Research on factors affecting the satisfaction of the community tourists in the Northwestern

The main data analysis method in the author's study is regression analysis.

Large sample sizes are required for this method of analysis. Currently there are many

grounds for determining the size of a sample:

Based on research by Hair, Anderson, Tatham and Black (1998) for reference

on expected sample size. Accordingly, the minimum sample size is 5 times the total

number of observed variables. This is a sample size suitable for research using factor

analysis (Comrey, 1973; Roger, 2006). n = 5 * m. So if based on this basis, the author

must survey at least n = 46 * 5 = 230 community tourists.

For multivariate regression analysis: the minimum sample size needed is

calculated using the formula n = 50 + 8 * m (m: number of independent variables)

(Tabachnick and Fidell, 1996). Thus, based on this basis, the author will have to

survey at least 90 community tourists

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in the Northwest region in terms of: Climate and soil potential; Potential in indigenous culture, specialties in the Northwest. (iii) Analyze the current status of the community tourism development in the Northwest of the community tourism destinations: Number of visitors and tourism revenue; facilities for community tourism; human resources for community tourism; and tourism promotion and promotion. (iv) Combine the analysis of the current situation of cultural heritage conservation with the community tourism development in the Northwest. The accessible cultural heritages: Physical cultural heritage; heritage of historical artifacts, landscapes’ history and culture, and intangible cultural heritages. 2.1.2 Research on community tourists’ satisfaction Suthathip Suanmali (2014) studied the factors affecting tourist satisfaction in the northern provinces of Thailand. The study was conducted in a northern Thai province, Chiang Mai, where there are many natural and cultural attractions. Influencing factors are determined using statistical techniques. Primary data was collected through distributing random questionnaires to foreign tourists visiting Chiang Mai. Quantitative data was then analyzed using factor analysis and multiple regression analysis to identify important factors. Research results showed that the most important factor affecting visitor satisfaction was the cost of stay, the next most important factors were hospitality, natural landscape and infrastructure. Naidoo et al. (2011) conducted a study aimed at examining the community tourists’ assessment of natural tourism on the island of Mauritius. Research was carried out to determine the factors influencing the satisfaction of the community tourists for nature tourism in Mauritius. Factors mentioned to consider the impact on the community tourists’ satisfaction include: Infrastructure, prices, indigenous culture, safety, and natural resources on a scale developing from Parasuraman's scale of service quality. Research methods applied to the research include: test the reliability of the Crobach's Alpha scale, exploratory factor analysis, linear regression. The research results were conducted through interviews with 600 community tourists showed that the factors in the research model have statistical significance and impact on visitor satisfaction, in which factors Natural resources have the strongest impact. 2.1.3 Researchgap First, the community tourism’s content - The studies have not yet analyzed and assessed the potential of developing the community tourism based on a full approach include: The potentials on climate 9 and soil; indigenous cultural potentials, traditional festivals and Northwest specialties. Because many works are only done in tourist destinations with a narrow scope such as: Cam Thach seven-acre coconut forest, Hoi An; Bidup National Park - Nui Ba; Garhwal Himalaya of Uttarakhand State; Nam Cat Tien National Park ... Most of the studies are still discrete for each type and locality, each tourist destination without going into general solutions to improve the quality of community based tourism, contribute to the community tourism development in the Northwestern region associated with preserving and promoting the ethnic cultural values in the context of integration. Second, the content of the satisfaction of tourists with community tourism The studies of domestic and foreign scholars related to the satisfaction of tourists with the type of community tourism are still theoretical, just stop at the level of general and academic research. There are many detailed surveys aimed at examining the factors influencing the satisfaction of the tourists at community tourism destinations in the Northwest. The number of research projects on community tourism satisfaction in the Northwest is still small. Therefore, the studies have not almost clearly reflected the cultural characteristics, customs and practices of each locality in the Northwestern provinces. Studies on tourist satisfaction with the community tourism have not clearly assessed the impact of each factor on the satisfaction of tourists, making solutions still general, low feasibility if applicable to the community tourism in the Northwest. There has not been a study to comprehensively assess the impact of indigenous culture on the satisfaction of the tourists at community tourism sites in the Northwestern mountainous region. The studies have not synthesized the attributes of indigenous cultures in the Northwest. Therefore, solutions to develop the community based tourism based on indigenous cultural factors have not been mentioned. In the Northwest mountainous region, this form of community tourism is developing. However, although there are many studies on assessing service quality as well as the satisfaction of community tourists, most studies focused on only one festival or a few cultural activities in a tourist destination. In addition, indigenous cultural factors are a characteristic feature in the community tourism in the Northwest, but there are no studies to assess in detail and comprehensively the impact of indigenous cultural factors on satisfaction of community tourists. Therefore, in the dissertation, the author will go into depth research on the impact of indigenous cultural factors on the satisfaction of the community tourists in the Northwest, this is a new point of the study compared to other announced studies. In summary, with gaps in the research on tourism, community tourism related to the dissertation mentioned above, the author of the dissertation will conduct a survey 10 of the the community tourism data in the Northwest region, where there is a lot of potential to develop form of the community tourism, here the components of indigenous culture are very rich and diverse, from which the influence of these factors can be generalized the satisfaction of the community tourists with the type of community tourism in the Northwest of our country with the features of indigenous culture. 2.2. Theoretical basis for destination quality, community tourism and tourist satisfaction 2.2.1. Theory of customer satisfaction in the service industry Tourists' satisfaction with community tourism services is the tourist's emotional state about the tourism products/ service determined on the basis of perceived actual experience compared to previous expectations using the community tourism products/ services. Through experiencing the service at the community tourism destination, visitors will feel the service and compare it with other destinations, thereby making comments and reviews about the community tourism destination. 2.2.2 The quality of the destination and the satisfaction of tourists 2.2.2.1 Features related to destination quality 2.2.2.2 The relationship between destination quality and tourist satisfaction The analysis of the author showed that perceived quality has a strong impact on visitor satisfaction. However, most of the studies only approach the concept of the overall perceived quality of tourists to destinations, but have not tested the different components of destination quality visitor satisfaction. 2.2.3 Community tourism 2.2.3.1 The concept of the community tourism Synthesizing from many theories of organizations and researchers, within the scope of this dissertation, the community tourism is understood as follows: Community tourism is a type of tourism in which local communities play the main role and the local government plays a supporting role in the effective introduction, organization, management and exploitation of tourism resources in order to bring about economic benefits and protect the general environment. 2.2.3.2 Characteristics of the community tourism Community tourism is a type of tourism where the local community is the subject directly participating in activities. 2.3 Research Model 2.3.1 Inheritance research model 2.3.1.1 Research model of Ismail et al (2016) 2.3.1.2 Research model of Naidoo et al (2015) 2.3.1.3 Research model of Mohamadia et al (2016) 11 2.3.1.4 Research model of Ly Thi Tuyet et al (2014) 2.3.1.5 Research model of Hoang Trong Tuan (2015) 2.3.1.6 Research model of Nguyen Hoang Phuong (2017) 2.3.2 Proposed model and research hypothesis 2.3.2.1 The proposed model Thus, based on the opinions drawn from discussions with experts and researchers along with the inheritance of published research models, the author proposes a research model for the dissertation as follows: H1 . H2 H3 H6 H4 H5 Picture 2.7: The proposed model 2.3.2.2 Research hypothesis Indigenous culture with quality of community tourism destinations Hypothesis H1: Indigenous culture has a positive influence on the quality assessment of the tourist destination when participating in the community tourism products. Sightseeing environment with community tourism destination Hypothesis H2: The sightseeing environment positively affects the assessment of the quality of the tourist destination when participating in the community tourism products. Natural attraction to the community tourism destination Hypothesis H3: The attractiveness of nature has a positive influence on the quality assessment of the tourist destination when participating in the community tourism products. Infrastructure with community tourism destination Hypothesis H4: Infrastructure has a positive influence on the quality of the tourist destination's assessment when participating in the community tourism products. Community tourists’ satisfaction The quality of the community tourism destination Service price at the tourism site Indigenous culture Natural attraction Infrastructure Sightseeing environment Demographic characteristics of community tourists 12 Prices of service at tourist sites with community tourism destinations Hypothesis H5: Service prices at the tourist destination have a positive influence on the quality of a tourist destination's assessment when participating in the community tourism products. Quality of community tourism destination with community tourist satisfaction Hypothesis H6: The quality of the the community tourism destination positively affects tourist satisfaction when participating in the community tourism. CHAPTER 3: METHODOLOGY 3.1 Research background 3.1.1 Northwest natural features - Geographical location: The Northwest region is the western mountainous region of northern Vietnam, sharing the border with Laos and China including 4 provinces: Hoa Binh, Son La, Dien Bien and Lai Chau. The terrain is mostly hilly and mountainous, with high slopes. 3.1.2 Socio-economic situation in the Northwest - This is an area where over 20 ethnic minorities live, life is still difficult. Over the past years, the economic structure in the Northwest region has moved slowly, with low efficiency and limited competitiveness. The conditions for socio-economic development still face many difficulties and challenges. 3.1.3 Typical tourism products in the Northwest Including specific types of tourism: Adventurous sports tourism, research and discovery tourism, exploration tourism, experiencing traditional cultural values of ethnic minorities in highland areas, ecotourism agriculture. 3.1.4 Selecting the research site The author selected the study site including 4 provinces: Hoa Binh, Son La, Dien Bien, Lai Chau. 3.2 Selecting the research methods The author chooses qualitative research methods combined with quantitative research methods. Selection of appropriate statistical analysis tools to solve the problems posed by the study based on survey data obtained from reality in the Northwestern region. The dissertation used quantitative research methods to analyze and measure the satisfaction of the community tourists. The thesis used 7-point Likert scale to analyze and measure the factors. With the EFA test analysis tool to group variables into latent variables and eliminate inappropriate variables, CFA tool to reconfirm the impact relationship (one way or multidimensional) and measure the degree of this system, 13 groups of factors affecting the satisfaction of the community tourists. The main tool of the factor analysis model is the quantitative assessment and the statistical hypothesis test. Factor analysis skills supported by SPSS statistical software. 3.3 The research process Picture 3.1: The research process 3.4 The method of data collection 3.4.1 Collect secondary data The method of data collection is done through the collection of secondary data from previous studies at home and abroad, reports of the Department of Culture, Sports and Tourism, Provincial Statistical Office and Vietnam national administration of tourism. Linear structure model Analyse factor EFA, CFA Cronbach Alpha Questionnaire development Expert interview Research method Theoretical basis Aim of the study Determine the topic of the study Recommendations Assess the tourist’s satisfaction Quantitative research Qualitative research 14 3.4.2 Collect primary data The author collected data by interviewing the the community tourism sites in the Northwestern region using survey questionnaires. Before conducting the survey, the author contacted the local community tourism destinations including: Hoa Binh; Son La; Dien Bien; Lai Chau, the author stated that the purpose of the survey and the confidentiality of the information provided are for the purpose of research. The data survey period was from September 6th, 2017 to April 28th, 2018. To conduct the official data survey for the study, the author conducted guidance for 10 plus authors on how to distribute and collect survey questionnaires, these are people with certain communication skills and experience in the tourism field, specifically: In Lai Chau, there are 1 tour guide and 1 city member of the Tourism Promotion Center of Lai Chau Province; In Dien Bien, the author collaborated with 1 homestay guesthouse owner and 1 member of the tourist promotion center of Dien Bien province; In Son La employed 2 senior business administration students of Tay Bac University and 1 member of the tourism promotion center. In Hoa Binh, 2 tour guides and 1 homestay business owner were used to distribute and collect survey questionnaires. Survey locations and results are as follows: In Lai Chau, the community tourism sites were surveyed: Ban Hon; Na Luong village; Gia Khau village; Sin Suoi Ho village and Vang Pheo village. In Son La, the community tourism sites were surveyed: Na Bai; Ang village; Bo village; Na Tau village and Hum village. In Hoa Binh, the survey was conducted at the community tourism sites: Giang Mo village; Lac village; Ai group; Ke group; Da Bia group. In Dien Bien, the survey was conducted at the community tourism sites: Him Lam 2 village; Men village; Na Ten village; Nam Can village; Noong Chun village; Che Can village and Chi Luong village. Table 3.3. Survey results Province Delivered Questionaires Received Questionaires Unanalysed Questionaires Analysed Questionaires Lai Chau 168 116 15 101 Đien Bien 256 198 23 175 Son La 185 138 17 121 Hoa Binh 203 169 21 148 Total 812 621 76 545 Source: The author summarised Survey results are collected as follows: Total number of survey questionnaires emitted: 812 15 Total number of questionnaires collected: 621 Total number of questionnaires not included in analysis due to lack of many contents: 76 Total number of questionnaires included in the analysis: 545 (The number of these samples will be explained in detail in section 3.6.5) 3.5 Methods of analysis and data processing 3.6 Design of quantitative research 3.6.1 Quantitative research objectives 3.6.2 Design of quantitative research The research process of the dissertation is done according to the steps summarized in the table below. Table 3.4. The order of implementation the quantitative research Steps Contents 1. Construct the scales - Through the research review process, choose the appropriate scales for variables, for the Likert scale, choose the scale with the most suitable indicators for each variable, each research context. - Most scales are inherited from previous studies in English, so the scale is translated into Vietnamese, then asked someone fluent in English to translate back into English, then asked someone else to compare. These 2 translations are to ensure that the content is not misplaced, causing confusion in the translation process. 2. Evaluate the scale - Ensure the validity Conduct discussions, interviews with experts (lecturers, managers, ... knowledgeable about the research content) to ensure that the respondents do not misunderstand, understand not all the content of the question, remove or correct some of the rare questions that are mentioned, which can be misleading. - Ensure the reliability + After ensuring "validity", issue questionnaires for experimental research. + For each variable, it is necessary to ensure Cronbach Alpha index> 0.7 to ensure that the scale is stable and reliable through the measurements. + If not ensure, it is necessary to review steps (1) overview of the scale, (2) translation, (3) expert discussion, (4) remove a few indicators of inappropriate. 3. Formal research - Complete questionnaire for official distribution. - Choose a delivering pattern and collect data 4. Data analysis - Using software SPSS 20 and AMOS 20 to analyze data, analyze models. Source: The author summarised 16 3.6.3 Build scales of variables Include 7 scales: Destination quality scale (CLDD symbol); Scale of visitor satisfaction (Symbol SA); Scale indigenous culture (Symbol of VHBĐ); Scale of the visiting environment (Notation of MTDL); Scale of infrastructure (Symbol of infrastructure); Natural gravity scale (Symbol HDTN); The scale of service prices at the destination (GC symbol) is measured through comments and uses the 7-point Likert Scale to measure. 3.6.4 Evaluate the reliability of the scale Measurements with Cronbach Alpha coefficients of 0.63 or more are considered acceptable. Measurements with Cronbach Alpha coefficients from 0.7 to 0.8 are usable. Many researchers believe that a reliable measure of 0.8 to nearly 1 is a good measure (Joseph F Hair et al., 1998). 3.6.5 Sampling method The main data analysis method in the author's study is regression analysis. Large sample sizes are required for this method of analysis. Currently there are many grounds for determining the size of a sample: Based on research by Hair, Anderson, Tatham and Black (1998) for reference on expected sample size. Accordingly, the minimum sample size is 5 times the total number of observed variables. This is a sample size suitable for research using factor analysis (Comrey, 1973; Roger, 2006). n = 5 * m. So if based on this basis, the author must survey at least n = 46 * 5 = 230 community tourists. For multivariate regression analysis: the minimum sample size needed is calculated using the formula n = 50 + 8 * m (m: number of independent variables) (Tabachnick and Fidell, 1996). Thus, based on this basis, the author will have to survey at least 90 community tourists. According to Burns and Bush (1995), there are three factors that need to be considered when considering sample size: - Number of changes in the population; - Accuracy desire; - Allowable confidence level in estimating the overall value. Therefore, the formula for estimating the sample size to achieve 95% accuracy at 95% confidence is: N = Z2 (pq) / e2 = 1.962 (0.5 * 0.5) / 0.052 = 385 Inside: - N is the sample size; - Z standard deviation with allowable confidence level (95%); - Estimated value of change in population (50%) (according to Burns and Bush, 1995, the number of changes in the population of 50% is often indicated in social studies, so studies in practice often choose 50% of the p-value because this is the value that guarantees the safety level in determining the sample size); - q = 100 - p; 17 - e permissible error (level of error): + - 5%. Thus, according to the author, to ensure the analysis requirements, the minimum sample size must reach 385. In the study, the author conducted a survey in 4 provinces: Dien Bien, Lai Chau, Son La, Hoa Binh to ensure that the number of questionnaires collected is enough for the study, the author conducted a survey of 812 community tourists by distributing the questionnaires directly to each of the community tourists with the support and assistance of the community collaborators at local community tourism sites. At the end of the survey, the author collected 621 survey questionnaires, of which 76 questionnaires could not be used (due to the lack of content and lack of content), the remaining 545 questionnaires were put in the analysis. 3.6.6 Data analysis method This study aims to evaluate socio-economic statistics in which a number of methods are used: Descriptive statistics, exploratory factor analysis (EFA), confirmation factor analysis (CFA), tissue analysis, linear structure configuration (SEM). Descriptive statistics are used to exploit basic information about the variables in the observed sample. Thereby, we can test the normal distribution of observed variables to apply for the next analysis. The author used exploratory factor analysis (EFA), which is a statistical method to reduce the set of variables used into a set of variables (called factors) less (after remove the garbage variables), to make them more meaningful but still contain the information of the original set of variables. In the preliminary study used (EFA) and continued to apply in official research to check study consistency. Factor analysis confirms that CFA is one of the techniques of SEM linear structure model. CFA allows us to test how well the observed variables represent factors. CFA is the next step of EFA, CFA is used to reconfirm the univariate, multivariate, convergence value and differentiation of the scale. In hypothesis testing and research model, the SEM linear structure model allows us to combine implicit concepts with their measures and can consider measurements independently or in combination with theoretical model at the same time. Therefore, the SEM analysis method has been widely used in the social sciences in recent years and is often referred to as the second generation data analysis method (Hulland, 1996). CHAPTER 4: THE RESULTS 4.1 Research results of the current situation 4.1.1 Current situation of community tourism development in the Northwest 4.1.2 Current situation of cultural conservation combined with regional community tourism development in the Northwest 4.2 Research results of factors affecting tourist satisfaction with the type of the community tourism in the Northwest 4.2.1 Descriptive statistics of the survey object 18 4.2.2 Evaluation of scale reliability 4.2.2.1 Verify the reliability of the scale with Cronbach-alpha In general, the results showed that the scales are highly reliable, when the Cronbach-alpha coefficients are all greater than 0.7 in the first test with each scale, the variable-total correlation of the observed variables representing a concept are greater than 0.4, showing that these variables correlate well with the overall scale, and these variables are suitable to represent each concept of the sightseeing environment , infrastructure, prices, indigenous culture, natural attraction, satisfaction. With reliability, the scales are suitable to use to represent the concepts of each scale in factor analysis and regression. 4.2.2.2 Exploratory Factor Analysis (EFA) scale of independent variables According to the analysis results, the coefficient KMO = 0.892 ensures reliability for factor analysis, the coefficient of variance extracted = 65.37 shows the variation of 5 factors, representing 65.37% of the variation bias of the whole. This is a high percentage that shows the obtained data converges quite well, representing well for the 5 factors given from the analysis. 4.2.2.3 Exploratory Factor Analysis (EFA) scale of dependent variables 4.2.2.4 Confirmation factor analysis The results of CFA confirmed factor analysis show that the standardized critical model has 686 degrees of freedom, the criteria measuring the suitability of the mod

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