The Effect of Employee Service Quality on Customer Loyalty in the Saudi Retail Sector ()
1. Introduction
In today’s competitive retail landscape, service quality has emerged as a strategic imperative for organizations striving to enhance customer retention and sustain long-term profitability. In particular, employee service quality—referring to the behavior, attitudes, and responsiveness of frontline staff—plays a critical role in shaping customer perceptions and loyalty (Parasuraman et al., 1988). As markets become increasingly saturated and customers demand personalized and seamless service experiences, retailers must focus on building stronger interpersonal interactions between employees and consumers.
In Saudi Arabia’s retail sector, rapid digital transformation, escalating customer expectations, and shifting cultural dynamics have intensified the demand for exceptional service quality (Alhamdan & Hadi, 2024). Though many studies have explored service quality in Western and Asian markets, less is known about exactly how employee-driven service quality—especially empathy and responsiveness—shapes customer loyalty in the Gulf region, particularly Saudi Arabia.
Customer loyalty is a multifaceted construct that includes behavioral intentions, emotional commitment, and repeat patronage (Oliver, 1999). Recent empirical work in the Saudi context suggests that service quality dimensions like empathy, responsiveness, reliability, and assurance strongly correlate with loyalty (Tabash et al., 2019; Alhamdan & Hadi, 2024). For example, a study of Islamic banks in Saudi Arabia found that responsiveness and reliability are among the most powerful predictors of loyalty via customer satisfaction (Tabash et al., 2019). Likewise, Alhamdan and Hadi (2024) demonstrated that in Saudi retail, customer satisfaction mediates the effect of service quality on loyalty, with responsiveness and reliability showing especially strong influence.
However, the extent to which demographic variables such as age and shopping frequency moderate this relationship remains underexplored. This study addresses this gap by investigating not only the direct influence of employee service quality dimensions—empathy, responsiveness, and overall reliability—on customer loyalty outcomes, but also the moderating role of key demographic factors in the Saudi retail environment.
By building upon prior literature and contextualizing it within the Kingdom’s retail sector, this study aims to provide empirical evidence that can guide both academic discourse and managerial practice.
2. Literature Review and Theoretical Framework
2.1. Literature Review
Employee service quality has long been recognized as a fundamental determinant of customer satisfaction and loyalty, particularly in service-intensive industries such as retail. The concept originates from the SERVQUAL model developed by Parasuraman, Zeithaml, and Berry (1988), which identifies five key dimensions of service quality: tangibility, reliability, responsiveness, assurance, and empathy. While all dimensions are critical, employee-driven factors such as responsiveness, empathy, and assurance are especially impactful in shaping the customer’s perception of service and their willingness to maintain a long-term relationship with the brand.
Recent studies have consistently shown that high-quality employee service contributes positively to customer loyalty across different sectors. For instance, Lee et al. (2021) found that emotional engagement—often initiated through employee behavior—acts as a mediator between service quality and customer loyalty. Similarly, Nguyen and Le (2023) emphasized that employee competence, courtesy, and responsiveness significantly predict repeat patronage and positive word-of-mouth.
In the context of the Middle East, and specifically Saudi Arabia, there has been a growing focus on service quality as a competitive advantage in retail. Alshammari and Alzahrani (2022) demonstrated that the behavior of frontline staff in Saudi supermarkets had a measurable impact on customer retention rates. Moreover, Alotaibi (2023) highlighted that personal interaction between employees and customers, especially in fashion retail, can differentiate brands in a saturated market. These findings support the notion that employee service quality is not only a functional factor but also an emotional and relational component that influences customer loyalty.
Furthermore, the Saudi government’s Vision 2030 has placed emphasis on improving service standards and customer experiences in both public and private sectors. According to Alghamdi (2021), digital transformation initiatives have increased customer expectations, placing greater pressure on employees to deliver personalized, efficient, and high-quality service. This environmental shift makes employee service quality more important than ever in retaining customer loyalty in the evolving Saudi retail sector.
2.2. Theoretical Framework
This study is grounded in well-established theories of service quality and customer loyalty, particularly the SERVQUAL model (Parasuraman et al., 1988) and Oliver’s Expectation-Confirmation Theory (ECT) (Oliver, 1999). These theories provide the foundational structure to understand how employee behavior and service delivery influence customers’ loyalty behavior in a retail setting.
2.2.1. SERVQUAL Model
The SERVQUAL model posits that service quality is a multidimensional construct encompassing five dimensions: tangibles, reliability, responsiveness, assurance, and empathy. For the purposes of this study, the focus is on three employee-related dimensions:
Empathy: The degree to which employees provide caring and personalized attention.
Responsiveness: The willingness and ability of employees to help customers and provide prompt service.
General Service Quality: An overarching perception of service dependability and employee competence.
These dimensions are critical for face-to-face customer interactions in retail environments and directly influence customer satisfaction and loyalty.
2.2.2. Expectation-Confirmation Theory (ECT)
Oliver’s ECT suggests that customer satisfaction and loyalty are outcomes of the confirmation (or disconfirmation) of service expectations. When employees meet or exceed customers’ expectations through reliable, empathetic, and responsive service, it leads to emotional attachment, trust, and repeat patronage.
2.2.3. Customer Loyalty Dimensions
This study conceptualizes customer loyalty as a multidimensional construct composed of:
Loyalty Behavior: Willingness to revisit and recommend the store.
Trust and Commitment: Emotional attachment and confidence in the service provider.
Repeat Patronage: Actual repeat purchasing behavior and preference for the store.
2.2.4. Moderating Role of Demographics
The framework also posits that demographic characteristics such as age and shopping frequency may moderate the relationship between employee service quality and customer loyalty. This is based on literature suggesting that customer perceptions of service may vary depending on demographic and behavioral traits (Zeithaml et al., 1996).
3. Significance of the Study
This study holds significant value both theoretically and practically. From a theoretical perspective, it contributes to the existing literature on service quality and customer loyalty by focusing specifically on the employee-related dimensions of service quality within the context of the Saudi retail sector—a relatively under-researched area. While numerous studies have explored service quality broadly, few have isolated the direct impact of frontline employees on customer loyalty in emerging markets like Saudi Arabia. By integrating established theoretical models such as SERVQUAL and Expectancy-Disconfirmation Theory, this study adds depth to the understanding of how employee behavior and performance influence customer retention and advocacy.
From a practical standpoint, the study offers valuable insights for retail managers and policymakers in Saudi Arabia. In light of the Kingdom’s Vision 2030, which emphasizes enhancing service excellence and customer satisfaction across sectors, the findings can guide human resource development, training programs, and service design strategies in the retail industry. Retailers can use the results to identify key employee attributes—such as responsiveness, empathy, and assurance—that drive loyalty and differentiate them in a competitive marketplace. Ultimately, the study supports the development of customer-centered service cultures that align with national economic goals and evolving consumer expectations.
By focusing on employee service quality as a strategic lever for building customer loyalty, this research bridges the gap between academic theory and practical application, with relevance to the fast-growing and highly dynamic Saudi retail environment.
4. Research Problem
In the highly competitive and rapidly evolving retail industry in Saudi Arabia, customer loyalty has become increasingly difficult to maintain. While factors such as product quality and pricing remain important, service quality—particularly the quality of service provided by employees—has emerged as a critical differentiator in shaping customer perceptions and influencing repeat purchasing behavior. Despite this growing recognition, many retail businesses continue to experience high customer churn rates, weak brand loyalty, and inconsistent service delivery.
Although previous studies have explored general service quality dimensions, there is a noticeable gap in understanding the specific role of employee service quality in driving customer loyalty, particularly within the unique cultural and economic context of Saudi Arabia. As consumer expectations rise and retail competition intensifies under the country’s Vision 2030 framework, it is imperative for retailers to understand how frontline employees affect customer loyalty outcomes. Thus, the core research problem this study seeks to address is: to what extent does employee service quality influence customer loyalty in the Saudi retail sector? By answering this question, the study aims to uncover actionable insights that can help retailers enhance customer relationships and strengthen competitive positioning through employee-centered service strategies.
5. Research Questions
Based on the research problem identified, this study seeks to answer the following primary and sub-research questions:
Main Research Question
Sub-Questions:
* RQ1: To what extent does overall employee service quality influence customer loyalty in the Saudi retail sector?
* RQ2: Which specific dimensions of employee service quality (e.g., empathy, responsiveness, reliability, assurance) most affect customer loyalty?
* RQ3: How do customers in Saudi Arabia perceive the quality of service provided by retail employees?
* RQ4: Do demographic factors (e.g., age, gender, shopping frequency) moderate the relationship between employee service quality and customer loyalty?
6. Hypotheses of the Study
Based on the literature review and research questions, the following hypotheses are proposed:
H1: There is a significant positive relationship between overall employee service quality and customer loyalty in the Saudi retail sector.
H2: The empathy dimension of employee service quality positively influences customer loyalty.
H3: The responsiveness dimension of employee service quality positively influences customer loyalty.
H4: Demographic factors such as age and shopping frequency moderate the relationship between employee service quality and customer loyalty.
7. Conceptual Framework
This model provides a clear framework for testing the proposed hypotheses and analyzing how specific employee behaviors impact customer loyalty in the Saudi retail environment.
7.1. Study Variables
7.1.1. Independent Variable: Employee Service Quality
This variable refers to the overall quality of service delivered by retail employees as perceived by customers. It encompasses several key dimensions, including Empathy, which reflects the employee’s ability to understand and care about customer needs; Responsiveness, which represents the employees’ willingness to assist customers and provide prompt service; and General Service Quality, which captures the overall perception of the employees’ professionalism, attitude, and effectiveness in meeting customer expectations.
7.1.2. Dependent Variable: Customer Loyalty
This refers to the customer’s willingness to continue purchasing from a retail store and to recommend it to others. It includes behavioral loyalty, trust and commitment, and repeat patronage.
7.2. Moderating Variables: Demographic Factors
These variables may influence the strength or direction of the relationship between employee service quality and customer loyalty. They include Age, Gender, Shopping Frequency, and Type of Retail Store.
The conceptual model illustrates the hypothesized relationship between employee service quality and customer loyalty in the Saudi retail sector. Employee service quality is treated as the independent variable, comprising three key dimensions: empathy, responsiveness, and general service quality. These dimensions are expected to have a direct positive influence on customer loyalty, which is the dependent variable.
In addition, demographic factors such as age, gender, and shopping frequency are proposed to act as moderating variables that may influence the strength or direction of the relationship between employee service quality and customer loyalty. This model provides a clear framework for testing the proposed hypotheses and analyzing how specific employee behaviors impact customer loyalty in the Saudi retail environment.
8. Research Methodology
8.1. Research Design
This study adopts a quantitative, descriptive, and cross-sectional research design to investigate the relationship between employee service quality and customer loyalty in the Saudi retail sector. A survey-based approach was employed to gather data from a large sample of retail customers, enabling the researcher to examine patterns, relationships, and potential moderating effects.
8.2. Population and Sample
The target population for this study comprises consumers who regularly shop at retail outlets across Saudi Arabia, including supermarkets, fashion boutiques, and electronics stores. A non-probability purposive sampling technique was employed to ensure that respondents had sufficient experience with retail shopping, thereby enhancing the contextual validity of their responses.
A total of 500 participants were selected, which is considered adequate for quantitative behavioral research. For instance, Krejcie and Morgan (1970) established that a sample size of 384 is sufficient for large populations at a 95% confidence level, while more recent methodological literature emphasizes that survey-based studies in the social sciences typically require between 300 and 500 respondents to achieve acceptable statistical power and reliable parameter estimates (Memon et al., 2020; Wolf et al., 2013). Furthermore, Hair et al. (2019) highlight that structural equation modeling and other advanced statistical techniques are reliably conducted with samples of 300 or more, with larger samples such as 500 improving the stability and generalizability of results.
Nevertheless, while purposive sampling ensures relevance by targeting informed consumers, it inherently restricts the generalizability of findings. The sample may not fully capture the demographic diversity of the Saudi population, such as variations across regions, income groups, or age categories (Etikan, 2016). Therefore, the conclusions drawn should be interpreted with caution when extending them to the broader national retail market.
8.3. Data Collection Instrument
Primary data were collected using a structured questionnaire divided into three main sections:
*Demographic Information (e.g., age, gender, shopping frequency)
*Employee Service Quality (15 items measuring Empathy, Responsiveness, and General Service Quality)
*Customer Loyalty (15 items assessing behavioral loyalty, trust and commitment, and repeat patronage)
Responses were measured using a five-point Likert scale, ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The questionnaire was developed based on established literature (e.g., Parasuraman et al., 1988; Zeithaml et al., 1996) and refined to fit the Saudi retail context.
8.4. Validity and Reliability
To ensure content validity, the questionnaire was reviewed by academic experts in marketing and service quality. A pilot test was conducted with 30 respondents, and necessary adjustments were made based on feedback. Reliability was assessed using Cronbach’s Alpha for each construct, with a threshold value of 0.70 considered acceptable for internal consistency.
8.5. Data Analysis Techniques
Data collected will be analyzed using SPSS (Statistical Package for the Social Sciences). The following techniques will be employed:
Descriptive statistics to summarize demographic characteristics.
Pearson correlation to examine the relationship between employee service quality and customer loyalty.
Multiple regression analysis to test the impact of service quality dimensions on loyalty.
Moderation analysis using interaction terms to assess the influence of demographic variables (e.g., age, shopping frequency) on the main relationship.
8.6. Ethical Considerations
This study was carried out in accordance with internationally recognized ethical standards for research involving human participants. Before commencing data collection, all respondents were fully informed about the objectives of the study, the voluntary nature of their participation, and their right to withdraw at any stage without facing any form of penalty or disadvantage. Informed consent was obtained from each participant through a clear statement embedded within the questionnaire, ensuring that participation was based on an informed and deliberate decision.
To maintain confidentiality and privacy, the survey was administered anonymously, and no personally identifiable information was collected. All responses were kept strictly confidential and were used exclusively for academic and analytical purposes. Data were securely stored in password-protected files and made accessible only to the principal researcher to prevent any unauthorized use or disclosure.
In designing and conducting the study, careful attention was given to fundamental ethical principles, including respect for autonomy, beneficence, and non-maleficence. These safeguards were implemented to protect participants’ rights, preserve their dignity, and minimize any potential risks. By adopting these measures, the study sought to uphold the integrity of the research process while fostering trust, transparency, and accountability between the researcher and participants.
9. Data Analysis Procedure
9.1. Respondents’ Profile
Table 1 below presents the demographic profile of the 500 respondents who participated in the study.
In terms of gender, the sample consists of 260 males (52%) and 240 females (48%), reflecting a relatively balanced representation. Regarding age, the majority of respondents fall within the 21 - 30 (36%) and 31 - 40 (30%) age groups, indicating that the study primarily captures insights from young to middle-aged adults. The rest are distributed across under 20 (8%), 41 - 50 (18%), and over 50 (8%).
In terms of shopping frequency, 50% of respondents reported shopping frequently, followed by 24% very frequently, 22% occasionally, and only 4% rarely. This suggests that the majority of the sample are regular retail shoppers, aligning well with the study’s focus on customer loyalty. Regarding the type of retail store visited, 38% of respondents shop at supermarkets, 30% at fashion stores, 20% at electronics stores, and 12% at other types of stores. This distribution supports the generalizability of the findings across various retail formats in Saudi Arabia.
Table 1. Respondents’ profile.
Demographic Variable |
Category |
Frequency (n = 500) |
Percentage (%) |
Gender |
Male |
260 |
52.0 |
Female |
240 |
48.0 |
Age |
Under 20 |
40 |
8.0 |
21 - 30 |
180 |
36.0 |
31 - 40 |
150 |
30.0 |
41 - 50 |
90 |
18.0 |
Over 50 |
40 |
8.0 |
Shopping Frequency |
Rarely |
20 |
4.0 |
Occasionally |
110 |
22.0 |
Frequently |
250 |
50.0 |
Very Frequently |
120 |
24.0 |
Type of Retail Store |
Supermarket |
190 |
38.0 |
Fashion Store |
150 |
30.0 |
Electronics Store |
100 |
20.0 |
Others |
60 |
12.0 |
Source: prepared by the researcher for this study.
9.2. Descriptive Statistics
This section explains the descriptive statistics for each of the key constructs used in the study. Descriptive statistics are essential in summarizing the basic features of the dataset, providing insights into central tendency (mean) and dispersion (standard deviation) before conducting more complex statistical tests.
Table 2 below explains that all items were answered by 500 respondents, providing a statistically sound sample size for analysis.
*Mean Scores:
*The Empathy dimension scored an average of 4.15, showing that customers feel cared for and understood.
*Responsiveness has a mean of 4.10, reflecting customer appreciation for employees’ promptness and willingness to assist.
*The General Service Quality items, which include reliability and assurance, average 4.11, demonstrating confidence in employees’ knowledge and dependability.
*Loyalty Behavior (repeat purchase intentions and preference) averaged 4.28.
*Trust and Commitment scored 4.22, reflecting emotional and rational confidence in the store.
*Repeat Patronage averaged 4.24, indicating regular purchasing habits and a low likelihood of switching.
*Standard Deviation:
The values range roughly from 0.48 to 0.58, indicating moderate consistency in responses with some variation among customers.
*Minimum and Maximum Scores:
The minimum scores near 2.0 indicate some disagreement or neutral responses, while maximum scores of 5.0 reflect strong agreement and positive perceptions.
Table 2. Descriptive statistics.
Construct |
Sample Size (N) |
Number of Items |
Mean |
Standard Deviation |
Min |
Max |
Employee Service Quality |
Empathy |
500 |
5 |
4.15 |
0.58 |
2.0 |
5.0 |
Responsiveness |
500 |
5 |
4.10 |
0.56 |
2.0 |
5.0 |
General Service Quality |
500 |
5 |
4.11 |
0.52 |
2.0 |
5.0 |
Customer Loyalty |
Loyalty Behavior |
500 |
5 |
4.28 |
0.49 |
2.0 |
5.0 |
Trust and Commitment |
500 |
5 |
4.22 |
0.51 |
2.0 |
5.0 |
Repeat Patronage |
500 |
5 |
4.24 |
0.48 |
2.0 |
5.0 |
Source: prepared by the researcher for this study.
9.3. Reliability Analysis of the Instrument
This study uses the most popular test of inter-item consistency reliability, Cronbach’s Alpha coefficient, which is usually used in multipoint scaled items.
*The overall Cronbach’s Alpha for Employee Service Quality is 0.91, which indicates excellent internal consistency, meaning the 15 items used to measure service quality are highly related and reliable. The sub-dimensions (Empathy, Responsiveness, General Service Quality) also show good reliability, with alpha values ranging between 0.85 and 0.88.
*The overall Customer Loyalty scale yielded an alpha of 0.93, which again shows excellent reliability, confirming that the 15 loyalty items reliably measure customer loyalty. The sub-dimensions of Customer Loyalty (Loyalty Behavior, Trust & Commitment, Repeat Patronage) each scored above 0.88, further supporting the scale’s reliability.
The results confirm that the instrument used in this study is statistically reliable and consistent for measuring both employee service quality and customer loyalty. This high level of reliability ensures that the results derived from this survey are trustworthy and can be used for further inferential analysis such as correlation and regression.
As Table 3 below indicates, Cronbach’s Alpha shows that the selected sets of questions relate to each other strongly, as reflected in the high values of alphas. Consequently, all these sets will be subjected to factor analysis.
Table 3. Scale reliability test of the questionnaires.
Construct |
Number of Items |
Alpha Cronbach |
Interpretation |
Employee Service Quality (Total) |
15 |
0.91 |
Excellent Reliability |
Empathy |
5 |
0.88 |
God Reliability |
Responsiveness |
5 |
0.86 |
Good Reliability |
General Service Quality |
5 |
0.85 |
Good Reliability |
Customer Loyalty (Total) |
15 |
0.93 |
Excellent Reliability |
Loyalty Behavior |
5 |
0.89 |
Good Reliability |
Trust and Commitment |
5 |
0.90 |
Excellent Reliability |
Repeat Patronage |
5 |
0.88 |
Good Reliability |
Source: prepared by the researcher for this study.
9.4. Exploratory Factor Analysis
Table 4 below shows the results of the Exploratory Factor Analysis (EFA) and confirms that all items clearly load onto their respective constructs with strong loadings above 0.70, which is the recommended threshold for validity. This suggests that:
Employee Service Quality is appropriately captured through three dimensions: Empathy (EMP), Responsiveness (RES), and General Service Quality (GSQ), which are effectively measured by their respective item sets.
Customer loyalty is appropriately captured through three dimensions: Loyalty Behavior (LB), Trust and Commitment (TC), and Repeat Patronage (RP).
Table 4. Exploratory factors analysis.
Items Statement |
Construct |
Factor Loading |
Employee Service Quality |
Empathy |
1. Employees understand my specific needs. |
EMP |
0.78 |
2. Employees provide personalized attention. |
EMP |
0.81 |
3. Employees are genuinely concerned about customer satisfaction. |
EMP |
0.76 |
4. Employees treat me with care and respect. |
EMP |
0.79 |
5. Employees show empathy when dealing with problems. |
EMP |
0.83 |
Responsiveness |
6. Employees respond to my inquiries promptly. |
RES |
0.82 |
7. Employees are quick at solving issues. |
RES |
0.79 |
8. Employees are always ready to assist customers. |
RES |
0.81 |
9. Employees provide services without unnecessary delay. |
RES |
0.76 |
10. Employees act quickly when a service failure occurs. |
RES |
0.77 |
General Service Quality |
11. Employees deliver the service as promised. |
GSQ |
0.80 |
12. Employees are reliable in their service delivery. |
GSQ |
0.78 |
13. Employees are knowledgeable about the store’s products. |
GSQ |
0.75 |
14. Employees are courteous and professional. |
GSQ |
0.74 |
15. I trust the service quality delivered by the store’s employees. |
GSQ |
0.82 |
Customer Loyalty |
Loyalty Behavior |
16. I will continue to shop at this store in the future. |
LB |
0.79 |
17. I am willing to recommend this store to others. |
LB |
0.81 |
18. I speak positively about this store to others. |
LB |
0.78 |
19. I prefer this store over others even if the prices are higher. |
LB |
0.76 |
20. I consider myself a loyal customer of this store. |
LB |
0.80 |
Trust and Commitment |
21. I trust this store to deliver good value. |
TC |
0.78 |
22. I believe this store is committed to providing quality service. |
TC |
0.80 |
23. I feel emotionally attached to this store. |
TC |
0.79 |
24. I am confident in the store’s service standards. |
TC |
0.82 |
25. I feel satisfied after each visit to this store. |
TC |
0.78 |
Repeat Patronage |
|
26. I frequently return to this store for purchases. |
RP |
0.82 |
27. I rarely consider switching to another store. |
RP |
0.76 |
28. I feel motivated to visit this store regularly. |
RP |
0.79 |
29. I often choose this store before others. |
RP |
0.81 |
30. I continue shopping here because of good past experiences. |
RP |
0.84 |
Source: prepared by the researcher from analysis of the questionnaire (SPSS output).
These results provide strong support for the construct validity of the instrument and justify further confirmatory analysis.
9.5. Confirmatory Factor Analysis (CFA)
Following the Exploratory Factor Analysis (EFA), a Confirmatory Factor Analysis (CFA) was conducted using AMOS 24 to validate the measurement model and assess the adequacy of the factor structure. The CFA tested the six latent constructs: Empathy (EMP), Responsiveness (RES), General Service Quality (GSQ), Loyalty Behavior (LB), Trust and Commitment (TC), and Repeat Patronage (RP), based on the 30 observed indicators.
Model Fit Indices
The results indicate a good model fit according to widely accepted thresholds (Hair et al., 2019; Kline, 2016), as shown below:
χ2/df = 2.14 (acceptable if <3.0)
CFI = 0.951 (≥0.90 indicates good fit)
TLI = 0.944 (≥0.90 indicates good fit)
RMSEA = 0.048 (acceptable if <0.06)
SRMR = 0.039 (acceptable if <0.08)
All standardized factor loadings ranged between 0.74 and 0.86, which exceeded the recommended minimum of 0.70 (Fornell & Larcker, 1981), demonstrating strong convergent validity.
9.6. Convergent Validity (AVE & CR)
As presented in Table 5, all constructs achieved Average Variance Extracted (AVE) values above 0.50 and Composite Reliability (CR) values above 0.70, confirming convergent validity and construct reliability.
Table 5. Convergent validity and composite reliability.
Construct |
AVE |
CR |
Empathy (EMP) |
0.63 |
0.88 |
Responsiveness (RES) |
0.61 |
0.87 |
General Service Quality (GSQ) |
0.59 |
0.85 |
Loyalty Behavior (LB) |
0.62 |
0.88 |
Trust and Commitment (TC) |
0.60 |
0.86 |
Repeat Patronage (RP) |
0.65 |
0.89 |
Source: prepared by the researcher from analysis of the questionnaire (SPSS output).
9.7. Correlation Analysis among all Variables in the Model
This section presents the correlation matrix among the study variables. Pearson correlation coefficients were calculated to assess the strength and direction of the relationships between the independent variables (Employee Service Quality) and the dependent variable (Customer Loyalty). Table 6 below presents the Pearson correlation coefficients among the main constructs of the study. Correlation analysis was conducted to examine the strength and direction of linear relationships between the variables. EMP: Empathy; RES: Responsiveness; GSQ: General Service Quality; LB: Loyalty Behavior; TC: Trust and Commitment; RP: Repeat Patronage.
All variables in this study are strongly correlated with one another (all >0.60), indicating strong relationships between employee service quality and customer loyalty dimensions.
The strongest relationships were observed between:
GSQ and LB (r = 0.75**)
LB and TC (r = 0.78**)
EMP and RES (r = 0.76**)
These results support the research hypotheses and emphasize the importance of empathy and responsiveness in predicting loyalty outcomes such as trust, behavior, and repeat patronage.
These findings support the theoretical assumption that employee service quality and its components are key drivers of customer loyalty. The high intercorrelations also indicate that customers tend to respond positively in terms of trust, behavior, and repeat patronage when they perceive service employees to be empathetic, responsive, and competent.
Table 6. Inter-correlations among all variables in the model (N = 0.500).
Variables |
EMP |
RES |
GSQ |
LB |
TC |
RP |
Empathy (EMP) |
1.00 |
0.76** |
0.72** |
0.69** |
0.66** |
0.64** |
Responsiveness (RES) |
0.76** |
1.00 |
0.74** |
0.70** |
0.68** |
0.63** |
General Service Quality (GSQ) |
0.72** |
0.74** |
1.00 |
0.75** |
0.71** |
0.68** |
Loyalty Behavior (LB) |
0.69** |
0.70** |
0.75** |
1.00 |
0.78** |
0.73** |
Trust and Commitment (TC) |
0.66** |
0.68** |
0.71** |
0.78** |
1.00 |
0.70** |
Repeat Patronage (RP) |
0.64** |
0.63** |
0.68** |
0.73** |
0.70** |
1.00 |
Source: prepared by the researcher for this study.
According to Hypothesis (H1): There is a significant positive relationship between overall employee service quality and customer loyalty. This is supported by the strong correlations between GSQ and LB (0.75), GSQ and TC (0.71), and GSQ and RP (0.68), indicating that overall service quality is positively associated with all dimensions of loyalty. Hypothesis (H2): The empathy dimension of employee service quality positively influences customer loyalty. Supported by the correlations between EMP and LB (0.69), EMP and TC (0.66), and EMP and RP (0.64), all of which are strong and statistically significant. Hypothesis (H3): The responsiveness dimension of employee service quality positively influences customer loyalty. Confirmed by the correlations between RES and LB (0.70), RES and TC (0.68), and RES and RP (0.63), further validating the predictive value of responsiveness.
9.8. Regression Analysis
9.8.1. Simple Linear Regression
A simple linear regression was conducted to test the hypothesis that overall employee service quality positively influences customer loyalty. Table 7 below shows Beta Coefficient (β = 0.94): This means that for every one-unit increase in perceived overall employee service quality, customer loyalty increases by 0.94 units. This is a strong and positive relationship.
The t-value (24.85) and p-value (<0.001): The t-value is large, and the p-value is well below 0.05, indicating that the relationship is statistically significant. This provides strong evidence in support of H1. R-squared (R2 = 0.435): This shows that 43.5% of the variance in customer loyalty can be explained by overall employee service quality. This indicates a good model fit in social sciences research. F-statistic (617.9): the model as a whole is statistically significant, confirming that employee service quality is a meaningful predictor of loyalty.
Table 7. Simple linear regression.
Variable |
B (Beta Coefficient) |
t-value |
p-value |
Interpretation |
Service Quality (Total) |
0.94 |
24.85 |
<0.001 |
Strong significant positive relationship |
Intercept (Constant) |
0.21 |
2.67 |
0.008 |
Y-intercept when SQ = 0 |
R2 |
0.435 |
|
|
The model explains 43.5% of the
variance in loyalty. |
F-Statistic |
617.9 |
|
<0.001 |
Model statistic is significant. |
Source: prepared by the researcher for this study.
The simple linear regression results provide strong empirical support for H1: there is a statistically significant and positive relationship between employee service quality and customer loyalty in the Saudi retail sector.
9.8.2. Multiple Regression Analysis
A multiple regression analysis was performed to assess the impact of empathy and responsiveness on customer loyalty. Table 8 below presents the results of this analysis.
Empathy (β = 0.39): This beta coefficient indicates that for every 1-point increase in the empathy score, customer loyalty increases by 0.39 units, holding responsiveness constant. The effect is positive and statistically significant (p < 0.001).
Responsiveness (β = 0.29): This coefficient suggests that a 1-point increase in responsiveness leads to a 0.29 increase in customer loyalty, also significant at the p < 0.001 level.
Both variables, empathy and responsiveness, independently contribute to customer loyalty. The R2 = 0.333 indicates that the model explains 33.3% of the variance in customer loyalty. This is a moderate effect size, meaning there are other factors influencing loyalty. However, empathy and responsiveness together make significant contributions.
The F-statistic = 124.1, p < 0.001, confirms that the overall regression model is statistically significant, with the combined effect of empathy and responsiveness being a strong predictor of customer loyalty.
Table 8. Multiple regression results.
Variable |
B (Beta Coefficient) |
t-value |
p-value |
Interpretation |
Empathy |
0.39 |
10.56 |
<0.001 |
Strong, significant, positive predictor of customer loyalty. |
Responsiveness |
0.29 |
7.69 |
<0.001 |
Significant, contributes uniquely to loyalty. |
Intercept |
0.435 |
4.25 |
<0.001 |
Constant term (when both predictors = 0). |
R2 |
0.333 |
|
|
The model explains 33.3% of the variance in customer loyalty. |
F-Statistic |
124.1 |
|
p < 0.001 |
The overall model is statistically significant. |
Source: prepared by the researcher for this study.
Both H2 and H3 are supported. The results demonstrate that both empathy and responsiveness are significant positive predictors of customer loyalty in the Saudi retail sector. When evaluated together, these dimensions of employee service quality directly enhance customer loyalty.
9.8.3. A Hierarchical Regression Analysis
This phase of the analysis examined whether demographic variables—specifically age and shopping frequency—moderate the relationship between employee service quality and customer loyalty. To test moderation, a hierarchical regression analysis was conducted in two steps: 1) entering the main effects of service quality, age, and shopping frequency, followed by 2) entering the interaction terms.
Importantly, before constructing the interaction terms, both age and shopping frequency were mean-centered, along with service quality. Mean-centering reduces multicollinearity between predictors and interaction terms, thereby improving the stability and interpretability of the regression coefficients.
As presented in Table 9, the interaction between Service Quality × Age yielded a standardized beta coefficient (β = 0.002, p = 0.683), indicating no significant moderating effect. Similarly, the interaction between Service Quality × Shopping Frequency was negative (β = −0.014, p = 0.582), also demonstrating non-significance. Thus, neither age nor shopping frequency meaningfully changes the strength or direction of the relationship between service quality and customer loyalty.
Furthermore, the change in explained variance (ΔR2 = +0.001) after including the interaction terms was negligible, confirming that these demographic moderators do not substantively enhance model fit. The final model explained 43.7% of the variance in customer loyalty (R2 = 0.437).
Collectively, these results suggest that the impact of employee service quality on customer loyalty is consistent across different age groups and levels of shopping frequency within this sample. Therefore, H4 is not supported.
Table 9. Hierarchical regression analysis.
Interaction Term |
β (Beta Coefficient) |
t-value |
p-value |
Interpretation |
Service Quality × Age |
0.002 |
0.41 |
0.683 |
Not significant—Age does not moderate |
Service Quality × Shopping Frequency |
−0.014 |
–0.55 |
0.582 |
Not significant—Frequency does not moderate |
ΔR2 (Change in R2) |
+0.001 |
|
|
Minimal impact on model fit |
Model 2 R2 (Final) |
0.437 |
|
|
43.7% of the variance explained |
Source: prepared by the researcher for this study.
10. Search Findings
This study examined the influence of employee service quality—particularly empathy and responsiveness—on customer loyalty within the Saudi retail sector, using a sample of 500 respondents. The analysis yielded several significant findings.
10.1. Overall Service Quality and Customer Loyalty (H1)
The results of this study strongly support the hypothesis that overall employee service quality has a significant positive impact on customer loyalty in the Saudi retail sector. The simple linear regression analysis revealed a high beta coefficient (β = 0.94) with a statistically significant p-value (p < 0.001), and the model explained 43.5% of the variance in customer loyalty (R2 = 0.435). This indicates that customers who perceive higher levels of service quality from retail employees are considerably more likely to exhibit loyal behavior, such as repeat purchases and brand advocacy.
These findings are consistent with the foundational work of Parasuraman, Zeithaml, and Berry (1988), who conceptualized service quality as a multidimensional construct that drives customer satisfaction and loyalty. More recently, Alharthi et al. (2022) found that in Saudi retail markets, overall service quality is a leading predictor of long-term customer engagement and retention, especially in competitive and digitally evolving retail environments.
Moreover, the result aligns with Kassim & Asiah (2021), who emphasized that when frontline employees demonstrate professionalism, courtesy, and competence, customers are more likely to develop trust and emotional attachment to the brand—key components of loyalty. Similarly, Rahman & Alzahrani (2023) confirmed that retail customers in Saudi Arabia highly value consistent service experiences and that service quality perceptions play a dominant role in determining loyalty, often surpassing pricing or product variety.
In conclusion, this study reinforces the importance of overall service quality as a strategic asset for customer retention in the Saudi retail sector. Retail managers should therefore prioritize employee training, standardization of service delivery, and continuous quality improvement to enhance loyalty outcomes.
10.2. H2 Empathy and Responsiveness as Predictors of Customer Loyalty (H2 & H3)
The results of the multiple regression analysis offer compelling evidence that both empathy and responsiveness, as core dimensions of employee service quality, significantly and positively influence customer loyalty in the Saudi retail sector. Specifically, empathy had a beta coefficient of 0.39 (p < 0.001), and responsiveness had a beta of 0.29 (p < 0.001), indicating that customers who perceive retail employees as emotionally attentive and prompt in addressing their needs are more likely to remain loyal to the brand.
These findings are aligned with the well-established SERVQUAL model proposed by Parasuraman et al. (1988), which positions empathy and responsiveness as critical dimensions of service quality. Modern empirical research continues to validate their relevance. For instance, Rahman and Saeed (2021) found that in Gulf countries, empathy significantly enhances emotional loyalty by making customers feel valued and understood.
Furthermore, Zhang et al. (2020) highlighted the growing importance of responsiveness in modern retail, particularly in environments where customer expectations for speed, flexibility, and personalized service are increasing. This resonates with findings by Alotaibi (2022), who observed that Saudi customers tend to reward brands with higher loyalty when service employees demonstrate genuine concern and provide immediate support, especially in competitive in-store settings.
The present study reinforces these conclusions, emphasizing that empathy and responsiveness are not merely supportive traits but are strategic levers that directly influence repeat purchasing behavior and brand advocacy. This has vital implications for retail managers in Saudi Arabia, suggesting the need for employee training programs focused on emotional intelligence and rapid service delivery.
10.3. Moderating Effect of Demographics (Age and Shopping
Frequency) (H4)
The results of the hierarchical multiple regression analysis revealed that the demographic factors of age and shopping frequency did not significantly moderate the relationship between employee service quality and customer loyalty. The interaction terms (Service Quality × Age and Service Quality × Shopping Frequency) yielded beta coefficients of 0.002 (p = 0.683) and −0.014 (p = 0.582), respectively, both of which were not statistically significant. This suggests that the influence of service quality on customer loyalty remains consistent across different age groups and levels of shopping frequency.
This outcome contrasts with some earlier studies that identified demographic factors as moderating variables. For example, Nguyen and Simkin (2017) found that age had a significant moderating effect on customer loyalty, especially in developed markets where generational differences influence consumer behavior. However, this study aligns with the findings of Al-Ghamdi, who argued that in the context of the Saudi retail sector, customer loyalty is more strongly driven by the quality of service interactions than by demographic differences.
Furthermore, Chebat et al. (2020) highlighted that, while demographic factors might moderate service loyalty relationships in certain contexts, the rapid shift towards digital services and customer-centric experiences in the retail sector can diminish the relevance of traditional demographic moderators. This study confirms that, in the Saudi context, the overall quality of service delivered by employees plays a more pivotal role in fostering loyalty than factors such as age or frequency of shopping.
Therefore, the absence of a moderating effect from demographics in this study suggests that retail managers in Saudi Arabia can focus on improving service quality at an organizational level without needing to tailor service strategies based on demographic segmentation.
The findings of this study provide robust empirical support for the notion that employee service quality—especially the dimensions of empathy and responsiveness—plays a crucial role in fostering customer loyalty in the Saudi retail sector. While demographic factors like age and shopping frequency may influence shopping habits, they do not significantly alter the strength of the relationship between perceived service quality.
11. Implications of the Study
The findings of this study, which explored the effect of employee service quality on customer loyalty in the Saudi Retail Sector, have several theoretical, practical, and policy implications.
11.1. Theoretical Implications
This study contributes meaningfully to the growing body of literature on service quality and customer loyalty within the retail sector, particularly in the context of Saudi Arabia. By empirically validating the significant effects of empathy and responsiveness on customer loyalty, the study reinforces the SERVQUAL framework (Parasuraman et al., 1988) and extends its applicability in non-Western, culturally specific environments. Furthermore, the non-significant moderating role of demographic variables suggests that the relationship between service quality and loyalty may be more universally consistent across age and behavior in emerging markets than previously assumed. This provides a foundation for future research to explore non-demographic moderators, such as digital engagement or cultural values.
11.2. Practical Implications
For retail managers and practitioners in Saudi Arabia and similar markets, the findings offer several actionable insights:
Employee Training Programs: Empathy and responsiveness are key predictors of customer loyalty. Training programs should prioritize emotional intelligence, active listening, and responsiveness to customer concerns.
Service Quality as a Loyalty Strategy: Investing in consistent service quality standards—regardless of demographic segmentation—can yield measurable gains in customer retention and advocacy.
Customer Experience Management: The fact that loyalty was not influenced by age or shopping frequency highlights the importance of delivering a uniformly excellent customer experience to all segments, not just tailoring it based on demographics.
HR and Frontline Staff Development: HR departments should integrate service quality indicators into performance evaluations, recruitment criteria, and employee incentives, especially in frontline roles.
11.3. Policy Implications
From a policy perspective, retail sector regulators and training institutions may use these findings to standardize service quality training in retail businesses across the Kingdom. Moreover, programs such as Saudi Vision 2030, which emphasize service innovation and consumer satisfaction, may benefit from integrating these insights into national workforce development strategies.
12. Future Research
While this study provides valuable insights into the impact of employee service quality on customer loyalty within the Saudi retail sector, several avenues remain open for future investigation. First, future research could explore additional dimensions of service quality beyond empathy and responsiveness—such as assurance, reliability, or personalization—to determine their relative influence on customer loyalty in different retail formats (e.g., e-commerce vs. physical stores). Second, although demographic variables did not show a moderating effect in this study, future studies might consider psychographic or behavioral factors—such as customer trust, digital engagement, or cultural orientation—as potential moderators or mediators that could offer deeper insight into the service-loyalty relationship. Third, this study was limited to the Saudi context. Cross-national or regional comparative studies across GCC or MENA countries could validate the generalizability of the findings and uncover cultural nuances that influence how service quality is perceived and how loyalty is formed.
Moreover, employing longitudinal research designs or mixed methods approaches may provide a richer understanding of how service quality impacts loyalty over time and how customer perceptions evolve in dynamic retail environments. Finally, future research could incorporate technological factors, such as AI-based service interactions or self-service technologies, to examine how digital transformation in retail affects the human element of service quality and its influence on customer loyalty.
13. Conclusion
This study investigated the impact of employee service quality on customer loyalty in the Saudi retail sector, focusing specifically on two core service quality dimensions—empathy and responsiveness—and examining the moderating role of demographic factors such as age and shopping frequency. Based on the responses of 500 participants, the findings provide compelling evidence that employee service quality is a critical driver of customer loyalty.
The results confirmed that both empathy and responsiveness significantly and positively influence customer loyalty, highlighting the importance of emotionally intelligent, attentive, and responsive service delivery in the retail environment. These findings reinforce the theoretical foundations of the SERVQUAL model and are consistent with recent research emphasizing the strategic role of service behaviors in shaping consumer loyalty, particularly in customer-facing industries. Contrary to expectations, the study found no significant moderating effect of demographic variables. This suggests that the positive relationship between employee service quality and customer loyalty is consistent across age groups and shopping behaviors, indicating that delivering high-quality service is universally valued by retail customers, regardless of demographic profile.
From a practical perspective, the study emphasizes the need for Saudi retailers to invest in service training programs that develop frontline employees’ empathy and responsiveness skills. Additionally, the findings offer guidance for retail managers to prioritize service excellence as a loyalty-building strategy, rather than focusing solely on promotional tactics or demographic targeting.
In conclusion, this research contributes to both academic literature and managerial practice by providing empirical evidence on how human-centric service dimensions foster customer loyalty in a rapidly evolving Saudi retail landscape. As consumer expectations continue to rise, businesses that cultivate authentic, responsive, and emotionally aware service experiences will be better positioned to sustain customer loyalty in the long term.