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THE RELATIONSHIP BETWEEN SERVICE QUALITY AND CUSTOMER
SATISFACTION: THE CASE OF MUONG THANH HOTEL, HANOI
1. CHAPTER 1: INTRODUCING THE STUDY
1.1. Background of research topic
Academics and practitioners have progressively noticed service performance in the
hospitality field. Upchurch (2008) stated that from an academic view, studies in the hospitality
field have been regarded as a subject of multi-disciplinary investigation and provided knowledge
into some sectors like customer attitude, economics, marketing, education, and the like. When
considering the practical view, many academic projects in the hotel industry have been
conducted, which is regarded as a primary area of research increasingly over the globe. For
example, according to the International Council on Hotel (1999), in the United States, there has
been an increase in hundreds of projects associating with the hotel industry, conducted by
tertiary academics.
Client gratification is commercial thinking that leads to the constitution of benefits for
clients, expecting and administrating their anticipations and illustrating capability and credibility
to fulfill demands. It is essential to understand and to expect the client's desires and to be capable
of pleasing them so that client gratification can be obtained. Businesses that are capable of
comprehending and fulfill clients' demands can gain more beneficial profits than organizations
that can not perceive and serve them (Barsky & Nash, 2003). Because the price of getting new
clients is more significant than the price of maintaining the present customers, employers should
focus on keeping current clients by exercising efficient methods of client gratification and
commitment. It is particularly correct in the hospitality field. Currently, offering and maintaining
client contentment are significant difficulties for employers in the hospitality field. Lam & Zhang
(1999), Yen & Su (2004) stated that client demands for good merchandises and performance in
the hospitality field have turned out to be essential to experts. In the hotel industry, good
connections can result in client's superior loyalty and raise their profit. Choi & Chu (2001)
maintained that continuing and reciprocated beneficial correlations between clients and the
hospitality institution are getting increasingly significant as a result of the significantly positive
relationship between customers' general gratification degrees and the chances of their reciprocal
benefits to the similar institution. Jones et al. (2001) claimed that hospitality organizations are
raising their funds to enhance performance features and the comprehensible benefits for
customers to obtain superior guest gratification and commitment, hence leading to excellent
correlations with each client. Kim et al. (2001) stated that the correlation aspect influences
positively on customers' feelings; it gives positive verbal promotion and profit repeated customer
proportions.
The hospitality field has achieved numerous significant successes after the Vietnamese
authority changed its commercial policy from a command economy to a market economy in
1986, which is named the "New Innovation" policy. The nation provides a good instance of a
transition country (Pham, 2013). Bui & Holliffe (2011), Lai & Vinh (2013) stated that Vietnam
has turned out to be a prevalent tourist location for global travelers, and its hospitality field has
developed continuously in recent years.
Notwithstanding, it seems that study in the hospitality sector can not keep up with
practical life because it examines in the environment of developing nations such as Vietnam, and
this is only the situation for Hanoi. Eventually, it is crucial to focus on attempts to specifically
investigating service operation and guest gratification in the tourism field. The perceptions and
understanding achieved from such empirical study are fundamental for practitioners and
authority to improve the hospitality field in Hanoi; specifically, it is Muong Thanh hotel.
1.2. Aims
The investigation aims are two-fold. First of all, it analyses the perceptions and
evaluation of service operation in Muong Thanh hotel (Hanoi, Vietnam). Additionally, the
correlation between service operation and guest gratification is investigated.
1.3. Research question and hypotheses
The investigation aims to answer the question: What are the factors pertaining to service
quality influence the satisfaction of customers when staying in Muong Thanh Hotel, Hanoi?
Even though there exist multiple conceptual models concerning service quality, the
SERVQUAL model proposed by Parasuraman et al. (1985) dominates the existing research
papers on service quality. SERVQUAL has five levels, and it measures service quality by
calculating the gap between the expectation and experience of customers. This method is
developed by a group investigating the marketing aspect, including Berry, Parasuraman, and
Zeithaml (1985). The model identifies five constructs of service quality that customers consider
to be the most important while assessing any types of services as follows
Tangibles: The outlook of the infrastructures, equipment, employees,
transportation, and traditional materials.
Reliability: the ability to satisfy demands credibly and precisely.
Responsiveness: the willingness to please customers and provide services quickly.
Assurance: the knowledge and behavior of employees and the capability of
creating joys and trust to the customers.
Empathy: The attention not only to everyone but also to individual customers.
Five hypotheses were developed as follows to answer the above investigation questions:
H1: Tangibles has a significant relationship with customer satisfaction.
H2: Reliability has a significant relationship with customer satisfaction.
H3: Responsiveness has a significant relationship with customer satisfaction.
H4: Assurance has a significant relationship with customer satisfaction.
H5: Empathy has a significant relationship with customer satisfaction.
2. CHAPTER 2: MAPPING THE THEORETICAL FRAMEWORK – A LITERATURE
REVIEW
2.1. Customer satisfaction
In the literature, for over three decades, there has been much attempt to define the
concept of “customer satisfaction”. According to Oliver (1980, p. 460), satisfaction refers to “a
function of an initial standard and some perceived discrepancy from the initial reference point”.
Customer satisfaction was considered by scholars to be an antecedent to customer loyalty, and
thus, a crucial determinant of a firm’s performance and profitability (Heskett, Sasser and
Schlesinger, 1997). Generally speaking, there are two main approaches to defining customer
satisfaction. Some of the scholars see customer satisfaction as an outcome. For instance,
Churchill and Surprenant (1982) described the concept as an outcome of purchase and
consumption stemming from the customers’ juxtaposition of costs and rewards of their shopping
with reference to the expected consequences. In addition, Westbook (1981) considered customer
satisfaction to be an emotional response that a customer has when he or she experiences a service
or a product. The definition proposed by Churchill and Suprenant (1982) indicates that
satisfaction is reliant on a cognitive process of collating what purchasers are offered (rewards)
and what they exchange to obtain the service or product (cost). On the other hand, the latter
description considers customer satisfaction to be an emotional feeling stemming from a process
of evaluation. Woodruff et al. (1991) also adopted the same approach to defining the term.
Other researchers, on the other hand, regard customer satisfaction as a process. Tse and
Wilton (1988) defined customer satisfaction as customers’ reaction to the assessment of the
perceived difference between their expectation and the actual quality of a service/ product after
using it. Oliver (1980) was among the first scholars to describe in details how satisfaction
judgements are delivered by customers from the lens of the expectation confirmation theory.
Firstly, customers build up particular expectations of the commodity or service before they make
the purchase decision. After that, their usage of the product or service uncovers a perceived
quality degree affected by their expectations under the condition that the discrepancy between
expectation and real quality is modest. Thirdly, perceived quality might verify or repudiate pre-
purchase expectations.
In the literature, there have been several studies confirming that in service-based
industries, the thriving of a firm is decided by its capability to satisfy the needs of their guests in
a consistent and continual manner (Azmian, Nasrinahr, and Foroughi, 2012). In the hotel
segment, the service provided for customers entails mixed characteristics of perishable services
and tangible products. Subsequently, customer satisfaction is shaped upon both services and
products (Forozia, Zadeh and Gilani, 2013).
As postulated by Irawan (2008), there are three factors affecting customer satisfaction in
connection with a service or product. The first one is emotional factor, which is of utmost
importance since customer satisfaction can be reliant on the degree of connectedness with the
commodities or services they receive. Albeit extremely intangible, this factor exerts a significant
effect on customer satisfaction. The second factor to be taken into account is the ease of
obtaining a service or product. Specifically, if a customer finds it challenging to communicate
with the provider of a service or product, this might wield a negative influence on his or her
satisfaction. The last factor is service quality, which will be discussed in details later in this
chapter (Irawan, 2008). According to Poon and Low (2015), customer satisfaction, in the
hospitality industry, is reliant on accommodation, recreational activities, hospitality, additional
services, safety, food and beverage, innovation, location, transportation and appearance, coupled
with more fundamental elements like payment or pricing.
2.2. Service quality
2.2.1. The concept “Service quality”
The concept of service quality has kindled significant interest in the literature due to the
challenges of measuring and conceptualizing it in the absence of overall consensus among
scholars (Wisniewski, 2001). There exist varying schools of thoughts when it comes to defining
the term. One frequently-adopted approach is describing the concept as the degree to which a
service satisfies the needs or expectations of purchasers (Lewis and Mitchell, 1990).
Subsequently, service quality is considered to be the discrepancy between perceived service and
customer expectations. If customer expectations of the service are higher than its actual
performance, perceived quality is not sufficiently satisfactory and subsequently, customers
would feel dissatisfied (Parasuraman et al. 1985).
2.2.2. The SERVQUAL model and the RATER dimensions
2.2.2.1. The SERVQUAL model
Several scholars have formulated their own models identifying different constructs of
service quality measurement. For instance, in 1984, the Nordic model was popularized by
Gronroos (1984). According to the model, customers take into account three components of
service quality, namely image, functional quality and technical quality. However, the
SERVQUAL model by Parasuraman, Zeithaml and Berry (1985) is the best-known framework
which has been adopted in a wide array of research papers. To formulate the SERVQUAL
model, the authors designed a list of questions so that customers can rate the services with
regards to their expectation and the actual performance. After analyzing the datasets, the revised
scale was distributed to a second group of respondents, and the questions were tested.
Eventually, a multi-item scale that measures five fundamental constructs including tangibles,
reliability, empathy, responsiveness and assurance was suggested Parasuraman, Zeithaml and
Berry (1985).
The primary purpose of the model is to function as a diagnostic methodology for
revealing the strengths and limitations of a firm’s service quality and at the same time,
recognizing the principle requirements for providing customers with excellent service quality.
The model highlights the comparative differentiation in terms of service quality in reference to
the perceptions and expectations of customers towards the service they receive, as they evaluate
the actual performance of the service acquired in a specified period of time (Parasuraman,
Zeithaml and Berry, 1985). The discrepancy between customer expectations and perceptions of
service quality is applicable to the model. And the results decide the perceived service quality. If
the gap is small, it means that customers feel satisfied with the service quality.
The SERVQUAL model has been tested, adjusted and extended by several researchers
(Knutson et al., 1990; Cronin and Taylor, 1992). Those who disapprove of the model argued that
it has limitations in terms of the measurement and methodological facets. It concentrates on the
unidimensional construct instead of carrying out measurements on the basis of the five-
dimensional construct. For instance, Carman (1990) argued that the model should be adjusted by
changing the wording or adding items. Peter, Churchill and Brown (1993) criticized the fact that
the model largely depends on the difference in scores between customer expectation and
perception to decide their satisfaction with five primary constructs (Parasuraman, Zeithaml and
Berry, 1988). They argued that the approach leads to a low degree of reliability and restriction of
variance (which makes it difficult to display relationships with other variables). The gap score
approach adopted by the SERVQUAL model, as stated by Schneider and White (2004), also
suffers from questionable validity, specifically with regards to showing a construct is different
from other constructs. Brown, Churchill and Peter (1993) even pointed out that every issue
associated with the difference scores approach can be found in the SERVQUAL model. In terms
of content validity, as stated by Lapierre and Filiatrault (1996), the definitions of two constructs,
reliability and empathy are considered to be confusing and the reliability dimension appears to
overlap with the “technical quality” dimension proposed by Gronroos (1984). In addition, while
tangible and reliability appear to be distinct constructs, the rest of the constructs seem to embody
one single dimension (Getty and Thompson, 1994).
Such criticisms have given rise to multiple industry-specific models. For instance, the
LODGSERV model developed by Knutson et al. (1990) contains 26 lodging-related items and is
aimed at measuring customer expectation in the lodging segment. Nonetheless, the adoption of
the model remains limited in the hospitality industry since it was only utilized in a modest
quantity of research papers (Lockyer, 2003). Additionally, on the basis of the SERQUAL model,
Stevens et al. (1995) proposed a service quality model for the restaurant segment called
DINESERV. The researchers revealed that for restaurants, the most crucial dimension of service
quality is reliability. It is also worth mentioning the SERVPERF model by Cronin and Taylor
(1992), which is regarded as an alternative of the traditional service quality model. Jain and
Gupta (2004) suggested that this model is more parsimonious than the model proposed by
Parsuraman, Zeithaml and Berry (1985) since it has fewer questions and provides a better
explanation for the service quality dimensions.
Although there exist several debated methodological issues surrounding the SERVQUAL
model, it is considered to be the most frequently used framework and probably the most
powerful model of service quality measurement (Ahmad, Ahmad and Papastathopoulos, 2019). It
was even argued that “service quality has effectively become SERVQUAL and vice versa”
(Woodall, 2001). One of the main reasons for such a popular application is that the model seeks
to comprehend general factors of service quality that are popular for several services and
applicable to varying industries (Polyakova and Mirza, 2015). In addition, as postulated by
Carrillat, Jaramillo and Mulki (2017), who conducted a meta-analytic study on the adoption of
two service quality models (SERVPERF and SERVQUAL) in 17 years across five continents,
the SERVQUAL model is useful for practitioners because of its richer diagnostic value.
Subsequently, it is generally approved that the model is a reliable predictor of service quality
(Msoka and Msoka, 2014).
2.2.2.2. The RATER dimensions
The five constructs of service quality, which are frequently referred to as the RATER
dimensions, are explained as below:
Responsiveness: This dimension represents employees’ readiness to provide assistance
for customers and offer them prompt service (Cronin and Taylor, 1992). Such a construct is
specifically important when guests have requests or complaints regarding a firm’s services
(Ahmad, Ahmad and Papstathopoulos, 2019). According to Oschell (2009), different age groups
hold different perceptions on the responsiveness dimension. Specifically, what an older customer
views as responsive and attentive might be regarded by a younger customer as unnecessary and
frustrating. It is also worth mentioning the recent study by Lo et al. (2015), which revealed that
this construct can be achieved through standardized employee training courses and service-
related procedures.
Assurance: The assurance construct revolves around employees’ courtesy and knowledge
as well as their capability to pass on confidence or trust. This is of utmost importance for firms
providing legal, health and financial services (Lu et al., 2015). According to Aleshaiwy (2015),
in the hotel segment, to optimize the assurance dimension, hotels need to display a high degree
of confidence and ensure that every customer feels secure during their stay at the property. It is
also worth mentioning the study by Wattanacharoensil and Yoopetch (2012), which seeks to
examine the service quality offered by the airline industry in Thailand. The research revealed
that while the flight attendants perform excellently in terms of the empathy construct, they are
considered to be ineffective in optimizing the assurance dimension. The reason for such a
phenomenon, as explained by the authors, is that Thailand is characterized by a strong emphasis
on personal relationship and sometimes a negligence on adhering to particular protocols – which
is highly expected by international passengers.
Tangibles: The tangibles facet of service quality refers to every tangible item of the
service provider, such as appearance of staff, facilities, equipment that customers can see and
touch, coupled with materials used to interact with customers (Howard, 1998). The application of
this construct varies across industries (Aleshaiwy, 2015). For instance, the tangibles dimension
of a hospital is manifested through the cleanness of patient rooms, the modern medical
equipment, and so on. Liang (2008) argued that in the luxury hotel segment, this construct makes
a significant contribution to service quality since luxury hotels are frequently perceived by the
public as manifesting an elegant, beautiful appearance through their facilities and employees. In
addition, Kim (2005) argued that the tangibles dimension of a golf course contributes
significantly to the satisfaction of Generation Y since they hold the greatest expectation of
service among the studied age groups.
Empathy: This dimension appears to be quite confusing from some scholars. It is related
to the company’s understanding the demands of each customer, and delivery the service in a
caring manner (Presbury, 2009). Small-sized enterprises perform better than their larger
competitors in terms of treating their consumers as individuals. In the context of the hospitality
industry, this construct entails a high degree of communication between employees and guests so
that employees can grasp a profound understanding of customers’ demands, and thereby,
offering them enough attention (Shafiq, Mostafiz and Taniguchi, 2019). In addition, Mbuthi,
Muthoni and Muchina (2013), who studied the relationship between service quality and
satisfaction of domestic guests in Kenya’s hotels, pointed out that even when customers feel
contented with the physical aspects of their hotel, they might still rate their overall experience as
not satisfactory if they feel dissatisfied with the empathy dimension of the service.
Reliability: The reliability construct refers to the service provider’s capability to deliver
the promised service in a dependable, consistent and accurate fashion (Miyoung and Haemoon,
1998). As posited by Markovic and Jankovic (2013), this dimension makes a significant
contribution to customer satisfaction and might be beneficial to helping a firm generate a
competitive advantage. However, the measurement of this dimension is heavily criticized since it
takes into account the outcome of the service. In contrast, the four above-mentioned dimensions
are associated with the process of the service. Shafiq, Mostafiz and Taniguchi (2019) argued that
in the hotel industry, a firm’s inability to fulfill its promises with customers would give rise to
their negative emotions, and eventually exert a detrimental effect on the firm’s image.
2.2.3. Service quality in the hotel industry
As mentioned above, the SERVQUAL model reckons effective in measuring service
quality in several industries. Several studies also revealed that the model is beneficial to
measuring service quality of the hotel segment (Kandampully, Juwaheer and Hu, 2011; Ahmad,
Ahmad and Papastathopoulos, 2019, ABC). And some of these studies targeted at hotels located
in developing countries such as China, Mauritius, Malaysia, etc. For instance, the research paper
by Kandampully, Juwaheer and Hu (2011) adopted the SERVQUAL model to examine the
service quality gaps of nearly 1,5000 customers staying at a lodging company in Mauritius for at
least six nights. The research findings revealed that service quality wields a significant influence
on the company’s image, and thereby, affecting customer retention. It can be suggested that a
positive corporate image results in customer satisfaction. Also targeting at Mauritius, Juwaheer
(2004) was aimed at measuring the five constructs of service quality in more than 400 beach
hotels in the country. The results revealed that the service quality of these lodging companies
was rated poorly due to the lack of reliability, the attitude of hotels’ staff, the interior design of
the rooms and the surrounding areas of the hotels.
Similarly, the research paper carried out by Akbaba (2006) involved 234 hotels in
Turney. The authors pointed out that the most crucial dimension was tangibles
The study also argued that the SERVQUAL model is deemed conducive to assessing
service quality in the lodging industry. Nevertheless, it might be better if scholars make some
adjustments so that the model can be tailored
2.3. Customer gratification
Hoffman and Bateson (2010) claimed that although there are many clarities of guest
gratification, the most popular definition is that it is a guest's assessment by valuing between
typical anticipations of a service type and comprehension of a specific service by the experience
of the service. The evaluation is fundamentally formed by a model, which is named as the
expectancy disconfirmation paradigm. It is if the guest's comprehensions satisfy his
anticipations, the anticipations are considered to be stated; hence, the guest is pleased. In
contrast, if the client's comprehensions can not meet the assumptions, the assumptions are
regarded as unstated. Moreover, gratification is defined as a concluded mental state experienced
by the customer when agreed or disagreed anticipations subsist with a particular experience
transaction through service (Getty and Thompson, 1995).
Consumer gratification includes two different factors, consumer anticipations and
comprehensions (Gronroos, 1990; Williams and Uysal, 2003). Client gratification is defined by
how the merchandise satisfies consumer anticipations for the merchandise. Additionally,
consumer gratification is considered as the method that clients are pleased when they experience
service equals or surpasses their hopes (Williams and Uysal, 2003).
2.3.1. Expectations
Standards like word of mouth, individual demands, exterior interactions, and prior
experiences influence consumer's anticipations (Zeithaml et al., 1987). Moreover, additional
causes, such as consumer's actual demands and the expectations of the services, are added by
Williams and Uysal (2003). Apparent feature of comprehended risk and value will impact client
anticipation before purchasing a merchandise or service. These are the products, which have
personally, and constitute a consumer gratification in provided services and resulted in
contentment.
2.3.2. Perception
The way how a consumer thinks about a service is based only on as an assessment to high
quality in provided service by consumers (Taylor, 1994). Zeithaml et al. (1997) stated that the
perceptions of a client and where the consumer attitude to the service begins to show is the time
when a service operates and after the ending of the proceeded service.
Consumer service comprehension is combined groups of discernments conducted during
and at the finish stage of the experience, which when they fulfill or surpass anticipations from
consumer gratification.
2.4. Importance of Customer Satisfaction
For decades, customer-centered firms have placed a significant emphasis on building a
more profound understanding of their customers demands so that they can transform it into the
ability to provide their customers with what they want, or in other words, improve customer
satisfaction (Ekinci, 2004). Tam (2004) even claimed that customer satisfaction is an important
determinant of a company’s survival and thriving. In addition, as stated by Huang, Lee and Chen
(2017), a firm which continuously seeks to satisfy its customers has a higher chance of achieving
higher customer retention level as well as gaining more profitability, which arise from customer
loyalty.
Service assessment and its aspects are a challenge to investigate and evaluate it.
Moreover, it may be efficiently assessed; if consumer gratification nearly starts to be shown out,
its feature might be very significant and operates fundamentally in the extremely competitive
context. The following years will be the time when the hotel industry will provide services at
growingly perceived people, who may not be ready to experience deficient service operation;
they will make judgments and ostracize the render of service performance (Callan, 1994). This
statement matches the real clarity that the present consumer is conscientious about the demands
and wants. Current clients are dealing with difficulty relating to a wide variety of merchandise
and service, which are the foundation to maintain and underpin the guest base. Existing
businesses cope with their most challenging competition features, and things will become worse
in the following years (Kotler et al., 1996). Williams & Uysal (2003) stated that because of the
complexity of the client gratification, they are typically practiced to the operation of the tourism
service, which is palpable and unpalpable features and also challenging to work out.
Besides, previously, hospitality has been repeatedly regarded as the natural result of the
contextual and cultural properties of a particular area. In this perspective, the significance of
tourism businesses may not be able to affect need degrees and is simply refrained from the
provision of services to travelers. Marketing attempts have to be exercised to illustrate the
contextual features of the destination to obtain new clients (Le Blanc & Nguyen, 1996). The
consistent rise of the need of hospitality services, and the demand for better criteria by the
customers, has raised the competitive feature among tourism companies and show the
relationship between hospitality location attraction and the requirements of the hotel service
provisions. In this view, offering excellent services and enhancing guest gratification are
extensively realized as vital elements to increase the enterprises' operations in the hospitality
field (Barsky & Labagh, 1992; Opermann, 1998). Oh & Parks (1997) maintained that hotels that
have high service performance would eventually enhance their return. Choi & Chou (2001)
stated that because the hotel industry provides identical services, meaning that the field is very
competitive, hospitality companies have to be capable of pleasing clients superior to their
opponents. Hospitality companies must have an excellent guest gratification degree for the
service provided to gain commitment and surpass counterparts. The demands and wants of
travelers are investigated in some researches. The hotel feature comprehension is stated as the
level to which customers can have numerous services and infrastructures for their visit to a hotel.
Atkinsons (1988), McCleary et al. (1993) claimed that features like sanitation, cost, destination,
safety, individual service, tactile appeal, relaxing chances, service criteria, attractive appearance,
and prestigiousness are considered as determinants by tourists to evaluate the hotel operation.
3. CHAPTER 3: METHODOLOGICAL APPROACH
3.1. Research paradigm
There exist four main forms of research philosophies, including positivism, realism,
interpretivism (Saunders et al., 2009). As stated by Sullivan (2001), positivism is related to the
the situation in which the existence of the world or knowledge is assumed to be separate from
people’s thoughts about it and the fact that science adopts objective methods to investigate what
exist in the world. Irshaidat (2019) also argued that positivism paradigm involves the generation
of hypotheses through existing theoretical frameworks and the testing of such hypotheses
through quantitative and logic-based techniques. In addition, the positivistic philosophy must not
involve the personal values of the scholar to gain a neutral result (Savigny, 2008). In this
dissertation, the philosophy of positivism is used. Subsequently, existing theoretical frameworks
and models related to service quality and customer satisfaction are used throughout this
dissertation, and on such a basis, hypotheses are proposed.
3.2. Research approach and strategy
The deductive approach first involves the formulation of hypotheses or theories and then
includes the formulation of an appropriate strategy to to test these hypotheses or theories
(Saunders et al., 2016). According to Bryman and Bell (2001), the deductive research approach
is appropriate for the philosophy of positivism and most frequently adopted in quantitative
studies. Additionally, this approach can identify the correlations among distinctive variables and
validate the proposed hypotheses (Saunders et al. 2016). In the thesis, the online questionnaire
containing open ended questions, is the only method for gathering necessary datasets. A total of
five hypotheses are proposed on the basis of the research objectives and previous research papers
by Parasuraman et al. (1985)
H1: Tangibles has a significant relationship with customer satisfaction.
H2: Reliability has a significant relationship with customer satisfaction.
H3: Responsiveness has a significant relationship with customer satisfaction.
H4: Assurance has a significant relationship with customer satisfaction.
H5: Empathy has a significant relationship with customer satisfaction.
H6: Customer satisfaction has a significant relationship with repurchase intention
H7: Customer satisfaction has a significant relationship with word of mouth
3.3. Time Horizon
A research design might be cross-sectional or longitudinal. A research that is deemed cross-
sectional investigates a specific phenomenon (sample) in a specific time span (Saunders et al.,
2016). In this dissertation, the time horizon is cross-sectional as datasets will be gathered from
customers of Muong Thanh hotel at a specific point of time.
3.4. Sampling Method
Non-probability, judgmental sampling (also known as purposive sampling) was adopted which
requires the researcher to approach specific targeted respondents who are judged appropriate to
provide the necessary information (Malhotra, 2007; Bryman, 2016). In particular, customers who
have had experiences with Muong Thanh Hotel are selected. A minimum of 100 responses will
be gathered to ensure the reliability of the thesis.
3.5. Data Collection Method
The questionnaire developed for this research is adapted from Kim-Soon et al. (2014), with few
amendments made in order to suit this research. The modifications are primarily grammatical
and sentence structure. Past tense is used in the sentences to match the context since only those
customers are contacted who had already had the service experience. At some places the helping
examples were changed to better explain the meaning. In all these changes, it is ensured that the
meaning of the questions remains the same.
The questionnaire consists of three parts: first contained filter and demographic questions which
aimed to accept responses only from the appropriate respondents. The second part sought
answers regarding the service quality of Muong Thanh Hotel. This part constituted the five
dimensions of SERVQUAL, measured on a five-point Likert scale (Cooper and Schindler, 2008;
Sekaran and Bougie, 2010), where 1 represented “strongly disagree” and 5 represented “strongly
agree.” The third part of the questionnaire sought responses on customer satisfaction on a five-
point Likert scale.
3.6. Analysis, results and discussion
3.6.1. Reliability
In order to establish the internal consistency among the items of the questionnaire reliability tests
are applied (Sekaran, 2003; Ponbamrungwong and Chandsawang, 2009). Reliability coefficient,
or Cronbach’s α, values range from 0 to 1, where a value close to 1 means higher internal
consistency and close to 0 means lower reliability (Ponbamrungwong and Chandsawang, 2009).
The Cronbach value must be at least 0.7 to ensure the reliability.
3.6.2. Correlation test
Pearson’s correlation is the coefficient used to measure the association of the independent
variables with the dependent variable (Sekaran, 2003; Pallant, 2007; Ponbamrungwong and
Chandsawang, 2009). The coefficient values range from 0 to 1, where values near to 1 indicate a
strong correlation, while those near to 0 indicate a week correlation (Ponbamrungwong and
Chandsawang, 2009).
3.6.3. Multiple linear regression
After establishing the reliability of the items and confirming a correlation between the
independent and the dependent variables, the next step was to establish whether or not, and by
how much, are the independent variables predictive of the dependent variable. This is done
through multiple linear regression (Ponbamrungwong and Chandsawang, 2009), which allows
researchers to quantify the impact of various simultaneous influences upon a single dependent
variable (Pallant, 2007).
4. CHAPTER 4: DATA ANALYSIS AND RESULTS
This chapter presents the SPSS-based analysis of the primary data and the content analysis of
the secondary data. It includes five main parts.
The section discusses the frequencies of each construct of the questionnaire, followed by a
statistically descriptive analysis. The correlations among variables are also displayed. Lastly, the
section presents the mediation analysis.
4.1.1. Frequencies
The questionnaire has a total of 25 questions. The first part of the questionnaire covers the
demographic data of the respondents (2 questions). Respondents were asked to provide
information about their age and gender. The total number of responses was 131 in which 11
responses were excluded due to the fact that these respondents did not answer all the questions
asked. As result, 120 responses were used for further analysis.
The proportions of male and female respondents are relatively equal. Men accounted for 45% of
the respondents, the figure for female customers was 50.8%. 4.2% of the respondents did not
want to reveal their gender (see Figure 1).
Male45%
Female51%
Prefer not to say 4%
Gender
Male Female Prefer not to say
Figure 1. Gender of the Respondents
In terms of the age group, the majority of the respondents are aged between 35 and 44 years old
(28.3%). 20% of the respondents belong to the 45-54 age group. The 25-34 age group is the third
popular, accounting for 17.5% of the respondents. 16 respondents are under 18 years old
(13.3%). The figures for the under 18 and above 55 age groups are 13.3% and 10.8%
respectively.
Under 1813%
18-2410%
25-3418%
35-4428%
45-5420%
Above 5511%
Age
Under 18 18-24 25-34 35-44 45-54 Above 55
Figure 2. Age of the Respondents
4.1.2. Descriptive Analysis
The lowest mean value is 3.45 and the highest mean value is 4.24. In order to eliminate the
question error, the researcher also checked the Skewness and Kurtosis measures. For Skewness,
the accepted value should be within -1 to +1 and for Kurtosis, it should be within -3 to +3
(Landau & Everitt, 2004). No questions are removed since the Skewness and Kurtosis measures
of all questions are within the accepted level.
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation Skewness Kurtosis
Statistic Statistic Statistic Statistic Std. Error Statistic Statistic Std. Error Statistic Std. Error
TAN1 120 1.00 5.00 3.9667 .09897 1.08414 -.859 .221 -.070 .438
TAN2 120 1.00 5.00 4.1750 .08588 .94079 -1.221 .221 1.309 .438
TAN3 120 1.00 5.00 3.4917 .07577 .83006 -.511 .221 -.092 .438
TAN4 120 2.00 5.00 4.1333 .08529 .93425 -.900 .221 -.053 .438
TAN5 120 1.00 5.00 3.4833 .08198 .89802 -.551 .221 .527 .438
REL1 120 2.00 5.00 3.5000 .06482 .71007 .072 .221 -.209 .438
REL2 120 1.00 5.00 4.0833 .06960 .76239 -1.183 .221 2.667 .438
REL3 120 2.00 5.00 4.1000 .06525 .71479 -.851 .221 1.422 .438
REL4 120 2.00 5.00 4.0500 .07376 .80805 -.772 .221 .455 .438
REL5 120 1.00 5.00 3.5083 .07001 .76692 -.256 .221 .293 .438
RES1 120 1.00 5.00 3.5250 .08110 .88842 -.589 .221 .725 .438
RES2 120 1.00 5.00 4.0833 .08980 .98376 -1.031 .221 .825 .438
RES3 120 1.00 5.00 3.5583 .07742 .84809 -.690 .221 .429 .438
RES4 120 1.00 5.00 4.1083 .08435 .92397 -.999 .221 .606 .438
RES5 120 1.00 5.00 3.9917 .09650 1.05716 -1.198 .221 1.051 .438
ASS1 120 2.00 5.00 4.1583 .08199 .89814 -.744 .221 -.409 .438
ASS2 120 1.00 5.00 3.9583 .07237 .79278 -.646 .221 .859 .438
ASS3 120 2.00 5.00 4.2417 .08368 .91666 -.901 .221 -.298 .438
EMP1 120 2.00 5.00 3.5500 .07086 .77622 -.115 .221 -.334 .438
EMP2 120 2.00 5.00 3.9667 .07192 .78786 -.780 .221 .675 .438
SAT 120 2.00 5.00 3.9833 .07483 .81975 -.807 .221 .532 .438
REP 120 1.00 5.00 3.4583 .07090 .77672 -.242 .221 .166 .438
WOM 120 1.00 5.00 3.6583 .07343 .80436 -.481 .221 .373 .438
Valid N
(listwise)
120
4.1.3. Reliability – Cronbach’s’ Alpha
After data gathering for the pilot study, the researcher has measured internal consistency, using
Cronbach’s alpha. Cronbach’s alpha is the most commonly used for measuring the internal
consistency reliability, associated with scores derived from a scale. Cronbach’s alpha is the basic
measure for reliability (Green & Salkind, 2008). Mackey & Gass (2015) defined reliability as
consistency of a score or a test. A good Cronbach’s alpha value should be more than 0.77. After
conducting the reliability test, one item of the reliable dimension is removed due to their low
level of Cronbach’s alpha.
Variables related to the tangible dimension
Reliability Statistics
Cronbach's
Alpha N of Items
.834 5
Item-Total Statistics
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Cronbach's
Alpha if Item
Deleted
TAN1 15.28 7.818 .713 .778
TAN2 15.08 8.860 .637 .800
TAN3 15.76 9.311 .654 .798
TAN4 15.12 9.364 .538 .827
TAN5 15.77 9.021 .647 .798
No variables are removed because all the Cronbach alpha values are higher than 0.6.
Variables related to the reliable dimension
Reliability StatisticsCronbach's Alpha N of Items
.759 5
Item-Total StatisticsScale Mean if
Item Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Cronbach's Alpha
if Item Deleted
REL1 15.74 6.126 .170 .825
REL2 15.16 4.420 .694 .653
REL3 15.14 4.980 .544 .710
REL4 15.19 4.291 .682 .654
REL5 15.73 4.701 .582 .695
The REL1 variable (My reservation was handled efficiently) is removed because the corrected
item-total correlation value is smaller than 0.3.
Reliability StatisticsCronbach's Alpha N of Items
.825 4
Item-Total StatisticsScale Mean if
Item Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Cronbach's Alpha
if Item Deleted
REL2 11.66 3.605 .670 .771
REL3 11.64 3.862 .624 .792
REL4 11.69 3.375 .707 .753
REL5 12.23 3.743 .605 .801
No variables are removed because all the Cronbach alpha values are higher than 0.6.
Variables related to the responsive dimension
Reliability StatisticsCronbach's Alpha N of Items
.842 5
Item-Total StatisticsScale Mean if
Item Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Cronbach's Alpha
if Item Deleted
RES1 15.74 9.034 .715 .793
RES2 15.18 8.840 .656 .808
RES3 15.71 9.771 .594 .825
RES4 15.16 9.143 .653 .809
RES5 15.27 8.588 .635 .816
No variables are removed because all the Cronbach alpha values are higher than 0.6.
Variables related to the assurance dimension
Reliability StatisticsCronbach's Alpha N of Items
.736 3
Item-Total StatisticsScale Mean if
Item Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Cronbach's Alpha
if Item Deleted
ASS1 8.20 2.128 .585 .619
ASS2 8.40 2.477 .545 .670
ASS3 8.12 2.138 .556 .657
No variables are removed because all the Cronbach alpha values are higher than 0.6.
Variables related to the empathy dimension
Reliability StatisticsCronbach's Alpha N of Items
.712 2
Item-Total StatisticsScale Mean if
Item Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Cronbach's Alpha
if Item Deleted
EMP1 3.97 .621 .552 .
EMP2 3.55 .603 .552 .
No variables are removed because all the Cronbach alpha values are higher than 0.6.
4.1.4. Exploratory Factor Analysis
KMO and Bartlett's TestKaiser-Meyer-Olkin Measure of Sampling Adequacy. .838
Bartlett's Test of Sphericity Approx. Chi-Square 957.566
df 171
Sig. .000
Total Variance Explained
Component
Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 6.059 31.887 31.887 6.059 31.887 31.887 3.417 17.985 17.985
2 2.701 14.215 46.102 2.701 14.215 46.102 3.114 16.391 34.376
3 1.524 8.024 54.125 1.524 8.024 54.125 2.651 13.952 48.329
4 1.226 6.455 60.580 1.226 6.455 60.580 1.830 9.632 57.960
5 1.159 6.102 66.681 1.159 6.102 66.681 1.657 8.721 66.681
6 .778 4.092 70.774
7 .687 3.617 74.391
8 .631 3.319 77.709
9 .600 3.158 80.868
10 .565 2.975 83.842
11 .482 2.538 86.380
12 .425 2.239 88.619
13 .398 2.097 90.716
14 .361 1.898 92.614
15 .344 1.813 94.427
16 .332 1.749 96.176
17 .273 1.437 97.613
18 .241 1.271 98.884
19 .212 1.116 100.000
Extraction Method: Principal Component Analysis.
Rotated Component Matrixa
Component
1 2 3 4 5
RES1 .774
RES3 .757
RES4 .750
RES5 .731
RES2 .711
TAN1 .814
TAN2 .793
TAN3 .761
TAN5 .724
TAN4 .674
REL3 .776
REL4 .772
REL2 .762
REL5 .710
ASS3 .805
ASS1 .779
ASS2 .567 .588
EMP1 .856
EMP2 .734
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
The ASS2 variable is removed.
KMO and Bartlett's TestKaiser-Meyer-Olkin Measure of Sampling Adequacy. .832
Bartlett's Test of Sphericity Approx. Chi-Square 867.312
df 153
Sig. .000
The KMO value is equal to 0.832, which indicates that the sampling is adequate. The sig value is
less than 0.05, indicating that the scale can do factor analysis.
Total Variance Explained
Component
Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 5.685 31.581 31.581 5.685 31.581 31.581 3.162 17.567 17.567
2 2.659 14.771 46.352 2.659 14.771 46.352 3.077 17.093 34.661
3 1.484 8.243 54.594 1.484 8.243 54.594 2.634 14.632 49.292
4 1.181 6.563 61.158 1.181 6.563 61.158 1.669 9.274 58.566
5 1.053 5.850 67.008 1.053 5.850 67.008 1.520 8.442 67.008
6 .771 4.285 71.293
7 .687 3.815 75.108
8 .606 3.368 78.475
9 .584 3.245 81.720
10 .545 3.026 84.746
11 .475 2.637 87.383
12 .422 2.343 89.726
13 .377 2.094 91.821
14 .357 1.981 93.801
15 .343 1.908 95.709
16 .303 1.685 97.394
17 .244 1.358 98.752
18 .225 1.248 100.000
Extraction Method: Principal Component Analysis.
The eigenvalue of the fifth component is equal to 1.053, which is higher than 1. Rotation Sums
of Squared Loadings (Cumulative %) = 67.008% > 50 %, which means a total of 67.008% of the
variance can be explained by five components
4.1.5. Pearson Correlation
SAT
TAN Pearson Correlation 0.420*
Sig. (2-tailed) 0.000
REL Pearson Correlation 0.238**
Sig. (2-tailed) 0.009
RES Pearson Correlation 0.335*
Sig. (2-tailed) 0.000
ASS Pearson Correlation 0.292**
Sig. (2-tailed) 0.001
EMP Pearson Correlation 0.380**
Sig. (2-tailed) 0.000
WOM Pearson Correlation 0.641**
Sig. (2-tailed) 0.000
REP Pearson Correlation 0.646
Sig. (2-tailed) 0.000
Table 1. Pearson Correlation
*. Correlation is significant at the 0.05 level (2-tailed)
**. Correlation is significant at the 0.01 level (2-tailed)
The p-values for the correlations between five dimensions of service quality and customer
satisfaction are all less than the significance level of 0.05, which indicates that the correlation
coefficients are significant. The same goes for the correlation between word-of-mouth,
repurchase intention and customer satisfaction.
4.1.6. Linear Regression
In this study, two linear regressions were conducted respectively. The first regression was to test
the relationship between the five dimensions of service quality and customer satisfaction. The
five dimensions are treated as independent variables while customer satisfaction is considered to
be dependent variables.
The second regression aimed to investigate customer satisfaction and their behavioral intention.
Customer satisfaction is regarded as independent variables, and behavioral intention is treated as
dependent variables.
4.1.6.1. Service Quality and Customer Satisfaction
Model R R
Square
Adjusted R Square Std. Error of the
Estimate
1 0.532a 0.283 0.251 0.70937
Table 2. Model Summary 1
Table 6 is used to evaluate the appropriateness of the linear regression model. As can be seen
from the table, the Adjusted R Square is 0.251, meaning 25.1% of the variance on the dependent
variables can be explained by the independent variables. According to Landau & Everitt (2004),
the higher the value of the Adjusted R Square is, the better the hypothesis is tested. In other
words, 25.1% of customer satisfaction can be elucidated by the five dimensions of service
quality.
Model Unstandardized
Coefficients
Standardize
d
Coefficients
t Sig. Collinearity
Statistics
B Std.
Error
Beta Tolerance VIF
Constant 0.823 0.532 1.547 0.125
TAN 0.354 0.099 0.315 3.561 0.001 0.802 1.246
REL -0.078 0.127 -0.059 -0.614 0.541 0.683 1.465
ASS 0.108 0.094 0.103 1.151 0.252 0.780 1.282
RES 0.240 0.105 0.216 2.292 0.024 0.706 1.417
EMP 0.193 0.112 0.162 1.730 0.086 0.714 1.400
Table 8 provides necessary statistics to test explain the correlations between the five dimensions
of service quality and customer satisfaction. As can be seen from the table, the tangible and
responsive dimensions of service quality are correlated to customer satisfaction (p<0.05). This
indicates that H1 and H5 are supported and H2, H3, H4 are rejected.
4.1.6.2. Customer Satisfaction and Word of Mouth
Model R R
Square
Adjusted R Square Std. Error of the
Estimate
1 0.641a 0.411 0.406 0.61981
Table ABC is used to evaluate the appropriateness of the linear regression model. As can be seen
from the table, the Adjusted R Square is 0.406, meaning 40.6% of word of mouth can be
elucidated by customer satisfaction.
Model Unstandardized
Coefficients
Standardize
d
Coefficients
t Sig. Collinearity
Statistics
B Std.
Error
Beta Tolerance VIF
Constant 1.152 0.282 4.087 0.000
SAT 0.629 0.069 0.641 9.078 0.000 1.000 1.000
Table ABC provides necessary statistics to test explain the correlation between repurchase
intention and customer satisfaction. As can be seen from the table, customer satisfaction is
significantly correlated to repurchase intention (p<0.01). This indicates that H6 is supported.
4.1.6.3. Customer Satisfaction and Repurchase Intention
Model R R
Square
Adjusted R Square Std. Error of the
Estimate
1 0.646a 0.417 0.412 0.59567
Table ABC is used to evaluate the appropriateness of the linear regression model. As can be seen
from the table, the Adjusted R Square is 0.412, meaning 41.2% of repurchase intention can be
elucidated by customer satisfaction.
Model Unstandardized
Coefficients
Standardize
d
Coefficients
t Sig. Collinearity
Statistics
B Std.
Error
Beta Tolerance VIF
Constant 1.022 0.271 3.772 0.000
SAT 0.612 0.067 0.646 9.183 0.000 1.000 1.000
Table ABC provides necessary statistics to test explain the correlation between repurchase
intention and customer satisfaction. As can be seen from the table, customer satisfaction is
significantly correlated to repurchase intention (p<0.01). This indicates that H7 is supported.
4.2. Summary of Results
Table ABC summarizes the test results of the proposed hypotheses
No Hypothesis Result
Hypothesis 1
(H1)
There is a statistically significant relationship between
the tangible dimension and customer satisfaction
Supported
Hypothesis 2
(H2)
There is a statistically significant relationship between
the empathy dimension and customer satisfaction
Rejected
Hypothesis 3
(H3)
There is a statistically significant relationship between
the reliable dimension and customer satisfaction
Rejected
Hypothesis 4
(H4)
There is a statistically significant relationship between
the assurance dimension and customer satisfaction
Rejected
Hypothesis 5
(H5)
There is a statistically significant relationship between
the responsive dimension and customer satisfaction
Supported
Hypothesis 6
(H6)
There is a statistically significant relationship between
repurchase intention and customer satisfaction
Supported
Hypothesis 7
(H7)
There is a statistically significant relationship between
word of mouth and customer satisfaction
Supported
Questionnaire
Online questionnaire for “The impact of service quality on customer satisfaction in Muong
Thanh Hotel, Ha Noi, Viet Nam”
Thank you for participating in an online data collection for my dissertation which is part of my
study in Master Degree in Hospitality, Events and Tourism. You have read and understand the
participation and consent form. You can opt out of completing the form at any time. All data
collected will be processed and kept according to the data protection law. Please complete the
form by filling the provided spaces. Once you have submitted the form you cannot edit.
I ………………….. (name) agree and consent to participate in the research. I have read
and understood the Participants information and Consent form.
Sign ……………..………………………….. Date ………………………..
1. Age
a. Under 18
b. 18-24
c. 25-34
d. 35-44
e. 45-54
f. Above 54
2. Gender
a. Male
b. Female
c. Prefer not to say
3. Nationality
4. Service quality
1 = totally disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = totally agree
Tangible 1 2 3 4 5
The employees had clean, neat
uniforms
The guestroom met my needs
The TV, radio, telephone, A/ C, lights,
and other mechanical equipment were
modern and clean
The food was good
The facilities (health club, pool,
meeting rooms, banquet halls, etc.)
were clean and inviting
Reliability
My reservation was handled efficiently
My guestroom was ready as promised
I received the type of room requested
TV, radio, A/C, lights, and other
mechanical equipment worked properly
The employees did what they said they
would do
Responsiveness
Employees responded promptly to my
requests
Employees were willing to answer my
questions
Employees responded quickly to solve
my problems
Room service was prompt
Check-in and check-out procedures
were fast and efficient
Assurance
Employees were consistently courteous
Employees treated me with respect
Employees were polite when answering
my question
Empathy
I was given personal attention
Employees understood and satisfy my
individual needs
Customer Satisfaction
I will visit Muong Thanh Hotel again
I will recommend the hotel to other
people
References
Atkinson A. (1988). Answering the eternal question: what does the customer want? The Cornell
Hotel and Restaurant Administration Quarterly, 29 (2): 12–14.
Barsky J., and Labagh R. (1992). A strategy for customer satisfaction. The Cornell Hotel and
Restaurant Administration Quarterly 35 (3): 32–40.
Barsky J., and Nash L. (2003). Customer satisfaction: Applying concepts to industry- wide
measures. The Cornell
Hotel and Restaurant Administration Quarterly, 44 (4): 173-183.
Bui, H. T., and Jolliffe, L. (2011). Vietnamese domestic tourism: an investigation of travel
motivations. Austrian Journal of South-East Asian Studies, 4(1), 10-29.
Callan, R. J. (1995). Hotel classification and grading schemes a paradigm of utilisation and user
characteristics. International Journal of Hospitality Management, 14, 271-284
Choi T. Y., and Chou R. (2001). Determinants of hotel guests’ satisfaction and repeat patronage
in Hong Kong hotel industry. International Journal of Hospitality Manag
Choi T. Y., and Chu R. (2001). Determinants of hotel guests’ satisfaction and repeat patronage in
Hong Kong hotel industry. International Journal of Hospitality Management, 20: 277-297.
Getty, J. M., and Thompson, K. N. (1995). The Relationship Between Quality, Satisfaction, and
Recommending Behavior in Lodging Decisions. Journal of Hospitality and Leisure Marketing.
Gronroos, C. (1990). Service Management and Marketing: Managing the Moments of Truth in
Service Competition. Lexington Books.
Hoffman, K. D., and Bateson, J. E. G. (2010). Services Marketing: Concepts, Strategies, and
Cases: Concepts, Strategies, and Cases. Cengage Learning.
International Council (1999). A Guide to College Programs in Culinary Arts, Hospitality, and
Tourism A Directory of CHRIE Member Colleges and Universities. New York, N.Y: Wiley.
Jones D. L., Mak B., and Sim J. (2007). A New Look at the Antecedents and Consequences of
Relationship Quality in the Hotel Service Environment. Services Marketing Quarterly, 28(3): 15-
31.
Kim W. G., Han J. S., and Lee E. (2001). Effects of relationship marketing on repeat purchase
and word of mouth. Journal of Hospitality and Tourism Research, 25 (3): 272-288.
Lai, W. H., and Vinh, N. Q. (2013). How promotional activities and evaluative factors affect
destination loyalty: evidence from international tourists of Vietnam. International Journal of
Marketing Studies, 5(1), 70-85.
Lam T., and Zhang H. (1999). Service quality of travel agents: the case of travel agents in Hong
Kong. Tourism Management, 20: 341–349.
LeBlanc G., and Nguyen N. (1996). An examination of the factors that signal hotel image to
travelers. Journal of Vacation Marketing 3 (1): 32–42.
McCleary K.W., Weaver P.A., and Hutchinson J.C. (1993). Hotel selection factors as they relate
to business travel situations. Journal of Travel Research, 32 (2): 42–48.
Oh H., and Parks, S.C. (1997). Customer satisfaction and service quality: a critical review,of the
literature and,research implications for the hospitality industry. Hospitality, Research Journal, 20
(3): 35–64.
Oppermann M. (1998). Destination Threshold Potential and the Law of Repeat Visitation,
Journal of Travel Research, 37 (2): 131-137.
Parasuraman, A., Zeithaml, V. A., and Berry, L. L. (1988). SERVQUAL: A Multiple-item Scale
for Measuring Consumer Perceptions of Service Quality. Journal of Retailing, 64(1), 12-40.
Pham, H. (2013). Vietnam is a country, not a war-trauma and nostalgia in the anthology The
Perfume River. Creative Industries Journal, 6(1), 17-27.
Rivera, M. A., and Upchurch, R. (2008). The Role of Research in The Hospitality Industry: A
Content Analysis of the IJHM Between 2000 and 2005. International Journal of Hospitality
Management, 27(4), 632-640.
Taylor, S. A., and Baker, T. L. (1994). An Assessment of the Relationship Between Service
Quality and Customer Satisfaction in the Formation of Consumers’ Purchase Intentions. Journal
of Retailing, 70(2), 163-178.
Williams, J. A., Uysal, M., 2003. Introduction. Journal of Quality Assurance in Hospitality and
Tourism, 4(3/4), 1-27.
Wuest B.E.S., Tas R.F., and Emenheiser D.A. (1996). What do mature travelers perceive as
important hotel/ motel customer service?, Hospitality Research Journal, 20 (2): 77–93.
Yen A., and Su L. (2004). Customer satisfaction measurement practice in Taiwan hotels.
Hospitality Management, 23: 397–408.
Zeithaml, V. A. (1987). Defining and Relating Price, Perceived Quality, and Perceived Value.
Marketing Science Institute.