BUSN20019 Professional Project

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To study the impact of loyalty cards on customers in Middle East retail industries

To critically assess the customer satisfaction strategies used by Middle East companies. This is a challenging task and may go beyond the scope of the project.

What impact does loyalty card have on customer satisfaction? What are some customer satisfaction methods used in the Middle East?


Researchers and marketing managers should be focusing on customer satisfaction to increase loyalty.

According to current research, customer satisfaction may generate more loyalty than customer happiness (Kim and Vogt & Knutson (2015)).

The first segment of this report includes the background and problem statement, as well the aims and objectives and justification.

A literature review will provide more detailed information about the topic in the second segment.

The section before would provide details about the methodology used, including data collection as well as data analysis (Sachs (2015)).

The last section concludes the research project.

Marketing managers and researchers now focus on loyalty. This is a multiphase concept that provides valuable information to customers, as well as targeted strategies.

This study examines customer delight, loyalty, satisfaction and delight.

The main purpose of this study was to examine how loyalty is influenced by customer satisfaction and customer pleasure to establish the multiphase framework for loyalty and cognitive loyalty (Bowen, Chen McCain 2015).

The knowledge base is key to loyalty cards in retail.

Due to rapid growth in globalization, there is more competition in the retail industry.

It helps a retailer to succeed and create a competitive advantage (Maier, et al. 2014).

An analytical study using primary collected data from Middle East countries such as Qatar, Saudi Arabia and Jordan shows that there is a rapidly growing graph.

Hossain, Leo (2014). Tangibles have the highest perceptions of customers while competence areas have the lowest (Hossain und Leo, 2014).

This research project aims to determine if customer loyalty and satisfaction are linked.

This could be accomplished by asking the following questions:

Are there any other factors that are associated with frequency level?

What is the relationship between frequency and customer trust?

Do commitment and frequency have a correlation?

Is there a relationship between customer trust and service quality?

What is the relationship between customer loyalty, service quality and customer loyalty?

Is there a relationship between customer trust and commitment?

Is there any relationship between customer trust and shopping?

The report’s main purpose is to evaluate the quality service in the Middle East retail hospitality industry.

This depends on different levels of consumer perceptions regarding the quality of service.

The goal of e-business is usually to improve its technological and organizational capabilities (Sayigh (2014)).

This is in line with the resource-based model to integrate value-creating marketing.

The study is designed to determine the impact of customer loyalty on quality and dimension of services.

We examine two types of retail analytics: person-to–person (salesperson) and store-to–firm (store).

It was found that customers are more loyal to quality service than they are to their stores.

Loyalty of customers is an important predictor of company reputation and level.

We will continue to discuss loyalty cards with frequency and managerial implications on retail trading.

The increasing competition in retail hospitality means that customer service is becoming an integral part of business. Therefore, hospitality managers must consider how to increase satisfaction with customers and improve quality of service (Kim.Vogt. and Knutson 2015).

Service quality should be higher in order to attain higher quality retail services, such as restaurant and accomodation.

The current context is that customers have high expectations about the quality of infrastructure and accommodation at restaurants. This is followed by returns on deposits.

This report also contains the international dimensions of the retail services literature.

The research on the resource-based approach to product innovation suggests that loyalty cards can be strategically used to ensure customer satisfaction and quality service.

This report explores the relationship between satisfaction of customers and customer perceptions in the retail sector.

It was found that customer satisfaction can be affected by the quality of service, shopping habits and frequency.

Flexibility is key to achieving innovative solutions.

2.3 The Retail Industry Scenario In Middle East

The Middle East is an attractive and growing market that has caught the attention of the international economy for its economic benefits.

The exploratory study examined the link between small and large retail businesses (Wong, shoal 2003).

The organizational commitment and the perception of employees of services by management and employees is what led to a number managers and employees proposing the profit-enhancing business (Lee, et al. 2014).

This behavior is similar to the western world.

In terms of cultural and business characteristics, however, there are some deviations from the West and Middle East.

The Middle East is an area rich in diversity, and more specifically, a myriad unique cultures (Mallakh-Mallakh, 2015).

The quality of the service is more valuable as the market becomes more sophisticated.

Customer satisfaction and customer treat will rise if quality of service improves.

A loyalty card that is more frequent and has a higher commitment level would be more effective.

3.1 Data Collection

This research project seeks to find out if loyalty cards can influence customer satisfaction levels.

We can classify the study as descriptive since it examines the relationship between customer loyalty and customer satisfaction.

The secondary data used to create the data analysis are also used.

Data that is publicly available can be used to collect data about customer satisfaction in the retail industry, such as banking and hospitality.

It examines eight retailing areas in eight cities.

Cairo, Dubai Dubai, Doha Jerusalem, Amman Damascus, Damascus, Damascus, and Riyadh were the areas that were included in the retailing survey.

There are eight restaurants that have been rated by the survey organization.

The restaurants are Zitouni (Grossvenor House), Taboula; Choices; Machneyuda; Sufra; Red Roster, Spazio.

Restaurants can be classified as cafes, hotels or food courts.

These data are used for analysis and provide an average index of customer satisfaction.

This website collects anonymously data from customers and loyalty levels.

This includes ratings of companies based on their popularity and reputation.

These restaurants may be rated by customers on a five-point scale, with five being the highest.

The average of all reviews determines the customer’s satisfaction and trust.

3.2 Data Analysis

This research project is focused on the study of the relationship between customer satisfaction, the dependent variables (such as frequency count and shopping) and the mediating variable of trust.

Multivariate and bivariate regression analyses can be used to examine the relationship between customer loyalty and customer satisfaction.

To analyze the relationship between customer trust, quality of service and frequency, logistic regression was used (Sekaran, Bougie, 2013).

This hypothesis is being tested by Lee et al. (2014)

H1: All factors are linearly correlated with frequency level.

H2: The relationship between frequency and customer trust.

H3: There is an association between frequency level, commitment.

H4: Trust is a key component of service quality.

H5: Customers loyalty and service quality are interrelated.

H6: Customers trust commitment.

H7: The linkage between trust and shopping.

3.2.1Analysis Process and Software Approach

First, we will analyze the descriptive statistics for the eight factors that were listed in order to measure customer satisfaction.

Customer loyalty, service quality customer trust, commitment, shopping, frequency, and other continuous variables are the numeric and continuous variables.

Bivariate regression analysis could therefore explain the association.

Any functional association that is detected would be measured in order to determine the strengths of the relationships among factors.

Minitab and MS Excel were used for analysis.

There are three non-numeric variables that can be observed. These include Types, Names of restaurants and Area.

These variables are not relevant for descriptive statistics, bivariate and logistic regression model analysis.

3.2.2 Summary of Qualitative data:

The “Sufra Food Market” in Amman has the highest Customer loyalty (0.74901), while it is lowest at “Choices’ food stores (0.33631).

The best service quality is at the “Choices” Doha food store (3.7854), while “Machneyuda,” a Jerusalem lodging place, has the lowest (1.5739).

Customer trust in Riyadh’s “Zitouni,” Cairo, and “Spazio,” wholesale stores in Riyadh is respectively highest (98) or lowest (53) respectively.

This is also true for commitment level. “Zitouni,” and “Spazio,” have respectively the highest (87), and lowest (47) levels of commitment.

The shopping criterian is also highest at “Zitouni”, (0.17845), but lowest at “Spazio”, (0.06016).

Final note: The frequency count in “Zitouni”, 388, and “Sufra,” 60 respectively.

Analyses have shown that the Cairo-based “Zitouni Cafe” is the most successful, while the wholesale store “Spazio”, which has the lowest performance overall, ranks eighth among all eight retail outlets.

The descriptive statistics display the mean, standard error, sample variance, median and maximum of different factors.

Customer loyalty, service quality customer trust, commitment and shopping are the factors (Beekman 2017).

The highest number of customers (measurement customer satisfaction) in terms frequency is 388 in Zitouni and the lowest in Sufra (60).

Analysis of Bivariate-Regression Analysis

Bivariate regression analysis tests hypotheses H1, H2, and H3 as well as H4.

The analysis results are presented in Table 3.

The R-square values below 0.05 indicate weak associations, while the values close to 1 indicate strong correlations between hypothesis factors.

The analysis is statistically insignificant if the p value is higher than 0.05 (Haresh, et al. 2016).

This shows that a change of customer satisfaction is linearly correlated with a change of customer trust (Draper, Smith 2016).

Multiple R-square (0.951407) shows that the linear relationship between predictors, and responses is linear in nature (Darlington Hayes, 2015).

However, no p value is lower than 0.05 (5% confidence interval).

Frequency level is the most important factor.

The frequency level has a strong association with loyalty and commitment from customers.

The bivariate relationship shows that R-square is 0.0042973.

These two factors do not have a linear relationship.

The p value is 0.991, which is higher than 0.05. Therefore, we accept the null hypothesis regarding an association between service quality & consumer trust.

The bivariate relationship shows that R-square is 0.7413305.

These two factors have a high linear relationship to one another.

We cannot accept the null hypothesis linking consumer trust to shopping index. The p-value of 0.0353 is lower than 0.05.

The bivariate relationship shows that R-square is 0.742657.

These two factors are very linearly related.

The p value is 0.0348, which is lower than 0.05. Therefore, we cannot accept that there is a causal relationship between consumer service and quality of service.

The bivariate relationship shows that R-square is 0.088061.

This means that these facors are only weakly linearly related.

The p value is 0.835736, which is greater than 0.05. Therefore, we accept the null hypothesis regarding an association between commitment to quality and service.

Logistic Regression Analysis 4.3

The logistic regression analysis can be used to analyze H5, H6.

The dependent variable is frequency level.

Customer loyalty, Customer trust, and customer loyalty are independent variables (Henkel 2017).

Tables 8 through 9 provide the results of logistic regression analysis.

Odds 95% Confidence Indicator

Logit 1 (3364/388).

Loyalty of customers -5150.66 184562-0.03 0.978, 0.00 0.00

Logit 2: (356/388).

Loyalty of customers -5748.63201026 0.03 0.977 $0.00 0.00

Logit 3 (113/388).

Customer loyalty 934.81 97917.3 0.010.992 *0.00

Logit 4 : ( 94/388 )

Loyalty of customers -4808.02173449-0.03 0.978, 0.00 0.00

Logit 5 ( 89/388 )

Customer loyalty -3891.32150393 0.03 0.979 $0.00 0.00

Logit 6 ( 73/388 )

Loyalty of customers -6378.47.223933-0.03 0.977-0.00 0.00

Logit 7 – ( 60/388).

Customer loyalty 1251.95 12.5543 0.01 992 * 0.00

Check that all slopes point to zero. G = 33.271, DF = 7, P Value = 0.000

Goodness-ofFit Tests

Method Chi-Square PDF

Pearson 0.0000017 41 1.000

Deviance 0.0000033 41 1.000

It is a nomial logistic modeling between commitment of customers and frequency count.

The p values show that frequency level and commitment have significant effects in this model (Hasley et. al., 2015).

95% Confidence Interval

Logit 1 (3364/388).

Customer trust -39.5985 2299.050 -10.7 0.863 0.0.00 5.94357E+177

Logit 2: (356/388).

Customer trust -44.6117 252.097- 0.00 0.64059E+195

Logit 3 (113/388).

Customer trust -3.37584/88.2917 0.04 0.970 0.030.00 E+73

Logit 4 : ( 94/388 )

Customer trust -18.5517 164.030-0.11 0.900 0.00 3.69891E+131

Logit 5 ( 89/388 )

Customer trust -11.7620 0.931.00 0.00 8.70367E+109

Logit 6 ( 73/388 )

Customer trust -36.0437 215.722 -0.17 0.8867 0.00 19.56876E+167

Logit 7 – ( 60/388).

Customer trust -25.3053.187.941-0.130.893 9.75057E+148

Check that all slopes point to zero: G = 2483.645 DF = 7, P Value = 0.000

Goodness-ofFit Tests

Method Chi-Square PDF

Pearson 0.0000440 41 1.000

Deviance 0.0000879 41 1.000

It is a nomial logistical model that links frequency count and customer trust (Henkel et. al., 2016,).

The p values show that Customer Trust is significant and has a positive association with frequency levels.


Analyses of qualitative and quantitative data, both descriptive and bivariate as well as logistic regression analyses of logistic regression for both qualitative and quantitative data indicate the popularity and poor performance of “Zitouni”, Cafe of Cairo, in Middle East retail marketing.

It is also apparent in the descriptive statistics.

Bivariate regression analyses also show strong correlations between many numerical consecutive factors.

Logistic regression models also reveal a positive association with customer trust and customer loyalty in relation to Frequency count.

This report concludes that factors related to customer satisfaction and royalties influence are strongly linked.


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