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Although hotels usually have clients from different nationalities, the research analyses the multicultural effects on hotel customers’ satisfaction is still scant. This paper aims to contribute to the realm of hotel management by providing interesting managerial insights into how different nationalities perceive hotel attributes differently using two hotels located in Saint Petersburg as a case study. To that end, a fuzzy hybrid method based on the technique of similarity to ideal solution (FTOPSIS) is proposed. The results are based on a sample of 447 guests and show that: (1) nationality influences the hotel guests’ satisfaction; (2) customers are, in general, more elastic in three-star hotels than in four-star hotels; (3) welcome gifts in the room and in the bathroom are key attributes in the clients’ satisfaction; and (4) Italian and Spanish guests are the least and the most satisfied customers, respectively. The study offers a number of important managerial insights to hotel managers and practitioners. The average figures obtained by general hotel satisfaction surveys usually hinder important peculiarities that need to be addressed when managers develop strategic satisfaction enhancement programmes. In particular, our results show that managers need to adapt the programmes to the differences observed by nationalities.
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administrative
sciences
Article
The Role of Nationality and Hotel Class on Guests’
Satisfaction. A Fuzzy-TOPSIS Approach Applied in
Saint Petersburg
Juan Carlos Martín1, * , Veronika Rudchenko 2and María-Victoria Sánchez-Rebull 3
1Department of Applied Economic Analysis, Institute of Tourism and Sustainable Economic Development,
University of Las Palmas de Gran Canaria, 35017 Las Palmas de Gran Canaria, Spain
2Department of Management, National Research University Higher School of Economics,
Saint-Petersburg 194100, Russia; erudchenko@hse.ru
3Department of Business Management, University Rovira i Virgili, 43204 Reus, Spain;
mariavictoria.sanchez@urv.cat
*Correspondence: jcarlos.martin@ulpgc.es
Received: 24 July 2020; Accepted: 3 September 2020; Published: 5 September 2020


Abstract:
Although hotels usually have clients from dierent nationalities, the research analyses
the multicultural eects on hotel customers’ satisfaction is still scant. This paper aims to contribute
to the realm of hotel management by providing interesting managerial insights into how dierent
nationalities perceive hotel attributes dierently using two hotels located in Saint Petersburg as
a case study. To that end, a fuzzy hybrid method based on the technique of similarity to ideal
solution (FTOPSIS) is proposed. The results are based on a sample of 447 guests and show that:
(1) nationality influences the hotel guests’ satisfaction; (2) customers are, in general, more elastic in
three-star hotels than in four-star hotels; (3) welcome gifts in the room and in the bathroom are key
attributes in the clients’ satisfaction; and (4) Italian and Spanish guests are the least and the most
satisfied customers, respectively. The study oers a number of important managerial insights to
hotel managers and practitioners. The average figures obtained by general hotel satisfaction surveys
usually hinder important peculiarities that need to be addressed when managers develop strategic
satisfaction enhancement programmes. In particular, our results show that managers need to adapt
the programmes to the dierences observed by nationalities.
Keywords:
hotel guests’ satisfaction; guest nationality; multicultural analysis; fuzzy numbers;
TOPSIS; key hotel attributes
1. Introduction
There is an increasing demand for better hotel services, mostly because the customers become
more experienced and expect that the service could satisfy the individual needs. Thus,
hotels are
obliged to produce an adequate level of service according to new customer needs and wishes,
and service
quality and guests’ satisfaction are considered key elements for the survival and success
of the hotels.
Travel behaviour
and preferences could strongly vary among dierent cultural groups
(Kim and Lee 2000)
. In general, Reisinger and Turner (2003) contend that satisfaction in tourism is
determined by material and physical needs and its measurement can be aected by dierent operational
buying motives, and conclude that tourists from dierent countries and culture can experience dierent
levels of satisfaction because the preferences and needs are aected by the culture.
Barsky and Nash (2003) argue that only the enterprises that can adapt rapidly to the changes in
customer needs and preferences can survive in the market. Gundersen et al. (1996) define customer
satisfaction as a post-consumption evaluative judgement concerning a specific product. However,
Adm. Sci. 2020,10, 68; doi:10.3390/admsci10030068 www.mdpi.com/journal/admsci
Adm. Sci. 2020,10, 68 2 of 24
despite many attempts to explain customer satisfaction by dierent authors (Bowen and Clarke 2002;
Kozak 2001;Neal and Gursoy 2008), a uniform definition of customer satisfaction does not exist.
Nevertheless, customer satisfaction is one of the most frequently examined topics in tourism because
it plays an important role in any tourist product or service (Neal and Gursoy 2008). Pizam (1999)
contends that the definition of satisfaction in tourism is more problematic than in other industries
as customers from dierent nationalities and cultures join together during the service provision.
Huang et al. (1996)
contend that guests’ satisfaction depends on dierent personal traits in which
culture is one of the most important ones to be considered. In this sense, cross-cultural dierences
do not only play a key role in tourist attractiveness but do also pose challenges in tourism industry
development
(Kim and McKercher 2011)
. In addition, Sann et al. (2020) find evidence of the existing
gap that still exists in the analysis of whether the relationship between complaints made by hotel guests
with respect to some attributes depend on the guests’ cultural background or the hotel classification.
Nowadays, the research on understanding how cross-cultural consumer behaviour aects
customers’ satisfaction in the hotel industry is more crucial than ever because hotel managers
are usually confronted with dierent cultures and preferences. In the hospitality area,
cross-cultural consumer behaviour and its influence on satisfaction started only around the late
1980s
(Richardson and Crompton 1988)
. More recently, analyses of how culture and language
aect tourists’ judgements in online reviews have been carried out (Alrawadieh and Law 2019;
Cenni and Goethals 2017
;Liu et al. 2017;Sann et al. 2020;Schuckert et al. 2015). De Carlos et al. (2018)
extend the analysis taking also into consideration the country of origin, disentangling the fact that
some tourists might have a second language to express the comments.
The current lodging industry confronts strong competition, and hotels are obliged to delight
their guests as a managerial tool that increases profitability and survival rate (Torres and Kline 2006).
The authors
contend that ‘customer delight’ is a better approach than ‘customer satisfaction’ for
customer relationship management (CRM), so delighting guests is now a priority for management
as satisfying guests might not be enough. The authors show that customer delight is an important
competitive advantage source given that policies based on implementing a culture of exceeding
expectations cannot be easily copied. Thus, hotel managers need to focus on hiring the best talent and
on training the employees to delight the guests adapting the behaviour to what guests might demand.
In this respect, guests’ nationality is a trait that cannot be undermined when hotel statry to excel and
not simply meet guests’ expectations.
Thus, the aim of this paper is to shed some light in the realm of hotel management by providing
interesting managerial insights into how diverse nationalities perceive hotel attributes dierently in
three and four-star hotels located in Saint Petersburg. For this reason, the following research questions
are analysed: (RQ1) Does hotel guests’ satisfaction depend on the guests’ nationality?
(RQ2) Is
the nationality moderating eect on hotel guests’ satisfaction invariant across three- and four-star
hotels? (RQ3) How can hotel managers take into account the results in order to tailor the satisfaction
enhancement programmes in the hotels? Thus, the following preliminary hypotheses are studied:
(H1) Hotel guests’ satisfaction depends on the guest’s nationality; (H2) The nationality moderating
eect on hotel guests’ satisfaction is not uniform across dierent hotel class; and (H3) Hotel managers
need to take into account the observed nationality moderating eect in order to envisage the guests’
satisfaction enhancement programmes.
We start to contextualise the paper with a synthesis of the previous literature on cross-cultural
tourist research with an emphasis on the studies that analyse the eects of guests’ nationality on hotel
satisfaction. Secondly, we present an overview of the questionnaire and the dataset of the case study
which is grounded in two dierent hotels located in Saint Petersburg (Russia). Afterwards,
applying a
hybrid multicriteria method based on fuzzy logic and TOPSIS (FTOPSIS), we present important insights
into how nationality aects the experienced hotel guests’ satisfaction. Finally, at the end of the paper,
we propose some satisfaction enhancement programmes in the respective hotels as an eective way to
satisfy the customers more conveniently.
Adm. Sci. 2020,10, 68 3 of 24
2. Literature Review
Culture could be described as a “blueprint” of human activity that determines behaviours,
preferences and satisfaction in vacation destinations visited (McCracken 1986). The national character
is the core cultural element to divide customers by group to analyse their preferences, needs and
satisfaction (Lenartowicz and Roth 1999). The management of cultural dierences must be investigated
under the context of globalisation and the growth of international enterprises (Wilson 1996).
In the
hotel industry, globalisation is the norm, and it is believed that a gap in customer satisfaction research
exists because culturally diverse customers have dierent expectations and preferences (Emir 2013).
Schuckert et al. (2015) review the relevant literature and find that cultural dierences play a determinant
role in explaining guests’ perception, expectation, emphasis, and complaint toward hotel production,
which are the main factors that conform guests’ satisfaction.
The majority of the studies that analyse the guests’ cultural dierences are mainly based on
primary data and statistical methods such as factor analysis (Chen and Tsai 2019;
Kozak 2001
;
Pizam and Reichel 1996
;Pizam and Sussmann 1995;Selma Ozdipciner et al. 2012), t-tests
(Chen and Tsai 2019
;Pizam and Sussmann 1995;Schuckert et al. 2015), analysis of variance (ANOVA)
(Chen and Tsai 2019;Emir 2013;Pizam and Sussmann 1995;Selma Ozdipciner et al. 2012),
and structural
equation model (SEMs) (Bihamta et al. 2017;Chun et al. 2018;
Reisinger and Turner 2003
;
Turner et al. 2002
). Additionally, as we will analyse below, hotel guests’ satisfaction has also been
studied through hybrid multicriteria decision-making mathematical methods in which Technique for
Order of Preference by Similarity to Ideal Solution (TOPSIS) have been applied jointly with fuzzy logic
or machine learning (Mart
í
n et al. 2018;Nilashi et al. 2019). However, up to now, these methods have
not been applied to study the eects of guests’ cultural dierences.
Most of the analysed studies are usually limited in the number of countries or regional areas
such as Western vs. Eastern regions. Thus, clearly, there is a need to study customer satisfaction
from a cross-cultural perspective as dierent cultural values of customers play a determinant role
(
Bowen and Clarke 2002
;Weiermair 2000). For instance, Ahmed and Krohn (1992) indicate that
American and Japanese cultures are divergent, and, consequently, the behaviour of guests is very
dierent. A similar analysis with a dierent approach was done to identify the dierences between
British and German guests in a group of hotels in Mallorca (Spain) (Kozak 2001),
and between
English and non-English-speaking guests in Hong Kong hotels (Schuckert et al. 2015). Additionally,
significant dierences
were also found between cultures (Australian, USA/Canadian, Japanese,
Mandarin speakers) for dierent levels of satisfaction resulting from the importance emphasis given to
levels of service received in Melbourne (Turner et al. 2002). Williams et al. (1998) characterised the
Western cultures of North America and Europe with less interpersonal orientation, while the Eastern
cultures of Asia with high social bonding. In other words, Asian cultures tend to be collectivist and to
score highly on power distance and long-term orientation, whereas Western cultures mostly reveal
individualism (Hofstede 1991) and are more oriented to uncertainty avoidance and individualism
(Chen 2000).
In the tourism area, the intercultural perspective has also been researched analysing the eect
on some key variables. For example, the tour selection made by Japanese and Korean business
tourists is very dierent from the Australian counterparts. The first group sought suggestions
and information in travel agencies, whereas Aussies preferred to use information from tourist
information oces or the Internet (Hofstede 1991). The perceptions of British tour guides of Japanese,
French, Italian, and American tourists are also very dierent. Japanese tourists were perceived to
be the most distinct regarding the behavioural characteristics (
Pizam and Sussmann 1995
). In this
sense,
the dierences
between English and French-Canadian travellers have also been demonstrated
(
Sussmann and Rashcovsky 1997
). Dierences in the overall satisfaction of Korean and International
tourists visiting South Korean Buddhist temples have also been identified (Chun et al. 2018).
For international
tourists, nature and relaxation are significant antecedents of satisfaction,
while for
Korean tourists, self-growth was an additional key significant driver. Specifically related to Russian
Adm. Sci. 2020,10, 68 4 of 24
Federation, Stepchenkova et al. (2015) analysed cultural dierences in Russia among American
and Korean tourists studying photographs of Russia posted on the net (Flickr and travel blogs).
The photograph
images were categorised into 10 disjoint groups as: People, Nature-Landscape, Place,
Space, Transport and Infrastructure, Activities, Season, Architecture, Heritage, and State Power.
Surprisingly, the authors found that in terms of image content, Americans and Koreans do not show
dierences in only three groups: Nature-Landscape, Activities and Season. In general, culture does
not only aect needs and preferences but societal values, and values of an exciting life and pleasure are
also constructs that aect the formation of travel market segments (Vinson and Munson 1976).
McCracken (1986) analyses how multicultural traits have an influence on the visitors’ preferences
and satisfaction. Dierent nationalities create dierent preferences among customers in tourism
(
Pizam and Reichel 1996
). For example, Zeithaml and Bitner (1996) find that Japanese clients are
the least satisfied with airline in-flight service among international travellers. The hotel industry
in Spanish and Turkish resorts according to cross-cultural dierences of British and German has
also been addressed (Kozak 2001), and the author finds that British visitors are likely to be more
satisfied than Germans for almost all the attributes included in the analysis. Medical tourism is also
analysed in Yu and Ko (2012), and the authors find that Korean and Chinese segments are very dierent
because the first group puts more emphasis on destination attributes whereas the second one shows
more preference for cost levels. Schuckert et al. (2015) find that, in Hong Kong, English speaking
guests rate the hotel attributes higher than non-English speaking guests who tend to be more satisfied
with middle-class hotels. On the other hand, the English speaking segment prefers high-class hotels.
Interestingly, the authors find that high-class hotels tend to be more homogenous in guests’ satisfaction
levels in comparison with low and middle-class hotels. A study conducted in a five-star hotel in
Antalya (Turkey) explored the satisfaction of tourists from six dierent countries (Turkey, Germany,
Russia, the Netherlands, Ukraine, and the United Kingdom) and concluded that satisfaction varies
with respect to nationalities (Emir 2013). Turkish and German customers presented the highest levels
of overall satisfaction, especially in the front oce, housekeeping, and employee services, while Dutch
and Ukrainian guests exhibited the lowest satisfaction levels, especially in F&B, physical facilities,
health/hygiene, customer relations, and other services.
Francesco and Roberta (2019) analyse two main issues regarding cross-country dierences using
online hotel reviews: (1) hotel attributes emphasis (importance); and (2) hotel attributes perception
(performance). The cross-country dierences are also analysed according to the hotel class and tourists’
profiles. The authors find that significant cross-country dierences exist and persist independently of
the hotel class and tourists’ profiles. The hotel class is divided into five categories from one to five
stars, and the tourists’ profiles are also split into five categories, namely, business, couple, friends,
family, and single. The study finds that cleanliness and comfort are more important for Chinese,
restaurants are
more important for Italians and stacompetence, and sports facilities and quietness
are more important for Americans. Regarding the attributes’ perception, cleanliness and quietness are
more positively perceived by Americans, restaurants by Chinese and Internet and location by Italians.
On the other hand, quietness, service attitude and service competence are perceived more negatively
by Chinese and comfort and restaurants by Italians.
Yuksel et al. (2006) use for the first time the concept of nationality to analyse the complaining
attitudes and behaviour of tourists from the UK, the Netherlands, Israel, and Turkey. The authors
show that the complaining dissimilarities between them are more significant than ex-ante guests’
attitudes toward complaining. Regarding the attitudes, the dierences are only observed in two
items.
For example
, the authors find that compared to Western tourists, Turkish tourists who are less
individualist than the rest of the nationalities analysed may feel sad when they have to complain.
The authors
conclude that as Turkey can be seen as a moderate collectivist and feminine society,
and caring
for others has a positive value, Turkish tourists may anticipate that their complaint might
create problems for some employees. On the other hand, regarding the complaining behaviour,
dierences are seen in six items from which voicing the satisfaction to the sta, demanding the
Adm. Sci. 2020,10, 68 5 of 24
intervention of a manager, and writing a letter of complaint to the headquarters are especially relevant.
More recently, Sann et al. (2020) investigate online complaining behaviour with respect to six hotel
attributes (service, cleanliness, room, sleep quality, location, and value) in 353 hotels using 2020
complaining reviews that represent five continents and 63 nationalities. The authors find that Asian
guests are more likely to complain about service, while non-Asian guests complain more likely about
cleanliness, room, sleep quality, and location. Regarding the class of the hotels, the authors also
find dierent complaining behaviour in which high-class hotels are characterised by receiving more
complaints about service and value than medium-class hotels.
3. Questionnaire and Data
The data was collected via a questionnaire that is considered a normal procedure in the literature
of hospitality satisfaction (Armstrong et al. 1997;Gundersen et al. 1996;Kozak 2001). The survey was
administered from September 2014 to June 2016 in two hotels located in Saint Petersburg that have
a dierent class category, three- and four-star hotels, respectively. These two hotels were selected
by availability reasons as hotel managers gave us permission to administer the survey on the hotel
premises. The four-star hotel built in 2005 is relatively modern and it is located in the new district of
the city. It has 251 rooms and 160 employees worked in the hotel during the survey administration.
The three-star
hotel is located in the district centre near the main historical attractions of the city.
This hotel can be considered a medium-size hotel with 164 rooms.
Saint Petersburg in Russia was selected for being a paradigmatic case study within the object
of our investigation. First of all, it is a convenient city to analyse the multicultural aspects of hotel
guests’ satisfaction as it is jointly with Moscow the most visited cities by international tourists in
Russia. In fact, 7.2 million tourists (half of them international) visited the city in 2017, an increase of
4.3% with respect to 2016 (St. Petersburg Travel Guide 2020). Secondly, it has a border location with
other countries that facilitate the arrival of tourists from dierent countries. Thirdly, Saint Petersburg
was a place for the world football championship of 2018 that also influenced the city’s importance as
a world tourist destination. And finally, hotel guests’ satisfaction is still under-researched in Russia
(Martín et al. 2018).
The questionnaire was designed after a deep literature review over customer satisfaction in tourism,
putting emphasis on the hotel industry (Chand 2010;Choi and Chu 2001;
Dominici and Guzzo 2010
;
Lee et al. 2014;Markovi´c and Jankovi´c 2013;Matzler et al. 2006;Zhou et al. 2014). The literature review
was used to set a comprehensive list of 32 attributes that proxy the hotel guests’ satisfaction.
The questionnaire of four pages in length was written in Russian and translated into English in
order to facilitate the administration to international tourists who do not speak Russian. A four-point
semantic-type scale was used to measure the guests’ satisfaction over all the attributes included
in the questionnaire. The Likert scale, developed by Andrews and Withey (1976) and applied by
Bitner and Hubbert
(1994), is a suitable method to compile information about guests’ satisfaction.
During the questionnaire design and following Dolnicar (2013), it was decided to use a four-point
semantic scale to measure the perception for each of the attributes included in the scale (bad =‘1’;
fair =‘2’;
good =‘3’; very good =‘4’) as the inclusion of a neutral midpoint usually incorporates
‘evasion’ responses, and for that reason, the answer format scale was preferred to other common scales
of five and seven points.
The questionnaire was initially reviewed by a professional group that consisted of the general
managers of hotels and professors of universities in the field of tourism. During the focus group issues
regarding the wording for the questions, the semantic scale and the labels were discussed. Finally,
the questionnaire consisted of 62 questions distributed into five sections. The first part consisted of
respondents’ basic demographic profiles. In our study, the eects of guests’ nationality are the main
object of interest; so, the nationality of each respondent was asked. The following parts contained
questions concerning facilities of the hotels, satisfaction, expectation and fulfilment levels over the
services provided by the hotels.
Adm. Sci. 2020,10, 68 6 of 24
A pilot study involving 30 questionnaires was conducted on the premises of the selected
hotels. After the pilot study, it was decided that the survey could be given in the hotel premises
with the respondent’s compromise of filling the survey and leaving it at the hotel’s reception.
Questionnaires were
distributed to tourists personally by one of the authors of the study and by
the hotels’ managers. The tourists who lodged in the selected hotels older than 18 years old were
the objective target of the survey. In total, 447 complete questionnaires were finally obtained and
considered valid for data analysis (58% in the four-star hotel).
Table 1shows that, in general, among respondents, there are more males (52%) than females (48%).
In terms of age, there are five general categories, where the most representative group is
46–55 years
(46%), and the least representative group is 26–35 years old (2.5%). In total, 73% of the guests
indicate business as the main purpose of the visit. With respect to the respondent’s origin,
the more
representative nationalities are Chinese (19.5%) and Russians (19.2%), respectively.
Chinese visited
Saint Petersburg because 2017 was the year of China in Russia, and, more importantly, because a
simplified visa regime between Russia and China was established in 2014. Apart from these two
countries, the USA also plays a dominant position among international visitors (11.9%) and France is
the leading country in the EU (7%).
Table 1. Guests’ profile (source: compiled by authors).
Variables Frequency
Three-Star Hotel %Frequency
Four-Star Hotel %Frequency
Total %
Gender
Male 84 44.44 149 57.75 233 52.13
Female 105 55.55 109 42.25 214 47.87
Age
Under 25
years 0 0 0 0 0 0
26–35 years 7 3.70 4 1.55 11 2.46
36–45 years 33 17.46 75 29.07 108 24.16
46–55 years 63 33.33 130 50.39 193 43.18
56–65 years 52 27.51 33 12.79 85 19.02
Over 65
years 34 17.99 16 6.20 50 11.19
Nationality
China 15 7.94 72 27.91 87 19.46
Russia 42 22.22 44 17.05 86 19.24
USA 17 8.99 36 13.95 53 11.86
France 15 7.94 17 6.59 32 7.16
Italy 5 2.65 13 5.04 18 4.03
UK 6 3.17 11 4.26 17 3.80
Spain 5 2.65 12 4.65 17 3.80
Other 84 44.44 53 20.54 137 30.65
Purpose of the trip
Holidays 92 48.68 29 11.24 121 27.07
Business 97 51.32 229 88.76 326 72.93
4. Methodology
In this paper, a hybrid method based on fuzzy logic and the technique of similarity to ideal solution
FTOPSIS is applied to calculate a synthetic satisfaction indicator on the selected hotels.
This method
is
gaining popularity to measure service quality, risk assessments, or satisfaction in dierent research
fields like for example: (1) hotels (Ban et al. 2016;Benitez et al. 2007;Mart
í
n and Rom
á
n 2017);
(2) e-retailers
(Yue and Yue 2018;Zhu et al. 2013); (3) railroads (Aydin 2017;Tang et al. 2017); (4) banks
Adm. Sci. 2020,10, 68 7 of 24
(Hosseini and Keshavarz 2017;Morsaghian et al. 2015); (5) events (Mart
í
n et al. 2017a,2017b); (6) tourist
destinations (Martín et al. 2019b); and (7) airlines (Deveci et al. 2018).
FTOPSIS techniques have been developed after the introduction of fuzzy logic (
Zadeh 1965
,
1973) as well-adjusted tools to handle distinct decision-making processes. Researchers find these
methods very appealing when customers make choices aected by multiple attributes that feature
both qualitative and quantitative aspects. Thus, the measurement of synthetic hotel guests’ satisfaction
indicators using the information provided by the survey is possible.
The Likert scales based on linguistic and semantic terms are more suitable to better approximate
the style of human thinking. It is usually dicult to express a judgement about any attribute in
the hotel as a single numeric value (crisp information). As a result, the fuzzy methods have been
largely developed and applied to resolve dierent problems. Fuzzy methods capture the essence of the
human’s ambiguity judgement that deals with multidimensional attributes (Chang 1996).
In this study, we follow the approach employed by Mart
í
n and Rom
á
n(2017) and
Martín et al. (2019a)
where triangular fuzzy numbers (TFNs) are employed to represent each of
the linguistic terms answered by the respondents. The steps of the method can be synthesised as
follows: (1) The raw information matrix is represented by a segment TFN information matrix; (2) The
matrix obtained in the first step is clarified; (3) The ideal solutions are obtained applying TOPSIS to
the obtained matrix in step 2; (4) The synthetic satisfaction indicators are obtained for each segment;
and (5) the elasticity of the satisfaction is obtained for each segment with respect to all the attributes
included in the scale of guests’ satisfaction.
Table 2shows how each linguistic term in the semantic scale is represented by a TFN.
The definition
of the TFNs, the membership function, and the fuzzy algebraic operations can be consulted in other
technical papers. It can be seen that the extreme points degenerated at the beginning and end of the
0–100 interval, and that the length of the range is 50 when the satisfaction is bad and 30 when the
satisfaction is very good. Thus, the researchers assume that the uncertainty associated is higher in the
inferior extreme of satisfaction than in the superior extreme. The range of the other two triangular
fuzzy numbers is equal to 40, a figure between the other two cases, and the intervals are centred
symmetrically on the most likely values 50 and 70, respectively. The segmentation analysis is based on
the algebra of the TFNs (Buckley 1985), and the average value for each segment is obtained as:
e
A=(a1,a2,a3)=1
ne
A1e
A2⊕ · · · e
An=
n
P
i=1a(i)
1,n
P
i=1a(i)
2,n
P
i=1a(i)
3
n
(1)
where
e
Ai
is a TFN,
is the external operator of a scalar and a fuzzy number, and
is the sum
operator of fuzzy numbers. The algebra of fuzzy numbers guarantees that
e
A
, the average value of
the pair observation-attribute (hotel-attribute) over a segment of interest, nationalities, or any other
sociodemographic segment, is also a TFN.
Table 2. Triangular fuzzy numbers (TFNs). Representatives of the semantic scale (source: authors’ elaboration).
Linguistic Term TFNs
Bad (0, 0, 50)
Fair (30, 50, 70)
Good (50, 70, 90)
Very good (70, 100, 100)
The second step serves to clarify the information obtained in the first step. Analogously to other
studies, we clarify the information through the average neutral value
ve
A=(a1+2a2+a3)/
4 that was
Adm. Sci. 2020,10, 68 8 of 24
proposed by Chen (1996). This method presents a number of advantages over other more sophisticated
methods as for example the simplicity and the absence of any prior requirement made by researchers
about pessimism or optimism (Martín et al. 2017a).
The third step obtains the ideal solutions following the logic that the positive ideal solution is the
one that maximises all the criteria associated with benefit and minimises all the criteria associated with
cost, that is, for each attribute iand all the observed guests’ segments j, a vector of is obtained with the
best-observed satisfaction. Similarly, the ideal negative solution is obtained with the opposite logic.
Thus, the ideal solutions are computed as:
PIS =nmaxVi jj=1, · · · ,n,i=1, 2, . . . ,mo(2)
NIS =nminVi jj=1, · · · ,n,i=1, 2, · · · ,mo(3)
PIS and NIS are then vectors defined by the number of attributes included in the satisfaction scale.
The fourth step is now straightforward as the relative distance of each observation determined by
each segment is now obtained with respect to the obtained ideal solutions by applying the TOPSIS
method (Hwang and Yoon 1981;Zeleny 1998). Now, similarly to other ranking problems that appear
in social science, the satisfaction of each of the segments can be evaluated and ranked according to the
synthetic satisfaction indicator obtained by the application of TOPSIS. Thus, the segment iwould be
more satisfied than the segment jwhen the synthetic indicator of the i-observation is greater than the
synthetic indicator of the j-observation. The ranking of all the segments according to the experienced
satisfaction is now possible by comparing the synthetic satisfaction indicator obtained by TOPSIS.
Mathematically, the synthetic satisfaction index SAT for each segment jis determined as follows:
S+
j=dist(Vj,PIS) = v
tm
X
i=1Vij PISi2j=1, · · · ,n(4)
S
j=dist(Vj,NIS) = v
tm
X
i=1Vij NISi2j=1, · · · ,n(5)
SATj=
S
j
S+
j+S
j
j=1, · · · ,n(6)
The above equations show that the synthetic indicator of guests’ hotel satisfaction depends on the
distance of each observed segment with respect to the ideal solutions, and how far each observation is
from the negative ideal solution. Equation (6) can be used to obtain the satisfaction that each segment
experiences. This approach has been used in other hotel studies (Benitez et al. 2007;Fu et al. 2011;
Martín and Román 2017;Stylos and Vassiliadis 2015).
Finally, the fifth step consists of the analysis of critical success factors that can be performed
by obtaining the elasticity of SAT with respect to each attribute for particular segments of interest.
The elasticity
value measures how SAT varies when each of the attributes considered in the analysis
changes infinitesimally. The elasticity is usually understood or defined as the percentage change
variation. In mathematical notation, the elasticity can be calculated for each segment j, and each
satisfaction attribute ias:
ηij =
%SATj
%Vij
=dSATj
dVij
Vij
SATj
(7)
Hotel managers can use the elasticity values for each of the segments to deploy individual
management programmes that enhance the guests’ satisfaction for each particular segment.
The knowledge
of the critical attributes is crucial to plan adequate strategies in the hotel that align the
triad satisfaction, loyalty, and long-term sustainability. In the current study, we show that these values
Adm. Sci. 2020,10, 68 9 of 24
depend on the nationality and hotel selection, so the programmes need to be individually adapted to
these circumstances.
5. Results
For the ease of exposition, we omit here the results of the first two steps of the method in which
the individual information matrix based on the semantic scale is converted to a clarified segment
information matrix. Thus, we start the analysis of the results with the third step in which the ideal
solutions are obtained. Table A1 shows the positive and negative ideal solutions and percentage
variation for the 32 attributes of satisfaction. This table is very useful for hotel managers in order to
know which attributes generate more or less satisfaction to guests, and which attributes are more or
less homogeneous.
According to the obtained results for both hotels, it can be seen that there is more homogeneity
in the four-star hotel. It is also remarkable that all the attributes with the exception of two attributes
related with the welcome gifts show a negative value higher than 50, that is, even in this least satisfied
segment, the performance is not perceived very negatively. In some of the attributes, it can be seen that
there exist some segments that evaluate the attribute at the maximum and minimum level, and this
case is characterised by presenting the highest heterogeneity. Hotel managers need to evaluate whether
this case is rooted in very dierent guests’ preferences or by real dierences in service performance.
It is also remarkable that in the four-star hotel, a particular segment (“accommodation”—breakfast
is not included) can be distinguished as the most repeated segment that evaluates negatively most
of the attributes for the negative ideal solution. In this case, hotel managers need to further explore
what causes can underpin this apparently hidden behaviour. It can be inferred that some guests can
be very disappointed if they primarily think that they have paid a fee to have the breakfast included.
For example
,Lu and Zhu (2006), analysing the Chinese domestic market, find that the area of Food
and Beverage is not considered important in particular hotel rating standards because the majority of
the guests are not often using the service, and that this is especially relevant in the case that most of the
hotels do not oer complimentary breakfast or include it in the room rate. Unfortunately, in our study,
this idea could not be finally tested.
Regarding the three-star hotel, there are 10 attributes that present the highest potential level of
percentage variation, so are more heterogeneous. The attributes in this set are drinks, quietness in
the room, room and hotel security, furniture/decoration in restaurants and bars, view from the hotel
room, hotel location (closeness to the city centre), easy reservation, and attentiveness of the front desk
clerk. In the three-star hotel, we find some other attributes with an intermediate level of homogeneity
in terms of satisfaction such as room furniture and hotel decoration and design. These results are
similar to those obtained by Schuckert et al. (2015) in which the authors show that the satisfaction
dierence is also influenced by hotel class, and lower class hotels show much bigger satisfaction
dierences than high-class hotels. Normally, guests’ satisfaction is more homogeneous in luxury hotels,
whereas middle or low-class hotels usually exhibit more varied opinions.
Analysing now the observed segments in the ideal solutions, it can be seen that some relevant
segments of the NIS are characterised by ‘I would not visit this hotel for sure’ and those who paid
a very high price (‘Price 501–750 euros’). The idea of the existing relationship between satisfaction
and loyalty and value for money has been explored by dierent authors (Cheng and Abdul 2013;
Jani and Han 2014
). The studies find that unsatisfied guests do not recommend the hotel to friends or
relatives and they do not visit the hotel again.
Moving on now to the results obtained in the fourth step—the satisfaction synthetic index, it can
be seen (Figures 1and 2) that nationality plays a moderating eect on the guests’ experienced level
of satisfaction. This result needs to be taken into account by hotel managers as they usually have
guests from dierent nationalities. Figure 1shows that Italian, British, and Chinese guests are the least
satisfied in the three-star hotel. Meanwhile, guests from the UK are the least satisfied in the four-star
hotel (Figure 2). Other studies have already analysed this topic. For example, Matzler et al. (2006) find
Adm. Sci. 2020,10, 68 10 of 24
that hotel guests’ satisfaction relationship is strongly moderated by the guests’ nationality, and they
conclude that cross-cultural dierences should be taken into account by hotel managers. Interestingly,
the authors analyse the cross-cultural dierences between Austrian and German guests who can be
seen as closer cultures than those analysed in this study. Another interesting study analyses the main
dierences between domestic and foreign markets in China (Liu et al. 2017). The authors find that
Chinese guests are more familiar with the local culture, language, and living environment in China,
so this causes a dual eect between being less demanding for service and more demanding for hotel
room characteristics and design. In our case, this issue will be discussed further with the help of
the elasticities.
Adm. Sci. 2020, 10, x FOR PEER REVIEW 10 of 23
Figure 1. Guests’ satisfaction index by nationality in the three-star hotel.
Figure 2. Guests’ satisfaction index by nationality in the four-star hotel.
This section ends with the fifth step of the method—the analysis of the elasticity values (Tables
A2 and A3). As explained above, the elasticity values show the percentage variation of SAT by total
and some nationality segments with respect to a 1% variation in each of the attributes included in the
analysis.
Thus, the attributes could be split according to what extent the overall guests’ satisfaction is
more or less elastic with respect to changes in each attribute. This information will provide very
important insights to hotel managers in order to design programmes that enhance the overall guests’
satisfaction.
Tables A2 and A3 inform about which attributes have more or less influence on guest satisfaction
for the two hotels. As said, this information is crucial to hotel managers in order to decide the best
actions they have to implement in order to improve the level of satisfaction of the guests. As we first
can observe, for all attributes, guests’ satisfaction is quite inelastic in the two hotels. Nevertheless, the
results for the three-star hotel show that all the segments are usually less elastic with respect to the
0.709
0.755
0.656
0.755
0.775
0.708
0.752 0.751
0.580
0.600
0.620
0.640
0.660
0.680
0.700
0.720
0.740
0.760
0.780
0.800
China France Italy Russia Spain UK USA Other
Guests' satisfaction index
Nationality
SAT 3 stars hotel
0.968
0.960
0.945
0.964
0.972
0.921
0.958
0.963
0.890
0.900
0.910
0.920
0.930
0.940
0.950
0.960
0.970
0.980
China France Italy Russia Spain UK USA Other
Guests' satisfaction index
Nationality
SAT Four-star hotel
Figure 1. Guests’ satisfaction index by nationality in the three-star hotel.
Adm. Sci. 2020, 10, x FOR PEER REVIEW 10 of 23
Figure 1. Guests’ satisfaction index by nationality in the three-star hotel.
Figure 2. Guests’ satisfaction index by nationality in the four-star hotel.
This section ends with the fifth step of the method—the analysis of the elasticity values (Tables
A2 and A3). As explained above, the elasticity values show the percentage variation of SAT by total
and some nationality segments with respect to a 1% variation in each of the attributes included in the
analysis.
Thus, the attributes could be split according to what extent the overall guests’ satisfaction is
more or less elastic with respect to changes in each attribute. This information will provide very
important insights to hotel managers in order to design programmes that enhance the overall guests’
satisfaction.
Tables A2 and A3 inform about which attributes have more or less influence on guest satisfaction
for the two hotels. As said, this information is crucial to hotel managers in order to decide the best
actions they have to implement in order to improve the level of satisfaction of the guests. As we first
can observe, for all attributes, guests’ satisfaction is quite inelastic in the two hotels. Nevertheless, the
results for the three-star hotel show that all the segments are usually less elastic with respect to the
0.709
0.755
0.656
0.755
0.775
0.708
0.752 0.751
0.580
0.600
0.620
0.640
0.660
0.680
0.700
0.720
0.740
0.760
0.780
0.800
China France Italy Russia Spain UK USA Other
Guests' satisfaction index
Nationality
SAT 3 stars hotel
0.968
0.960
0.945
0.964
0.972
0.921
0.958
0.963
0.890
0.900
0.910
0.920
0.930
0.940
0.950
0.960
0.970
0.980
China France Italy Russia Spain UK USA Other
Guests' satisfaction index
Nationality
SAT Four-star hotel
Figure 2. Guests’ satisfaction index by nationality in the four-star hotel.
This section ends with the fifth step of the method—the analysis of the elasticity values (Tables A2
and A3). As explained above, the elasticity values show the percentage variation of SAT by total
Adm. Sci. 2020,10, 68 11 of 24
and some nationality segments with respect to a 1% variation in each of the attributes included in
the analysis.
Thus, the attributes could be split according to what extent the overall guests’ satisfaction is more
or less elastic with respect to changes in each attribute. This information will provide very important
insights to hotel managers in order to design programmes that enhance the overall guests’ satisfaction.
Tables A2 and A3 inform about which attributes have more or less influence on guest satisfaction
for the two hotels. As said, this information is crucial to hotel managers in order to decide the best
actions they have to implement in order to improve the level of satisfaction of the guests. As we first
can observe, for all attributes, guests’ satisfaction is quite inelastic in the two hotels. Nevertheless,
the results
for the three-star hotel show that all the segments are usually less elastic with respect to the
majority of the attributes than for the four-star hotel. This result is not surprising for what has already
been mentioned above about the eects of hotel class on guests’ satisfaction.
Table A2 shows that the most elastic values in the three-star hotel are observed in the following
attributes (in parenthesis the respective nationalities are shown): Welcome gifts in the hotel room
(Spanish, Russian, and other nationalities); Attentiveness of front desk (French); Welcome gifts in the
bathroom (Russians and Americans). On the other hand, analysing now the most inelastic values,
we obtain
the following results: Attentiveness of front desk (Spanish); Restaurant a la cart (Spanish and
British); Information and Signs (French and Russians); Front desk facilities (Russians); Breakfast in the
restaurant (British); Easy reservation (Russians and Chinese); Front desk service (check-in) (Russians).
These results show that for the three-star hotel, it seems that SAT is more elastic with respect to
some tangibles and is more inelastic with respect to services. It is especially important to the obtained
result for the welcome gifts in the hotel room. This result is partly concordant with (Arin et al. 2005),
where the authors find that “presentation of appreciation token such as welcoming drinks or gifts
upon checking-in at the counter is one of the hotel hospitality ways to create surprise and excitement
. . .
guests would be able to experience the warm welcoming even more if the hotel stawalk or guide
them to their rooms upon check-in at the lobby” (p. 196). The cross-cultural dierences can also be
clearly explained with the results obtained for the attribute “Attentiveness of front desk”, as SAT is
very inelastic for Spanish guests and highly elastic for French clients. Thus, it becomes clear that
the design of satisfaction enhancement programmes should be tailored having in mind that dierent
nationalities’ preferences are dierent.
Doing the same analysis for Table A3, it can be concluded that the most elastic values for the
four-star hotel are obtained for the following attributes and nationalities: Accessibility (Spanish,
Russians, Americans, and Chinese); Welcome gifts in the room, and Welcome gifts in the bathroom
(Italians and Americans). On the other hand, we find that the most inelastic values are obtained for the
majority of the attributes for the British segment (19 attributes out of 32). This is an interesting result
that should be addressed in more depth in the future. The result of accessibility is interesting as the
four-star hotel is located in a modern district of Saint Petersburg which is not conveniently located to
visit the main attractions of the historical city centre. De Oliveira and Glauber (2016) finds that the most
important attributes in the hotel industry are cleanliness, location, and facilities.
Li and Ryan (2020)
find that location in medium-class hotels acts as an excitement factor for international guests, and a
performance factor for domestic guests, while for high-class hotels, location is a performance factor for
all the guests. On the other hand, Sann et al. (2020) find that the rating of location is the highest of the
six attributes under analysis, and conclude that guests have a high level of satisfaction with respect to
the location of the hotels in comparison with the rest of the attributes. It is interesting to have in mind
that these results can be considered as average results for 404 TripAdvisor listed British hotels which
present at least 20 negative reviews.
According to the results, the managers of both hotels have a very dierent pattern of possible
strategies that increase the guests’ satisfaction in the hotels. In the case of the three-star hotel,
managers should
analyse a policy of incorporating welcome gifts in the room and in the bathroom,
or even
they can substitute this for a less ambitious programme like, for example, inviting the guests
Adm. Sci. 2020,10, 68 12 of 24
to a drink during the check-in (Arin et al. 2005). Nevertheless, another interesting policy that could
be introduced at a very low cost is related to paying more attention to the attentiveness of the front
desk especially when French guests come. For example, according to Smith (1994), hospitality is
an expression of welcome by local residents to tourists who visit a particular destination. In the
hotel contextualisation, the ritual of welcoming could be personally conducted according to each
nationality giving some sort of appreciation between each nationality and the history of Saint Petersburg.
For example
, the hotel stacould recognise the intense links that exist between French history and
the development of the Enlightenment period in Saint Petersburg. Meanwhile, the managers in the
four-star hotel need to make further research regarding accessibility.
6. Conclusions
Tourism is one of the main industries in the modern economy of each country, and hospitality
plays a critical role in tourism. Consequently, the increase in guest satisfaction in hospitality might
determine the competitiveness of tourist destinations. Understanding tourists’ levels of satisfaction is
an essential point to hospitality managers for improving services, eectively promoting and creating
the repetition of visits of guests. A hotel has to commit to a great deal of resources and eort to satisfy
customers from dierent nationalities. If hotel managers are not well aware that nationalities play a
determinant role in the design of satisfaction enhancement programmes, multiple problems could be
present at the time of implementing them.
Our study oers very interesting practical assistance for hotel managers and other stakeholders in
the hotel industry, as well as researchers in academia. One of the many interesting insights developed
in the study is related to the importance of segmenting hotel guests in terms of nationality when
studying the preferences and satisfaction in the hotel industry. The literature on this topic is still scarce
as other types of segmentation based on gender and age have been usually more common in previous
studies. Our findings indicate that the dierences in the preferences of the segments under analysis are
not negligible, and that the hotel class also determines important observed peculiarities.
Analysing the ideal solutions, it can be easily inferred that nationality is going to play a moderating
eect on the level of guests’ satisfaction because in some attributes the representative segment for some
components of the PIS vector is based on some nationality. The SAT synthetic indicator shows that
Italian and Chinese guests are substantially less satisfied in the three-star hotel than in the four-star
hotel, so it can be concluded that the moderating eect of the nationality is not uniform in all the
hotel categories. Finally, SAT is more elastic with respect to the attributes related to the welcome gifts,
and the location in the four-star hotel.
The study oers a number of important managerial insights to hotel managers and practitioners.
We have highlighted that the hotel is better perceived by some nationalities than others. It is true
and a general fashion that hotel managers use the satisfaction surveys to analyse overall average
marks,
and this
approach hinders important dierences observed when the analysis considers guests’
heterogeneity accrued by nationality. In this regard, we show that the guests’ segmentation by,
for example
, the nationality may leverage more detailed and precise information on the peculiarities of
specific hotel guests’ preferences. Thus, it is clear that to increase the levels of satisfaction experienced
by guests, the associated strategies need to take into account the dierences observed by nationalities,
and hotel
managers should make an eort in developing adequate and specific satisfaction enhancement
programmes for individual nationalities.
It is important to note that this study uses a hybrid fuzzy-TOPSIS model to analyse hotel guests’
satisfaction on the base of 32 attributes through a survey of 447 guests in two hotels located in Saint
Petersburg. However, this study also presents some limitations. Firstly, due to time and resource
limitations, the researchers could only take one representative hotel of the group of three- and four-star
hotels in Saint Petersburg (Russia), so we recognise that our results are neither generalisable to other
hotels nor to other destinations that can greatly dier from Saint Petersburg. Secondly, the survey
instrument used in this study was originally designed only in Russian and in English, and many guests
Adm. Sci. 2020,10, 68 13 of 24
are neither English nor Russian native speakers, so it is not easy to arm that respondents similarly
understood the wording of the questions. This is especially relevant because it might be possible that
French or Spanish guests who cannot fill the questionnaire in English also hinder some dierences.
Thirdly, the dierent education, economic, cultural and social levels of responders also could influence
the answers. Fourthly, other important issues related to some unexplored results of the ideal solutions
such as value for money will need further attention in the future. Liu et al. (2017) find that there exists
an important interaction between expectation and demands for a given value for money that is when
guests perceive a high value for money the expectations are fulfilled and the guests are less harsh with
the service demands. The authors conclude that the results are very likely to be generalisable to all
hotel guests.
Other important extensions for future research are more related to the type of accommodation
that has been used in the study. In this sense, it is dicult to anticipate whether the results can also be
generalisable in luxurious five-star hotels, where a priori more homogeneous standard levels exist.
New lines for future research can also be based on the analysis of the interaction of the nationalities with
other segmentation variables like previous visits, length of stay, and type of accommodation. In any
case, similarly to Moro et al. (2020), we arm that, even in a globalised world, hotels need to carefully
balance between a uniform production plan and adaptations to specific nationalities’ preferences.
Author Contributions:
Survey administration and data curation, V.R. The authors have contributed equally in
the research design and development, the data analysis, and the writing of the paper. All authors have read and
agreed to the published version of the manuscript.
Funding: This research received no external funding.
Acknowledgments:
We acknowledge the hotel managers who gave us permission to administer the survey at the
hotel premises and help us in collecting the filled questionnaires. The help support of other colleagues at our
universities during the phase of the questionnaire design is also acknowledged.
Conflicts of Interest: The authors declare no conflict of interest.
Adm. Sci. 2020,10, 68 21 of 24
References
Ahmed, Zafar U., and Franklin B. Krohn. 1992. Understanding the unique consumer behavior of Japanese tourists.
Journal of Travel & Tourism Marketing 1: 73–86. [CrossRef]
Alrawadieh, Zaid, and Rob Law. 2019. Determinants of hotel guests’ satisfaction from the perspective of online
hotel reviewers. International Journal of Culture, Tourism and Hospitality Research 13: 84–97. [CrossRef]
Andrews, Frank M., and Stephen B. Withey. 1976. Social Indicators of Well-Being: American’s Perceptions of Life
Quality. New York: Plenum Press.
Arin, Muhammad A.K., Ahmad Azmi M., and Atefeh Maghzi. 2005. A preliminary study on customer
expectations of hotel hospitality: Influences of personal and hotel factors. International Journal of
Hospitality Management 31: 191–98. [CrossRef]
Armstrong, Robert W., Connie Mok, and Allan C.K. Chan. 1997. The importance of cross-cultural
expectations in the measurement of service quality perceptions in the hotel industry. International Journal of
Hospitality Management 16: 181–90. [CrossRef]
Aydin, Nezir. 2017. A fuzzy-based multi-dimensional and multi-period service quality evaluation outline for rail
transit systems. Transport Policy 55: 87–98. [CrossRef]
Ban, Olimpia-Iuliana, Tara Ioan Gheorghe, Bogdan Victoria, Tu¸se Delia, and Simona Gabriela Bologa. 2016.
Evaluation of hotel quality attribute importance through fuzzy correlation coecient. Technological and
Economic Development of Economy 22: 471–92. [CrossRef]
Barsky, Jonathan D., and Leonard Nash. 2003. Customer satisfaction: Applying concepts to industry- wide
measures. The Cornell Hotel and Restaurant Administration Quarterly 44: 173–83. [CrossRef]
Benitez, Juan Manuel, Juan Carlos Mart
í
n, and Concepcion Rom
á
n. 2007. Using fuzzy number for measuring
quality of service in the hotel industry. Tourism Management 28: 544–55. [CrossRef]
Bihamta, Hassan, Jayashree Sreenivasan, Rezaei Sajad, Okomus Fevzi, and Roya Rahimi. 2017. Dual pillars of
hotel restaurant food quality satisfaction and brand loyalty. British Food Journal 119: 2597–609. [CrossRef]
Bitner, Mary Jo, and Amy R. Hubbert. 1994. Encounter satisfaction versus overall satisfaction versus quality:
The customer’s
voice. In Service Quality: New Directions in Theory and Practice. Edited by Roland T. Rust and
Richard L. Oliver. Thousand Oaks: Sage, pp. 72–94.
Bowen, David, and Jackie Clarke. 2002. Reflections on tourist satisfaction research: Past, present and future.
Journal of Vacation Marketing 8: 297–308. [CrossRef]
Buckley, James J. 1985. Ranking alternatives. Using fuzzy numbers. Fuzzy Sets and Systems 15: 21–31. [CrossRef]
Cenni, Irene, and Patrick Goethals. 2017. Negative hotel reviews on TripAdvisor: A cross-linguistic analysis.
Discourse, Context & Media 16: 22–30. [CrossRef]
Chand, Mohinder. 2010. The impact of HRM practices on service quality, customer satisfaction and performance
in the Indian hotel industry. The International Journal of Human Resource Management 21: 551–66. [CrossRef]
Chang, Da-Yong. 1996. Applications of the extent analysis method on fuzzy AHP. European Journal of
Operational Research 95: 649–55. [CrossRef]
Chen, Shyi-Ming. 1996. Evaluating weapon systems using fuzzy arithmetic operations. Fuzzy Sets and Systems 77:
265–76. [CrossRef]
Chen, Joseph S. 2000. Cross-cultural dierences in travel information acquisition among tourists from three
Pacific-rim countries. Journal of Hospitality & Tourism Research 24: 239–51. [CrossRef]
Chen, Chien-Min, and Tsung-Hsein Tsai. 2019. Tourist motivations in relation to a battlefield: A case study of
Kinmen. Tourism Geographies 21: 78–101. [CrossRef]
Cheng, Boon-Liat, and Abdul. 2013. Service Quality and the Mediating Eect of Corporate Image on the
Relationship between Customer Satisfaction and Customer Loyalty in the Malaysian Hotel Industry.
Gadjah Mada International Journal of Business 15: 99–112. [CrossRef]
Choi, Tat Y. Choi, and Raymond Chu. 2001. Determinants of hotel guests’ satisfaction and repeat patronage in the
Hong Kong hotel industry. International Journal of Hospitality Management 20: 277–97. [CrossRef]
Chun, Byunggil, Eugene Y. Roh, Samuel A. Spralls, and Youngjoong Kim. 2018. Predictors of Templestay
Satisfaction: A Comparaison between Korean and International Participants. Leisure Sciences 40: 423–41.
[CrossRef]
Adm. Sci. 2020,10, 68 22 of 24
De Carlos, Pablo, Al
é
n Elisa, P
é
rez-Gonz
á
lez Ana, and Beatriz Figueroa. 2018. Cultural dierences,
language attitudes
and tourist satisfaction: A study in the Barcelona hotel sector. Journal of Multilingual and
Multicultural Development 40: 133–47. [CrossRef]
De Oliveira, Santos, and Eduardo Glauber. 2016. Worldwide hedonic prices of subjective characteristics of hostels.
Tourism Management 52: 451–54. [CrossRef]
Deveci, Muhammet, Özcan Ender, John Robert, and Sultan Ceren Öner. 2018. Interval type-2 hesitant fuzzy set
method for improving the service quality of domestic airlines in Turkey. Journal of Air Transport Management
69: 83–98. [CrossRef]
Dolnicar, Sara. 2013. Asking Good Survey Questions. Journal of Travel Research 52: 551–74. [CrossRef]
Dominici, Gandolfo, and Rosa Guzzo. 2010. Customer satisfaction in the hotel industry: A case study from Sicily.
International Journal of Marketing Studies 2: 3–12. [CrossRef]
Emir, Oktay. 2013. A multi-national satisfaction analysis: An application on tourists in Antalya. Tourism 61:
347–59.
Francesco, Galati, and Galati Roberta. 2019. Cross-country analysis of perception and emphasis of hotel attributes.
Tourism Management 74: 24–42. [CrossRef]
Fu, Hsin Pin, Chu Kuo-Kuang, Chao Pai, Lee Hung-Hsuan, and Yen-Chun Liao. 2011. Using fuzzy AHP and
VIKOR for benchmarking analysis in the hotel industry. The Service Industries Journal 31: 2373–89. [CrossRef]
Gundersen, Marit G., Heide Morten, and Ulf H. Olson. 1996. Hotel Guest Satisfaction among Business Travelers:
What are the Important Factors? The Cornell Hotel and Restaurant Administration Quarterly 37: 72–81. [CrossRef]
Hofstede, Geert. 1991. Organization and Cultures: Software of the Mind. New York: McGraw-Hill.
Hosseini, Mirza Hassan, and Elham Keshavarz. 2017. Using fuzzy AHP and fuzzy TOPSIS for strategic analysis
measurement of service quality in banking industry. International Journal of Applied Management Science 9:
55–80. [CrossRef]
Huang, Jen-Hung, Huang Chun-Te, and Soushan Wu. 1996. National character and response to unsatisfactory
hotel service. International Journal of Hospitality Management 15: 229–43. [CrossRef]
Hwang, Ching-Lai, and Kwangsun Yoon. 1981. Multiple Attribute Decision Making: Methods and Application.
New York: Springer.
Jani, Dev, and Heesup Han. 2014. Personality, satisfaction, image, ambience, and loyalty: Testing their relationships
in the hotel industry. International Journal of Hospitality Management 37: 11–20. [CrossRef]
Kim, Chulwon, and Seokho Lee. 2000. Understanding the Cultural Dierences in Tourist Motivation between
Anglo-American and Japanese Tourists. Journal of Travel & Tourism Marketing 9: 153–70. [CrossRef]
Kim, Samuel Seongseop, and Bob McKercher. 2011. The collective eect of national culture and tourist culture on
tourist behavior. Journal of Travel and Tourism Marketing 28: 145–64. [CrossRef]
Kozak, Metin. 2001. Comparative assessment of tourist satisfaction with destinations across two nationalities.
Tourism Management 22: 391–401. [CrossRef]
Lee, Yong-Ki, Jeong Yeon-Kook, and Joowon Choi. 2014. Service quality, relationship outcomes, and membership
types in the hotel industry: A survey in Korea. Asia Pacific Journal of Tourism Research 19: 300–24. [CrossRef]
Lenartowicz, Tomasz, and Kendall Roth. 1999. A framework for culture assessment. Journal of International
Business Studies 30: 781–98. [CrossRef]
Li, Fangxuan, and Chris Ryan. 2020. Western guest experiences of a Pyongyang international hotel, North Korea:
Satisfaction under conditions of constrained choice. Tourism Management 76: 1–11. [CrossRef]
Liu, Yong, Teichert Thorsten, Rossi Matti, Li Hongxiu, and Feng Hu. 2017. Big data for big insights: Investigating
language-specific drivers of hotel satisfaction with 412,784 user-generated reviews. Tourism Management 59:
554–63. [CrossRef]
Lu, Zhen, and Feng Zhu. 2006. The post-purchase evaluation of the China’s star rated hotel service quality:
A content
analysis of guest comments on third party hotel booking websites. The Journal of China
Tourism Research 2: 93–103.
Markovi´c, Suzana, and Sanja Raspor Jankovi´c. 2013. Exploring the relationship between service quality and
customer satisfaction in Croatian hotel industry. Tourism and Hospitality Management 19: 149–64.
Mart
í
n, Juan-Carlos, and Concepcion Rom
á
n. 2017. Measuring service quality in the hotel industry: The value of
user generated content. Tourism 65: 390–405.
Mart
í
n, Juan Carlos, Concepcion Rom
á
n, and Clara Gonzaga. 2017a. Fuzzy numbers and TOPSIS for analyzing
service quality in the mice industry. Event Management 21: 13–25. [CrossRef]
Adm. Sci. 2020,10, 68 23 of 24
Martín, Juan Carlos, Concepcion Román, and Clara Gonzaga. 2017b. Quality of service and segmentation in the
MICE industry: An approximation based on fuzzy logic. Journal of Convention & Event Tourism 18: 1–25.
[CrossRef]
Mart
í
n, Juan Carlos, Maria Victoria S
á
nchez-Rebull, and Veronika Rudchenko. 2018. Hotel Guests’ Satisfaction:
A Segmentation
Analysis Based on Age and Gender Using Topsis Fuzzy Methodology.
Fuzzy Economic Review
23: 63–85. [CrossRef]
Mart
í
n, Juan Carlos, Luis Mart
í
n-Domingo, Gui Lohmann, and Bojana Spasojevic. 2019a. The role of travel patterns
in airport duty-free shopping satisfaction: A case study from an Australian regional airport.
Journal of
Air
Transport Management 80: 101–19. [CrossRef]
Mart
í
n, Juan Carlos, Melville Saayman, and Evangeline du Plessis. 2019b. Determining satisfaction of international
tourist: A dierent approach. Journal of Hospitality and Tourism Management 40: 1–10. [CrossRef]
Matzler, Kurt, Birgit Renzl, and Sandra Rothenberger. 2006. Measuring the Relative Importance of Service
Dimensions in the Formation of Price Satisfaction and Service Satisfaction: A Case Study in the Hotel
Industry. Scandinavian Journal of Hospitality and Tourism 6: 179–96. [CrossRef]
McCracken, Grant. 1986. Culture and consumption: A theoretical account of the structure and movement of the
cultural meaning of consumer goods. Journal of Consumer Research 13: 71–81. [CrossRef]
Moro, Sergio, Guilherme D Pires, Rita Paulo, and Paulo Ivo Cortez. 2020. A cross-cultural case study of consumers’
communications about a new technological product. Journal of Business Research. in press. [CrossRef]
Morsaghian, Mohammad, Zadeh Iman Attar, and Sabina Nobari. 2015. Providing a way to Recognize Bank
Customers’ needs Eectively based on Clustering Techniques, the Fuzzy TOPSIS and Kano Model: A Case
Study in Bank of Qarzollhassaneh Mehr Iran in Khuzestan. Indian Journal of Science and Technology 8: 1–10.
[CrossRef]
Neal, Janet D., and Dogan Gursoy. 2008. A multifaceted analysis of tourism satisfaction. Journal of Travel Research
47: 53–62. [CrossRef]
Nilashi, Mehrbakhsh, Mardani Abbas, Liao Huchang, Ahmadi Hossein, Abdul Manaf Azizah, and Wafa Almukadi.
2019. A Hybrid Method with TOPSIS and Machine Learning Techniques for Sustainable Development of
Green Hotels Considering Online Reviews. Sustainability 11: 6013. [CrossRef]
Pizam, Abraham. 1999. Cross-cultural tourist behavior. In Consumer Behavior in Travel and Tourism. Edited by
Abraham Pizam and Yoel Mansfeld. New York: Haworth Press, pp. 393–412.
Pizam, Abraham, and Arie Reichel. 1996. The eect of nationality on tourist behavior: Israeli tour-guides’
perceptions. Journal of Hospitality Marketing and Management 4: 3–49. [CrossRef]
Pizam, Abraham, and Silvia Sussmann. 1995. Does nationality aect tourist behavior? Annals of Tourism Research
22: 901–17. [CrossRef]
Reisinger, Yvette, and Lindsay Turner. 2003. Cross-Cultural Behavior in Tourism. Concepts and Analysis. Oxford:
Butterworth-Heinemann.
Richardson, Sara L., and John L. Crompton. 1988. Latent demand for vacation travel: A cross-cultural analysis of
French- and English-speaking residents of Ontario and Quebec. Leisure Sciences 10: 17–26. [CrossRef]
Sann, Raksmey, Lai Pei-Chun, and Yi Liaw. 2020. Online complaining behavior: Does cultural background and
hotel class matter? Journal of Hospitality and Tourism Management 43: 80–90. [CrossRef]
Selma Ozdipciner, Nuray, Li Xiangping, and Muzaer Uysal. 2012. Cross-cultural dierences in purchase
decision-making criteria. International Journal of Culture, Tourism and Hospitality Research 6: 34–43. [CrossRef]
Schuckert, Markus, Liu Xianwei, and Rob Law. 2015. A segmentation of online reviews by language groups: How
English and non-English speakers rate hotels dierently. International Journal of Hospitality Management 48:
143–49. [CrossRef]
Smith, Stephen L.J. 1994. The tourism product. Annals of Tourism Research 21: 582–95. [CrossRef]
St. Petersburg Travel Guide. 2020. St. Petersburg Tourism Statistics. 2017. Available online:
https://guidetopetersburg.com/st-petersburg-tourism-statistics-2017/#:~{}:text=As%20the%20city\T1\
textquoterights%20tourism%20committee,That\T1\textquoterights%20the%20biggest%20number%20ever
(accessed on 1 July 2020).
Stepchenkova, Svetlana, Kim Hany, and Anderi Kirelenko. 2015. Cultural dierences in pictorial destination
images: Russia through the camera lenses of American and Korean tourists. Journal of Travel Research 54:
758–73. [CrossRef]
Adm. Sci. 2020,10, 68 24 of 24
Stylos, Nikolaos, and Chris A. Vassiliadis. 2015. Dierences in Sustainable Management Between Four-and
Five-Star Hotels Regarding the Perceptions of Three-Pillar Sustainability. Journal of Hospitality Marketing
& Management 24: 791–825. [CrossRef]
Sussmann, Silvia, and Catherine Rashcovsky. 1997. A cross-cultural analysis of English and French Canadian’s
vacation travel patterns. International Journal of Hospitality Management 16: 191–208. [CrossRef]
Tang, Zhaoping, Qin Jin, and Jianping Sun. 2017. Railway emergency resource dispatching optimization based
on fuzzy satisfaction degree under the priority principle. Journal of Intelligent & Fuzzy Systems 33: 2677–86.
[CrossRef]
Torres, Edvin N., and Sheryl Fried Kline. 2006. From satisfaction to delight: A model for the hotel industry.
International Journal of Contemporary Hospitality Management 1: 290–301. [CrossRef]
Turner, Lindsay W., Reisinger Yvette, and Lisa McQuilken. 2002. How cultural dierences cause dimensions of
tourism satisfaction. Journal of Travel and Tourism Marketing 11: 79–101. [CrossRef]
Vinson, Donald E., and J. Michael Munson. 1976. Personal values: An approach to market segmentation.
In Marketing: 1877–1976 and Beyond
. Edited by Kenneth L. Bernhardt. Chicago: AMA, pp. 313–17. [CrossRef]
Weiermair, Klaus. 2000. Tourists’ perceptions towards satisfaction with service quality in the cross-cultural service
encounter: Implications for hospitality and tourism management. Managing Service Quality 10: 397–409.
[CrossRef]
Williams, Jerome D., Han San-Lin, and Wiliam J. Qualls. 1998. A conceptual model and study of cross-cultural
business relationships. Journal of Business Research 42: 135–43. [CrossRef]
Wilson, Alan. 1996. The nature of corporate culture within a service delivery environment. Paper presented at 4th
International Research Seminar in Service Management, La Londe Les Maures, France, 11 June.
Yu, Ji Yun, and Tae Gyou Ko. 2012. A cross-cultural study of perceptions of medical tourism among Chinese,
Japanese and Korean tourists in Korea. Tourism Management 33: 80–88. [CrossRef]
Yue, Chuan, and Zhongliang Yue. 2018. A soft approach to evaluate the customer satisfaction in E-retailing.
Advances in Intelligent Systems and Computing 646: 282–96. [CrossRef]
Yuksel, Atila, Kilinc Ugurk, and Fisun Yuksel. 2006. Cross-national analysis of hotel customers’ attitudes toward
complaining and their complaining behaviours. Tourism Management 27: 11–24. [CrossRef]
Zadeh, Lotfi A. 1965. Fuzzy sets. Information and Control 8: 338–53. [CrossRef]
Zadeh, Lotfi A. 1973. Outline of a new approach to the analysis of complex systems and decision processes.
IEEE Transactions on Systems, Man, and Cybernetic 3: 28–44. [CrossRef]
Zeithaml, Valarie A., and Mary Jo Bitner. 1996. Services Marketing. New York: McGraw-Hill.
Zeleny, Milan. 1998. Multiple criteria decision making: Eight concepts of optimality. Human Systems Management
17: 97–107.
Zhou, Lingqiang, Ye Shun, Pearce Philip L., and Mao-Ying Wu. 2014. Refreshing hotel satisfaction studies by 871
reconfiguring customer review data. International Journal of Hospitality Management 38: 1–10. [CrossRef]
Zhu, Xiaoning, Zhang Qun, Zhang Lingping, and Jiaqin Yang. 2013. Online Promotion of the E-Commerce
Websites in Retail Market in China: An Empirical Study. Journal of Electronic Commerce in Organizations 11:
23–40. [CrossRef]
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