UK Fast Food: Service Quality Dimensions and Customer Satisfaction

This report investigates the impact of the five dimensions of service quality (tangibles, reliability, responsiveness, assurance, and empathy) on customer satisfaction within the UK fast food market, focusing on KFC, McDonald's, and Burger King. Primary data was collected through questionnaires from customers at these restaurants. The findings indicate that tangibles, responsiveness, and assurance are the most significant drivers of customer satisfaction, followed by reliability and empathy, with tangibles having the most impact. The research contributes original insights into the British fast food market, highlighting the importance of physical facilities and attributes. The study uses the SERVPERF model to measure service quality and provides managerial implications for improving service quality and customer satisfaction in the competitive UK fast food industry.

ABSTRACT
Purpose: The purpose of this study is to examine the impact of the five dimensions of service quality on
customer satisfaction in the UK fast food market and to indicate which factors among the five dimensions
have a main role in driving overall customer satisfaction.
Design/methodology/approach: Primary data in the form of 147 questionnaire responses werebeen
collected from a variety of quick service fast food restaurants in the UK. Likert seven-point rating scales
were used to structure the questionnaire. Data were collected from the customers at two KFC restaurants,
two McDonald’s restaurants, and one Burger King Restaurant.
Findings: The results of the analysis indicate that tangibles, responsiveness and assurance play the most
important role in driving customer satisfaction in the UK fast food industry, followed by reliability and
empathy. Results of correlation and regression analysis show that physical attributes (tangible) of service
quality are key to customer satisfaction. In a nutshell, the tangibles variable is the most important factor
driving customer satisfaction in the context of the UK fast food market.
Originality/value: This research incoporates unique and original insights in relation to the British fast food
restaurants market and the results constitute novel findings pertaining to the importance of physical
facilities and attributes. This account of the relative importance of service quality dimensions in fast food
restaurants in the UK adds value to the field. The findings of this research have contributed to a better
understanding of the main factors that influence service quality and customer satisfaction and have
implications from a managerial point of view in the highly competitive UK fast food and wider foodservice
industry.
1. Introduction
The global fast food restaurant industry has experienced strong growth in recent years in response to
changes in consumer tastes and challenging global economic conditions. According to IBISWorld (2015),
in the period since the global financial crisis and theworldwide decrease in individuals’ income there has
been a decline in spending on luxuries such as eating out which has increased consumerpreferences for
lower-priced and more convenient food options. Globally, the fast food market has shown modest growth
since 2011 reaching a total value of $2, 849,950.5 in 2015 (Marketline, 2016). In terms of global
segmentation of the foodservice industry, full service restaurants represent 40% of the market value,
quick service restaurants (QSR) and fast food are the second largest segment of the market with 22% of
market value, while pubs, clubs and bars have 11% of the market value and 9% relates to the
accommodation sector (Marketline, 2016). .
The foodservice industry in the UK grew by an annual compounded rate of 2.3% over the period 2012-
2016 and by 2.6% in 2016 to reach a total value of $95.5 billion (Marketline, 2017). The foodservice
industry in the UK is structurally different in relation to the most important sectors with pubs, clubs and
bars representing 35.7% of total market value, followed by the quick service restaurant and fast food
sector with 26.1% and full service restaurants with only 15.5%. This is a significant cultural difference in
preferences for foodservice encounters and differs markedly in comparison to other European and
Western contexts, and relates to the popularity of eating out in pubs as evidenced in the growth of chains
such as Wetherspoons and the higher-quality gastro-pub market. When it comes specifically to the fast
food industry in the United Kingdom the sectoroverall has seen major developments over the years such
as the introduction of the drive-through restaurant format in the 1980s (Duffill and Martin, 1993) and the
current expansion of home delivery services . It is clear that the global fast food industry and the UK fast
food market in particular, have grown consistently in the recent past and generatesignificant annual

revenue. This makes for a promising operational context for fast food chains to improve their performance
and increase profits, especially in the UK. This study therefore investigates the impact of service quality
on customer satisfaction in the UK fast food restaurant industry for the purposes of developing
understanding that might help drive such continued growth.
For this study, three leading chains in the UK fast food restaurant industry are taken as subjects:
Kentucky Fried Chicken (KFC), McDonald’s and Burger King. The three chains selected for this study
together constitute 50% of the total value in the UK fast food market with McDonald’s the leading brand
with 28,8%, Kentucky Fried Chicken with 12.5% and Burger King with 8.7% (Euromonitor International,
2017). The three restaurants also represent the only significant players in the quick service restaurant
sector nationally and currently operate in a diverse fast food market where there are significant
challenges from Greggs bakery (8.7% of market value), Subway (6.6%), and the casual dining sector
which includes Nando’s (7.7%) (Euromonitor International, 2017). In a competitive environment such as
this, it is important that quick service restaurants are able to understand the determinants of service
quality and customer satisfaction.
Service quality can be seen as one of the key factors affecting customer satisfaction. Due to time and
length restrictions, the research addresses the impact of service quality on customer satisfaction results
of KFC, McDonald’s and Burger King restaurants through the five dimensions of the SERVPERF model,
namely tangibles, reliability, responsiveness, assurance and empathy. The purpose of this study is to
examine relationships between the five dimensions of service quality and customer satisfaction in order to
find out which factors drive customer satisfaction. More importantly, the results of the research will
contribute to the development of service quality as well as of customer satisfaction in fast food companies
in the UK. This study seeks to answer the following questions:
 To identify specific service quality dimensions that have an impact on customer satisfaction in the
UK fast food restaurant market.
 To explore the effects of tangibles, reliability, responsiveness, assurance, and empathy on
customer satisfaction in UK fast food restaurants.
2 Literature Review
2.1 Service Quality
Parasuraman et al. (1988, p. 14) defined service quality as “the discrepancy between consumers’
perceptions of services offered by a particular firm and their expectations about firms offering such
services”. Parasuraman et al. (1985) proved that if expectations are higher than performance then
perceived quality is lower than satisfactory and hence customer dissatisfaction happens. Service quality
is also considered to be a perceived attribute based on the experience of the customer regarding the
service that the customer perceived during the delivery process of the service (Zeithaml, Parasuraman,
and Berry, 1990). Delivering quality service means conforming to customer expectations on a consistent
basis (Angelova and Zekiri, 2011). In the specific terms of the fast food restaurant, whenever personal
exchanges occur between a customer and service employees thiscan be considered to be a service
encounter (Bitner et al., 1990). Similarly, Shostack (1985, p. 243) defined a service encounter as “a
period of time during which a consumer directly interacts with a service”. Wilson et al. (2012) proved that
many positive experiences create a composite image of high quality service in the customer’s mind, while
a single negative experience can obliterate a composite image of high quality service.

Measuring Service Quality
Measuring service quality is difficult because the evaluation of service quality is not only based on the
outcome of a service, but this assessment is made during the process of service delivery. Angelova and
Zekiri (2011, p. 246) indicated that “measuring goods quality is easier because it can be measured
objectively with indicators like durability and number of defects, but service quality is an abstract item”.
During the purchase of services, there are some tangible indicators which are usually limited to the
service provider’s facilities, equipment and personnel. If tangible evidence for evaluating quality is absent,
the customer has to base the assessment on other indicators. Overall, the abstract nature of service
quality creates difficulties for organisations in terms of defining variables, making measurements and also
in understanding how consumers ultimately perceive services and service quality. There are, however, a
number of well-established frameworks for analysis of service quality such as the Nordic Model
(Gronroos, 1984), and the SERVQUAL (Parasuraman et al., 1985), SERVPERF (Cronin and Taylor,
1992) and DINESERV (Stevens, Knutson and Patton, 1995) models as detailed below.
 Gronroos/Nordic Model
According to Chaipoopirutana (2008), Gronroos (1984, 2007), the initiator of measuring service quality,
used a traditional customer satisfaction/dissatisfaction (CS/D) model to measure and explain service
quality. Based on the work of Gronroos (1984), there are two variables; expected service and perceived
service, both of which play an important role in measuring quality of service. Gronroos (1984) claimed
that the corporate image can be considered a quality dimension and the image is created by technical
and functional quality along with the effects of other factors such as traditional marketing activities
(advertising, pricing, PR), WOM, ideology and tradition (Angelova and Zekiri 2011).
 The SERVQUAL Model
Also based on the work of Gronroos (1982, 1984), Parasuraman et al. (1985) developed a conceptual
framework called the gap model, to show causes of service quality shortfalls because they found that
service quality perceptions are the consequence of the comparison of consumer expectations to actual
service performance. Palmer (2011, p.328) suggested that “the GAPS model is an analysis of the causes
of differences between what customers expect and what they get”. There are ten dimensions of service
quality: tangibles, reliability, responsiveness, competence, access, courtesy, communication, credibility,
security and understanding/knowing the customer. However later on the authors reduced the ten
dimensions to five and outlined a scale named SERVQUAL to measure possible gaps (Parasuraman et
al., 1988), listed below:
 Tangibles: aspects of physical facilities, equipment and personnel
 Reliability: the ability to perform the promised service dependably and accurately
 Responsiveness: willingness of the firm to help customers and to perform the service
promptly
 Assurance: competence and politeness of the personnel, and the capability to inspire
confidence
 Empathy: personalized assistance that the firm conveys to its customers
 The SERVPERF model
Based upon various conceptual and operational grounds, many researchers have criticized the limited
effectiveness of the SERVQUAL model as a means of understanding customer satisfaction and loyalty.
Cronin and Taylor (1992) developed an account of how the conceptualization and application of

SERVQUAL does not address the associations between service quality, customer satisfaction and
purchase intentions. They also discovered that the conceptual basis of the SERVQUAL scale does not
accurately define customer satisfaction in its totality and, as a result, suggested the SERVPERF scale.
Based on the studies of Cronin and Taylor (1992) on dry cleaning, banking, pest control, and fast food
industries, the researchers sought to prove the advantages of their “performance – only” (SERVPERF)
model in practice (Chaipoopirutana, 2008). SERVPERF operationalises only the performance-related
criteria within the SERVQUAL model and effectively eliminates the measures relating to expectation
(Carrilat, Jaramillio and Mulki, 2007). In terms of the fast food restaurant industry, Jain and Gupta (2004)
confirmed that the SERVPERF scale is more successful than the SERVQUAL scale in explaining the
service quality concepts and the distinctions between service quality scores in relation to the model
dimensions. In this paper, the SERVPERF model will be applied to measure the service quality of fast
food restaurants in the UK.
 The DINESERV Model
Based on the LODGSERV model, Stevens, Knutson and Patton (1995) built the DINESERV model to
evaluate the expectations of customer of service quality in quick service, casual and fine dining
restaurants. In the original DINESERV model, there were 40 statements about what should occur in a
restaurant and these were developed into 29 items that were measured on a seven-point scale ranging
from “strongly agree” (7) to “strongly disagree” (1) (Hansen, 2014). As a result of the DINESERVE
framework being more directly concerned with restaurant service quality, there is a different emphasis in
the measurements in relation to the original SERVQUAL dimensions that better matches the nature of the
service encounter in this specific sector (Hanks, Line and Kim, 2017; Wu and Mohi, 2015). In particular,
DINESERV pays more attention to the tangible aspects of service quality such as visual attractiveness,
comfort, and cleanliness. Markovic et al. (2010) supported the DINESERV model as a reliable and
relatively simple tool to determine how consumers view a restaurant’s quality and operations and to assist
in finding out where the problems are and how to solve them and a significant body of research has
emerged confirming the validity of the approach (Hanks, Line and Kim, 2017; Kim, Ng and Kim, 2009;
Kuo, Chen and Cheng, 2016; Wu and Mohi, 2015). For the stated reasons above, the items from the
DINESERV model will be tested in this paper.
2.2 Customer Satisfaction
The Concept of Customer Satisfaction
Customer satisfaction deals with known circumstances and known variables. Providing customer delight
is a dynamic, forward-looking process. A satisfied and delighted customer is a potential loyal customer
and a positive word-of-mouth (WOM) (Oliver et al., 1997). On the other hand once customers have been
delighted, their expectation levels are raised (Andaleeb and Conway, 2006), which means that service
providers have to make an extra effort to satisfy these customers. Andaleeb and Conway (2006) indicated
that dissatisfied customers are behind the spreading of negative word-of-mouth. Potential customers are
easily impacted by negative word-of-mouth and they may draw potential customers away from the service
provider (Wilson et al., 2012). With respect to the fast food industry, Khan et al. (2013) pointed out that all
the determinants of customer satisfaction fell into one of seven categories which were physical
environment, service quality, brand, promotion, customer expectations, price and taste of food. Their
results concluded that the main factors for customer satisfaction were service quality and brand.

Measurement of Customer Satisfaction
According to Murambi and Bwisa (2014), measuring customer satisfaction can be seen as an effort to
measure human feelings, and it is therefore very difficult at times for many researchers to do so. It is
important to note that “measuring customer satisfaction provides an indication on how an organization is
performing or providing products or services” Manani et al. (2013, p. 192). Specifically, the NBRI (2015)
proposed possible dimensions that one can use in measuring customer such as: pricing, quality of
service, speed of service, trust in employees, types of other services needed, complaints, positioning in
clients’ minds, and the closeness of the relationship between the customers and the firm.
According to Boulding et al. (1993), there were two conceptualisations of customer satisfaction,
transaction specific satisfaction and cumulative satisfaction. In the transaction specific approach
considers customer satisfaction as a post-choice evaluation judgment of a specific service encounter
(Oliver, 1993). Fornell (1992) pointed out that cumulative customer satisfaction is seen as an overall
evaluation that depends on the total purchase and consumption experience with a product or service over
time. According to Wilson et al. (2012) transaction specific satisfaction provides essential data for
identifying service issues and making immediate changes to improve customer satisfaction. They also
proposed that cumulative customer satisfaction is important in predicting, customer loyalty and motivating
a company’s investment in customer satisfaction.
2.3 Relationship between Service Quality and Customer Satisfaction
The works of Cronin and Taylor (1992) and Oliver (1993) revealed that while the concepts of service
quality and customer satisfaction are distinct, there is a close relationship between them. Parasuraman
et al. (1988) differentiated that while customer satisfaction is related to a specific transaction, perceived
service quality is a global judgment or attitude relating to the superiority of service. Sureshchandar et al.
(2002, p. 372) attested that “there exists a great dependency between service quality and customer
satisfaction, and an increase in one is likely lead to an increase in another”. In the works of Brady and
Robertson (2001) on fast food restaurants in America and Latin America, they found that service quality
and customer satisfaction were very closely related. Gronroos (2007) indicated that a perception of
service quality comes first, followed by a perception of satisfaction or dissatisfaction with this quality.
Based on the paradigm of Wilson et al. (2012), figure 1 illustrates the relationship between service quality
and customer satisfaction. In terms of the fast food industry, according to Heung et al., 2000, Jain and
Gupta (2004), Qin and Prybutok (2009), and Khan et al. (2013), price, product quality and service quality
relate directly to customer satisfaction; however, comparing product quality and price, the perceived
service quality factor plays the most important role on overall satisfaction.
2.4 Conceptual Framework and Hypotheses
In terms of the fast food restaurant industry, Jain and Gupta (2004) stated that the SERVPERF model is a
very popular model to measure service quality globally. The efficiency of the SERVPERF model was also
tested by many researchers such as Cronin and Taylor (1992), Jain and Gupta (2004), Qin et al. (2010)
and Khan et al. (2013). Due to its popularity, the SERVPERF scale is applied to measure the perceived
service quality of UK fast food restaurants in this study. There are five dimensions (Tangibles, Reliability,
Responsiveness, Assurance and Empathy) used to measure the service quality in the study. Based on
the DINESERV model of Steven, Knutson and Patton (1995), and the SERVPERF model of Cronin and
Taylor (1992), 23 items were tested corresponding to the five above mentioned dimensions.
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INSERT FIGURE 1 HERE
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This conceptual framework illustrates the correlation between dependent and independent variables. In
this framework, the five dimensions of service quality (Tangibles, Reliability, Responsiveness, Assurance
and Empathy) are the five independent variables and customer satisfaction is the dependent variable.
The framework of the five dimensions is the foundation upon which the entire study is built to investigate
the relationship between service quality and customer satisfaction. If customers are satisfied and provide
the five dimensions of service quality as the reasons for satisfaction, it can be concluded that customer
satisfaction has a significant relationship with the service quality dimensions. Based on the literature
reviews, the hypotheses of this study were based on the fact that the five dimensions of service quality
impact customer satisfaction. Based on the review of literature the following hypotheses were formulated:
H1 to H5: the Tangibles (H 1), Reliability (H 2), Responsiveness (H 3), Assurance(H4), and Empathy(H 5),
variables respectively have a positive relationship with customer satisfaction in UK fast food
restaurants.
3 Method
Data collection, research instrument
We employ positivism and this paradigm uses the deductive approach which isthe process of one step
following the other in a clear and logical sequence. This paper applies survey methodology to support
hypothesis testing of the relationship between service quality and customer satisfaction. We used the
questionnaire method to maximize the response rate for this study (Creswell, 2014 as a surveystrategy is
the best way to collect large amounts of data from a significant population. It is also is a cost-effective
method where there are a large number of variables to be addressed. The survey strategy was useful for
not only in collecting quantitative data for statistics and descriptive analysis but also in enabling the
exploration of correlations between variables in order to achieve the research goals (Saunders et al.,
2012).. When it comes to questionnaire structure, there are three parts of the survey. The first part
contains three questions which ask general personal information for classification purposes. In the
second part, there are 23 questions which explore the respondents’ perception towards the service
quality of the restaurants. Based on Likert seven-point rating scales, the questions sort the answer
statements from “strongly agree” (7) to “strongly disagree” (1) for the respondents to rate (Kumar, 2005).
The third part is divided into six questions which are designed to inquire about the overall level of
satisfaction of respondents with service quality in the restaurants they visited.
Before releasing the final version, the questionnaire was tested by five random customers in the
restaurants to remove redundant questions. The structure of the questionnaire survey was also checked
by restaurant staff to ensure that it was easy to follow. Based on this feedback, some necessary
improvements were made. We recognised that confusing questions could lead to ambiguous answers, so
sought to improve questions by way of pilot testing which was also important given the potential for
cultural difference between the United Kingdom and the North American context in which the SERVQUAL
and DINESERV models originated. The pilot test was carried out to ensure the reliability and validity of
the dimensions and the familiarity of customers with the items chosen for measurement. This pilot study
was undertaken with a small sample of five customers in each restaurant in order to finalise a list of 23
items for the study before the questionnaire was distributed in the main phase of data collection.

147 questionnaire responses were collected from the customers at two KFC restaurants, two McDonald’s
restaurants, and one Burger King Restaurant in the city of Bristol, in the south-west of England, in the
United Kingdom. An average of 30 questionnaires were used at each of the five restaurants using a
random sampling technique whereby every fifth customer was approached for participation during periods
of field-working. Data collection was undertaken at predetermined times which were related to periods of
peak and lower demand in order to maximise the number of responses at the same time as ensuring that
any variation in the customers using the restaurants at different times of day was also captured. A total of
4-5 hours was spent in each restaurant. Respondents were invited to answer the questionnaire after they
finished their meals so that they had more “neutral” time for responding to prevent threats to reliability.
For convenience, the respondents were invited to complete the questionnaire on tablets so thatthe data
were immediately saved at the time of collection. Data collection was conducted based on the voluntary
and anonymised submissions of the respondents, ensuring ethical practice.
Data was analysed using SPSS software. Chatterjee and Hadi (2006) defined regression analysis as an
analytical method that examines the possible functional relationship which may exist among different
variables at a given point in time. For these reasons, this research applies multiple regression analysis to
examine the proposed hypotheses on the constructs of the five service quality dimensions (Tangibles,
Reliability, Responsiveness, Assurance, and Empathy) and customer satisfaction. It is important to note
that the outcomes of regression analysis will indicate what factors impact customer satisfaction and which
have the most influence on customer satisfaction.
The following 23 items were incorporated in relation to each of the five dimensions of service quality
(adopted from Cronin and Taylor, 1992; Steven, Knutson and Patton, 1995; Qin and Prybutok, 2009; Qin
et al., 2010) for the purposes of this study:
Tangibles: (1) Parking availability; (2) seating availability; (3) clean and comfortable dining areas; (4)
well-dressed staff members; (5) easily readable menu; (6) clean restrooms; (7) adequate availability of
sauces, salt, napkins, wet-naps, and cutlery.
Reliability: (8) The speed of service is as fast as promised; (9) dependability and consistency; (10) quick
corrections to anything that is wrong; (11) accurate billing; (12) accuracy of customer’s order.
Responsiveness: (13) During the rush hours extra employees are provided to help maintain speed and
quality of service; (14) prompt and quick service; (15) employees willing to help and handle customers’
special requests.
Assurance: (16) Customers feel comfortable and confident in dealing with establishment; (17) feel safe
for financial transactions; (18) employees are consistently courteous; (19) employees have knowledge to
answer customer questions.
Empathy: (20) Employees are sensitive and anticipate individual customer needs and wants rather than
always relying on policies and procedures; (21) ability to make customers feel special; (22) employees
are sympathetic and reassuring if something is wrong; (23) customers’ best interests are at heart.
4 Results
4.1 Description of Research Sample
The information below in table 1 contains the traditional demographic groups based on age, gender and
the frequency of visits to UK fast food restaurants.

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INSERT TABLE 1 HERE
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4.2 Measurement Assessment
Reliability
According to Hair et al. (1995), if Cronbach’s alpha is over 0.7 in general and over 0.5 for the item-total
correlation; it means the survey questions in scale are reliable and connective. Cronbach’s alpha
coefficients of Tangibles, Reliability, Responsiveness, Assurance, and Empathy are 0.925, 0.828, 0.846,
0.932, and 0.836, respectively. The Cronbach’s alpha coefficients of the five variables are over 0.8 and
much higher than 0.7, so they exceed the suggested criterion. Furthermore, all the variables’ item-total
correlations are over 0.5, with the lowest being 0.520 and the highest being 0.921. Thus, it is clear that
the variables meet all requirements of reliability for analysis.
4.3 Factor Analysis
KMO and Bartlett’s Test
Factor analysis is generally employed to clarify the underlying structure among the variables in the
analysis. Scale reliability for variables and group of variables has indicated the suitability of the data
collected for structure detection. In other words, the Kaiser-Meyer-Olkin (KMO) and Barlett’s test measure
the sampling adequacy which should be higher than 0.5 for a satisfactory factor analysis to progress.
SPSS results indicate the KMO is 0.859 which is much greater than 0.5. As a result, it indicates that
factor analysis is relevant for this research. According to Malhotra and Birks (2007), a factor analysis is
only significant when the variables concerned are suitably correlated to one another. According to Burns
and Burns (2008), this result implies that the variables are related.
Individual observed response is supported by underlying common factors. The loading factor is based on
the weights and the correlation between each variable and the factor. According to Daniel and Berinyuy
(2010), the higher the number, the more important the variable is in defining the factor’s dimensionality. In
contrast, if the value is negative, it means that there is an opposite influence between the variable and the
factor. It is clear that all variables have practically significant loading on every certain factor so there are
no eliminated variables on the table. The individual variables, which are greater than 0.5, are chosen for
the specific factors. Finally, the five factors are generated from 23 individual variables and labelled as five
major dimensions of service quality.
4.4 Regression Analysis
As discussed in the literature review, it is assumed that there is a relationship between the five
dimensions of service quality (tangibles, reliability, responsiveness, assurance and empathy) and
customer satisfaction in UK fast food restaurants. In this part, the regression analysis will be conducted to
examine the rate of significance in the relationship between the independent variables, Tangibles,
Reliability, Responsiveness, Assurance and Empathy and the dependent variable (customer satisfaction).
The formula for regression analysis is as follows:

Customer Satisfaction = β0 + β1 x Tangibles + β2 x Reliability + β3 x Responsiveness + β4 x
Assurance + β5 x Empathy
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INSERT TABLE 2 HERE
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Table 2 above indicates the model summary of regression analysis. The R-value with 0.985 is known as
the correlation coefficient between the dependent variable and independent variables. According to Hair
(2010), the R-square value which accounts for 0.971 illustrates that 97.1% of the variance in customer
satisfaction is explained by the five independent variables, Tangibles, Reliability, Responsiveness,
Assurance and Empathy.
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INSERT TABLE 3 HERE
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Hair (2010) suggested that the function of the ANOVA Table is to present the statistic test for the overall
model fit in terms of the F ratio. The table 3 above shows that the independent variables influencing the
dependent variable are significant with a P-value of 0.00. It implies that if p is less than 0.001, there is
99% certainty of a linear relationship between the variables. On the other hand, Table 4 below provides
the coefficients of the variables with collinearity statistics.
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INSERT TABLE 4 HERE
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Based on the collinearity statistics, according to Janssens et al. (2008), the Varian Inflation Factor (VIF) is
a test to indicate that the variables are not highly correlated with each other. Table 4 shows that the VIF
of the five independent variables is equal to 1.000. It implies that the value illustrates a complete lack of
multicollinearity. It is evident that all tolerance values, which must be higher than 0.5 to prevent
multicollinearity (Janssens et al. 2008), are 1.000. As a result, it can be said that the five independent
variables are unaffected by each other and verifying the appropriateness of conducting the regression
analysis. Moreover, the results shown in Table 4 also indicate that the significance of the independent
variables is 0.000 which is less than 0.05. Therefore, it can be concluded that the five independent
variables have an influence on the dependent variable (customer satisfaction).
According to Hair (2010), the regression coefficient (B) and the standardized coefficient (Beta coefficient)
present the change in the dependent measure for each unit change in the independent variable. With the
coefficients provided in Table 4, the formula for regression analysis is:
Customer Satisfaction = 0.894 x Tangibles + 0.188 x Reliability + 0.214 x Responsiveness +
0.244 x Assurance + 0.179 x Empathy
It is clear that the β-values of the independent variables are positive and greater than 0. Therefore, it is
important to note that there is a positive correlation between the five independent variables and the
dependent variable. Based on the β-values, if tangibles, reliability, responsiveness, assurance, and

empathy factor change 1 unit, customer satisfaction will change 0.894, 0.188, 0.214, 0.244 and 0.179
units respectively.
H1: The results show that the beta coefficient of Tangibles is highest and positive at 0.894 and with p
< 0.05. Therefore, the variable Tangibles and customer satisfaction have a significant and positive
relationship. It is important to note that hypothesis H 1 is supported.
H2: Based on Table 4, it is obvious that the factor Reliability has a positive influence on customer
satisfaction with a beta coefficient of 0.188 and p < 0.05. Thus, it can be accepted that hypothesis H 2
is supported.
H3: Regarding the relationship between Responsiveness and customer satisfaction, it can be seen
from the results of Table 4 that the beta coefficient and p-value of Responsiveness are 0.214 and less
than 0.05, respectively. As a result, Responsiveness has a positive impact on customer satisfaction.
Thus, hypothesis H3 is supported.
H4: The results from Table 4 indicate that Assurance is significant in predicting the customer
satisfaction with second highest beta coefficient (0.244) and 0.00 in p-value (lower than 0.05).
Consequently, it is evident that hypothesis H 4 is supported.
H5: Finally, with the beta coefficient 0.179 and p < 0.05, the research findings point out that Empathy
is positively related to Customer Satisfaction of fast food restaurants in the UK. As a result, it can be
concluded that hypothesis H5 is supported.
5 Discussion, Conclusion & Implications of research
The aim of the first hypothesis was to establish a possible causal relationship between tangibles and
customer satisfaction in the context of the UK fast food industry. Its essential elements earned the highest
coefficient value of 0.894. Tangibles play a key role in driving customer satisfaction. Heung et al. (2000)
and Khan et al. (2013) also proved that ‘tangibles’ has a positive impact on customer satisfaction in
restaurants in Hong Kong, and Pakistan’s fast food industry. Similarly, Qin et al. (2009) maintained that
the tangibles of a fast food restaurant directly impact a customers’ experience and on its service. In stark
contrast, the research on service quality and customer satisfaction in the banking industry, Pham (2012)
argued that tangibles do not have any relationship with customer satisfaction. Consequently, it can be
concluded that the higher the customer’s perception of the tangibles variable, higher the satisfaction.
The second hypothesis tests the correlation between ‘reliability’ and customer satisfaction of fast food
restaurants in the UK. The correlation of reliability is significant at the 0.05 level with a low coefficient
value of 0.188. It is clear that this factor has a weak influence on customer satisfaction. Similarly, Quin et
al. (2010) and Bourgoure and Neu (2010) claimed that the level of customer satisfaction and the reliability
of service in China’s and Malaysia’s fast food industries have a weak relationship. Additionally, the
research results of Agbor (2011) indicated that the level of satisfaction depends lightly on the reliability of
service sectors.
The result the third hypothesis is supported by the high coefficient value of 0.214 at the significant
correlation (0.000 of p-value) with customer satisfaction. In this research, r’esponsiveness’ is comprised
of only three items; however, it has a higher coefficient value (0.214) than the other two factors empathy
(0.179) and reliability (0.188) which contain four and five items, respectively. The outcome of the third

hypothesis is in line with previous studies conducted in fast food restaurants in China (Qin and Prybutok,
2009) and in Malaysia (Bourgoure and Neu, 2010).
The purpose of hypothesis four was to examine the correlation between Assurance and Customer
Satisfaction. The result of the hypothesis provides a high coefficient value of 0.244 with a p-value less
than 0.001. It can be said that the more ‘assurance’ customers perceive, the more they are satisfied. This
outcome is further confirmed by a previous study examining Malaysian fast food restaurants (Bougoure
and Neu, 2010). Similarly, the result of the study done by Heung et al. (2000) in Hong Kong’s airport
restaurants also suggested that the higher a customer evaluates ‘assurance’, the higher is the level of
satisfaction.
Finally, based on the data analysis, the coefficient value (0.179) of ‘empathy’ is lowest compared to other
factors. It can be said that there is weak impact of empathy on customer satisfaction in the context of the
UK fast food industry. The result is confirmed by previous studies that empathy lightly affects customer
satisfaction (Agbor, 2011; Pham, 2012). According to Heung et al. (2000), the empathy factor is rarely
associated with quick service restaurants. Overall, based on the evidence, empathy is not a key driver in
customer satisfaction. However, the research finding supports hypothesis five.
Theoretical implications
This research contributes empirical support to the present theories which focus on the influence of the
five service quality dimensions on the satisfaction of customer in fast food restaurants in the UK. It is
worth noting that the variable ‘tangibles’ plays an essential role in driving customer satisfaction. In
addition, responsiveness and assurance are two further fundamental factors which significantly impact
customer satisfaction in the UK fast food market. Similarly, this study suggests that reliability and empathy
are also important for the overall customer satisfaction of quick service restaurants. It is clear that there is
a significant relationship between service quality and customer satisfaction. Furthermore, based on the
outcomes of the five hypotheses, the nomological validity of the SERVPERF model is valid as an efficient
tool in this study.
Managerial implications and Limitations
The findings of this research have contributed to a better understanding of the main factors that influence
service quality and customer satisfaction in the UK fast food market and specifically in the quick service
restaurant sector. There are clear implications from a managerial point of view in a highly competitive UK
fast food industry in understanding how customers evaluate their experiences and how this relates to
satisfaction. The ‘tangibles' variable, is the most essential factor driving customer satisfaction in the
context of the UK fast food market and this is an area in which restaurant settings potentially have an
advantage over takeaway and convenience-based competitors. It is important for fast food restaurants to
maintain attractive, clean and comfortable dining areas, with clear menu boards, well-maintained
restrooms and good availability of sauces, cutlery, trays, napkins, and utensils. This is especially
important in a British context where the largest foodservice market segment is the pubs, clubs and bars
sector which traditionally offers more comfortable surroundings than quick service restaurants. British
consumer expectations when eating out are likely to be shaped by pubs to a greater extent than by full
service restaurants, and this may be critical for fast food managers to understand given that pubs are
much more price competitive with quick service restaurants and thus may readily be chosen over
McDonald’s, KFC and Burger King.
This study uses only 147 questionnaire surveys, and this is a modest number and represents the largest
single limitation of the study. The second limitation is that the framework of the study is restricted to its

own objectives. This signifies that there are other possible factors that may influence customer
satisfaction, such as product quality and price. Thus, the five service quality dimensions are not the only
factors that have an effect on satisfaction. Consequently, based on the second limitation, future studies
should examine other factors, such as cleanliness and specific behavioural traits of staff and customers
that may impact customer satisfaction in UK fast food restaurants as well as developing a focus on
understanding the determinants of customer satisfaction and service quality in the pubs, clubs and bars
sector for comparative purposes. This is likely to prove important in a very diverse fast food marketplace
such as that found in the United Kingdom which has seen significant recent growth in takeaway, casual
dining and eating in pubs, clubs and bars. The distinctive competitive environment indicates that the quick
service restaurant sector cannot afford to be complacent with regards to service quality and customer
satisfaction.
References
Agbor, J. (2011) The relationship between Customer Satisfaction and Service Quality: a study of
three Service sectors in Umea. Master Thesis. Umea University.
Andaleeb, S.S., & Conway, C. (2006) Customer satisfaction in the restaurant industry: An
examination of the transaction-specific model. Journal of Services Marketing, 20(1), p. 3-11.
Angelova, B. and Zekiri, J. (2011) Measuring customer satisfaction with service quality using
american customer satisfaction model (acsi model).International Journal of Academic Research in
Business and Social Sciences. 1 (3), pp. 232-258.
Bailey, J. & Pearson, S. (1983) Development of a Tool for Measuring and Analyzing Computer User
Satisfaction. Management Science. 29 (5), pp. 530-545.
Bitner, M., Booms, B. & Tetreault, M. (1990) The Service Encounter: Diagnosing Favorable and
Unfavorable Incidents. Journal of Marketing. 54 (1), pp. 71 - 84.
Bougoure, U. & Neu, M. (2010) Service Quality in the Malaysian Fast Food Industry: An Examination
Using DINESERV. Services Marketing Quarterly. 31 (2), pp. 194-212.
Boulding, W., Kalra, A., Staelin, R. & Zeithaml, V. (1993) A Dynamic Process Model of Service
Quality: From Expectations to Behavioral Intentions. Journal of Marketing Research. 30 (1), pp. 7-27.
Brady, M., Robertson, C. (2001) Searching for a consensus on the antecedent role of service quality
and satisfaction: an exploratory cross-national study. Journal of Business Research, 51(1), pp. 53-68.
Burns, R. & Burns, R. (2008) Business research methods and statistics using SPSS. Los Angeles:
SAGE.
Carrillat, F.A., Jaramillio, F. and Mulki, J.P (2007) The validity of the SERVQUAL and SERVPERF
scales: A meta-analytic view of 17 years of research across five continents. International Journal of
Service Industry Management. 18 (5), pp 473-490.
Chaipoopirutana, S. (2008) The Development and Measurement of different service quality models.
Graduate School of Business, Assumption University.

Chatterjee, S. and Hadi, S. (2006) Regression analysis by example. 4th ed. New York: Wiley.
Creswell, J. (2014) Research design. 4th ed. Thousand Oaks, Calif.: Sage Publications.
Cronin, J. & Taylor, S. (1992) Measuring Service Quality: A Re-examination and Extension. Journal of
Marketing. 56 (3), pp. 55-68.
Daniel, C., Berinyuy, L. (2010). “Using the SERVQUAL Model to assess Service Quality and
Customer Satisfaction: An Empirical Study of Grocery Stores in Umea”, Umea School of Business.
Duffill, D., & Martin, H. (1993). The UK chain restaurant market: developments in this evolving
industry. British Food Journal, 95(4), 12-16.
Euromonitor International (2017) Fast Food in the United Kingdom. Report May 2017. Retrieved from
www.portal.euromonitor.com [Accessed 10th December 2017].
Fornell, C. (1992) A National Customer Satisfaction Barometer: The Swedish Experience. Journal of
Marketing. 56 (1), pp. 6-21.
Grönroos, C. (1983) Strategic management and marketing in the service sector. Cambridge, Mass.:
Marketing Science Institute.
Grö nroos, C. (1984) A Service Quality Model and its Marketing Implications. European Journal of
Marketing. 18 (4), pp. 36-44.
Grö nroos, C. (2007) Service Management and Marketing. 3 rd ed. Chichester; Wiley.
Hair, F., Anderson, E., Tatham, L., and Black, C. (1995) Multivariate data analysis: with readings. 4 th
ed. Englewood Cliffs, New Jersey: Prentice-Hall.
Hair, J. (2010) Multivariate data analysis. Upper Saddle River, N.J.: Pearson Education.
Hanks, L, Line, N. and Kim, W.G. (2017) The Impact of the Social Servicescape, Density and
Restaurant Type on Perceptions of Interpersonal Service Quality. International Journal of Hospitality
Management. 61, pp. 35-44.
Hansen, K.V. (2014) Development of SERVQUAL and DINESERV for Measuring Meal Experiences
in Eating Establishments. Scandinavian Journal of Hospitality and Tourism. 14 (2), pp. 116-134.
Heung, V., Wong, M. & Hailin Qu, (2000) Airport-restaurant Service Quality in Hong Kong: An
Application of SERVQUAL. Cornell Hotel and Restaurant Administration Quarterly. 41 (3), pp. 86-96.
IBISWorld, (2015) Takeaway & Fast-Food Restaurants. IBISWorld Industry Report I56.104.
IBISWorld.
Jain, S.K. and Gupta, G. (2004) Measuring service quality: SERVQUAL vs SERVPERF scales,
VIKALPA, 29 (2), pp. 25-37.
Janssens, W., Wijnen, K., De Pelsmaker, P., Van Kenhove, P. (2008). Marketing research with
SPSS. Harlow, England: Prentice Hall/Financial Times.

Khan, S., Hussain, S. & Yaqoob, F. (2013) Determinants of Customer Satisfaction in Fast Food
Industry A Study of Fast Food Restaurants Peshawar Pakistan. Studia commercialia Bratislavensia. 6
(21), pp. 56-65.
Kuo, T., Chen, C.T., and Cheng, W.J. (2016) Service quality evaluation: moderating influences of
first-time and revisiting customers. Total Quality Management and Business Excellence. 2016, pp. 1-
12.
Kumar, R. (2005) Research methodology: A step-by-step guide for beginners. 2 nd ed. London: SAGE
Publications Ltd.
Malhotra, N., & Birks, D. (2007) Marketing Research: an applied approach. 3 rd. NJ: Pearson/Prentice
Hall.
Manani, T., Nyaoga, R., Bosire, R., Ombati, T. & Kongere, T. (2013) Service Quality and Customer
Satisfaction at Kenya Airways Ltd. European Journal of Business and Management. 5 (22), pp. 170-
179.
Marketline, (2016) Food Service Global Industry Data. MarketLine Industry Proflile. MarketLine.
Marketline, (2017) United Kingdom Foodservice. MarketLine Industry Proflile. MarketLine.
Markovic, S., Raspor, S., Segaric, K. (2010) Does restaurant performance meet customers’
expectations? An assessment of restaurant service quality using a modified DINESERV approach.
Tourism and Hospitality Management. 16(2), pp.181-195.
Murambi, D. & Bwisa, H. (2014) Service Quality and Customer Satisfaction in Public Transport Sector
of Kenya: A Survey of Shuttle Travelers in Kitale Terminus. IJARBSS. 4 (9), p. 402-414.
NBRI (2015) Customer Satisfaction Surveys | Customer Survey. Available from:
https://www.nbrii.com/customer-survey-white-papers/why-and-how-to-measure-customer-satisfaction/
[Accessed 1 December 2017].
Oliver, R. (1993) Cognitive, Affective, and Attribute Bases of the Satisfaction Response. Journal of
Consumer Research. 20 (3), pp. 418-430.
Oliver, R., Rust, R. and Varki, S. (1997) Customer delight. Journal of Retailing. 73 (3), p. 311-336.
Palmer, A. (2011) Principles of Services Marketing. 6 th edition. Maidenhead: McGraw-Hill.
Parasuraman, A., Zeithaml, V., and Berry, L.L. (1988) SERVQUAL: A multiple-item scale for
measuring consumer perceptions of service quality. Journal of Retailing. 64 (1), pp. 12-40.
Parasuraman, Valarie A. Zeithaml, & Leonard L. Berry, (1985), “A conceptual Model of Service
Quality and Its Implications for Future Research”, Journal of Marketing, 49 (4), pp. 41-50.
Pham, L. (2012) The Relationship between Service Quality and Customer Satisfaction – a Case of a
Commercial Bank in Vietnam. Ph.D. University of Economics and Business, Faculty of Business
Administration.

Qin, H. & Prybutok, V. (2009) Service quality, customer satisfaction, and behavioral intentions in fast ‐
food restaurants. International Journal Quality & Service Sciences. 1 (1), pp. 78-95.
Qin, H., Prybutok, V. and Zhao, Q. (2010) Perceived service quality in fast ‐food restaurants: empirical
evidence from China. International Journal Quality & Reliability Management. 27 (4), pp. 424-437.
Saunders, M., Lewis, P., and Thornhill, A. (2012) Research methods for business students. 6 th ed.
Edinburgh Gate: Pearson Education.
Shostack, G.L. (1985) Planning the service encounter. In Czepiel, J., Solomon, M. and
Stevens, P., Knutson, B. & Patton, M. (1995) Dineserv: A Tool for Measuring Service Quality in
Restaurants. Cornell Hotel and Restaurant Administration Quarterly. 36 (2), pp. 56-60.
Sureshchandar, G., Rajendran, C. & Anantharaman, R. (2002) The relationship between service
quality and customer satisfaction – a factor specific approach. Journal of Services Marketing. 16 (4),
pp. 363-379.
Wilson, A., Zeithaml, V., Bitner, M., Gremler, D. (2012) Services Marketing. 2
nd ed. Maidenhead:
McGraw-Hill.
Wu, H-C., and Mohi, Z. (2015) Assessment of Service Quality in the Fast-Food Restaurant. Journal of
Foodservice Business Research. 18 (4), pp. 358-388.
Zeithaml, V., Parasuraman, A. and Berry, L. (1990) Delivering quality service. New York: Free Press.