) is considered a good fit. Table 5 revealed that the saturated model's SRMR was 0.057, less than 0.08, and is regarded as having a good match.
| Particulars | Standard deviation (STDEV) |
T statistics (|O/STDEV|) |
Path coefficient |
P values |
Decision |
| Assurance -> Customer satisfaction | 0.062 |
1.157 |
0.072 |
0.247 |
Not supported |
| Reliability -> Customer satisfaction | 0.066 |
3.553 |
0.233 |
0.000 |
Supported |
| Empathy -> Customer satisfaction | 0.066 |
0.082 |
-0.005 |
0.935 |
Not supported |
| Tangibility -> Customer satisfaction | 0.068 |
3.860 |
0.261 |
0.000 |
Supported |
| Responsiveness -> Customer satisfaction | 0.073 |
4.978 |
0.364 |
0.000 |
Supported |
The study aimed to investigate the relationship between five dimensions of service quality - assurance, reliability, empathy, tangibility, and responsiveness - and customer satisfaction and the results were revealed in Table 6 . The results of the path analysis revealed that only three out of the five dimensions significantly impacted customer satisfaction. Specifically, the path linking assurance to customer satisfaction was found to be insignificant at a 0.05 level of significance (t-1.157), indicating that assurance has no significant impact on customer satisfaction.
Therefore, Hypothesis H1 was not supported. In contrast, dependability was discovered to be a substantial driver of customer satisfaction since the path connecting the two variables was determined to be significant at a 0.05 level of significance (t-3.553).
Hence, Hypothesis H2 was supported. The path relating empathy to customer satisfaction was also found to be insignificant at a 0.05 level of significance (t-0.082), indicating that empathy does not affect customer satisfaction. Therefore, Hypothesis H3 was not supported. On the other hand, the path linking tangibility to customer satisfaction was found to be significant at a 0.05 level of significance (t-3.860), indicating that tangibility significantly contributes to customer satisfaction. Consequently, Hypothesis H4 was supported. Finally, the path linking responsiveness to customer satisfaction was found to be significant at a 0.05 level of significance (t-4.978), suggesting that responsiveness has a significant impact on customer satisfaction. Therefore, Hypothesis H5 was supported.
Figure 2 illustrates the results of path analysis and hypothesis testing. It indicates the relationships between the items in the service quality and customer satisfaction constructs. The path analysis supports the overall validity of the measurement model utilised in the analysis by showing that the items in both the service quality and customer satisfaction constructs are accurate and valid measurements of their respective constructs.
5. Conclusion
The primary objective of the present study was to assess the service quality and customer satisfaction among users of agriculture and educational loans under the priority sector lending scheme. To achieve this goal, the study employed Structural Equation Modeling (SEM) to measure customer satisfaction based on the five dimensions of service quality, namely assurance, reliability, empathy, responsiveness, and tangibility. The findings of the study indicated that customers expressed satisfaction with the reliability, responsiveness, and tangibility aspects of banking service quality. However, they felt that assurance and empathy were lacking during their agriculture and education loan processes. These results imply that there is potential for improvement in bankers' assurance and empathetic behaviour when processing loans under the priority sector lending programme. The study was limited to only the educational and agricultural loan beneficiaries thus the findings cannot be generalized to all banking services. The implications of these findings are significant, as they provide valuable insights into the service quality of priority sector lending. The study's recommendations could help improve the quality-of-service delivery in the priority sector lending scheme, which could, in turn, increase customer satisfaction and loyalty. The findings could also inform policymakers and banking institutions about the importance of prioritizing empathy and assurance in their service delivery processes. The study will also assist staff and consumers understand the services provided and received, and it will aid policymakers in making decisions that will result in exceptional customer service. Overall, the study's results contribute to the existing literature on service quality and customer satisfaction in the banking industry, specifically in the context of priority sector lending. Further research can be attempted on other priority sector lending with additional constructs such as customer experience, customer preferences, etc.
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