Investigation of Factors That Affecting on Customer Loyalty in Banking Sector in Egypt ()
1. Introduction
Customer loyalty has become a significant concern in the banking sector due to the increasing competition and instability of exchange rates in Egypt. Therefore, it is crucial to study customer loyalty from both scientific and practical standpoints to overcome the challenges that arise in the banking sector market. Customer loyalty refers to the degree to which a customer repeatedly chooses to do business with a company by using its services or buying its products. Loyalty is a feeling of attachment that ties consumers with the brand, and the result will be regular purchasing [1]. In recent years, there has been a growing need for banks to prioritize customer loyalty. Customer loyalty to services in the banking sector has become an essential point for researchers. While customer loyalty in the banking industry is influenced by various factors, customers demand a diverse range of services, and bank personnel strive to retain and expand their customer base. Consequently, banks offer a wide array of programs and recommendations that can be implemented to strengthen the bank’s presence and increase customer loyalty. Therefore, successful banks focus on earning customer loyalty. Customer loyalty is a vital concern for retail banks [2].
Customer loyalty is one of the strongest invisible assets of a company, and becoming unique is very potential for companies in terms of behavior and attitude. In addition, it allows companies to get a competitive advantage. In addition, in recent years, there has been an increase in academic studies that highlighted the loyalty of clients toward banks. Researchers have struggled to realize all aspects of customer loyalty, to protect how it can be influenced, and, subsequently, to expect the behavior of future consumers [3]. Previous studies have shown that several variables affect customer loyalty, with the most common being service quality, trust, customer satisfaction, and brand image. Different factors have an impact on customer loyalty, including service quality and customer satisfaction levels [4].
The problem of customer loyalty has emerged as one of the primary problems in many banking institutions because it determines, to a large extent, success or competitiveness. Customer loyalty is not easily obtained in banks because of factors such as satisfaction, trust, service and quality, and brand image. This paper highlights customer loyalty and the factors that affect it to achieve success in the banking sector. As explained by Hussein, M.A et al. (2023), the role of banks regarding the provision of financial services is critical: They have to contribute to the growth of economies; it is in the highly competitive environment of the banking sector that they try to work on customer loyalty so that customers gain durability [5].
As customer loyalty becomes increasingly important in competitive markets, scholars have indicated that research on banking customer loyalty is relatively scant and often focused on narrow aspects like customer satisfaction or trust, rather than being a comprehensive study. This shortfall has given a clear-cut direction that empirical studies must be conducted wherein such variables are looked at through a complete, integrated model to draw useful insights that go towards building loyal strategies in the banking sector. So, the objectives of this paper are to understand the importance of customer loyalty in success and achieving profits for banks (RO1). Examining factors that affect the loyalty of customers in the banks in Egypt (RO2). Investigation of the relationships between independent variables customer satisfaction, trust, service quality, brand image, and dependent variable customer loyalty (RO3). And examine the roles of service quality dimensions (Tangibility, Reliability, Responsiveness, Assurance, Empathy) in maintaining customer loyalty in banks (RO4). Assessing if the demographic factors of respondents who represent a sample act as moderators of the relationship between the independent factors and customer loyalty (RO5). Finally, analyze how these factors could affect customer decisions in choosing between banks and suggest recommendations for maintaining customer loyalty in banks (RO6).
Mainly, this research aims to understand the parameters of customer loyalty in banks in Egypt and formulate a plan to maintain it. Hypotheses were developed and tested through questionnaires, data analysis, and different methods to reach findings and constructive recommendations.
2. Literature Review & Hypothesis Development
This section discusses the literature reviews on customer loyalty within the context of the banking sector. The review starts with customer loyalty, highlighting a definition and the role of customer loyalty. Then, the discussion highlighted that most variables in the previous literature reviews affect customer loyalty, such as customer satisfaction, trust, and service quality, through its five dimensions: tangibility, reliability, responsiveness, assurance, and empathy. It’s highlighted that, if banks want to create close relationships with clients, they should be aware of influential factors of customer loyalty. Lastly, based on the proposed research model, there are hypotheses that are to be analyzed and tested.
2.1. Customer Loyalty
Previous studies highlighted that customer loyalty is how the consumer behaves towards a brand. It is an essential factor, to get business revenue. Customers want to maintain a valuable relationship with a brand. In other words, loyalty can guide the customer’s desire, if he will repeat his visit to the brand or not [6]. Marketing strategies are enhanced to catch consumers, but in the last few years, new challenges have appeared. They have been shifted to the maintaining of existing clients, to create their loyalty to the company [7]. Customer loyalty is the extent of adherence to a particular good, service, or brand over time.
It’s assumed that increasing competitiveness leads banks to focus on creating customer loyalty, as financial services organizations found that loyalty could protect them from poaching their customers [8]. Studies in customer loyalty have highlighted how existing customers are important to a bank. But if a customer buys repeatedly from a bank, it will depend on the situation allowed for him. Retailing banks in Tanzania compete with other financial institutions that offer relatively similar services. So, there will be Customer loyalty challenges. When customers become loyal, they won’t hesitate to speak positively about the bank’s services. Keeping existing consumers’ needs to take precedence over acquiring new ones, as the former is more difficult and expensive, and the latter results in a loss for the business should it decide to be part of loyal customers [9]. Customer loyalty is the backbone of companies because it’s important to increase their profits and sales. It is clear from previous studies that the cost of attracting new clients is more difficult than maintaining current customers [10].
2.2. Customer Satisfaction
Some authors suggested that customers feel satisfied when they purchase products that meet and exceed expectations. Satisfaction is a result when customers aren’t sure that their desires will achieved [11]. Customer satisfaction could defined as a measure of how products and services that are offered will engage and then attain customer expectations. Customer satisfaction is defined as the psychological condition that consumers feel towards items, and it’s the gap between the customer’s expectations and their experience in gaining service [12]. Various researchers believed in the importance of customer satisfaction and dissatisfaction, they linked success and failure with customer satisfaction. Fails in terms of satisfying the company’s and the customers’ expectations [13]. Customer satisfaction is considered a landmark in creating the relationship between an organization and the customer [14]. Satisfaction has a positive impact on customer loyalty. When customers feel satisfied, they will buy and convince others to purchase items from a company. Other authors stated that customer satisfaction is essential for determining customer loyalty. This would enhance the relationship between the bank and the customer, thereby enhancing customer loyalty. It’s argued that customer satisfaction could be seen as an outcome of the interactions between customers and customer service. In this respect, customer loyalty also arises from these experiences. Therefore, based on previous studies the first hypothesis emerged: H1 there is a significant effect of customer satisfaction on customer loyalty). If customers in Egypt are satisfied with their bank’, they are more likely to remain loyal, leading to increased customer loyalty.
2.3. Trust
Previous researchers suggested that trust has two definitions. Trust is defined as assurance in knowledgeable partners. Trust is also perceived as the intentional behavior that displays partner trust, which includes the trusting party’s aspect of uncertainty [15]. Trust could be defined as a feeling of mutual assurance between two parties. Trust is the willingness of a customer to be exposed to a product based on good expectations about the perfect quality that will be offered. Building trust with customers requires businesses to interact with them sincerely. Another one stated that customers trust banks when dealing honestly and sincerely together [15]. Besides this, cultivated customer trust can be a further strategic marketing tool in which customers refer relatives and family to the product of interest. In recent years, authors have found the loyalty of customers by re-purchasing products despite alternatives from competitors. Displays of loyalty to banks are evidence of trust toward the organization. Customer loyalty and trust are important factors in the banking sector. Working on building trust and commitment with provided services can be reasons for customer loyalty for firms. Trust is a tool that could be used to measure the loyalty of customers. Also, it’s stated that trust is essential for the attainment of customer loyalty. Customers’ loyalty decreases if they don’t trust a company that provides them with goods or services. Therefore, the second hypothesis is: H2 there is a significant effect of trust and customer loyalty. Having trust in a bank is crucial for customers to remain loyal in Egypt, even in the face of competition.
2.4. Service Quality
Service refers to action taken to benefit a customer. Therefore, service quality is the difference between the performance that a customer expects to receive, and the actual performance of the service provided. Customers differentiate the quality of service in banks based on physical features such as the accomplishment of services, and the time range of service provided. Service quality has been described in terms of five dimensions of quality including five aspects: tangible, reliability, responsiveness, assurance, and finally empathy, even though. The tangibility of the services given by materials machines and physical facilities of the organization. The reliability dimension refers to an organization’s ability to achieve clients’ requests on its promises to customers and desires. They also highlighted that reliability plays a crucial role in the operation of traditional service providers, encompassing accuracy in billing, quotations, records, and order fulfillment commitment. This definition has been revised by some authors to include the prompt delivery of services to counter the issues of long lines and waiting periods. Empathy is defined as a key aspect of service quality, where a company’s employees provide customers with the attention they deserve, address their unique concerns, and understand their needs.
The last dimension is the assurance dimension, which demonstrates the provision of security and safety to customers so that it will lessen their state of worries and anxieties about the services provided to them. Most marketers believe that the success of any business and establishing a good marketing strategy is formed by service quality provided for customers. Most banks nowadays prepare their strategies and build their philosophy for enhancing loyalty through service quality [16]. Excellent service quality could support the loyalty of customers [17]. It’s recommended that bank employees always be pleasant to customers as it increases loyalty by creating a positive impression of the bank’s service quality. Wakefield and Blodgett, 1999, discussed the fact that Tangible elements of the environment of service contact provide a significant basis for emotionally arousing customer responses and their loyalty. The hypothesis is: H3A there is a significant effect of tangibility on customer loyalty. Reliability is the most fundamental dimension and indicator of service quality. The hypothesis is: H3B there is a significant effect of reliability on customer loyalty. It’s also suggested that responsiveness highlights the standards of the firm being effective and also reflects the ability to interact continuously with clients. Therefore: The hypothesis is: H3C there is a significant effect of responsiveness on customer loyalty. Also, the empathy dimension of service, after experiencing it with a firm, impacts the reaction of a customer and improves his communication with the firm more than anything else could. Therefore, The hypothesis is: H3D there is a significant effect of empathy on customer loyalty. It’s highlighted that assurance is really significant in enhancing client confidence, due to which talented personnel interact directly with the customers. These staff have to be professional in providing services because they have to meet and exceed expectations regarding the clients.: the hypothesis is H3E there is a significant effect of assurance on customer loyalty.
2.5. Brand Image
Brand image is defined as a set of ideas that exist in the minds of consumers. Image concludes many aspects of attributes such as location, nature, and price [18]. Several researchers have highlighted that the image of an institution is largely shaped by the perceptions of specific stakeholder groups, such as consumers or investors. Brand Image is defined as views about a brand as expressed by brand associations held in consumer memory. Bank represents an exceptional business where positive or negative images may greatly affect its activities. Banks with a bad image struggle to attract and retain customers, while those banks with a good image will have a much easier task in achieving it [18]. A strong brand image can encourage customers to repeatedly use their services and eventually develop customer loyalty [19]. Bank image has a strong and important impact on customer loyalty. So, a good bank image supports good customer loyalty. Another author mentioned that brand image influences loyalty.
Brand image has a beneficial impact on consumer loyalty. Based on these findings, the last hypothesis is: H4 there is a significant effect of brand image on customer loyalty. Generally, people prefer using products and services with good image perceptions. And as per below, Figure 1 shows proposed research model for all hypotheses in this paper.
3. Research Methodology
This section aims to describe which is the methodological approach implemented by the researcher to answer the research question using empirical data.
Figure 1. Proposed research model.
Using a positivist philosophy and a deductive approach makes quantitative research an appropriate method for this study. This approach enables a thorough response to the research questions, as indicated by Cohen et al. (2011). This study employs a descriptive analysis to illustrate the demographic and other characteristics of the participants based on the introductory questions in the questionnaire and identify the relationships between the variables in each hypothesis.
Given the nature of the research problem, and based on previous studies of this topic, a correlational study is also utilized to examine the potential relationships between two or more variables. The investigation in this study is based on correlational analysis. In this correlational study, the researchers aim to describe the relationship between independent variables and the dependent variable. These relationships are examined through hypothesis testing. It has also been pointed out that reliability can be evaluated through statistical means by analyzing internal consistency or correlations between variables, often with Cronbach’s alpha reliability coefficient. Additionally, the validity of research results is a significant advantage of this method. By using approaches such as survey research, coupled with suitable sampling methods, instruments, and statistical analyses, this study guarantees solid quantitative results that effectively address the research questions.
In this research, the primary data were gathered using questionnaires. The respondents were given a similar set of questions in advance by the researcher. Gathering information through surveys takes considerable time, hence, efficient software tools are essential for creating, distributing, and quickly processing the results. One widely used tool for collecting information is a questionnaire [20]. This particular questionnaire facilitates understanding the perspectives of respondents and provides standardized responses; all of this organizes the information in a manner that reduces analysis time. To minimize interference, the research involved distributing questionnaires online. The researcher sent out questionnaires designed for completion 30 without any outside influence.
The scale used to measure the dependent variable “customer loyalty” and the independent variables affecting it, as well as the demographic questions that helped researchers identify more about respondents’ attitudes and reactions toward the bank, were extracted from the previous form in the previous study. Likert scales grounded in classical testing theory are widely accepted and favored by 31 researchers for capturing inherent characteristics. Therefore, the researcher decided to use this Likert scale, and participants recorded their responses on a 5-point Likert scale ranging from 1 = ‘‘Strongly Disagree’’ to 5 = ‘‘Strongly Agree’’ [21].
Individual bank customers in Egypt have been selected as the unit of analysis since the main goal of this study is to investigate the elements affecting customer loyalty in the banking industry. This study, on the other hand, used a cross-sectional time horizon. One kind of observational research when data is examined at one particular moment is called a cross [22] sectional study. In these investigations, the sample population’s exposures and outcomes are measured concurrently. This method is frequently compared to taking a “snapshot” of a certain group [23]. Consequently, a cross-sectional temporal horizon is used in this research, and data collection is planned for August 2024.
The target population in this research involved bank clients of different cities in Egypt. Information on variables affecting customer loyalty in the banking industry was collected from people in different cities to better represent the study [24].
Convenience sampling is a non-probability technique that was used in this study because there was no sampling frame for bank customers. Data collection was conducted in August 2024, when a total of 520 respondents were able to answer the survey questionnaire. The questionnaires were distributed online via social media platforms such as LinkedIn, WhatsApp, and Facebook to the selected sample of the population, which represented clients from different banks in Egypt. This was carried out with the assistance of employees while customers were inside the branches of various banks to guide them in case of any inquiries. After reviewing the responses, 16 responses were rejected for not being suitable for analysis and hence were excluded from this study. 96.6% of the questionnaires distributed were fit and represented 504 participants in this survey. SPSS software version 26 was used to analyze the data collected to achieve the research objectives. Analytical techniques such as validity analysis, frequency analysis, linear regression, and reliability analysis will be employed. Statistical methods used to test the associations between customer loyalty and its drivers: correlation and regression analyses.
4. Data Analysis
Analytical techniques such as validity analysis, frequency analysis, linear regression, and reliability analysis will be employed. Statistical methods used to test the associations between customer loyalty and its drivers: correlation and regression analyses.
4.1. Reliability and Validity Analysis
Construct reliability is the degree to which a set of indicators consistently and stability reflect given constructs. It identifies if the instrument is reliable, Cronbach’s alpha was used to analyze numbers of items and the result. Data is considered poor if the Cronbach alpha is less than 0.60 and it is acceptable at 0.70, moreover, if the value is over 0.80 then data is more reliable. The Cronbach’s alpha of each construct is the research model is presented in Table 1. Cronbach’s alpha for all constructs exceeds 0.80 which means more reliable, except Empathy 0.794 is reliable according to the recommended level of 0.70 for the research indicators.
Table 1. Reliability and validity analysis.
Variables |
Validity |
AVE % |
Cronbach’s
Alpha if item
deleted |
Customer loyalty: |
|
73.3 |
0.954 |
CL1 |
0.734 |
CL2 |
0.722 |
CL3 |
0.718 |
CL4 |
0.782 |
CL5 |
0.709 |
Customer satisfaction: |
|
53.5 |
0.948 |
CS1 |
0.566 |
CS2 |
0.579 |
CS3 |
0.462 |
CS4 |
0.533 |
Trust |
|
71.57 |
0.895 |
Tr1 |
0.784 |
Tr2 |
0.728 |
Tr3 |
0.657 |
Tr4 |
0.694 |
Service quality (Tangible): |
|
3.5 |
0.859 |
Tang1 |
0.643 |
Tang2 |
0.587 |
Tang3 |
0.674 |
Tang4 |
0.637 |
Service quality (Reliability): |
|
9.23 |
0.902 |
Rel1 |
0.467 |
Rel2 |
0.503 |
Rel3 |
0.537 |
Service quality (Responsiveness): |
|
67.9 |
0.844 |
Ress1 |
0.564 |
Ress2 |
0.668 |
Ress3 |
.706 |
Ress4 |
0.724 |
Ress5 |
0.733 |
Service quality (Empathy): |
|
63.62 |
0.794 |
Emp1 |
0.668 |
Emp2 |
0.549 |
Emp3 |
0.702 |
Emp4 |
0.624 |
Emp5 |
0.638 |
Service quality (Assurance): |
|
62.62 |
0.846 |
Ass1 |
0.627 |
Ass2 |
0.557 |
Ass3 |
0.673 |
Ass4 |
0.648 |
Brand image: |
|
77.2 |
0.948 |
BI1 |
0.826 |
BI2 |
0.798 |
BI3 |
0.756 |
BI4 |
0.708 |
Validity analysis is utilized in this study to assess the accuracy of scales. The scale’s measure, which is intended to evaluate specific constructs, is analyzed, including 48 comparisons between the results and established standards. It’s also highlighted that discriminant validity assesses the extent of measurement if does not correlate with other constructs. The researcher used the mentioned analysis to identify whether or not the scale measures the variables accurately. Also, assess if this scale captures all relevant aspects of the construct. In this research, factor loading is utilized to ensure the relationships between the item and the factor; If factor loading is higher than 0.30, it means a moderate correlation between the item and the factor.
Table 1 shows that all results are above 0.30, which means that these items successfully represent these variables. Also, the average variance extracted (AVE) is used in this study to evaluate construct validity. Thus, the value of average variance refers to how well a hidden latent construct contributes to variation in its indicators. Since the Average Variance Extracted (AVE) is higher than 0.50, the results are valid for at least half of their respective indicators.
4.2. Frequency Analysis
Frequency analysis is used to display the frequency count of responses on demographic variables: gender, age, education, marital status, employment, and income. This statistical method will help present the distribution of responses on each demographic variable and describe how often different values are taken in the data. Also, it’s pointed out that frequency distribution refers to how frequently a value occurs in a set of data. Data is also divided into subgroups across the range of values [25]. This analysis leads scholars to reach clear conclusions about the population under study. The majority of the respondents to the questionnaire were female accounting for 59.6% of the sample while males were 49.4%. The ages of the participants are as follows: 5.6% of respondents are between 18 and 24 years old, 41.5% are aged 25 to 34 years, 36.9% are aged 35 to 44 years, 9.9% are aged 45 to 54 years, 5.2% are aged 55 to 64 years, and only 1.0% are 65 years old or above. The majority, at 60.1%, hold a bachelor’s degree, while 31.7% have pursued postgraduate studies. The largest group of participants is from Cairo, which accounts for 32.3% of the total sample. Those residing in Alexandria make up 25.2%, while participants from Asyut represent 29.0%. Finally, 13.5% from other cities in Egypt. Also t 39.7% of the sample is single, 55.6% are married, 4.0% are divorced, and 0.8% are widowed. Finally, the largest group, 46.8%, comprises individuals with incomes ranging from 5,001 EGP to 10,000 EGP. Following this, 30.8% of respondents have incomes between 10,001 EGP and 30,000 EGP. Only, 8.9% report earning more than 30,000 EGP.
4.3. Correlational Analysis
Correlation analysis is utilized to measure the degree of strength relationship between two variables. Correlation does not refer to causality like regression, it measures association relationships without predictions; Also, it helps identify the strong degree and direction between two variables in an environment. In addition, it’s highlighted if the p-value is less than 0.05, this refers to significance at the 5% threshold. So researchers can utilize correlation analysis to explore the relationship between two variables. Table 2 shows correlation coefficient between customer loyalty as dependent variably and other independent variables.
Table 2. Correlation coefficient between customer loyalty and other variables.
Dependent variable |
Independent variable |
r Person |
Significance |
Customer
loyalty |
Customer satisfaction |
0.709 |
0.000 |
Trust |
0.566 |
0.000 |
Service quality (tangible dimension) |
0.768 |
0.000 |
Service quality (reliability dimension) |
0.600 |
0.000 |
Service quality (responsiveness dimension) |
0.606 |
0.000 |
Service quality (empathy
dimension) |
0.577 |
0.000 |
Service quality (assurance
dimension) |
0.532 |
0.000 |
Brand image |
0.509 |
0.000 |
H1 there is a significant effect of customer satisfaction on customer loyalty. Using correlation analysis which is shown in the above table to test the relationship between variables dependent (Customer loyalty) and (Customer satisfaction). The value of r Person is (0.709) results from the analysis. The significance value is (0.000), these results refer to a significant, positive, and strong relationship between customer loyalty and customer satisfaction. As the r Person value is above 0.5 thus. There is a significant strong relationship that supports the first hypothesis.
H2 there is a significant effect between trust on customer loyalty. There is a relationship between the dependent variable(Customer loyalty) and the independent variable (Trust). The results of the analysis show the value of r Person is (0.566) and the significance value is (0.000), these results refer to a significant, positive, and moderate relationship between customer loyalty and trust. As the r Person value is between values 0.3 and 0.5 thus. There is a significant moderate relationship that supports the second hypothesis.
H3A there is a significant effect of tangibility on customer loyalty. There is a relationship between the dependent variable(Customer loyalty) and the service
quality dimension (Tangible). The results of the analysis show the value of r Person is (0.768) and the significance value is (0.000), these results refer to a significant, positive, and strong relationship between customer loyalty and Tangible. since the r Person value is higher than 0.5 thus. There is a significant strong relationship that supports the third hypothesis.
H3B there is a significant relationship effect of reliability on customer loyalty. There is a relationship between the dependent variable (Customer loyalty) and the service quality dimension (Reliability).
Results of the analysis show the value of r Person is (0.600) and the significance value is (0.000), above results indicate a significant, positive, and strong relationship between customer loyalty and Reliability. since the r Person value is higher than 0.5, therefore. There is a significant strong relationship that supports the third hypothesis.
H3C there is a significant effect of responsiveness and customer loyalty. There is a relationship between the dependent variable (Customer loyalty) and the service quality dimension (responsiveness). The results of the analysis show the value of r Person is (0.606) and the significance value is (0.000), these results refer to a significant, positive, and strong relationship between customer loyalty and responsiveness. Since the r Person value is over 0.5, so. There is a significant strong relationship that supports the third hypothesis.
H3D there is a significant effect of empathy on customer loyalty. There is a relationship between the dependent variable (Customer loyalty) and the service quality dimension (empathy). The results of the analysis show the value of r Person is (0.577) and the significance value is (0.000), these results refer to a significant, positive, but strong relationship between customer loyalty and empathy. Since the r Person value is a little bit higher than 0.5, so. There is a significant strong relationship that supports the third hypothesis.
H3E there is a significant effect of assurance on customer loyalty. There is a relationship between the dependent variable (Customer loyalty) and the service quality dimension (assurance). The results of the analysis show the value of r Person is (0.532) and the significance value is (0.000), these results refer to a significant, positive, and relatively strong relationship between customer loyalty and assurance. Since the r Person value is higher than 0.5, so. There is a significant relatively strong relationship that supports the third hypothesis. Overall, since all dimensions of service quality have a significant relationship with customer loyalty, so it’s supported that there is a significant relationship between the independent variable (Service quality) and the dependent variable customer loyalty.
H4 there is a significant effect of brand image on customer loyalty. Finally, there is a relationship between the dependent variable (Customer loyalty) and the independent variable (Brand Image). Results of the analysis show the value of r Person is (0.509) and the significance value is (0.000), these results refer to a significant, positive, and moderate relationship between customer loyalty and Brand Image. As the r Person value is between values 0.3 and 0.5 thus. There is a significant moderate relationship that supports the fourth hypothesis.
4.4. Regression Analysis
Linear regression is a regression test technique that uses two types of regression: simple and multiple regressions. Simple linear regression is used when there is only a single dependent variable and only a single independent variable. Both the them have to be continuous and the relationship is described by a straight line (linear). Multiple linear regression is utilized if there is one continuous dependent variable and more than one single independent variable.
Correlation analysis is essential before conducting multiple regression, it enables a more advanced exploration of the relationships among variables [25]. The researcher examines the ANOVA which stands for Analysis of Variance to determine if the model as a whole fits well for the data or not. ANOVA can analyze as many groups, it examines the relationship between variables when there is a nominal level independent variable and a normally distributed interval/ratio level of dependent variable resulting in an F-ratio, which explores statically the significance of results (Singh, 2007). For a good model fit, the p-value of the ANOVA has to be higher than 0.05m so that the relationship will be significant. Adjusted R Squared value meaning the coefficient of determination is utilized to explore the extent of variance in the dependent variable that contributes to the model. Additionally, the researcher analyzed the Beta coefficient of each independent variable to examine whether one has a wide influence and impact on the dependent variable. A higher Beta coefficient value means a higher contribution. As for the b value it shows for each one unit change in (IV), how much is the variation that is expected to occur on the (DV). Table 3 shows that multiple regression analysis results.
Table 3. (a) multiple regression analysis results; (b) model summery.
(a) |
Model |
Unstandardized
coefficients |
Standardized
coefficients |
t |
Sig. |
B |
Std. Error |
Beta |
1 |
(Constant) |
5.705 |
0.688 |
|
8.290 |
0.000 |
Customer satisfaction |
0.546 |
0.054 |
0.501 |
10.148 |
0.000 |
Trust |
0.007 |
0.061 |
0.006 |
0.114 |
0.909 |
Service quality (Tangible) |
0.276 |
0.037 |
0.270 |
9.873 |
0.000 |
Service quality (Reliability) |
0.056 |
0.069 |
0.050 |
0.822 |
0.411 |
Service quality (Responsiveness) |
0.128 |
0.058 |
0.142 |
2.191 |
0.029 |
Service quality (Empathy) |
0.129 |
0.056 |
0.133 |
2.324 |
0.021 |
Service quality (Assurance) |
0.011 |
0.081 |
0.010 |
0.135 |
0.893 |
Brand image |
0.025 |
0.055 |
0.026 |
0.452 |
0.651 |
(b) |
Model summary |
Model |
R |
R square |
Adjusted R square |
Std. error of the estimate |
1 |
0.732a |
0.536 |
0.529 |
2.34495 |
a. predictors: (constant), brand image, satisfaction, trust, empathy, service. Quality, reliability, responsiveness, assurance |
ANOVAa |
Model |
Sum of squares |
df |
Mean square |
F |
Sig. |
1 |
Regression |
3146.021 |
8 |
393.253 |
71.516 |
0.000b |
Residual |
2721.907 |
495 |
5.499 |
|
|
Total |
5867.929 |
503 |
|
|
|
a. dependent variable: loyalty |
b. predictors: (constant), brand image, satisfaction, trust, empathy, service. Quality, reliability, responsiveness, assurance |
H1 there is a significant effect of customer satisfaction on customer loyalty. Multiple regression analysis was utilized to test the hypothesis. Table 2 and Table 3 show the Value of ANOVA (p) = 0.000 which refers to the significance of the presented relationship. The Adjusted R squared = 0.529 suggests that the model causes a 53.9% variance-dependent variable value. Tables show also that the model is significant (F = 71.516) p < 0.000, the predictors collectively affect customer loyalty. The beta coefficient highlights the largest influence of the independent variable on Customer loyalty, results showed that the value of Beta = 0.501 for customer satisfaction, which means customer satisfaction has the strongest impact on customer loyalty. As for the B coefficient, the results imply that for every unit change in customer satisfaction, leading to changes in customer loyalty by 0.546, other variables are still consistent. This hypothesis is supported by p-value equal to 0.000
H2 there is a significant effect of trust on customer loyalty. Value of ANOVA (p) = 0.909 for the second variable (Trust) which refers to an insignificant positive relationship between customer loyalty and trust. Value of Beta = 0.006 for trust. B coefficient, the results imply that for every unit change in trust, leading to changes in customer loyalty by 0.007, other variables are still consistent. This hypothesis is not supported by p-value equal to 0.909
H3A there is a significant effect of tangibility on customer loyalty. Value of ANOVA (p) = 0.000 for the service quality dimension (Tangible) which refers to the positive significance of the relationship. value of Beta = 0. 270 for Tangible, which means Tangible has a strong impact on customer loyalty. B coefficient, the results imply that for every unit change in tangible, leading to changes in customer loyalty by 0.276, other variables are still consistent. This dimension hypothesis is supported by p-value equal to 0.000
H3B there is a significant effect of reliability on customer loyalty. Value of ANOVA (p) = 0.411 for the service quality dimension (reliability) which refers to the positive insignificance of the relationship. value of Beta = 0.050 for reliability. B coefficient, the results imply that for every unit change in reliability, leading to changes in customer loyalty by 0.056, other variables are still consistent. This dimension hypothesis is not supported with p-value equal to 0.411.
H3C there is a significant effect of responsiveness on customer loyalty. Value of ANOVA (p) = 0.029 for the service quality dimension (responsiveness) which refers to the positive significance of the relationship. Value of Beta = 0.142 for responsiveness, which means responsiveness has a strong impact on customer loyalty. B coefficient, the results imply that for every unit change in responsiveness, leading to changes in customer loyalty by 0.128, other variables are still consistent. This dimension hypothesis is supported with p-value equal to 0.029
H3D there is a significant effect of empathy on customer loyalty. Value of ANOVA (p) = 0.021 for the service quality dimension (empathy) which refers to the positive significance of the relationship. Value of Beta = 0.133 for empathy, which means empathy has a strong impact on customer loyalty. B coefficient, the results imply that for every unit change in empathy, leading to changes in customer loyalty by 0.129, other variables are still consistent. This dimension hypothesis is supported by p-value equal to 0.021
H3E there is a significant effect of assurance on customer loyalty. Value of ANOVA (p) = 0.893 for the service quality dimension (assurance) which refers to the positive insignificance of the relationship. Value of Beta = 0.010 for assurance. B coefficient, the results imply that for every unit change in assurance, leading to changes in customer loyalty by 0.011, other variables are still consistent. This dimension hypothesis is not supported by p-value equal to 0.893.
Overall, there are 3 dimensions of service quality out of 5 that have a strong significant relationship with customer loyalty, then this hypothesis is supported.
H4 there is a significant effect of brand image on customer loyalty. Value of ANOVA (p) = 0.651 for the last variable (Brand Image) which refers to the positive insignificance of the relationship. Value of Beta = 0.026 for brand image. B coefficient, the results imply that for every unit change in brand image, leading to changes in customer loyalty by 0.025, other variables are still consistent. This hypothesis is not supported by p-value equal to 0.651.
5. Research Conclusions and Discussion
In summary, this research study aims to investigate factors affecting customer loyalty in banking sector in Egypt. The significance of customer loyalty in the banking sector and its profound impact on business cannot be overstated, especially given the strong competition for retaining customers. Banks aim to create positive relationships with customers and build loyalty [26]. Comprehensive literature review highlights that customer loyalty in banking results from multiple interacting factors, including customer satisfaction, trust, service quality, and brand image. In addition, the researcher also examined the five aspects of service quality, tangibility, assurance, responsiveness, empathy, and reliability. These should not be left out of this study. The researcher provides a thorough discussion of each variable, defining them based on prior studies and exploring their roles and importance in the banking sector. The relationship between these variables and customer loyalty is a focal point of the research, which emphasizes customer loyalty within the context of banking. Frequency analysis is used to understand participants through their answers, and also clarifies the sample demographics, in addition, reliability and validity analyses are used to emphasize the credibility of scales. The results of this research are important for bank management, which intends to compete in creating customer loyalty in the future. It plays an important role in the success of any organization. Bank managers should focus on customer satisfaction and service quality to make a positive recommendation to others.
The researchers recommend that although the results showed that trust and brand image are not factors that directly and significantly affect customer loyalty in Egypt. This may be due to several reasons that are more related to the social, economic, and behavioral aspects of the Egyptian market. For instance, relying on direct practical benefits such as better financial offers or easy access to services instead of relying on trust as a major factor. ِAlso, bank clients in Egypt favor banks that have personal relationships with their employees regardless of the general trust in the bank. Also, regarding the bank’s brand image, its lack of importance in achieving customer loyalty in banks in Egypt may be due to the lack of brand distinction, as banks in Egypt offer largely similar banking products,
which makes it less important than others. Also, customers tend to go towards government banks in Egypt as they consider them safer and more stable due to the government’s support.
5.1. Academic Contribution
Research added deep definitions of customer loyalty and gave new insights into the meaning and role of customer loyalty in the banking industry. It has also pointed out the importance of investigating service quality and customer satisfaction to strengthen customer loyalty, especially in developing markets like Egypt. The study strengthens existing literature value by relating a list of factors to customer loyalty [27]. The study also contributed by helping to address the shortage in the number of studies focused on the relationships of these factors to customer loyalty in the Egyptian banking sector, which provided more comprehensive data and comparisons with different countries and cultures that add to the possibility of their application to similar emerging markets. It’s confirmed in a previous study there is a limited number of valid research journals handling customer loyalty in the banking sector. Finally, by analyzing the relations between the variables: satisfaction, trust, service quality, brand image, and loyalty, the researcher presented a model that can be adopted later for studies on the subject or modified in further studies. It’s fundamental to determine which variables are most indicative of loyalty, measure relationships, and track their results.
5.2. Practical Contribution
In the Egyptian context, bank staff must make their customers feel satisfied by creating innovative products for them. Branches of the bank must coordinate their activities and work together in one team to meet the needs of their clients and provide an enjoyable banking experience through bank and continuous interactions with customers to identify their feedback to enhance customer service experience, Providing incentives to customers who use the bank’s services regularly, such as points on debit or credit cards that can be exchanged for other benefits. Top management should focus on the tangible aspects of service quality as customers in Egypt appreciate the material aspects and they play a major role in enhancing their dealings with the bank such as; the external appearance of the branch, the cleanliness of the bank branch from the inside, modern decorations, and its advanced equipment for the branch through their experience such as, advanced ATM for withdraw and deposits of money. Based on the findings, it has been revealed that the application of three important factors, the service quality, customer satisfaction, and customer loyalty variables, significantly relate to each other [28].
It’s pointed out that customers become loyal to the bank only if the technology system used is advanced and comfortable facilities will lead finally to loyalty.
Also, it was found that customers in Egypt always expect a quick response to their inquiries and to provide the required service from the bank, as delayed response negatively affects loyalty. Responsiveness is important and must be considered by banks as it’s the most influencer of loyalty.
Additionally, customers are keen to form friendly relationships with employees, which will show their impact on the service provided to them, for example, in the ability of employees to manage crises that the customer goes through, such as delayed service or a specific complaint. All of this makes the customer feel distinguished, which enhances his loyalty and creates a positive impression of him. Empathy has no effect on achieving customer loyalty.
5.3. Research Limitations
This research provides clear and detailed insights regarding achieving customer loyalty in the banking sector in Egypt. However, it is fundamental to highlight the limitations of this study.
Most of the participants in this research are from Cairo, Alexandria, and Asyut City. A small percentage of participants are from other cities, so future research could be conducted on a larger scale among Egypt’s cities. It was impossible to determine a causal relationship between the variables because this study used a cross-sectional sampling technique rather than a longitudinal one.
Use of a convenience sample despite it being practical, the results finally were not 68 truly representative and might introduce potential biases. Also using the nonprobability sampling technique hinders the ability of the researcher to be sure of the accuracy of the sample representative of the population. Also, this study was conducted in a short and unstable period of time on the global economic and political levels, which affected Egypt economically in particular.
Finally, the researcher could not know the type of banks that the participants deal with, as the study did not focus on a specific type such as (private, government, Islamic banks, and business sector) did not mention the type of bank in the questionnaire questions, and thus the results may be different if each type was studied separately.
5.4. Direction for Future Research
Scholars should develop a possible mechanism in the future to involve a larger number of clients in other cities in Egypt while paying attention to obtaining accurate valid results, as most of the study participants were concentrated in only three governorates, namely Cairo, Alexandria, and Assiut, which may affect the generalization of the results.
Future researchers on this topic can rely on trust and brand image as secondary supporting factors that indirectly affect loyalty by combining them into one strategy to improve the general perception of banks. Also, it should focus on studying and analyzing trust as the factor that indirectly affects loyalty through customer satisfaction.
Conflicts of Interest
The authors declare no conflicts of interest.