The relationship between social network, perception of sustainability and tourist’s destination decision in Tay Nguyen

arch methods. The qualitative approach is used while interviewing experts related to the tourism field to adjust and supplement the scale. The quantitative method is used to test Cronbach's Alpha reliability, analyze EFA exploratory factor, analyze CFA confirmatory factor, set up a hypothesis testing model using the structural equation modelling. The result of this research validates the status quo that tourist's intentions have an active role in the relationship between social networks, awareness of sustainable development and decisions to choose destinations of tourists. The research has proved that the tourist’s intention has a significant impact on the relationship between social network, perception of sustainability and destination decision. The findings also help prove the correlation between social theory, action theory and technology acceptance model. The research provides a meaningful result for both tourist companies in Tay Nguyen and the tourist industry in Viet Nam regarding the utilization of a well-informed social network marketing strategy on the tourist decision. Thus, the tourist company should place its focus on sustainable plan and customer’s intention; the tourist should focus on the perception of sustainability to preserve the surrounding community and the tourist destination. 2 1.1. Research Context 1.1.1. Theoretical Framework There have been multiple types of research targetted at a tourist destination, social network and sustainability, respectively. However, each research has an individual, non- overlap goal in which the tested population varied among countries. According to Bose and the associate (2019) or Shankar (2018), tourists valued the diversification of service suppliers when choosing a destination. Before taking the trip, tourists often set certain expectations on the destination from primary or secondary information, specifically gathered from word-of-mouth, critics review, advertisement, past experiences, or the belief of community. According to Ramseook-Munhurrun and Naidooa (2014), the process of gathering and deciding a travelling destination would make the tourists dependent on the marketing on the social network. Hence, advertising on the social network could build a positive image in social perception, which would increase the attraction of that destination. In terms of the influence of social networks, Yazdanifard and Yee's (2014) research is typical research that laid a foundation for any further studies. Moreover, Twumasi and Adu-Gyamfi (2013) also claimed that online social interaction significantly influences the decision on the destination. According to Zhang & Zhang (2018), social network positively affects the relationship between the awareness of sustainable development and the plan of tourism companies and tourists. 1.1.2. Practical Context The tourism industry in Viet Nam has shown big development steps and become one of the most significant sources of foreign currency. In which in short-term, the tourism industry in Tay Nguyen has the potential to become a considerable factor contributing to that improvement. However, with the sustainable goal, tourist decision in Tay Nguyen should pay more attention to preserving the cultural heritage, environmental protection, cultural 3 value of the community. Hence, the listed factor should be taken into account when expanding the tourism industry in Tay Nguyen. The sustainable success of the tourism industry is guaranteed by the cooperation with other related parties with a mutual benefit (Vu Minh Ta, and Nguyen Van Tien, 2017). According to Keegan, B.J., and Rowley (2017), the social network is mostly used for entertainment and marketing purposes. For the above reasons, the author has decided to research “ The relationship between social network, perception of sustainability and tourist’s destination decision in Tay Nguyen „ in order to identify the correlation among related factors – between Social Network – SN, Sustainability Perception – SP and Destination Decision – DD. 1.2. Research Purpose The general purpose of the study is to identify the relationship between social network, sustainability perception and destination decision to suggest relevant management decisions for tourist companies, communities and tourists to build a well- developed business environment. The specific goals are listed as follow: First, the study proves the correlation between social theory, action theory and technology acceptance model. Second, the study identifies the intermediate role of tourist’s intention in the relationship between the social network and the perception of sustainability that leads to destination decision. Third, the study is the latest research on tourism in Tay Nguyen in terms of the relationship between the social network and the perception of sustainability that leads to destination decisions 1.3. Research Problem Question 1: Is there a relationship between social network, perception of sustainability and decision to make a travelling destination? 4 Question 2: How strongly are the correlation between social networks, perception of sustainability and decision to make a travelling destination? Question 3: What are the relevant suggestion made to benefit Tay Nguyen’s tourism? 1.4. Research subject and topic The research subjects are social networks, perception of sustainability concerning the decision to make a travelling destination. The research is conducted on Tay Nguyen’s tourists. Location: The research is conducted in Tay Nguyen. Time: Secondary data collected on Tay Nguyen’s tourism from 2016 to 2019. Field: The tourism industry. 1.5.Methodology The purpose of this study is to test the relationship between social networks and perceptions of sustainable development to tourism intentions and decisions to choose a visiting destination, conducting on the Tay Nguyen region. The research used both qualitative and quantitative research methods to build and test the measurement scale of the factor influence from the planning and testing phase. The primary data was collected from Google Docs tools, email, questionnaires. The data was analyzed using Cronbach's Alpha reliability, analyze EFA exploratory factor, analyze CFA confirmatory factor, set up a hypothesis testing model using the structural equation modelling. 1.6. Research Contribution This is the latest study on Tay Nguyen tourism, in which the writer has analyzed the statistical number to suggest a relevant management decision. The findings have shown the significant impact that utilization of a positive, well-informed social network marketing strategy would have on the development of the tourist industry, applicable to both tourist company in Tay Nguyen and Viet Nam in general. 5 1.7. Contents The study contains five chapters: - Chapter 1: Introduction - Chapter 2: Methodology - Chapter 3: Research Regression Model - Chapter 4: Analysis and Results - Chapter 5: Conclusions 6 2.CHAPTER 2: METHODOLOGY 2.1. Tourist Destination The concept of a tourist destination is a vast category. The destination can be a continent (according to the statistics of the World Tourism Organization such as America, Africa, Europe), which can be an area like ASEAN, a country or a locality, city, town. "A destination consists of many different stakeholders and can be linked to form a larger network" (UNWTO, 2019, p.14). Alrousan and the associates (2019) explained that destinations are places where every visitor chooses to come and stay for a while to experience certain unique features or aspects such as perceptions of identity, the attraction of several types of destinations. 2.2. Social Network A social network is defined by the behavioural patterns and the relationships among members of this network (Chung et al., 2016). Social networks can be used to predict the behaviour, structure and activities that occurred inside the network (Casanueva et al., 2016). Social network theory explains how networks work, analyzes complex sets of relationships in a network of individuals or organizations, and views individual attributes as less important than the relationships and their connection with other entities in the network (Panzer-Krause, 2019; Proskurnikov and Tempo, 2017). Social networks are often considered under the following points of view: Social networks from a perspective of many individuals (Egocentric Networks), networks viewed from a holistic perspective (Sociocentric Network / Whole Network), views from an angle many open systems (Open-Systems Network). 2.3. Sustainable Perception According to Almuhrzi, H. M. and Al-Azri, H. I. (2019), sustainable development is a process of fulfilling current demand without affecting the utilization of future 7 generations. Therefore, sustainable development is meant to create a better life for society as a whole in either the present or future. The three dimensions or "pillars" of sustainable development are now recognized as economic sustainability, social sustainability and environmental sustainability. It is crucial to appreciate that these three pillars are, in many ways, interdependent and can be mutually reinforced. Sustainable development is needed to create a balance between these three pillars 2.4. Tourism Intention The intention to travel is considered as a mental process, turning the driving factors into tourism behaviour (Jeon et al., 2017). Tourists' intention to travel can be investigated by developing insight into issues such as awareness or attitudes toward a destination with influences, limitations and levels of cognitive control for the resources needed to achieve targeted behaviour (Hsieh et al., 2016). 2.5. Relevant Theories The research applies the following theories: - The theory of social exchange; - Technology acceptance model - TAM; - The theory of social responsibility SR; - Stakeholder theory ST; - Rational action theory TRA; - Theory of planned behaviour TPB; - The theory of motivating agents - hindering PPF 2.6. Model and Research Hypotheses Through the related theories, the author proposed a research model, as shown in Figure 1 and the research hypotheses, as shown in Table 1. 8 Hình 1. Research Model Bảng 1. Research Hypothesis Hypothesis Factors Reference H1 Tourist Intention (TI) with a positive impact on the Destination Decision (DD) Gursoy & associates, 2010 H2 Sustainable Perceptions (SP) with impact on Tourist Intention (TI) Dolcemascolo & Martina, 2011 H3 Sustainable Perception (SP) with a positive impact on the Destination Decision (DD) Sharpley, 2010 H4 Social Network (SN) with an impact on Sustainable Perception (SP) of the tourist. Zhang & Zhang, 2018 H5 Social Network (SN) with impact on Tourist Intention (TI) Pietro & associates, 2012 9 H6 Social Network (SN) with positive impact on the Destination Dcision (DD) Jeng & Fesenmair, 2002; Almeida-Santana & Moreno-Gil, 2017 10 3.CHAPTER 3: RESEARCH REGRESSION MODEL Hình 2. Research Diagram 11 The proposed research model is based on the theory of destination theory, the theory of social networks, the theory of awareness of sustainable responsibility, the theory of intent. In which, there is an overlap result among the theories. The study used a combination of qualitative and quantitative research methods. Qualitative methods are implemented through face-to-face interviews with each guest, such as teachers who teach in tourism, directors, managers at various levels in travel companies. The author conducts in-depth discussions and interviews with experts who are leaders, managers of tourism organizations, businesses, officials and lecturers. The research model is evaluated and built to standardize the theoretical model. The interview results have been recorded, developed and adjusted to form a preliminary scale that helps preliminary quantitative research to have precise results. The preliminary questionnaire used in this step emailed the survey, distributed the live questionnaire and interviewed via Google docs with sample size n = 137. The scale of the preliminary quantitative study was meant to assess the reliability using Cronbach's Alpha reliability coefficient and EFA discovery factor analysis. After this step, a full scale will be used for proper quantitative research. Conducting quantitative research by direct survey method, sending questionnaires via email, social networks, surveys on Google Docs with 557 samples. Assessing the suitability of the measurement model using Cronbach’s Alpha reliability coefficient, EFA discovery factor analysis, CFA confirmatory factor analysis and SEM linear structure model. Conventional scale: 1 - Very few, 2 - Little, 3 - Moderate, 4 - Many, 5 - Very much. . 12 4.CHAPTER 4: ANALYSIS AND RESULTS 4.1. Statistical Results Descriptive statistical results are presented in Table 2. In particular, female tourists make up the majority with 59.6%, tourists aged 26 to 35 with a stable job, hence, explains the high travelling demand (39.9% of the four groups); tourists with intermediate level or lower and colleges, universities account for the majority with nearly 80% of the number Table 2. Descriptive Statistic Results n = 557 Frequen cy Percentage Gender Male 225 40,4 Female 332 59,6 Age 18-25 108 19,4 26-35 222 39,9 36-50 128 23,0 Above 50 99 17,8 Educatio n Level Intermediate or lower 198 35,5 College and University 250 44,9 Prograduate 109 19,6 13 4.2. Results of reliability analysis The conceptual Cronbach's Alpha reliability coefficient must reach a value of 0.6 or higher and the correlation coefficient of the total variable of 0.3 or higher to prove the reliability or significance of the scale. The results of all Cronbach’s Alpha coefficients and the total correlation coefficients are satisfactory (Table 3) and should be retained for EFA discovery factor analysis. Table 3. Results of reliability analysis Variables Correlated Total Variable Cronbach's Alpha (excluded unreliable variables) Social Network: Cronbach’s Alpha = 0,939 SN1 0,898 0,914 SN2 0,847 0,923 SN3 0,796 0,933 SN4 0,766 0,938 SN5 0,878 0,918 Sustainable Perception: Cronbach’s Alpha = 0,800 SP6 0,681 0,716 SP7 0,609 0,751 SP8 0,539 0,785 SP9 0,624 0,744 Tourist Intention: Cronbach’s Alpha = 0,871 14 TI10 0,808 0,770 TI11 0,723 0,846 TI12 0,732 0,839 Destination Decision: Cronbach’s Alpha = 0,890 DD13 0,702 0,871 DD14 0,702 0,871 DD15 0,653 0,879 DD16 0,654 0,879 DD17 0,807 0,858 DD18 0,744 0,864 4.3. Results of exploratory factor analysis Results of EFA discovery factor analysis in Table 4 showed that the KMO coefficient reached 0.861 (very good), Sig value. Of Barlett’s test reached 0,000 (<0.05), which is satisfied to conduct discovery factor analysis. There are four extracted factors (with Eigenvalue value greater than 1) with a total variance of 71,444% (greater than 50%), the composition of the variables does not change, the load factor of all variables is greater than 0.500 (satisfactory bridge). Table 4. Results of exploratory factor analysis Variable Factors 1 2 3 4 SN1 0,938 15 SN5 0,916 SN2 0,880 SN3 0,824 SN4 0,792 DD5 0,870 DD6 0,796 DD2 0,764 DD1 0,755 DD3 0,694 DD4 0,691 TI1 0,930 TI3 0,798 TI2 0,775 SP1 0,801 SP4 0,729 SP2 0,699 SP3 0,603 Eigenvalue 4,764 3,541 2,478 2,077 Accumulated Variance (%) 26,467 46,140 59,908 71,444 16 KMO 0,861 Barlett’s Test 0,000 4.4. Result of confirming factor analysis According to the results of Table 5, all the evaluation indicators are suitable. The conclusion resulted from the measurement model is consistent with actual data. Table 5. Result of confirming factor analysis Index Test Statistic Critical Value Results Sig. (χ2) 0,019 < 0,05 Suitable χ2/df 1,275 ≤ 5 Suitable TLI 0,993 > 0,900 Suitable CFI 0,994 > 0,900 Suitable RMSEA 0,022 < 0,05 Suitable 17 Figure 3. Result of confirming factor analysis 4.5. Results of linear structure analysis The results of assessing the suitability of the linear structure model are presented in Figure 4. The number of correlations between the CFA affirmative factor model and the SEM linear structure model is the same (six linkages), and the level of the relationships are nearly the same, so the values to assess the suitability level between the 18 CFA affirmation factor model and the SEM linear structure model are similar; however, the Regression coefficient among the independent variables are different. Figure 4. Results of linear structure analysis 4.6. Hypothesis Test The results of the hypothesis test, according to Table 6, are as follows: H1: There is a positive relationship between (TI) and (DD), with r = 0,187 and p-value = 0,000 < 0,05. H2: There is a positive relationship between (SP) and (TI), with r = 0,222 and p-value = 0,007 < 0,05. H3: There is a positive relationship between (SP) and (DD), with r = 0,123 and p-value = 0,015 < 0,05. 19 H4: There is a positive relationship between (SN) and (SP), with r = 0,057 and p-value = 0,030 < 0,05. H5: There is a positive relationship between (SN) and (TI), with r = 0,174 and p-value = 0,000 < 0,05. H6: There is a positive relationship between (SN) and (DD), with r = 0,061 and p-value = 0,017 < 0,05. Table 6. Hypothesis Test Test Statistic S.E. C.R. p-value SP < SN 0,057 0,026 2,167 0,030 TI < SN 0,174 0,041 4,188 *** TI < SP 0,222 0,082 2,704 0,007 DD < SN 0,061 0,026 2,387 0,017 DD < SP 0,123 0,05 2,434 0,015 DD < TI 0,187 0,040 4,117 *** 4.7. Multiple Regression Model Analyzing the multiple regression model in SEM aims to determine whether the influence between each independent factor and the dependent factor is different among groups (demographic variables). Consider the variable model and the invariant model (in part). In the variable model, the estimated parameters in each model of the groups are not constrained. In the invariant model, the measurement component is not constrained, but 20 the relationships between the concepts in the research model are equally binding for all groups. A Chi-square test is used to compare two models. Hypothesis: H0: There is no difference between the Chi-square of the variable model and the invariant model H1: There is a difference in Chi-square between the variable model and the invariant model. If the Chi-square test shows that there is no difference between the invariant model and the variable model (Sig.> 0.05), the invariant model will be selected (higher order of freedom) conversely, if the Chi-square difference is significant between the two models (Sig. <0.05) then choose the variable model (with higher compatibility). Table 7 will summarize the results of the multiple regression analysis of gender variables, age and education level. Table 7. Multiple Regression Model Factor Model χ2 df Sig. Gender Variable 260,533 258 0,130 Invariant 270,414 264 Difference 9,881 6 Age Variable 549,191 516 0,612 Invariant 564,914 534 Difference 15,723 18 Education level Variable 937,250 903 0,852 Invariant 964,528 939 21 Difference 27,278 36 Sig value. Represents the Chi-square difference of all three variables is higher than 0.05; hence, we fail to reject H0, with no sufficient evidence to support H1, there is no difference between the invariant model and the variance model. Therefore, the invariant model will be chosen for the analysis process. There was no difference in the effect of the independent variables on Tourist Intention and Destination Decision among different sex groups, age groups and education levels. 4.8. Research Results The results have overcome the disadvantages and limitations of the previous related studies: - Conduct qualitative and quantitative research. - The research sample is quite reasonable with standard demographic variables. - Values and research factors are satisfactory. - Research results are implemented and applied in a wide geographical area (Central Highlands includes five provinces). - Perform with SEM linear structure analysis method. 22 5.CHAPTER 5: CONCLUSION 5.1. Policy Implications In terms of Social Network: In the hospitality and tourism industry, social networking sites are one of the vital tools that play an essential and beneficial role as consumers seek information to make decisions related to travel and hotels through sharing experiences (Yazdanifard, R., and Yee, LT, 2014). Here are five suggestions to apply to brand promotion and attract tourists: (1) Create and build a channel for visitors to for consumer feedback (2) Increase the level of sharing/liking online (3) Focus on customer service (4) Adjustment of business model (5) Change loyalty/loyalty programs. In terms of Sustainable Perception: The study has proved a positive correlation between social networks and sustainable development. The tourism destination management unit also needs to build and spread the image of sustainable development through social networks to promote tourists' destination decisions. Sustainable tourism development should minimize costs and maximize benefits to the natural environment and local communities. Sustainable tourism should be planned with three main goals: income generation, environmental protection and community development. It is necessary to combine sustainable tourism with local communities, sustainable tourism with local authorities, sustainable tourism with tourism, sustainable tourism with tourists. In terms of Tourist Intention: 23 The research results show that there exists a relationship between the social network and tourist intention, as well as a relationship between sustainable perception and tourist intention. In particular, the relationship between sustainable perception and tourist intention is the most significant, with a positive correlation. Thus, the study recommends managers in the industry to study the design of programs to increase visitor awareness about sustainable destination development, thereby increasing the intention to visit the destination. In other words, the administrative implications of the Sustainable Development factors have a somewhat practical impact on the tourism industry. In terms of Destination Decision: The author's research results have confirmed that tourists who choose tourism destinations in the Central Highlands are directly affected by the Tourist Intention factor and are indirectly affected by the social network and sustainable perception factors. The destination decision in general and tourist destinations in the Central Highlands, in particular, considerably depends on tourist intention. From that intention, many factors can impact this driving ideal into a particular destination. The implication is that tourism businesses and organizations need external influences, such as stimulus programs and promotion to attract visitors According to other researches, factors that make the destination of a tourist destination attractive include amenities, facilities, infrastructure, facilities, transportation and guest services. Some other views include the core characteristics, the originality of the destination such as climate, ecosystems - biological environment, culture and architecture. traditional Hence, all of the mentioned above will help create a fulfillment recreational destination. 24 5.2. Conclusions Using qualitative and quantitative research methods, the study has achieved its objectives and answered three mentioned questions, namely: - Determine the relationship between social network, perception of sustainability and decision to make a travelling destination. - Determine the strength and direction of the correlation between social network, perception of sustainability and decision to make a travelling destination. - Present the management implications to promote Tay Nguyen’s tourism industry. The author also recommends government agencies and tourism companies in the Central Highlands region to consider implementing the administrative implications of the study to improve the performance of local tourism. Tourism management companies implement suggestions to improve operational efficiency. The off