AN EVALUATION OF FACTORS AFFECTING TOURIST SATISFACTION WITH SERVICE QUALITY: CASE STUDY OF SAM MOUNTAIN NATIONAL TOURIST AREA IN AN GIANG PROVINCE, VIETNAM - Full 10 điểm

Journal of Sustainability Science and Management eISSN: 2672-7226
Volume 18 Number 9, September 2023: 143-156 © Penerbit UMT

AN EVALUATION OF FACTORS AFFECTING TOURIST SATISFACTION
WITH SERVICE QUALITY: CASE STUDY OF SAM MOUNTAIN NATIONAL

TOURIST AREA IN AN GIANG PROVINCE, VIETNAM

TO MINH CHAU1,2*, LE THANH HOA2 AND NGUYEN THI PHUONG CHAU2

1Department of Geography, Faculty of Pedagogy, An Giang University, Vietnam National University, Ho Chi Minh City,
Vietnam. 2Faculty of Geography, University of Social Sciences and Humanities, Vietnam National University, Ho Chi Minh
City, Vietnam.

*Corresponding author:

Submitted final draft: 12 June 2023 Accepted: 30 June 2023 />
Abstract: This study was conducted at the National Tourist Area (NTA) of Sam Mountain
in Chau Doc City, An Giang Province, Vietnam. The study surveyed 150 tourists using a
questionnaire to assess the factors affecting visitor satisfaction with the quality of tourist
services in the Sam Mountain NTA. The responses from the questionnaire were encoded
and analyzed using Cronbach’s Alpha reliability coefficient, the EFA exploratory factor,
and regression analysis using SPSS 26.0. The research results showed that out of the four
studied factors: labor, type, infrastructure and tourist environment, the labor had the most
significant impact on tourists satisfaction when visiting the Sam Mountain NTA. The
study also found that environmental factors had the least impact on tourist satisfaction.
Addressing this issue requires local authorities at all levels to work together to implement
solutions to improve the quality of services and meet tourists’ satisfaction levels when
coming to the Sam Mountain NTA.

Keywords: Sam Mountain National Tourist Area, An Giang province, tourist satisfaction,

factors affecting tourists, Vietnam.
Abbreviations: National Tourist Area (NTA)

Introduction Tourist satisfaction is essential for effective
destination marketing because it influences the
The tourist industry is rapidly developing and choice of destination, the use of products and
plays an essential role in the economy worldwide services, and the decision to return (Kozak &
(Osman & Sentosa, 2013). Tourism benefits the Rimmington, 2000). In Vietnam, as the quality
economy and society, by providing increased of life improves, tourist becomes more familiar
revenue, creating many job opportunities and and popular. Therefore, the quality of services
attracting significant investment capital. In is also noticed by tourists, and destinations with
addition, the tourism industry also contributes better quality of services are chosen (To, 2023).
significantly to the preservation and development Beautiful and convenient facilities ensure that
of the local tangible and intangible heritage. The tourists have the best destination experience
development of the tourist industry also plays (Hung et al., 2021).
a vital role in reducing poverty and promoting
the restructuring of the economy (Giao et al., Sam Mountain NTA is located in Sam
2021). Indeed, traveling has many benefits, such Mountain Ward, Chau Doc City, An Giang
as relieving stress, experiencing new things, and province, Vietnam. Sam Mountain NTA is
improving knowledge about culture, tradition a place that has attracted a large number of
and cuisine of unfamiliar regions (Goliath tourists. It is about 60 km from Long Xuyen
& Yekela, 2020). Tourism activities include City, An Giang province, heading west along
visiting, learning, resting, and entertainment National Highway 91 and about 100 km from
activities at places other than a person’s daily Can Tho International Airport. The tourist area
environment for a certain period (Setokoe, is in an important geographical position, located
2020).

To Minh Chau et al. 144

in the center of the province’s tourist district and affecting customer satisfaction with the quality

adjacent to territories containing many unique of tourist services.
tourist resources, such as the Tri Ton and Tinh
Bien district (PCAGP, 2013). National Highway Literature Review
91 also connects Sam Mountain NTA to essential
tourist destinations throughout the Mekong Tourist
Delta region, allowing the tourist area to be
linked and developed with adjacent destinations. Tourists are individuals who travel to a
destination outside their usual place of residence
The Sam Mountain NTA has Sam Mountain for a period ranging from 24 hours to less than
with an area of about 280 hectares, with a height one year, for leisure, business, or other personal
of about 241 m. The area has many architectural purposes, excluding the purpose of working at
works, historical and cultural relics, and a specific access point or country (Giao et al.,
beautiful landscapes, such as Bach Van Hill 2020). Tourists also stay at resorts, hotels, or
and Tao Ngo Garden. The Sam Mountain NTA other forms of accommodation, to enjoy tourist
includes attractions such as Ba Chua Xu Sam activities and experiences for a short period
Mountain Temple, Tay An Pagoda, and Hang (Patwary et al., 2021).
Pagoda (Nguyen et al., 2023).
Service Quality
The main visitors to the Sam Mountain NTA
are primarily pilgrims, festival-goers to the Ba Service is an activity or benefit provided for
Chua Xu Nui Sam festival, and those interested exchange, primarily intangible and not resulting
in learning about the culture and history. Every in the ownership transfer. The performance of a
year, about five million visitors visit tourist service may or may not be linked to a tangible
sites from domestic and international locations product (Kotler & Keller, 2012). Service quality is
(Chau, 2021). The population around the Sam measured by comparing the value that customers
Mountain tourist area is dense, and the central expect before using the service and the value
and surrounding areas have a diverse ethnic that customers receive after using the service.
community consisting of the Kinh, Hoa, Cham, Service is an activity or a series of activities that
and Khmer peoples. The Kinh people make occur when there is an interaction between two
up the majority of the population in the tourist parties, the consumer and the service provider

area. Each ethnic group has its own cultural (Gronroos, 1990). Service quality is the degree
identity, contributing to a diverse cultural life of difference between consumers’ expectations
with numerous festivals, historical sites, and of service and their perceptions of the service
traditional craft villages, which are all significant outcome. In other words, service quality is the
resources that attract tourists. difference between customers’ expectations
and the quality they experience in the provided
The Sam Mountain NTA has recently service (Parasuraman et al., 1988). The quality
developed into one of the most attractive of tourist services is the level of suitability of
destinations in An Giang province and the the tourist service providers to satisfy the needs
Mekong Delta region. However, the Sam of tourists in the target market (Chuchu, 2020).
Mountain NTA must be developed further to
maximize its tourism potential. To meet the The Satisfaction of Tourists
needs of visitors, the quality of service at Sam
Mountain tourist resort needs to be improved. The satisfaction of tourists can be increased by
To achieve this, the Management Board of the the criteria and expectations of tourists about the
Tourist Area and related parties must carefully tour packages offered. Tourist organizations must
research, survey and evaluate the factors define this to support their continuous efforts to
balance capacity with demand and the quality

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FACTORS AFFECTING ON TOURIST SATISFACTION 145

of services provided (Kandampully, 2000). The Overview of the Research Sample
satisfaction of tourists is essential for effective
destination marketing because it influences the In order to evaluate the factors influencing the
choice of destination, the use of products, and level of tourist satisfaction with the quality of
the decision to return. Tourists’ happiness is the services at the Sam Mountain National Resort,
difference between such customer expectations a random sampling method was applied to
and the actual value. Satisfied tourists are more 150 tourists through a questionnaire. The

likely to return and encourage others to do the characteristics of the survey sample are shown
same, and the frequency of complaints from in Table 1. The survey results showed that there
tourists decreases as satisfaction increases. In is a gender imbalance in the structure of tourist
globalization, tourist satisfaction is the primary customers, with females outnumbering males
tool to increase tourist output. This relates to (accounting for 57 % of the total surveyed
efforts to provide tourists with the resources customers). This stems from the fact that the
to meet the needs of the industry. Satisfied majority of tourist customers come to the Sam
customers can also be an excellent strategy for Mountain NTA for spiritual and pilgrimage
spreading positive word of mouth (Pavlic et purposes, so the number of female visitors is
al., 2011). Satisfaction with tourist destinations higher than males. Regarding the occupation
results from the evaluation between desire and of tourist customers, students accounted for
encounter (Ibrahim & Gill, 2015). the highest proportion (64 %). Other customer
groups accounted for a relatively small
Infrastructure and Tourist Satisfaction proportion, such as business people (19 %),
state employees (5 %), and others (12 %).
Many studies have addressed the close Tourists visiting Sam Mountain NTA mostly
relationship between infrastructure and come during their leisure time (44 %), followed
tourist satisfaction (Khuong et al., 2020). The by the Tet holiday (34 %), and with lower
infrastructure component of tourist development percentages during summer vacation (17 %)
is vital because it supports the destination’s and weekends (5 %). This can be explained by
competitive advantage. Furthermore, the fact that the surveyed tourists are mainly
developing adequate public infrastructure is students who travel during their free time, on
necessary for high-quality tourist facilities at holidays and festivals. The Sam Mountain NTA
tourist destinations (Jovanovia & Ilia, 2016). has many unique and attractive festivals and
Tourist infrastructure refers to the physical spiritual rituals, which have attracted many
and technological infrastructure created by visitors during these occasions. Among 150
the government and tourist organizations survey responses collected, the results show
to exploit the potential of tourism, such as that the majority of tourists know about the Sam
hotel and residential complexes, products, Mountain NTA through recommendations from
amusement parks, transportation equipment, friends and family (90 people), followed by the

and infrastructure facilities. Infrastructure is internet (23 people), TV and radio (17 people),
viewed as a transportation network, including travel companies (11 people), and a minority
roads, railways, seaports and airports. Moreover, from books, newspapers, and magazines (4
tourist happiness is affected by the accessibility people), with the remaining 5 people from other
of the location, including infrastructure, sources. Therefore, it can be seen that tourists
operational variables, government regulations mainly know about Sam Mountain NTA through
and equipment (Virkar & Mallya, 2018). Other recommendations or invitations from friends
studies have shown that between the natural and and family. Promoting information about the
built environment, the built environment had a tourist area through the media (TV, radio, books,
significant effect on tourist satisfaction (Rahim internet) or travel agencies still needs to be
et al., 2022). improved.

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Table 1: Characteristics of the survey sample

Factors Component Amount Percent
Gender Male 65 43 %
Employment Female 85 57 %
The time for traveling 8 5 %
Purpose State employees 96 64 %
Student 28 19 %
Information source Business 18 12 %
Other 25 17 %
51 34 %
Summer vacation 66 44 %
Tet holiday 8 5 %
Leisure time 93 62 %

Weekend 3 2 %
39 26 %
Traveling, vacationing 4 3 %
Commerce 8 5 %
3 2 %
Religion, belief 90 60 %
Conference, seminar 17 11 %
11 7 %
Visit relatives 4 3 %
Others (please specify) 23 15 %
5 4 %
Friends, relatives
TV, Radio

Travel company, tour operator
Books, newspapers, magazines

Internet
Others (please specify)

(Source: Data analysis results from direct tourist survey in 2022, n = 150)

Material and method Sample size: This study uses exploratory factor
analysis (EFA). The process of factor analysis
Data collection and processing method at the is shown in in Figure 1. Typically, to use the
subordinate level exploratory factor analysis method, the sample
size is good when the ratio of observed variables
Method of collecting data: The project selects to measured variables is 5:1, meaning that at
a convenience sampling method, meaning that least five observed variables are needed for one
the interviewer will randomly approach tourists measured variable (Hair et al., 2009). The factor

at Ba Chua Xu temple, Thoai Ngoc Hau tomb scale influencing the quality of service of the
and other locations in the Sam Mountain NTA. Sam Mountain NTA is set up with 18 observed
These locations were selected for surveying variables included in the factor analysis, so the
because they have favourable conditions, such minimum sample size required is 90. Therefore,
as a concentrated space and are the busiest places the survey sample is based on interviewing 150
for visitors at Sam Mountain NTA. Content of tourists of the Sam Mountain NTA, which is
the survey: information on the factors affecting sufficient for the analysis methods in this study.
tourists’ satisfaction with the quality of tourist The proposed research includes four variable
services at Sam Mountain NTA.

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FACTORS AFFECTING ON TOURIST SATISFACTION 147

Figure 1: Factor analysis process

groups (factors) consisting of 18 observed Data Analysis Methods
variables as follows:
The steps of data analysis are shown in Figure
(1) Infrastructure includes six variables: HT1 3. The data analysis methods used in the study
(transportation); HT2 (parking lot); HT3 include descriptive statistics (gender, occupation,
(restroom); HT4 (accommodation); HT5 time, purpose, information source, and tourist
(communication); HT6 (electricity, water). destination) to analyse the current situation of
tourist activities at the Sam Mountain NTA site
(2) Labor includes three variables: LD1 (staff); and describe tourists’ perceptions of the quality
LD2 (local people); LD3 (professional of services provided by the site. In addition,
staff). (3) Type includes three variables: Cronbach’s Alpha analysis, EFA factor analysis,
LH1 (souvenir); LH2 (food service); LH3 and multiple regression analysis were used
(tourist type). to identify the key factors affecting tourists’
satisfaction with service quality at the Sam

(4) Environment includes six variables: MT1 Mountain NTA site. To analyse quantitative data,
(price); MT2 (soliciting tourists); MT3 the study used SPSS 20.0 software. Responses
(food hygiene); MT4 (tourist environment); were coded, and SPSS calculations were used
MT5 (scenery); MT6 (tourist connection). to ensure the accuracy and reliability of the data
obtained and to determine the benefits of the
The research model is built explicitly based on data.
four factors, as shown in Figure 2.

Figure 2: The research model
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Figure 3: Data analysis steps

Results and Discussion Table 2: Cronbach’s Alpha coefficients for all
components
The Cronbach’s Alpha method measures
unsuitable variables and reduces noise variables Cronbach’s Alpha N of Items
in the research process by evaluating the scale
using Cronbach’s Alpha reliability coefficient. 0.838 18
Variables with an item-total correlation
coefficient of less than 0.3 will be removed. (Source: Data analysis results from direct tourist survey in
The scale with a Cronbach’s Alpha coefficient 2022, n = 150)
of 0.6 or higher can be used in cases where the
concept being studied is new. To evaluate the Cronbach’s Alpha components are 0.838 >
factors affecting tourists’ satisfaction with the 0.6 satisfying the above conditions (Table 2), and
quality of services at the Sam Mountain NTA, we continue to analyze the scale of Cronbach’s
the study used four criteria (18 measurement Alpha coefficients for each component.
variables), including infrastructure (six

variables), labor (three variables), type (three Cronbach’s Alpha results of each component in
variables), and environment (six variables). The the service quality scale of Sam Mountain NTA
four criteria (18 variables) were evaluated to are presented in the following Table 3.
ensure the reliability of the measurement scale
and variables. Regarding the reliability of the The results in table three show that, out
measurement scale, Cronbach’s Alpha of 0.7 to of four criteria (consisting of 18 variables)
nearly 0.8 indicates an acceptable measurement included in the test, only one variable MT5 (in
scale, while a Cronbach’s Alpha of 0.8 to almost the Environment group), was removed from
1 indicates a good measurement scale (Hoang the scale due to a correlation coefficient of the
& Chu, 2008). Regarding the reliability of the total variable (0.263) being less than 0.3. The
measurement variables, they were considered remaining 17 variables belong to four groups:
reliable when the corrected item-total correlation
coefficient was ≥ 0.3 (Nguyen, 2011). After • Infrastructure group: consisting of six
conducting Cronbach’s Alpha, the results were variables (transportation; parking lot;
as follows, Table 2. restroom; communication; accommodation;
electricity, water)

• Labor group: consisting of three variables
(local people, staff, professional staff)

Table 3: Cronbach’s Alpha coefficient for each component

Ordinal Number The Scale Cronbach’s Alpha
0.834
1 Infrastructure 0.810
0.734
2 Labor 0.733

3 Type

4 Environment

(Source: Data analysis results from direct tourist survey in 2022, n = 150)

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FACTORS AFFECTING ON TOURIST SATISFACTION 149

• Type group: consisting of three variables indicating that this test is statistically significant
(food service, souvenir, tourist type) and the observed variables are correlated in the
population.
• Environment group: five variables (price;
soliciting tourists; tourist environment; The KMO coefficient (= 0.872 > 0.5)
tourist connection; food hygiene). indicates that factor analysis (EFA) is
appropriate for this analysis. The results of the
The scale evaluation is conducted by EFA factor analysis show that at the Eigenvalue
exploratory factor analysis (EFA). The Kaiser- = 1 level, using the factor extraction method
Meyer-Olkin (KMO) coefficient is a measure with Varimax rotation allows for the extraction
used to assess the suitability of factor analysis. A of four factors from 17 observed variables, and
high KMO value (between 0.5 and 1) indicates the extracted variance is 63.586%, indicating
appropriate factor analysis. In contrast, a value that these four factors explain 63.586% of the
less than 0.5 suggests that the factor analysis variation in the data. Therefore, the extracted
may not be suitable for the data (Hoang & conflict meets the requirement (> 50 %). In the
Chu, 2008). Variables with factor loadings less Rotated Component Matrix (shown in Table 5),
than 0.5 will be removed. The stopping point is all factors have loading coefficients greater than
when the Eigenvalue (representing the variance 0.5, which meets the condition, so no variables
explained by each factor) is more significant than need to be removed from the scale.
one, and the total extracted conflict is greater
than 50 %. The variable selection process in this Naming and Explaining the Factors
analysis is performed in two steps:

The explanation of the factors is based on
Step one: 17 observed variables are recognizing the observed variables with high
included in the analysis according to the factor loadings on the same factor. Thus, this
criterion that Eigenvalue is greater than one, and factor can be explained by variables with high
observed variables with factor loadings less than coefficients. Based on the factor analysis results
0.5 would be removed. The results yield four using SPSS above, there are four factors with
factors extracted. The total extracted variance explanations of the content of each factor, and
is 63.586 %, indicating that these four factors from there, based on the nature of specific
explain 63.586 % of the conflict in the data. The variables that the factor includes, a new name for
KMO coefficient is 0.872 (> 0.5), thus meeting the factor will be found (this property is called
the requirement. With the Varimax rotation, no the exploratory property of factor analysis).
variables are removed.
• First factor: Renamed as “Infrastructure”,
Step two: The 17 observed variables this factor includes two components
are included in the analysis again. The null (1) Infrastructure with variables HT1,
hypothesis H0 set in this analysis is that there HT2, HT3, HT4, HT5 andHT6, and (2)
is no correlation among the observed variables Environment with variable MT4. All of
in the population. The KMO and Barlett’s tests these variables have factor loadings greater
in the factor analysis (shown in Table 4) show than 0.5.
that this hypothesis is rejected (Sig = 0.000),

Table 4: KMO Test table

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.872
1159.357
Approx. Chi-Square
136
Bartlett’s Test of Sphericity df 0.000

Sig.

(Source: Data analysis results from direct tourist survey in 2022, n = 150)

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Table 5: Rotated Component Matrix

Observed Variables Factors

HT2 1 2 3 4
HT6 0.721
HT4 0.687 0.880
HT5 0.676 0.632
HT3 0.673 0.627
HT1 0.671
MT4 0.620
LD2 0.541
LD3
LD1 0.772
MT6 0.710
LH1 0.706
LH2 0.688
LH3
MT2 0.784
0.742
0.669

MT1

MT3

(Source: Data analysis results from direct tourist survey in 2022, n = 150)

• Second factor: Renamed as “Labor” this electricity & water, and tourist
factor includes the component (1) Labor environment).
with variables LD1, LD2, LD3, and (2)
Environment with variable MT6. All of • Labor group: consisting of four variables
these variables have factor loadings greater (staff, local people, professional staff and
than 0.5. tourist connection).

• Third factor: Renamed as “Type” in this • Type group: consisting of three variables
factor, which includes the Type component (souvenir; food service and tourist type).
with variables LH1, LH2, LH3. All of these
variables have factor loadings greater than • Environment group: three variables (price,
0.5. soliciting tourists and food hygiene).

• Fourth factor: Renamed as “Environment” Adjusting the Research Model
this factor includes the Environment
component with variables MT1, MT2, and Based on the factor analysis results above,
MT3. All of these variables have factor the research model is modified to include four
loadings greater than 0.5. components: (1) Infrastructure, (2) Labor, (3)
Type of service and (4) Environment. The
Interpretation of the Results adjusted model is shown in the diagram below.
Tourists’ satisfaction is still the dependent
The factor analysis results have produced variable, but the independent variables are the
a model that measures tourists’ satisfaction newly identified components through factor
with the service quality of tourist areas, which analysis. Some hypotheses are adjusted as
is a combination of measurement scales: follows:

Infrastructure; Labor; Type; and Environment.
F1: Infrastructure positively correlates with
• Infrastructure group: consisting of seven satisfaction.
variables (transportation; parking lot;
restroom; accommodation; communication; F2: Labor has a positive relationship with
satisfaction.

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FACTORS AFFECTING ON TOURIST SATISFACTION 151

Table 6: Factor analysis results

Observed Variables Factor Weight
F1 Infrastructure
HT1 Transportation 0.620
HT2 0.721
HT3 Parking lot 0.671
HT4 Restroom 0.676
HT5 Accommodation 0.673
HT6 Communication 0.687
MT4 Electricity & water 0.541
F2 Tourist environment
LĐ1 0.706
LĐ2 Labor 0.772
LĐ3 Staff 0.710
MT6 Local people 0.688
F3 Professional staff
LH1 Tourist connection 0.784
LH2 Type 0.742

LH3 Souvenir 0.669
F4 Food service
MT1 Tourist type 0.632
MT2 Environment 0.880
MT3 Price 0.627
Soliciting tourists
Food hygiene

(Source: Data analysis results from direct tourist survey in 2022, n = 150)

F3: Type of service has a positive relationship Regression Analysis
with satisfaction.
To determine, measure, and evaluate the
F4: Environment has a positive relationship influence of the factors on the satisfaction of
with satisfaction. domestic tourists, a multivariate regression
method is used among the four factors obtained
Building a Regression Model from the exploratory factor analysis, including
Infrastructure, Labor, Type of service and
After extracting the factors from the exploratory Environment that affect the satisfaction of
factor analysis, necessary assumptions in the tourists with the quality of service at Sam
multivariate regression model are tested for Mountain NTA in An Giang province. Multiple
violations, such as constant error variance regression model equation (Equation 1):
assumption, normality assumption of the
residuals, independence assumption of the Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + i (1)
errors, and no correlation assumption between
independent variables. If the premises are not where:
violated, a multivariate regression model is
built. Y: Dependent variable (customer satisfaction
with the quality of services at the Sam Mountain
tourist site in An Giang province).

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X1, X2, X3, X4: Independent variables, variance analysis table (Table 8). The F value is
factors influencing customer satisfaction 59.695, and the Sig value is 0.000, indicating
(X1: Infrastructure, X2: Labor, X3: Type, X4: that the multiple regression model is suitable for
Environment). the dataset and can be used.

β0: Regression constant. The variance inflation factor (VIF) for
each factor is less than ten (Table 9), indicating
βi (with i = 1,2,3,4,5,6): Regression coefficients. that the regression model does not violate the
multicollinearity phenomenon (independent
i: Error term. variables are highly correlated). Overall, all four
variables in the model positively correlate with
After inputting the four independent tourist satisfaction.
variables into the regression analysis using SPSS
software, the following results were obtained. Thus, with the significant regression
The results in Table 7 show that the adjusted R2 coefficients found, the equation can be written
value is 0.612, indicating that the independent as follows (Equation 2):
variables in the model can explain 61.2 % of
the variation in the dependent variable. The Satisfaction = 0.138 + 0.332*LD + 0.318*LH +
remaining 38.8 % is attributed to other factors
not included in the model and affect tourists’ 0.207*HT + 0.135*MT (2)
satisfaction with the quality of services at the
Sam Mountain NTA in An Giang province. (LD: Labor, LH: Type, HT: Infrastructure,
MT: Environment)
To assess the overall fit of the regression
model, we examine the F value from the ANOVA The coefficients of the equation show that

Labor and Type are the two most essential

Table 7: Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate
0.000a
52.869 4 13.215 59.695

32.100 145 0.221

84.960 149

(Source: Data analysis results from direct tourist survey in 2022, n = 150)

Table 8: Analysis of variance table of regression model (ANOVA)

Model Sum of Squares df Mean Square F Sig.
59.695 0.000a
Regression 52.869 4 13.215

1 Residual 32.100 145 0.221

Total 84.960 149

(Source: Data analysis results from direct tourist survey in 2022, n = 150)

Table 9: The Coefficients of regression analysis

Model B Std. Error Sig. VIF

Constant 0.138 0.227 0.544 1.985
HT (Infrastructure) 0.207 0.076 0.008 1.540
0.318 0.065 0.000 1.354
LH (Type) 0.135 0.054 0.013 1.858
MT (Environment) 0.332 0.069 0.000

LD (Labor)

(Source: Data analysis results from direct tourist survey in 2022, n = 150)

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components that significantly impact tourist provided to them because the staff are the ones
satisfaction at the Sam Mountain NTA. who interact with and directly provide services
Infrastructure and the Environment also have to tourists. If tourists rate the staff’s service
a significant impact. This is result shows that attitude higher, they will be more satisfied with
tourist sites need to improve the quality of the tourist site.
services for tourists. However, it does not mean
that low-impact factors in the model should be Variable X2 (Type)
ignored.
The above equation indicates that when tourists’
Conclusion perception of the type of tourism is excellent if the
other variables in the model remain unchanged,
The results of Cronbach’sAlpha analysis and EFA their satisfaction will increase by 0.318 points.
analysis revealed four factors that affect tourists’ Tourism is a period of enjoying comfortable
satisfaction, including labor, infrastructure, type, and relaxing moments after long, tiring working
and environment. After conducting a multiple days. Therefore, the diversity and differentiation
regression analysis, it was found that there is a of tourism types at the tourist site play a crucial

linear relationship between the four factors and role. The variety and differentiation of tourism
tourists’ satisfaction with a significance level types at the Sam Mountain NTA will determine
of sig = 0.000 (< 0.05). The regression analysis its competitiveness with other tourist sites.
showed that tourists’ happiness depends on the Therefore, researching and developing various
four factors in the following order of increasing tourist services at tourist sites will enhance
influence: environment, infrastructure, type, and tourists’ satisfaction. More amusement parks
labor. Based on these results, the theoretical and new games should be developed, and more
hypotheses F1, F2, F3, and F4 were tested and attention should be paid to promoting tourism
accepted. Therefore, the multiple regression types unique to the area.
equation that represents the degree of influence
of the factors on tourists’ satisfaction is Variable X3 (Infrastructure)
established as follows (Equation 3):
The equation above shows that when tourists’
Tourists’ satisfaction = 0.138 + 0.332 * Labor + perception of infrastructure is perfect, with
other variables in the model unchanged, tourists’
0.318 * Type + 0.207 * Infrastructure + 0.135 * satisfaction will increase by 0.207 points.
Infrastructure plays a vital role in the quality
Environment (3) of tourist services. Good infrastructure can
improve tourists’ travel experience, making it
Specifically, the influence of each factor on more convenient and comfortable. This includes
tourists’ satisfaction is as follows: transportation, accommodation, and other
facilities. Therefore, investing in infrastructure
Variable X1 (Labor) is an essential task for developing tourism.

The above equation indicates that tourists’ Variable X4 (Environment)
perception of labor at the Sam Mountain NTA
is the best among the variables. If the other The equation above shows that when tourists’
variables in the model remain unchanged, perception of the environment is excellent,
tourists’ satisfaction will increase by 0.312 with other variables in the model unchanged,
points. Therefore, tourists are delighted with the tourists’ satisfaction will increase by 0.135

the labor factor, meaning the staff are attentive, points. The setting is an essential factor that
enthusiastic and highly professional. At the affects the tourist experience of tourism. A clean
same time, the locals in the Sam Mountain NTA and beautiful environment can create a pleasant
are also amiable and hospitable. Therefore,
tourists will usually rely on the staff’s attitude
to evaluate the quality of the tourist services

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atmosphere, making tourists feel relaxed and Humanities and Social Sciences, 4, 2022.
comfortable. In contrast, a polluted environment />can negatively affect the tourist experience, 72
leading to dissatisfaction. Therefore, paying
attention to environmental protection and Chuchu, T. (2020). The impact of airport
management in tourist destinations is necessary. experience on international tourists’ revisit
intention: A South African case. GeoJournal
In conclusion, the study found four factors of Tourism and Geosites, 29(2), 414-427.
influencing tourists’ satisfaction in the Sam />Mountain NTA: Labor, Infrastructure, Type,
and Environment (figure 4). The results of the Giao, H. N. K., Vuong, B. N., Phuong, N. N.
multiple regression analysis showed that these D., & Dat, N. T. (2021). A model of factors
factors have a linear relationship with tourist affecting domestic tourist satisfaction on
satisfaction. Tourists’ happiness depends on eco-tourism service quality in the Mekong
these factors in the order of increasing influence: Delta, Vietnam. GeoJournal of Tourism and
Environment, Infrastructure, Type, and Labor. Geosites, 36(2spl), 663-671. https://doi.
The study also established a multiple regression org/10.30892/gtg.362spl14-696.
equation to quantify the impact of these factors
on tourist satisfaction. The equation can be Giao, H. N. K., Vuong, B. N., & Tushar, H.
used as a basis for tourist managers to develop (2020). The impact of social support on
strategies to improve the quality of tourist job-related behaviors through the mediating

services and increase tourist satisfaction in the role of job stress and the moderating role of
Sam Mountain NTA. locus of control: Empirical evidence from
the Vietnamese banking industry. Cogent
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Figure 4: The complete research model
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