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

eISSN: 2672-7226 © Penerbit UMT Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 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 CHAU 1,2 *, LE THANH HOA 2 AND NGUYEN THI PHUONG CHAU 2 1 Department of Geography, Faculty of Pedagogy, An Giang University, Vietnam National University, Ho Chi Minh City, Vietnam 2 Faculty of Geography, University of Social Sciences and Humanities, Vietnam National University, Ho Chi Minh City, Vietnam *Corresponding author: tmchau@agu edu vn Submitted final draft: 12 June 2023 Accepted: 30 June 2023 Introduction The tourist industry is rapidly developing and plays an essential role in the economy worldwide (Osman & Sentosa, 2013) Tourism benefits the economy and society, by providing increased revenue, creating many job opportunities and attracting significant investment capital In addition, the tourism industry also contributes significantly to the preservation and development of the local tangible and intangible heritage The development of the tourist industry also plays a vital role in reducing poverty and promoting the restructuring of the economy (Giao et al , 2021) Indeed, traveling has many benefits, such as relieving stress, experiencing new things, and improving knowledge about culture, tradition and cuisine of unfamiliar regions (Goliath & Yekela, 2020) Tourism activities include visiting, learning, resting, and entertainment activities at places other than a person’s daily environment for a certain period (Setokoe, 2020) Tourist satisfaction is essential for effective destination marketing because it influences the choice of destination, the use of products and services, and the decision to return (Kozak & Rimmington, 2000) In Vietnam, as the quality of life improves, tourist becomes more familiar and popular Therefore, the quality of services is also noticed by tourists, and destinations with better quality of services are chosen (To, 2023) Beautiful and convenient facilities ensure that tourists have the best destination experience (Hung et al , 2021) Sam Mountain NTA is located in Sam Mountain Ward, Chau Doc City, An Giang province, Vietnam Sam Mountain NTA is a place that has attracted a large number of tourists It is about 60 km from Long Xuyen City, An Giang province, heading west along National Highway 91 and about 100 km from Can Tho International Airport The tourist area is in an important geographical position, located 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) http://doi org/10 46754/jssm 2023 09 0010 To Minh Chau et al 144 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 in the center of the province’s tourist district and adjacent to territories containing many unique tourist resources, such as the Tri Ton and Tinh Bien district (PCAGP, 2013) National Highway 91 also connects Sam Mountain NTA to essential tourist destinations throughout the Mekong Delta region, allowing the tourist area to be linked and developed with adjacent destinations The Sam Mountain NTA has Sam Mountain with an area of about 280 hectares, with a height of about 241 m The area has many architectural works, historical and cultural relics, and beautiful landscapes, such as Bach Van Hill and Tao Ngo Garden The Sam Mountain NTA includes attractions such as Ba Chua Xu Sam Mountain Temple, Tay An Pagoda, and Hang Pagoda (Nguyen et al , 2023) The main visitors to the Sam Mountain NTA are primarily pilgrims, festival-goers to the Ba Chua Xu Nui Sam festival, and those interested in learning about the culture and history Every year, about five million visitors visit tourist sites from domestic and international locations (Chau, 2021) The population around the Sam Mountain tourist area is dense, and the central and surrounding areas have a diverse ethnic community consisting of the Kinh, Hoa, Cham, and Khmer peoples The Kinh people make up the majority of the population in the tourist area Each ethnic group has its own cultural identity, contributing to a diverse cultural life with numerous festivals, historical sites, and traditional craft villages, which are all significant resources that attract tourists The Sam Mountain NTA has recently developed into one of the most attractive destinations in An Giang province and the Mekong Delta region However, the Sam Mountain NTA must be developed further to maximize its tourism potential To meet the needs of visitors, the quality of service at Sam Mountain tourist resort needs to be improved To achieve this, the Management Board of the Tourist Area and related parties must carefully research, survey and evaluate the factors affecting customer satisfaction with the quality of tourist services Literature Review Tourist Tourists are individuals who travel to a destination outside their usual place of residence for a period ranging from 24 hours to less than one year, for leisure, business, or other personal purposes, excluding the purpose of working at a specific access point or country (Giao et al , 2020) Tourists also stay at resorts, hotels, or other forms of accommodation, to enjoy tourist activities and experiences for a short period (Patwary et al , 2021) Service Quality Service is an activity or benefit provided for exchange, primarily intangible and not resulting in the ownership transfer The performance of a service may or may not be linked to a tangible product (Kotler & Keller, 2012) Service quality is measured by comparing the value that customers expect before using the service and the value that customers receive after using the service Service is an activity or a series of activities that occur when there is an interaction between two parties, the consumer and the service provider (Gronroos, 1990) Service quality is the degree of difference between consumers’ expectations of service and their perceptions of the service outcome In other words, service quality is the difference between customers’ expectations and the quality they experience in the provided service (Parasuraman et al , 1988) The quality of tourist services is the level of suitability of the tourist service providers to satisfy the needs of tourists in the target market (Chuchu, 2020) The Satisfaction of Tourists The satisfaction of tourists can be increased by the criteria and expectations of tourists about the tour packages offered Tourist organizations must define this to support their continuous efforts to balance capacity with demand and the quality FACTORS AFFECTING ON TOURIST SATISFACTION 145 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 of services provided (Kandampully, 2000) The satisfaction of tourists is essential for effective destination marketing because it influences the choice of destination, the use of products, and the decision to return Tourists’ happiness is the difference between such customer expectations and the actual value Satisfied tourists are more likely to return and encourage others to do the same, and the frequency of complaints from tourists decreases as satisfaction increases In globalization, tourist satisfaction is the primary tool to increase tourist output This relates to efforts to provide tourists with the resources to meet the needs of the industry Satisfied customers can also be an excellent strategy for spreading positive word of mouth (Pavlic et al , 2011) Satisfaction with tourist destinations results from the evaluation between desire and encounter (Ibrahim & Gill, 2015) Infrastructure and Tourist Satisfaction Many studies have addressed the close relationship between infrastructure and tourist satisfaction (Khuong et al , 2020) The infrastructure component of tourist development is vital because it supports the destination’s competitive advantage Furthermore, developing adequate public infrastructure is necessary for high-quality tourist facilities at tourist destinations (Jovanovia & Ilia, 2016) Tourist infrastructure refers to the physical and technological infrastructure created by the government and tourist organizations to exploit the potential of tourism, such as hotel and residential complexes, products, amusement parks, transportation equipment, and infrastructure facilities Infrastructure is viewed as a transportation network, including roads, railways, seaports and airports Moreover, tourist happiness is affected by the accessibility of the location, including infrastructure, operational variables, government regulations and equipment (Virkar & Mallya, 2018) Other studies have shown that between the natural and built environment, the built environment had a significant effect on tourist satisfaction (Rahim et al , 2022) Overview of the Research Sample In order to evaluate the factors influencing the level of tourist satisfaction with the quality of services at the Sam Mountain National Resort, a random sampling method was applied to 150 tourists through a questionnaire The characteristics of the survey sample are shown in Table 1 The survey results showed that there is a gender imbalance in the structure of tourist customers, with females outnumbering males (accounting for 57 % of the total surveyed customers) This stems from the fact that the majority of tourist customers come to the Sam Mountain NTA for spiritual and pilgrimage purposes, so the number of female visitors is higher than males Regarding the occupation of tourist customers, students accounted for the highest proportion (64 %) Other customer groups accounted for a relatively small proportion, such as business people (19 %), state employees (5 %), and others (12 %) Tourists visiting Sam Mountain NTA mostly come during their leisure time (44 %), followed by the Tet holiday (34 %), and with lower percentages during summer vacation (17 %) and weekends (5 %) This can be explained by the fact that the surveyed tourists are mainly students who travel during their free time, on holidays and festivals The Sam Mountain NTA has many unique and attractive festivals and spiritual rituals, which have attracted many visitors during these occasions Among 150 survey responses collected, the results show that the majority of tourists know about the Sam Mountain NTA through recommendations from friends and family (90 people), followed by the internet (23 people), TV and radio (17 people), travel companies (11 people), and a minority from books, newspapers, and magazines (4 people), with the remaining 5 people from other sources Therefore, it can be seen that tourists mainly know about Sam Mountain NTA through recommendations or invitations from friends and family Promoting information about the tourist area through the media (TV, radio, books, internet) or travel agencies still needs to be improved To Minh Chau et al 146 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 Material and method Data collection and processing method at the subordinate level Method of collecting data: The project selects a convenience sampling method, meaning that the interviewer will randomly approach tourists at Ba Chua Xu temple, Thoai Ngoc Hau tomb and other locations in the Sam Mountain NTA These locations were selected for surveying because they have favourable conditions, such as a concentrated space and are the busiest places for visitors at Sam Mountain NTA Content of the survey: information on the factors affecting tourists’ satisfaction with the quality of tourist services at Sam Mountain NTA Sample size: This study uses exploratory factor analysis (EFA) The process of factor analysis is shown in in Figure 1 Typically, to use the exploratory factor analysis method, the sample size is good when the ratio of observed variables to measured variables is 5:1, meaning that at least five observed variables are needed for one measured variable (Hair et al , 2009) The factor scale influencing the quality of service of the Sam Mountain NTA is set up with 18 observed variables included in the factor analysis, so the minimum sample size required is 90 Therefore, the survey sample is based on interviewing 150 tourists of the Sam Mountain NTA, which is sufficient for the analysis methods in this study The proposed research includes four variable Table 1: Characteristics of the survey sample Factors Component Amount Percent Gender Male 65 43 % Female 85 57 % Employment State employees 8 5 % Student 96 64 % Business 28 19 % Other 18 12 % The time for traveling Summer vacation 25 17 % Tet holiday 51 34 % Leisure time 66 44 % Weekend 8 5 % Purpose Traveling, vacationing 93 62 % Commerce 3 2 % Religion, belief 39 26 % Conference, seminar 4 3 % Visit relatives 8 5 % Others (please specify) 3 2 % Information source Friends, relatives 90 60 % TV, Radio 17 11 % Travel company, tour operator 11 7 % Books, newspapers, magazines 4 3 % Internet 23 15 % Others (please specify) 5 4 % (Source: Data analysis results from direct tourist survey in 2022, n = 150) FACTORS AFFECTING ON TOURIST SATISFACTION 147 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 groups (factors) consisting of 18 observed variables as follows: (1) Infrastructure includes six variables: HT1 (transportation); HT2 (parking lot); HT3 (restroom); HT4 (accommodation); HT5 (communication); HT6 (electricity, water) (2) Labor includes three variables: LD1 (staff); LD2 (local people); LD3 (professional staff) (3) Type includes three variables: LH1 (souvenir); LH2 (food service); LH3 (tourist type) (4) Environment includes six variables: MT1 (price); MT2 (soliciting tourists); MT3 (food hygiene); MT4 (tourist environment); MT5 (scenery); MT6 (tourist connection) The research model is built explicitly based on four factors, as shown in Figure 2 Data Analysis Methods The steps of data analysis are shown in Figure 3 The data analysis methods used in the study include descriptive statistics (gender, occupation, time, purpose, information source, and tourist destination) to analyse the current situation of tourist activities at the Sam Mountain NTA site and describe tourists’ perceptions of the quality of services provided by the site In addition, Cronbach’s Alpha analysis, EFA factor analysis, and multiple regression analysis were used to identify the key factors affecting tourists’ satisfaction with service quality at the Sam Mountain NTA site To analyse quantitative data, the study used SPSS 20 0 software Responses were coded, and SPSS calculations were used to ensure the accuracy and reliability of the data obtained and to determine the benefits of the data Figure 1: Factor analysis process Figure 2: The research model To Minh Chau et al 148 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 Results and Discussion The Cronbach’s Alpha method measures unsuitable variables and reduces noise variables in the research process by evaluating the scale using Cronbach’s Alpha reliability coefficient Variables with an item-total correlation coefficient of less than 0 3 will be removed The scale with a Cronbach’s Alpha coefficient of 0 6 or higher can be used in cases where the concept being studied is new To evaluate the factors affecting tourists’ satisfaction with the quality of services at the Sam Mountain NTA, the study used four criteria (18 measurement variables), including infrastructure (six variables), labor (three variables), type (three variables), and environment (six variables) The four criteria (18 variables) were evaluated to ensure the reliability of the measurement scale and variables Regarding the reliability of the measurement scale, Cronbach’s Alpha of 0 7 to nearly 0 8 indicates an acceptable measurement scale, while a Cronbach’s Alpha of 0 8 to almost 1 indicates a good measurement scale (Hoang & Chu, 2008) Regarding the reliability of the measurement variables, they were considered reliable when the corrected item-total correlation coefficient was ≥ 0 3 (Nguyen, 2011) After conducting Cronbach’s Alpha, the results were as follows, Table 2 Table 2: Cronbach’s Alpha coefficients for all components Cronbach’s Alpha N of Items 0 838 18 (Source: Data analysis results from direct tourist survey in 2022, n = 150) Cronbach’s Alpha components are 0 838 > 0 6 satisfying the above conditions (Table 2), and we continue to analyze the scale of Cronbach’s Alpha coefficients for each component Cronbach’s Alpha results of each component in the service quality scale of Sam Mountain NTA are presented in the following Table 3 The results in table three show that, out of four criteria (consisting of 18 variables) included in the test, only one variable MT5 (in the Environment group), was removed from the scale due to a correlation coefficient of the total variable (0 263) being less than 0 3 The remaining 17 variables belong to four groups: • Infrastructure group: consisting of six variables (transportation; parking lot; 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 1 Infrastructure 0 834 2 Labor 0 810 3 Type 0 734 4 Environment 0 733 (Source: Data analysis results from direct tourist survey in 2022, n = 150) Figure 3: Data analysis steps FACTORS AFFECTING ON TOURIST SATISFACTION 149 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 • Type group: consisting of three variables (food service, souvenir, tourist type) • Environment group: five variables (price; soliciting tourists; tourist environment; tourist connection; food hygiene) The scale evaluation is conducted by exploratory factor analysis (EFA) The Kaiser- Meyer-Olkin (KMO) coefficient is a measure used to assess the suitability of factor analysis A high KMO value (between 0 5 and 1) indicates appropriate factor analysis In contrast, a value less than 0 5 suggests that the factor analysis may not be suitable for the data (Hoang & Chu, 2008) Variables with factor loadings less than 0 5 will be removed The stopping point is when the Eigenvalue (representing the variance explained by each factor) is more significant than one, and the total extracted conflict is greater than 50 % The variable selection process in this analysis is performed in two steps: Step one: 17 observed variables are included in the analysis according to the criterion that Eigenvalue is greater than one, and observed variables with factor loadings less than 0 5 would be removed The results yield four factors extracted The total extracted variance is 63 586 %, indicating that these four factors explain 63 586 % of the conflict in the data The KMO coefficient is 0 872 (> 0 5), thus meeting the requirement With the Varimax rotation, no variables are removed Step two: The 17 observed variables are included in the analysis again The null hypothesis H0 set in this analysis is that there is no correlation among the observed variables in the population The KMO and Barlett’s tests in the factor analysis (shown in Table 4) show that this hypothesis is rejected (Sig = 0 000), indicating that this test is statistically significant and the observed variables are correlated in the population The KMO coefficient (= 0 872 > 0 5) indicates that factor analysis (EFA) is appropriate for this analysis The results of the EFA factor analysis show that at the Eigenvalue = 1 level, using the factor extraction method with Varimax rotation allows for the extraction of four factors from 17 observed variables, and the extracted variance is 63 586%, indicating that these four factors explain 63 586% of the variation in the data Therefore, the extracted conflict meets the requirement (> 50 %) In the Rotated Component Matrix (shown in Table 5), all factors have loading coefficients greater than 0 5, which meets the condition, so no variables need to be removed from the scale Naming and Explaining the Factors The explanation of the factors is based on recognizing the observed variables with high factor loadings on the same factor Thus, this factor can be explained by variables with high coefficients Based on the factor analysis results using SPSS above, there are four factors with explanations of the content of each factor, and from there, based on the nature of specific variables that the factor includes, a new name for the factor will be found (this property is called the exploratory property of factor analysis) • First factor: Renamed as “Infrastructure”, this factor includes two components (1) Infrastructure with variables HT1, HT2, HT3, HT4, HT5 andHT6, and (2) Environment with variable MT4 All of these variables have factor loadings greater than 0 5 Table 4: KMO Test table Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0 872 Bartlett’s Test of Sphericity Approx Chi-Square 1159 357 df 136 Sig 0 000 (Source: Data analysis results from direct tourist survey in 2022, n = 150) To Minh Chau et al 150 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 • Second factor: Renamed as “Labor” this factor includes the component (1) Labor with variables LD1, LD2, LD3, and (2) Environment with variable MT6 All of these variables have factor loadings greater than 0 5 • Third factor: Renamed as “Type” in this factor, which includes the Type component with variables LH1, LH2, LH3 All of these variables have factor loadings greater than 0 5 • Fourth factor: Renamed as “Environment” this factor includes the Environment component with variables MT1, MT2, and MT3 All of these variables have factor loadings greater than 0 5 Interpretation of the Results The factor analysis results have produced a model that measures tourists’ satisfaction with the service quality of tourist areas, which is a combination of measurement scales: Infrastructure; Labor; Type; and Environment • Infrastructure group: consisting of seven variables (transportation; parking lot; restroom; accommodation; communication; electricity & water, and tourist environment) • Labor group: consisting of four variables (staff, local people, professional staff and tourist connection) • Type group: consisting of three variables (souvenir; food service and tourist type) • Environment group: three variables (price, soliciting tourists and food hygiene) Adjusting the Research Model Based on the factor analysis results above, the research model is modified to include four components: (1) Infrastructure, (2) Labor, (3) Type of service and (4) Environment The adjusted model is shown in the diagram below Tourists’ satisfaction is still the dependent variable, but the independent variables are the newly identified components through factor analysis Some hypotheses are adjusted as follows: F1: Infrastructure positively correlates with satisfaction F2: Labor has a positive relationship with satisfaction Table 5: Rotated Component Matri x Observed Variables Factors 1 2 3 4 HT2 0 721 HT6 0 687 HT4 0 676 HT5 0 673 HT3 0 671 HT1 0 620 MT4 0 541 LD2 0 772 LD3 0 710 LD1 0 706 MT6 0 688 LH1 0 784 LH2 0 742 LH3 0 669 MT2 0 880 MT1 0 632 MT3 0 627 (Source: Data analysis results from direct tourist survey in 2022, n = 150) FACTORS AFFECTING ON TOURIST SATISFACTION 151 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 F3: Type of service has a positive relationship with satisfaction F4: Environment has a positive relationship with satisfaction Building a Regression Model After extracting the factors from the exploratory factor analysis, necessary assumptions in the multivariate regression model are tested for violations, such as constant error variance assumption, normality assumption of the residuals, independence assumption of the errors, and no correlation assumption between independent variables If the premises are not violated, a multivariate regression model is built Regression Analysis To determine, measure, and evaluate the influence of the factors on the satisfaction of domestic tourists, a multivariate regression method is used among the four factors obtained from the exploratory factor analysis, including Infrastructure, Labor, Type of service and Environment that affect the satisfaction of tourists with the quality of service at Sam Mountain NTA in An Giang province Multiple regression model equation (Equation 1): Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + i (1) where: Y: Dependent variable (customer satisfaction with the quality of services at the Sam Mountain tourist site in An Giang province) Table 6: Factor analysis results Observed Variables Factor Weight F1 Infrastructure HT1 Transportation 0 620 HT2 Parking lot 0 721 HT3 Restroom 0 671 HT4 Accommodation 0 676 HT5 Communication 0 673 HT6 Electricity & water 0 687 MT4 Tourist environment 0 541 F2 Labor LĐ1 Staff 0 706 LĐ2 Local people 0 772 LĐ3 Professional staff 0 710 MT6 Tourist connection 0 688 F3 Type LH1 Souvenir 0 784 LH2 Food service 0 742 LH3 Tourist type 0 669 F4 Environment MT1 Price 0 632 MT2 Soliciting tourists 0 880 MT3 Food hygiene 0 627 (Source: Data analysis results from direct tourist survey in 2022, n = 150) To Minh Chau et al 152 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 X1, X2, X3, X4: Independent variables, factors influencing customer satisfaction (X1: Infrastructure, X2: Labor, X3: Type, X4: Environment) β0: Regression constant β i (with i = 1,2,3,4,5,6): Regression coefficients i: Error term After inputting the four independent variables into the regression analysis using SPSS software, the following results were obtained The results in Table 7 show that the adjusted R 2 value is 0 612, indicating that the independent variables in the model can explain 61 2 % of the variation in the dependent variable The remaining 38 8 % is attributed to other factors not included in the model and affect tourists’ satisfaction with the quality of services at the Sam Mountain NTA in An Giang province To assess the overall fit of the regression model, we examine the F value from the ANOVA variance analysis table (Table 8) The F value is 59 695, and the Sig value is 0 000, indicating that the multiple regression model is suitable for the dataset and can be used The variance inflation factor (VIF) for each factor is less than ten (Table 9), indicating that the regression model does not violate the multicollinearity phenomenon (independent variables are highly correlated) Overall, all four variables in the model positively correlate with tourist satisfaction Thus, with the significant regression coefficients found, the equation can be written as follows (Equation 2): Satisfaction = 0 138 + 0 332*LD + 0 318*LH + 0 207*HT + 0 135*MT (2) (LD: Labor, LH: Type, HT: Infrastructure, MT: Environment) The coefficients of the equation show that Labor and Type are the two most essential Table 8: Analysis of variance table of regression model (ANOVA) Model Sum of Squares df Mean Square F Sig 1 Regression 52 869 4 13 215 59 695 0 000 a Residual 32 100 145 0 221 Total 84 960 149 (Source: Data analysis results from direct tourist survey in 2022, n = 150) Table 7: Model Summary Model R R Square Adjusted R Square Std Error of the Estimate 52 869 4 13 215 59 695 0 000 a 32 100 145 0 221 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 HT (Infrastructure) 0 207 0 076 0 008 1 985 LH (Type) 0 318 0 065 0 000 1 540 MT (Environment) 0 135 0 054 0 013 1 354 LD (Labor) 0 332 0 069 0 000 1 858 (Source: Data analysis results from direct tourist survey in 2022, n = 150) FACTORS AFFECTING ON TOURIST SATISFACTION 153 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 components that significantly impact tourist satisfaction at the Sam Mountain NTA Infrastructure and the Environment also have a significant impact This is result shows that tourist sites need to improve the quality of services for tourists However, it does not mean that low-impact factors in the model should be ignored Conclusion The results of Cronbach’s Alpha analysis and EFA analysis revealed four factors that affect tourists’ satisfaction, including labor, infrastructure, type, and environment After conducting a multiple regression analysis, it was found that there is a linear relationship between the four factors and tourists’ satisfaction with a significance level of sig = 0 000 (< 0 05) The regression analysis showed that tourists’ happiness depends on the four factors in the following order of increasing influence: environment, infrastructure, type, and labor Based on these results, the theoretical hypotheses F1, F2, F3, and F4 were tested and accepted Therefore, the multiple regression equation that represents the degree of influence of the factors on tourists’ satisfaction is established as follows (Equation 3): Tourists’ satisfaction = 0 138 + 0 332 * Labor + 0 318 * Type + 0 207 * Infrastructure + 0 135 * Environment (3) Specifically, the influence of each factor on tourists’ satisfaction is as follows: Variable X1 (Labor) The above equation indicates that tourists’ perception of labor at the Sam Mountain NTA is the best among the variables If the other variables in the model remain unchanged, tourists’ satisfaction will increase by 0 312 points Therefore, tourists are delighted with the labor factor, meaning the staff are attentive, enthusiastic and highly professional At the same time, the locals in the Sam Mountain NTA are also amiable and hospitable Therefore, tourists will usually rely on the staff’s attitude to evaluate the quality of the tourist services provided to them because the staff are the ones who interact with and directly provide services to tourists If tourists rate the staff’s service attitude higher, they will be more satisfied with the tourist site Variable X2 (Type) The above equation indicates that when tourists’ perception of the type of tourism is excellent if the other variables in the model remain unchanged, their satisfaction will increase by 0 318 points Tourism is a period of enjoying comfortable and relaxing moments after long, tiring working days Therefore, the diversity and differentiation of tourism types at the tourist site play a crucial role The variety and differentiation of tourism types at the Sam Mountain NTA will determine its competitiveness with other tourist sites Therefore, researching and developing various tourist services at tourist sites will enhance tourists’ satisfaction More amusement parks and new games should be developed, and more attention should be paid to promoting tourism types unique to the area Variable X3 (Infrastructure) The equation above shows that when tourists’ perception of infrastructure is perfect, with other variables in the model unchanged, tourists’ satisfaction will increase by 0 207 points Infrastructure plays a vital role in the quality of tourist services Good infrastructure can improve tourists’ travel experience, making it more convenient and comfortable This includes transportation, accommodation, and other facilities Therefore, investing in infrastructure is an essential task for developing tourism Variable X4 (Environment) The equation above shows that when tourists’ perception of the environment is excellent, with other variables in the model unchanged, the tourists’ satisfaction will increase by 0 135 points The setting is an essential factor that affects the tourist experience of tourism A clean and beautiful environment can create a pleasant To Minh Chau et al 154 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 atmosphere, making tourists feel relaxed and comfortable In contrast, a polluted environment can negatively affect the tourist experience, leading to dissatisfaction Therefore, paying attention to environmental protection and management in tourist destinations is necessary In conclusion, the study found four factors influencing tourists’ satisfaction in the Sam Mountain NTA: Labor, Infrastructure, Type, and Environment (figure 4) The results of the multiple regression analysis showed that these factors have a linear relationship with tourist satisfaction Tourists’ happiness depends on these factors in the order of increasing influence: Environment, Infrastructure, Type, and Labor The study also established a multiple regression equation to quantify the impact of these factors on tourist satisfaction The equation can be used as a basis for tourist managers to develop strategies to improve the quality of tourist services and increase tourist satisfaction in the Sam Mountain NTA Acknowledgement The authors would like to thank the reviewers of this article The comments and contributions have helped to increase the article’s academic and practical value References Chau, T M (2021) Potential and reality development of spirit tourism in An Giang Province, Vietnam European Journal of Humanities and Social Sciences, 4 , 2022 https://doi org/ 10 29013/EJHSS-22-4-67- 72 Chuchu, T (2020) The impact of airport experience on international tourists’ revisit intention: A South African case GeoJournal of Tourism and Geosites, 29 (2), 414-427 https://doi org/10 30892/gtg 29203-478 Giao, H N K , Vuong, B N , Phuong, N N D , & Dat, N T (2021) A model of factors affecting domestic tourist satisfaction on eco-tourism service quality in the Mekong Delta, Vietnam GeoJournal of Tourism and Geosites, 36 (2spl), 663-671 https://doi 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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: tmchau@agu.edu.vn Submitted final draft: 12 June 2023 Accepted: 30 June 2023 http://doi.org/10.46754/jssm.2023.09.0010 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 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 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 the characteristics of the survey sample are shown same, and the frequency of complaints from in Table 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 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 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 To Minh Chau et al 146 Table 1: Characteristics of the survey sample Factors Component Amount Percent Gender Male 65 43 % Employment Female 85 57 % The time for traveling % Purpose State employees 96 64 % Student 28 19 % Information source Business 18 12 % Other 25 17 % 51 34 % Summer vacation 66 44 % Tet holiday % Leisure time 93 62 % Weekend % 39 26 % Traveling, vacationing % Commerce % % Religion, belief 90 60 % Conference, seminar 17 11 % 11 % Visit relatives % Others (please specify) 23 15 % % 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 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 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 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 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 Figure 2: The research model Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 To Minh Chau et al 148 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 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 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 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 Infrastructure 0.810 0.734 Labor 0.733 Type Environment (Source: Data analysis results from direct tourist survey in 2022, n = 150) Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 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- = 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) Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 To Minh Chau et al 150 Table 5: Rotated Component Matrix Observed Variables Factors HT2 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 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 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) Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 To Minh Chau et al 152 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 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 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 13.215 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) Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 FACTORS AFFECTING ON TOURIST SATISFACTION 153 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 Journal of Sustainability Science and Management Volume 18 Number 9, September 2023: 143-156 To Minh Chau et al 154 atmosphere, making tourists feel relaxed and Humanities and Social Sciences, 4, 2022 comfortable In contrast, a polluted environment https://doi.org/10.29013/EJHSS-22-4-67- 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 https://doi.org/10.30892/gtg.29203-478 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 Acknowledgement Business & Management, 7(1), 1-23 https://doi.org/10.1080/23311975.2020.18 The authors would like to thank the reviewers 41359 of this article The comments and contributions have helped to 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