The Impact of Internet Usage on Trip Planning: the case of foreign tourists in Vietnam

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College of Management

I-Shou University

Master Thesis

The Impact of Internet Usage on Trip Planning:

The Case of Foreign Tourists in Vietnam

Advisor: Dr. Yu-Chen Lan

Co-Advisor: Dr. Wan-Ching Chang

Graduate Student: Phan Thi Huynh Mai

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Acknowledgements

I would like to say thank to my thesis supervisor Dr. Yu-Chen Lan of the Department of Public Policy & Management at I-Shou University. He helps me with all of his willingness whenever I had questions about my research or writing. He consistently allowed this paper to be my own work but steered me in the right direction whenever he thought I needed it.

I would also love to give thanks to my co-supervisor Dr. Wan-Ching Chang of the Department of Tourism at I-Shou University. Without her passionate participation and helpful supporting, I could hardly to complete my thesis successfully.

Furthermore, I would appreciate to the participants who did an effective and amazing work on my thesis survey. Without their participation and input, the validation survey could not have been successfully conducted.

Finally, I am willing to express my very profound gratitude to my parents and to my amazing partner for providing me with unfailing support and continuous encouragement throughout my years of study and through the process of researching and writing this thesis. This accomplishment would not have been possible without them. Thank you!

Author Trish Phan.

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Abstract

The dramatic changes in technology during the past few decades have had an impact on the tourism industry. The development of the internet helped to increase the platform of tourism, giving tourists an opportunity to easily access travel information and travelers‟ communities. This study aims to investigate the influence of internet usage on tourism products, especially for the case of the international tourists of Vietnam tourism. This research aims to find out the significant important role of the internet on tourism products to contribute to better tourism development.

Quantitative research has been used to determine the outcomes of this study, the survey instrument was a structured questionnaire. The questionnaires were designed based on the past studies related to the variables of the study. The questionnaire consisted of three sections which involved 37 questions.

Descriptive and regression analysis were performed to approve the three hypotheses of tourists „behavior on tourism products. Frequency analysis for “tourists‟ usage of the internet” and demographics section. Findings indicate that the internet does have an important role to tourism development. It is shown that the tourists' behavior which consisted three sections (pre-travel, during travel, and post-travel), positively influence on tourism products. It is also revealed that the tourists‟ demographics have significant differences on tourism products. Moderator variables of “the usage of the internet” section did increase the impact of the tourists‟ behavior on tourism products.

Limitation and recommendations were given for the future research for better results to these kinds of studies.

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List of Tables

Table 1: Survey scale reliability ... 20

Table 2: Profile of respondents which has significant differences. ... 23

Table 3: The tourists‟ behavior in the pre-travel section. ... 25

Table 4: The tourists‟ behavior in the during-travel section. ... 25

Table 5: The tourists' behavior in the plan on the post-travel section. ... 26

Table 6: The tourists‟ behavior in the purchasing decision on tourism products session ... 26

Table 7: Tourists‟ behavior in four sections (PRE, DU, POS, PD). ... 27

Table 8: Coefficients Variables Resulting from Multiple Regression Analysis (PRE, DU, POS). ... 28

Table 9: Regression analysis results for the first three hypotheses. ... 28

Table 10: Respondents‟ Usage of the internet ... 29

Table 11: Results of Moderated Regression analysis for the variable of “Internet ... 31

usage for making travel plan” ... 31

Table 12: Results of Moderated Regression analysis for the variable of “Information trusting level”. ... 32

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List of Figures

Figure 1: International Tourists‟ Arrivals and Spending in Vietnam. ... 3

Figure 2: A conceptual model for the definition of virtual community. ... 5

Figure 3: Alternative model for the functions of virtual communities from the users‟ perspective”. ... 6

Figure 4: The conversation prism in Web2.0. ... 7

Figure 5: Major factors affecting consumer buying behaviour. ... 11

Figure 6: A typology of motivators in tourism. ... 12

Figure 7: Internal and External determinants affect tourists‟ decision. ... 13

Figure 8: The linear five-stage model of tourist purchasing behaviour. ... 13

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Chapter 1. INTRODUCTION

1.1 Research Background

The dramatic changes in technology during the past few decades have had an impact on the tourism industry. The internet has also become an important information source for tourists. The development of the internet helped to expand the platform of tourism, giving tourists an opportunity to easily access travel information and travelers‟ communities. Throughout the time, new economy represents a new world, where human work with their brain power instead of muscle strength as a result of the effect created by the information technologies and internet (Vantansever & Yildiz, 2014). Moreover, electronic ticketing, use of the social networking sites for promotion and sales of tourism products and other similar activities lead to important development in the field of tourism activities.

The innovation of the electronic word-of-mouth helps to clarify mostly the intangibility of tourism products (Ip et al., 2012). The internet plays an important role in planning, evaluating, comparing, sharing or even exposing in tourism among internet participants. The internet helps to expand the functions of the social networking sites sharing travel knowledge and travel experience among the virtual members.

According to the Vietnam National Administration of Tourism (Vietnamtourism.com), international tourists who visited Vietnam in October 2014 estimated 812,017 arrivals, increased 23.2% over the same period last year, saying that tourism is the most developed industry of Vietnam economy nowadays. The biggest social networking site in Vietnam is Facebook, which has 40 million Facebook subscribers and 42% penetration according to the data collected in June 2016 of the Internet World Stats (Global Web Index, 2014).

Despite the fact that there are a number of studies researched the role of the social networking sites related to tourism management (Hays et al. 2013; Kietzmann et al. 2011; Michaelidou et al.2011), there is necessary for research on the impact of internet usage on trip

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planning (the case of foreign tourists in Vietnam). This topic focuses on the behavior of the tourists involving three behavioral stages, including pre-travel, during-travel, and post-travel.

1.2 Research Objectives and Research Questions.

1.2.1 Research Objectives

The objective of this paper is to analyze the tourists‟ behavior of the internet usage before, during and after their trip. Besides, trying to shed light on the dimensions of tourists‟ behavior influence on their trip planning, and to prove the significant role of the internet in marketing tourism business.

1.2.2 Research Questions

1. How does the tourists‟ usage of the internet affect their behavior on purchasing decision of tourism products in Vietnam?

2. How do the tourists‟ characteristics/demographics affect purchasing decision of tourism products in Vietnam?

3. How does each factor of the tourists‟ behavior (pre-travel; travel; post-travel) affect the purchasing decision of tourism products?

1.3 The Significance of the Study

This research sheds more light on the link between the virtual community and purchasing decision of the international tourists on tourism products in order to contribute to better tourism business in Vietnam. With the finding of this study, it can help Vietnamese policy makers use as consistent and efficient tools for developing the international tourists‟ market. Also, it is designed to help tourism businesses develop their business strategy as well as marketing strategy, easily approach to the target segment, improve the quality of products or services, and increase competitive advantages in developing tourism in Vietnam.

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Chapter 2. LITERATURE REVIEW

2.1 The Development of Vietnam Tourism.

There are 7.9 million foreign visitor‟s arrivals in 2014, who contributed almost $7.9 billion or 60 percent of tourism revenue last year. More than fifty percent of them came to Vietnam based on recommendations from relatives and/or friends, while some of them took their trips after searching the travel information about Vietnam from the internet.

Figure 1: International Tourists‟ Arrivals and Spending in Vietnam.

Vietnam has released the annual report of tourism in 2014, listing the top traveller market and the biggest spenders. According to the report from VNAT – Vietnam National Administration of Tourism, visitors who come from Australia topped list in term of spending per trip. The number of Australian tourists increased steadily (321,089 visitors), making it the ninth largest market. Every Australian tourist spent $1,677 per trip, followed by the visitors who come from German and the UK. The average expenditure of foreign tourists was $1,114. The Australian tourists stayed an average of almost 15 and a half days per trip. Germany tourists stayed the longest, almost 16 days. Tourists who are Chinese was the biggest market

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with around 1.95 million travellers coming in last year. The Chinese stayed less than a week and spent $790 each trip.

2.2 Definition Scope of Tourism Products in the Study.

Tourism products has four main determinants for its definition, which involved tourist attractions, accessibility, facility, and the internet (networking sites). (Mason 2000, Poerwanto 1998).

Tourism characteristics were defined as “The products which satisfy tourist‟s leisure, pleasure or business needs at places other than their own normal place of residence are known as Tourism Products” (Sanyal, 2016). Factors demonstrated the tourism products‟ characteristics specifically, such as (1) Intangibility - the products are mostly felt by the customer‟s feeling or experience, it is very hard to show exactly how its quality is since every customer has their own feeling, thinking and opinion about a tourism product that they experienced. (2) Inseparability - has to be unseparated from some factors like tourism human resource or services. (3) Perishability - the product cannot be stored. (4) Variability - the quality of a tourism product or service cannot be standardized since every customer will properly have several feelings or experiences for the same product or service. (5) The absence of the ownership - the ownership always stays with the owner of a destination or the service belonged to the providing person or organization. (6) Customer participation - the participation of the customer plays an important role in judging a service or a tourism product.

2.3 The Development of Internet Usage.

The growth of internet usage has created the opportunity for the development of virtual community. Internet users have started to either create or join the virtual community for multiple purposes, they started to have demand in searching and sharing information.

Wang, Yu, and Fesenmaier (2001) did research on “Defining the virtual community: implications for tourism marketing”. They defined the definition of virtual community with a

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conceptual model, and what is the users‟ perspective for the functions of virtual communities with an alternative model.

Figure 2: A conceptual model for the definition of virtual community . People have different knowledge and understanding of virtual community, depending on their specific demand and the context in which they visit a virtual community. The definition of virtual community from a variety of perspectives, and conducting the unique characteristics of the community in cyberspace, its functions, and features viewed from both theoretical abstractions and empirical application.

The virtual community as a place - People group themselves into aggregated physical villages that they call communities---urban, rural, or suburban.

The virtual community as a symbol - Community, like other social constructs, embodies a symbolic dimension.

The virtual community as virtual - Being virtual is one of the most important defining characteristics which distinguish virtual communities from physical ones. (Wang, Yu, and Fesenmaier, 2001). People Purpose Policy Computer system Virtual community Place Symbol Virtual

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Figure 3: Alternative model for the functions of virtual communiti es from the users‟ perspective”.

Functional needs which are consisted of a transaction. Information, entertainment, convenience, and value. Functional needs are met when the members visit and follow specific activities, and gain their own purposes of that activities. For instance, the consumers need to have an English teaching website as they can spend their time on it at home and whenever they want.

Social needs involve relationship, interactivity, trust, communication, and escape among members to get their main aims of activities. An admin (a host) of a page can get the respect and trust from other members of that virtual community.

Psychological needs refer to identification, involvement, belonging, relatedness, and creativity. The virtual community has to be a part of each member‟s life, and help them to meet their psychological side.

Kaplan and Haenlein (2010) did a research on the overview of the virtual community, they gave out a model of the division in social media. The model showed factors that explain the reason why people use the internet. Since the internet can be used for such activities as feelings, sight, views, hearing, opinions, verbal and non-verbal communication. (Solis 2009; Kaplan & Haenlein, 2010).

Functional needs

Psychological needs

Social needs Virtual community

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Figure 4: The conversation prism in Web2.0 .

Activities above are the side of the social interaction of people‟s need. With the development of the internet nowadays, people tend to spend more time for those kinds of activities than the other activities, for either working or enjoying. Meanwhile, the companies or the organization can easily approach their target customer, since it reduces cost, time-wasting and human resource for some business activities. The internet can be seen as a very helpful tool for getting information for both companies and customers. However, there are plentiful sources of information, which are both truth and untruth, either helpful or harmful, required the internet users need to have skills to clarify and filter out.

The internet users also require being respected and recognized even though it is only something about the virtual life (Hanson, 2000; Kaplan & Haelein, 2010). They approach the internet with their own purposes of studying, working, researching, discovering, sharing, making friends, or even earning money, running a business. The internet users are all equal within the virtual world. (Hanson, 2000; Solis, 2008; Kaplan & Haenlein 2010).

However, there existed the disadvantage which is a lack of safety. For instance, it can be easily caused trouble about the impersonality, since it is easy to steal one's identity or even affect one's private life through personal account or information through the virtual network.

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Somehow it is harmful and unsafe for someone in reality. (Organization for Economic Co-Operation and Development. 2007. OECD Policy Guidance on Online Identify Theft).

The model of Moment of Truth (Carlzon, 1989) based on the theory presented earlier for the social networking sites dimension. In order to guarantee a successful service on the internet, a company has to pay attention to the functionality of the platform, the contents, reliability, interactivity, openness. It is important factors that the company should pay most attention to for having a working follow up a system and gather feedback from the users as well as the customers. The companies or organizations have to clarify and make a plan on their strategies, especially making Internet-based strategies, due to the non-stop growth of the social networking sites. There are activities for companies for keeping service promises in order to create customers‟ loyalty and faith. Such activities as gathering feedback, updating system and information, following up, interacting with openness, supporting. However, first of all, the company has to realize what are the customers‟ needs, and what they want to be satisfied from the company, or what they are looking for.

2.3.1 Social Networking Sites – Popular Tourism Platforms in

Vietnam.

TripAdvisor.com

TripAdvisor - a website that tourists rely on reviews or feedback to plan their trips, gather information, make a comparison or evaluation for tourism products. That is a platform that gives everybody an equally chance of sharing, recommending, talking or expressing their own idea and opinion.

TripAdvisor for Vietnam Travel Forum has recently had 69,652 topics from the community. Questions were mostly asked by both domestic and international tourists about destinations, tourism services or products.

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A "hotspot" survey for foreign tourists was by Indochina Research Vietnam in Ho Chi Minh City, Vietnam in May 2016. During two weeks, they interviewed foreign tourists in a key location of "hotspot" (popular tourist attractions) such as Ben Thanh Market, Bui Vien street, Dong Khoi Street as well as some popular museums. Data were collected by face-to-face interviews among non-Asian tourists. As the collected and analyzed result, 70 percent of the participants are traveling with at least one friend or relative, 95 percent of them have a smartphone, and 59 percent using Wi-Fi only. TripAdvisor is the most popular app since it was used by 72.6 percent. 72 percent of them stays more than 2 days in Ho Chi Minh City. Motivation for on-line research is to search for a place to visit, to sleep, to eat, or to go out at night. 97 percent of them are considering coming back among which 45 percent definitely wishes to come back (Indochina Research Vietnam, 2016). Indochina Research Ltd. (IRL) has been established in Vietnam since 1994. Regional specialist with offices in Cambodia, Laos, Myanmar and Vietnam. IRL delivers high-quality market research of international standards, with knowledge about what consumers and businesses are doing locally. Indochina Research (Vietnam) is part of the WIN/GIA Network of Independent Market Research Agencies.

Virtual community on Facebook

Facebook has 93.9% of account ownership and 56.9% of active use (at least once per month). Thus, it can be meant that the biggest social networking site in Vietnam is Facebook, which has 40 million Facebook subscribers and 42% penetration according to the data collected in June 2016 of the Internet World Stats (Global Web Index. 2016). The Vietnamese internet users spend an average of two hours and 30 minutes on Facebook every day, mostly are keeping in touch with friends and watching some Facebook pages. The Vietnamese spend twice as much time on Facebook as the amount they spend time on television or the newspapers (Tuoitrenews.vn, 2014).

My Destination Vietnam (www.mydestinationvietnam.com ) - a member of the global online travel networking site. It is an authoritative global travel brand offering local expert

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advice from every major continent and travel hotspot around the world. My Destination Vietnam was created on February 11st 2015, about 40.000 "liked", with their mission is to enrich travel experience through local expertise. Their point-of-product are information, travel advice, a place to go, special deals, hotel booking, insider tips, restaurants, tickets, nightlife, interactive maps, rent cars or scooters, photos, videos, and virtual tours of the place around the world.

An increasing demand of searching and sharing information on the internet becomes travel behavior in the virtual tourist community. They did an important role in supporting information source for tourists and the majority of tourists trust the information from the internet (Yoo and Gretzel, 2011).

Trivago.vn

Trivago – a multinational technology company from German, specializing in internet-related products and services in accommodation (hotels), lodging. Trivago was the first travel metasearch search engine, and is one of the fastest growing companies in German. Trivago has 7,792,424 fans on over the world nowadays, and has become one of the most popular travel metasearch engine in Vietnam.

The nature of consumption was changed and appeared new channels of communication with social media (Aramendia-Muneta, 2012). The foundation of Web 2.0 that allow and develop the ways of communication (Kaplan and Haenlein et al., 2010). Indeed, social networking sites allow the development and exchange of user-generated content and eWOM in the field of travel, leisure, and tourism (Litvin et al., 2008). A new context which is included the change of travel behavior by sharing information and interacting through the internet. Therefore, the virtual tourist community information searching behavior model has been extended to include the function of the internet (Gursoy and McCleary et al,. 2004; Jani et al., 2014). Besides, the behavior of the tourist community has been changed due to the evolution of social networking sites (Gretzel et al., 2008).

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2.4 Tourists’ Behavior on trip planning.

Cultural, Social, Personal, and psychological factors are those of the major factors affecting consumer buying behavior (Bhasin, 2016).

Figure 5: Major factors affecting consumer buying behaviour.

Personal Factors of this study can be used for the identification of the customers‟ background. Elements of the personal background factors, such as Age & Life, cycle stage, occupation, income, lifestyle, personality, can affect their own making decision process on purchasing a product or service, known as demographics factors (Kotler, 2000). One‟s psychology, such as motivation, perception, learning, memory, and characteristics, like cultural, social, personal affect mostly their feelings, thinking, beliefs, or impression on a service or product. Moreover, they may convince the others to have the same thinking and impression as them, it depends mostly on their relationship. Thus, a personal background is very important for strategy‟s analysis.

There are several determinants to define either personality or behavior of a tourist, even though there are lots of theories or framework which are described for the tourists‟ behavior, a specific typology of motivators in tourism was conducted with six terms of characteristics by a study of Swarbrooke and Horner (1999).

Cultural Culture Sub-culture Social class Social Personal Psychological Buyer Reference groups Family Roles & Status

Age & Life Cycle Stage Occupation Income Life Style Personality Motivation Perception Learning Beliefs & Attitudes

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Figure 6: A typology of motivators in tourism .

Six terms of characteristics (physical, emotional, personal, personal development, status, and cultural) affect tourist behavior and their decision-making process (Swarbrooke and Horner, 1999). It can be said that the environment where people are living currently or even used to live in the past for a long time can definitely impact on one's personality and characteristics since they have been affected by all of the things that they spent or experienced during the period of their lives.

According to data from the Vietnamese General Statistics Office, ten months of the year 2014, with more than 6.6 million foreign tourists visited Vietnam. The Chinese tourists were the highest which got 1,683,974 arrivals. The second place was visitors from South Korea with 686,706 arrivals. The third one was Japanese tourists with 535,840 arrivals. The fourth was the visitors come from the United State. Cultural and Social factors of the participants may also affect their evaluation and behavior in making a buying decision.

There are internal and external determinants that have an influence on tourists' decision-making process, which are depicted as a broad and specific mind map according to the study of Swarbrooke and Horner (1999).

Physical

Cultural Emotional

Status Personal

Personal development Tourist

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Determinants affect tourist’s decision

Internal Determinants External Determinants

 Personal motivators  Personality  Disposable income  Health  Family commitments  Past experience  Hobbies and interests

 Existing knowledge of potential holidays  Lifestyle

 Attitudes, opinions, and perceptions.

 Availability of suitable products  Advice of travel agents

 Information obtained from destinations, tourism organizations, and the travel media.  Word-of-mouth recommendation of friends

and family

 Political restrictions on travel.  Health problem and vaccination

requirements in destinations.

 Special promotion and others from tourism organizations

 The climate/destination of regions.

Figure 7: Internal and External determinants affect tourists‟ decision .

Those two determinants (either internal or external) are considered to affect the tourist' behavior on making a purchasing decision on tourism products (Swarbrooke and Horner, 1999).

Mathieson and Wall (1982) demonstrated the linear five-stage model of tourist purchasing behavior. As below:

Figure 8: The linear five-stage model of tourist purchasing behaviour. Wahab, Crampton, and Rothfield (1976) did research and conduct a linear model of the tourism decision-making process. As below:

Felt need/ travel desire Information collection and evaluation image Travel decision (choices between alternatives) Travel preparation and travel experiences Travel satisfaction outcome and evaluation

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Figure 9: The linear model of the tourism decision -making process. Those two models above (the linear five-stage model of tourist purchasing behavior, and the linear model of the tourism decision-making process) describe step-by-step the tourist decision-making process. In fact, those steps are really necessary and common for travellers whenever they plan on a trip. However, some of the tourists may think that it is too

complicated or time-wasting for following these models step-by-step, for some people, they just directly go for a contract with a travel agency which can help them to plan on everything for their trip, in case they are too busy or do not want to do too many things on planning it.

2.5 The Impact of the Internet on Tourists

Tourists need to gather information and get the confirmation of the other travellers that they have planned the best trip. Recommendation or review from friends or relatives has a huge impact on the tourists' travel decision-making process (Sigala, 2007). A reliable study by Mandala Research LCC collected the significantly important surveys from different sources related to the impact of social networking sites on consumers. The study revealed that social connection has a huge influence on purchasing decision. 83% of the participants tell their friends when they get a good deal, 90% of the respondents do trust recommendation from their friends, 300% more likely to buy when recommended by friends, 1000% more likely to buy deal after seeing their friends purchased it (Mandala Research LCC., 2010). Now, the Internet has a big impact on how traveller organizes, create, make a plan, and share tourism experiences, and to support this statement, some data were collected and analysed from different studies.

Initial framework  conceptual alternatives  fact gathering  definition of consumptions  design of stimulus  forecast of consequences  cost benefit of alternatives  decision  outcome.

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As a reliable study revealed that 90% of pleasure tourists took pictures and that 45% of them posted their pictures online (Lo et al., 2011). According to a survey of Gretzel et al. (2007) conducted a comprehensive survey in connection with the influence of online travel reviews on the consumer. In order to find out the role and influence of online travel reviews in pleasure trip planning behavior, they asked 1480 users of TripAdvisor.com, the main results of the study were that other tourists' opinions on online travel review sites were the most often used source of information (Gretzel et al., 2007).

2.6 Conceptual Framework

To conduct a framework for purchasing decision on tourism products, this study posits six determinants: (i) demographics – the participants‟ background; (ii) pre-travel behavior of the tourists; (iii) travel behavior of the tourists; (iv) plan on post-travel behavior; (v) Purchasing decision on tourism products; (vi) Usage of the Internet (of the participants).

Tourists‟ behaviors Pre-travel behavior During-travel behavior Plan on post-travel behavior Purchasing decision on tourism products H2

Usage of the internet

 Internet usage for making travel plan.

 Information trusting level. Demographics H4 H5

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Consequently, this study proposes the following hypotheses:

H1: Pre-travel behavior of the tourists positively influences on purchasing decision on tourism products.

H2: During-travel behavior of the tourists positively influences on purchasing decision on tourism products.

H3: Plan on post-travel behavior of the tourists positively influences on purchasing decision on tourism products.

H4: The tourists‟ demographics have significant differences on purchasing decision on tourism products.

H5: Tourists‟ usage of the internet is expected to increase the impact of the tourists‟ behavior on the purchasing decision on tourism products.

2.6.1 Explanation for Conceptual Framework.

Conducting the above conceptual framework based on the research of Swarbrooke and Horner (1999), Fortis et al. (2012), Rudez and Vodeb (2015).

Mathieson and Wall Model (1982) conducted a linear five-stage model of tourist purchasing behavior, which definitely support the determinants of tourists‟ behavior used in the given study. The model demonstrates tourists‟ behavior within five steps, such as: 1. travel desire; 2. information collection and evaluation image; 3. travel decision; 4. travel preparation and travel experience; 5. travel satisfaction outcome and evaluation. Of course, this model does not absolutely apply for all of the tourists, it is not compulsory that everybody has to follow this model step-by-step. However, it does define most of the tourists‟ behavior on planning their trip. This model is a very basic map, which describes tourists‟ behavior within five simple steps.

To be more specific, as it is shown from the conceptual framework of the study, tourist‟s behavior is divided into three main processes - pre-travel behavior, during travel

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behavior, and post-travel behavior, which is based on a research that named students‟ use of social media during the travel process (Rudez and Vodeb, 2015).

Pre-travel behavior which involved habit as searching for information, ideas, comments, or reviews from the internet, making comparison (destinations, services, suppliers). During travel behavior which consisted manner as exchanging information and keeping in touch with the virtual community, sharing photos or videos on the internet. Post-travel behavior which refers to share photos or videos on the internet, share opinions, feelings, or evaluation, and suggest recommendation to friends, relatives, or virtual community members. These three processes are supposed to have positively influences on purchasing decision on tourism products, which is mentioned as hypothesis 1, hypothesis 2 and hypothesis 3 in the study.

Tourist‟s demographics is considered to have significant differences on purchasing decision on tourism products, which is mentioned as hypothesis 4 in the study. Since tourist‟s characteristics which involved internal determinants of a tourist. Internal determinants refer to personal motivators, personality, disposal income, health, family commitments, work commitments, past experience, hobbies and interests, existing knowledge of potential holidays, lifestyle, attitudes, opinions and perceptions (Swarbrooke and Horner, 1999). Internal determinants are known as one‟s living environment which has impact on their behavior on making any decision.

Tourist‟s habit of internet usage is conducted to get more information about the respondents, which can define if it is a qualified response. Besides, tourist‟s habit of internet usage is supposed to be moderator variables which is expected to increase the impact of tourists‟ behavior on the purchasing decision on tourism products, especially the variable of “internet usage for making travel plan”, and the variable of “information trusting level”. External determinants are described as one‟s living habit, which involved availability of suitable products, advice of travel agents, information obtained from destinations, tourism

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organizations and travel media, word-of-mouth recommendation of friends and family, political restrictions on travel, health problems and vaccination requirements in destinations, special promotions and offers from tourism organizations, the climate/destination of regions (Swarbrooke and Horner, 1999).

The five-hypothesis are considered to describe a whole picture for the given study, which can answer the three main research questions of the study, and support more proof for this kind of research for making better tourism research and tourism development.

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Chapter 3. RESEARCH METHODOLOGY

3.1 Research design

The quantitative research method is employed to determine the relationship between the independent variable “internet usage” and the dependent variable “trip planning”.

A structured questionnaire was designed and distributed on-line to collect information on the travel process behavior among the tourists, especially the international tourists who had experience in visiting Vietnam. About 400 people were invited either by via email, social media - Facebook, TripAdvisor, tweeter, etc., or by approachable face-to-face survey at some hotspots (tourist attractions in Vietnam) to complete the online questionnaire hosted by Google Drive. The on-line questionnaire generated a total of 310 respondents who are foreign tourists visited Vietnam.

3.2 Sampling design

Sampling design was conducted as convenience sampling, which are collected data by selecting people due to the ease of their volunteering or choosing units because of the availability and easy access. Questionnaire structure contained 37 questions and was divided into three main sections.

 Section I: Participants were asked about their usage of the Internet for their travel purposes in order to identify the respondents‟ quality for this survey. The determinants of this section are also considered to be moderator variables that impact the tourists' behavior on tourism products.

 Section II: questionnaire was focused on the tourists‟ behaviours consisted of four processes which based on the literature review on “the use of social media during the travel process” (Fortis et al., 2012).

 Section III: the questionnaire was included socio-demographic questions on participants to gain the information about the respondents' basic background.

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Four processes (Pre-travel, During-travel, Plan on post-travel; Purchasing decision on tourism products) consisted of twenty-three statements based on the literature review of the research which named the use of social media during the travel process (Fortis et al., 2012). The latter split into four phases of the travel process. They were measured on seven-point Likert-type scale (1 = strongly disagree, 2 = mostly disagree, 3 = somewhat disagree, 4 = neutral, 5 = somewhat agree, 6 = mostly agree, 7 = strongly agree). Using SPSS to have descriptive statistics with mean was used to describe the behavior of the traveler during the travel process.

3.3 Reliability Statistics

As it is showed from the reliability statistics, the value of the Cronbach‟s  was 0.930 for 23 total items indicated that the scale was highly reliable. Cronbach‟s ‟s was 0.911 for eight items of PRE (pre-travel behavior), 0.949 for nine items of DU (during travel behavior), 0.882 for three items of POS (plan on post-travel behavior), and 0.831 of the Cronbach‟s ‟s was for three items of PD (purchasing decision on tourism products). Specific information was shown in Table 1 below:

Table 1: Survey scale reliability

Reliability Statistics

Cronbach‟s Alpha N of items

Entire Scale 0.930 23

PRE 0.911 8

DU 0.949 9

POS 0.882 3

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3.4 Data Collection, Measures, and Data Analysis.

The questionnaire was created on Google Drive website so that they can be easily putting the data into the SPSS for further analysis. Collecting data process was in both directed way and in-directed way. For the in-directed collecting way, participants were invited via e-mail or social networking sites (such as Facebook). For the directed collecting way, participants were approached directly in person, the surveyor invited the participants to do the survey, the survey was taken place at tourist attractions (Ho Chi Minh City, Vietnam) where are mostly gathered by the foreign tourists.

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Chapter 4. RESULT AND DISCUSSION

4.1 Result and data analyses

4.1.1 Profile of sample

Independent-Sample T test and One-Way ANOVA

The sample had the following characteristics from the respondents. As per the age groups, 55.4 percent from 20 to 39 years old, 17.4 percent from 40 to 49, and 14.5 percent were 60 and older. As per the gender, 68.6 percent were female. As per the currently travel Party, 46.8 percent were going with friends, and 18.1 percent were traveling with family/relatives. As per the trip purpose, 76.1 percent were enjoying the trip for leisure purpose, and 13.9 percent were going on their business trip. The analysis did not reveal any significant differences among age groups, gender, currently travel party and the purpose of the trip, since the significance from t-test and one-way ANOVA analysis were 0.529 (age groups), 0.115 (gender), 0.512 (currently travel party), and 0.562 (trip purpose).

However, there were some characteristics which had analysis from the profile sample did reveal significant differences, since its significant were smaller than the amount of 0.05. As per the occupation (p-value = 0.035), 40.3 percent were currently employed, 31.6 percent were the student, and 14.2 percent were retired. From ANOVA analysis, it did reveal in the mean difference that occupation differences were observed in making a purchasing decision on tourism products. More specific, there were different between self-employed and employed, and between self-employed and retired in making a purchasing decision on tourism products. As per the income (p-value = 0.05), 47.7 percent earn more than $2000 US per month, 30 percent were less than $500 US, and 3.2 percent were from $500 to $1000 US. The analysis did reveal significant difference among levels of income in making purchasing decision on tourism products, there were different between tourists who have income from $1000 to $2000 US and tourists who have less than $500 US per month, then between $1000 - $2000

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US and more than $2000 US per month. As per the nationality (p-value = 0.036), 28.7 per cent were Taiwanese, 13.2 percent were other nationalities like Singaporean, Thailand, Malaysian, and Indonesian, and 12.6 per cent were Australian. The analysis did reveal the significant differences among countries in making a purchasing decision on tourism products, there were different between Australian and Japanese, South Korean, Taiwanese; between Chinese and Japanese; between Japanese and Russian, the UK, French. As per the travel experience (p-value = 0.009), 40 percent were more than 3 times that the foreign tourists had visited Vietnam, 22.9 percent were the second time, and 15.2 percent were the third time. It did say that there were the differences in travel experience in making purchasing decisions on tourism products, such as between the first time and more than 3 times, between the second time and more than 3 times.

From the above analysis, it is evident that H4 (The tourists‟ demographics have significant differences on purchasing decision on tourism products) is accepted. Even though there were no significant differences among age groups, gender, travel party and trip purpose, there were significant differences among occupation, income, nationality, and travel experience in making a purchasing decision on tourism products. Occupation, income, nationality and travel experience can be demonstrated as one‟s social life, personality, psychology and culture which become factors that affect one‟s buying decision (Bhasin, 2016).

Table 2: Profile of respondents which has significant differences.

Variable Frequency % Occupation Student Self employed Employed Unemployed Retired 98 41 125 2 44 31.6 13.2 40.3 0.6 14.2 Income

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24 More than $2000 US Less than $500 US $1000-$2000 US $500 - $1000 US 148 93 59 10 47.7 30.0 19 3.2 Nationality Taiwanese Australian Germany Others 89 39 35 41 28.7 12.6 11.3 13.2 Travel experience

More than 3 times The second time The first time The third time

124 71 68 47 40 22.9 21.9 15.2 Source: Research results.

4.1.2 Tourists' behavior within four sections.

Descriptive Statistics

As it is showed from the descriptive statistics for the section II of the survey of this study, most of their responses to the questionnaire were from 4 (neutral) to 7 (strongly agree). It is also meant that the tourists somewhat or mostly agree with the statements mentioned in the survey. As per the pre-travel behavior, the top two highest score of mean were the statement of “I search for idea about travel when beginning from the virtual community” (Mean = 6.06), and “I search for information about destinations from the virtual community” (Mean = 6.06), and the least one of them was “I am influenced by reviews and/or comments of the others about tourism products from the virtual community” (Mean = 5.49). Specific information was shown as below:

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Table 3: The tourists‟ behavior in the pre-travel section.

Tourists‟ behavior

(N = 310, 7-point Likert scale: 1 = Strongly Disagree, 7 = Strongly Agree) Mean (SD) I search for idea about travel when beginning from the virtual community 6.06 (0.698) I search for information about destinations from the virtual community 6.06 (0.759) I am influenced by reviews and/or comments of the others about tourism

products from the virtual community 5.49 (1.082)

Source: Research results

As per the during-travel behavior, the top two highest score of mean were the statement of “I stay connect with friends and the others on the internet” (Mean = 5.83), and “I share photos and videos about my trip on the virtual community” (Mean = 5.79), and the least one was “the others „comments and/or reviews, from the virtual community, about tourism products can change my original plan” (Mean = 5.43). Specific information was shown as below:

Table 4: The tourists‟ behavior in the during-travel section.

(N = 310, 7-point Likert scale: 1 = Strongly Disagree, 7 = Strongly Agree) Mean (SD)

I stay connect with friends and the others on the internet 5.83 (0.871)

I share photos and videos about my trip to the virtual community 5.79 (0.843)

The others „comments and/or reviews, from the virtual community, about

tourism products can change my original plan 5.43 (1.169)

As per the plan on post-travel behavior, the highest score of mean was “I share photos or videos about my trip on the virtual community” (Mean = 5.81), and the least one was “I provide evaluation and reviews about my suppliers and/or my destinations to the virtual community” (Mean = 5.52). Specific information was shown as below:

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Table 5: The tourists' behavior in the plan on the post-travel section.

(N = 310, 7-point Likert scale: 1 = Strongly Disagree, 7 = Strongly Agree) Mean (SD)

I share photos or videos about my trip to the virtual community 5.81 (0.871)

I provide evaluation and reviews about my suppliers and/or my

destinations to the virtual community 5.52 (1.096)

As per the purchasing decision on tourism products, the highest score of mean was “I will give recommendation to my friends, relatives and/or other travelers on the virtual community when they make plan on their trip” (Mean = 5.75), and the least one was “I will tell the others not to buy the tourism products which I did not enjoy” (Mean = 5.41). Specific information was shown as below:

Table 6: The tourists‟ behavior in the purchasing decision on tourism products session

(N = 310, 7-point Likert scale: 1 = Strongly Disagree, 7 = Strongly Agree) Mean (SD) I will give recommendation to my friends, relatives and/or other travelers

on the virtual community when they make plan on their trip 5.75 (0.870)

I will tell the others not to buy the tourism products which I did not enjoy 5.41 (1.237) Source: Research results

The descriptive statistics showed the mean among PRE (pre-travel behavior), DU (during-travel behavior), POS (plan on post-travel behavior), and PD (purchasing decision on tourism products). According to the mean score, it is ranked that PRE was the highest one (Mean = 5.88), and the least one was PD (Mean = 5.5). the specific information was shown in Table 7 of the tourists' behavior in four sessions as below:

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Table 7: Tourists‟ behavior in four sections (PRE, DU, POS, PD).

Tourists‟ behavior Mean (SD)

PRE 5.88 (0.07)

POS 5.69 (0.09)

DU 5.68 (0.08)

PD 5.53 (0.09)

According to the analysis above, it is ranked from the highest number to the lowest one, it can be seen that most of the respondents had the mean score from 5.5 to 5.9, it is also said that most of the tourists did agree with the statements mentioned in the survey. Since the statements were mentioned in the survey tried to prove that the tourists‟ behavior of the PRE (pre-travel behavior), DU (during travel behavior) and POS (plan on post-travel behavior) section do have positively influenced the purchasing decision on tourism products, so it also can be meant that the collected data from this survey are qualified and met the main points of this study.

Regression Analysis

This study included variables (dependent and independent) which were tested to check the relationship among them. The regression analysis is undertaken to get the final results and outcome of the hypotheses mentioned in the given study. the outcome of the regression analysis did reveal significance among the variables of PRE (p-value = 0.000), DU (p-value = 0.000), and POS (p-value = 0.000), this also meant that they are all significant on the dependent variables (PD). The results of the regression analysis are presented below in Table 8 respectively.

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Table 8: Coefficients Variables Resulting from Multiple Regression Analysis (PRE, DU, POS). Unstandardized Coefficients Standardized Coefficients B Std. Error t Sig. (Constant) -0.501 0.238 2.109 0.036 PRE 0.240 0.066 0.173 3.662 0.000 DU 0.317 0.068 0.280 4.688 0.000 POS 0.497 0.055 0.474 9.119 0.000

Note: Fit for model R2= .744, Adjusted R= .741, F(3, 295)=69.28, p< .001

The table 8 showed that there existed the significance among the variables of PRE, DU, and POS since all of the p-value of them are lower than 0.05. Moreover, the t-value from the table, it is said that the t-value of the variables of PRE, DU, and POS are all positive number. The R Square (R) of these three variables (PRE, DU, POS) are 74 percent, this is also an explanation for the given hypotheses of this study. Therefore, it is definitely can be said that the hypothesis 1, hypothesis 2, and hypothesis 3 are accepted.

Table 9: Regression analysis results for the first three hypotheses.

Hypothesis

Coefficient

() P-Value

H1 - the Pre-travel behavior of the tourists positively

influences on purchasing decision on tourism products. 0.173 0.000

H2 - the During-travel behavior of the tourists positively

influences on purchasing decision on tourism products. 0.280 0.000

H3 – Plan on the post-travel behavior of the tourists positively influences on purchasing decision on tourism products.

0.474 0.000

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4.1.3 Tourists’ usage of the internet

Frequency Statistics

The frequencies (statistics) showed that there was no missing value of all of the variables. There was showing the valid percent of totally 310 respondents. 59.7 per cent said that they usually use the internet for making a plan on their trip, and 35.2 percent said "always”. For the question of the virtual community that they mostly use for their travel purpose, 49.4 percent were TripAdvisor.com, 25.5 percent were Trivago.com, and 9.7 per cent were others (such as some pages on Facebook or Google), 41.6 percent of them said they are not sure or they don't remember if there were any changes in their original plan by the virtual community, and 39.4 percent said "did make significant changes”. 53.2 percent of them said that they mostly trust the information for their travel purposes provided by friends and/or relatives from the Internet, and 28.1 percent said they trust some of it. 95.2 per cent were that they agree the information from the virtual community is helpful for their trip.

Table 10: Respondents‟ Usage of the internet

Variable Frequency %

Internet usage for making travel plan Seldom Usually Always 16 185 109 5.2 59.7 35.2 Internet usage for virtual community

TripAdvisor.com Trivago.com Other 153 79 30 49.4 25.5 9.7 Internet usage for changing original plan

Not sure/ cannot remember Did make significant changes

129 122

41.2 39.4 Information trusting level

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30 Some of it Most of it Completely trust 87 165 45 28.1 53.2 14.5 Is the internet helpful?

Yes Not sure 295 15 95.2 4.8 Source: Research results

Moderated Regression Analysis

Testing the variables in the section "Usage of the internet" as a moderator analysis for testing and proving the hypothesis 5 (Tourists‟ usage of the internet is expected to increase the impact of the tourists‟ behavior on the purchasing decision on tourism products). There are six questions as well as six variables to be tested as moderator variables to test H5. According to the result, there are only two variables which are existed and tested as moderator variables when using the moderated regression analysis. Those two variables of this section which are the determinants of "internet usage for making a travel plan", and "information trusting level". Those two main variables can be used as moderator variables.

As the regression analysis showed, as per the "internet usage for making a travel plan", all of the respondents said that they use the internet for their travel purpose. The respondents (N = 310) can be divided into three small groups, the first group said “seldom”, the second group said “usually”, and the third group said “always”. As per the “seldom” group, it did not reveal significance (all of the p-values are bigger than 0.05). As per the "usually" group, it did reveal significance for the DU (p-value = 0.001) and the POS (p-value = 0.000), the t-value and the -value are all positive number. As per the “always” group, it did reveal significance for the PRE (p-value = 0.000), DU (p-value = 0.004), and the POS (p-value = 0.000), the t-value and the -value are all positive number. Therefore, the variable of "internet usage for making travel purpose" do have a positive impact on the tourists' behavior on purchasing decision on tourism products. The table 11 below is shown the specific value for each variable.

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Table 11: Results of Moderated Regression analysis for the variable of “Internet

usage for making travel plan”

Unstandardized Coefficients Standardized Coefficients The usage of internet B Std.

Error Beta t Sig.

(Constant) -.212 -.809. -.262 .798 Seldom PRE .344 .335 .321 1.028 .324 DU .709 .435 .636 1.632 .129 POS -.110 .242 -.111 -.453 .659 (Constant) .056 .339 .166 .868 Usually PRE .036 .087 .025 .410 .682 DU .309 .091 .269 3.403 .001 POS .618 .069 .599 8.965 .000 (Constant) -.848 .464 -1.825 .071 Always PRE .448 .114 .307 3.934 .000 DU .298 .100 .277 2.978 .004 POS .365 .092 .350 3.950 .000

Note: Fit for model, Seldom, R2= .722, Adjusted R= .653, F(3, 10)=3.16, p< .001 Fit for model, Usually, R2= .720, Adjusted R= .715, F(3, 154)=36.6, p< .001 Fit for model, Always, R2= .716, Adjusted R= .708, F(3, 88)=24.48, p< .001

As per the "information trusting level", all of the respondents said that they trust the information for their travel purposes provided by friends and/or relatives from the internet. However, from the answers to this question, the respondents (N = 310) can be divided into four small groups, the first group said "a little", the second group said "some of it", the third group said "most of it", and the fourth group said "completely trust". As per the "a little" group, it did not reveal significance (all of the p-values are bigger than 0.05). As per the "some of it" group, it did reveal significance for the POS (p-value = 0.000), the t-value (4.549), and the -value (0.508) are all positive number. As per the “most of it” group, it did

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reveal significance for the PRE value = 0.030), the DU value = 0.009) and the POS (p-value = 0.000), the t-(p-value and the -value are all positive number. As per the “completely trust” group, it did reveal significance for the DU (p-value = 0.000) and the POS (p-value = 0.000), the t-value and the -value are all positive number. Further information is shown in the below table 12:

Table 12: Results of Moderated Regression analysis for the variable of “Information trusting level”. Unstandardized Coefficients Standardized Coefficients The usage of internet B Std.

Error Beta t Sig.

(Constant) -4.095 1.049 -3.904 .005 A little PRE 1.006 .571 .540 1.763 .116 DU .386 .391 .266 .990 .351 POS .310 .265 .200 1.171 .275 (Constant) .356 .465 .765 .447 Some of it PRE .239 .115 .193 2.078 .041 DU .189 .132 .188 1.431 .156 POS .466 .102 .508 4.549 .000 (Constant) -.348 .362 -.963 .337 Most of it PRE .216 .098 .149 2.194 .030 DU .250 .095 .219 2.631 .009 POS .567 .078 .537 7.251 .000 (Constant) -.158 .596 -.265 .792

Completely trust PRE -.122 .134 -.083 -.912 .367

DU .570 .145 .463 3.933 .000

POS .561 .113 .559 4.945 .000

Note: Fit for model, A little, R2= .913, Adjusted R= .881, F(3, 28)=1.40, p< .001 Fit for model, Some of it, R2= .650, Adjusted R= .637, F(3, 51)=21.6, p< .001

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Fit for model, Most of it, R2= .716, Adjusted R= .710, F(3, 135)=34.06, p< .001 Fit for model, Completely trust, R2= .842, Adjusted R= .830, F(3, 72)=4.9, p< .001

From the above analysis, variables of the usage of the internet that have significance and be moderator variables impacted on the tourists' behavior on purchasing decision on tourism products are the "internet usage for making a travel plan" and the "information trusting level". Those two variables are all positive number and have significance, so it can be said that the hypothesis 5 - Tourists‟ usage of the internet is expected to increase the impact of the tourists‟ behavior on the purchasing decision on tourism products, is accepted.

4.2 Discussion

This research was undertaken to find out the factors affecting the tourists‟ purchasing decision on tourism products (dependent variables) in perspective of Vietnam. The determinants of different sections - PRE, DU, POS, and other determinants - tourists‟ demographics; tourists‟ usage of the internet, were taken as the independent variables based and supported by previous studies and research. The final results and outcome depict that all the independent variables significantly influence the purchasing decision on tourism products - the case of the foreign tourists in Vietnam. All of the variables are highly reliable according to the reliability statistics above.

The tourists‟ behavior through three processes – PRE, DU, POS, did reveal that there is positively influence the purchasing decision on tourism products, approved by the reliability analysis, descriptive analysis, and regression analysis, which did support three hypotheses (H1, H2, H3 are all accepted). These findings are in the same outcome with Fortis et al. (2012) who found that social media are being used for the trip planning within three processes (Pre-trip, During the trip, and Post-trip), and had a conclusion that most of the tourists have habit of using the internet for their trip purposes. This result also has the same outcome with the research of Mandala Research LCC. (2010), 83% of the participants tell their friends when

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they get a good deal, and either has the same finding with the research of Lo et al. (2011), 90% of pleasure tourists took pictures and that 45% of them posted their pictures online. This result analysis did answer to the main question of this study – How does each factor of tourists‟ behavior within the three processes affect the purchasing decision on tourism products, and met the requirements to the research objectives. Besides, the results of this section can be considered to be another significant evidence for the basic tourists‟ behavior process: (1) felt need/ travel desire; (2) information collection and evaluation image, (3) travel decision (choices between alternatives), (4) travel preparation and travel experiences, (5) travel satisfaction outcome and evaluation (Mathieson and Wall Model, 1982. Tourist Behavior), or the gap model of service quality (Oliver, 2009; Zeithaml, Parasuraman, and Berry, 2009).

The tourists‟ demographics (independent variables) did affect the purchasing decision on tourism products (dependent variables) since it did reveal the significant difference from the analysis which did approve and support the hypothesis 4. The findings indicate that there is a significant difference among the determinants of occupation, income, nationality, and travel experience. As the “occupation” determinant, 40.3% of the respondents were employed people who have money and a certain day off per year that support and give them chance for having a trip, this kind of respondents usually go on a trip with their family or relatives. 31.6% were students who have lots of time for traveling, but do not really have their own earning or money for the trip, usually have to get the supporting from parents or relatives, these kinds of respondents usually go on a trip with friends or family. As the “income” determinant, 47.7% were the respondents who have earned more than $2000 US per month, these kinds of tourists have a huge chance of going on a trip, since they got a huge income per month, they are usually the VIP or potential VIP tourists of some popular travel agency or luxury service. As the “nationality” determinant, 28.7% of the respondents were the Taiwanese, and 13.2% were from the other countries as Singapore, Thailand, Philippine, and Malaysia, from the results, most of the respondents come from the Asian countries, it can be

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said that there are similarities in culture among Asian countries which can be the factor help to attract the Asian come to visit Vietnam. Culture consists of a society's complex set of beliefs, custom, and other specific forces that shape individual's perceptions behaviors and is thought to be a key characteristic of a national environment that produces a systematic difference in behavior across borders (Steenkamp, 2001). As the “travel experience” determinant, 40% were the respondents who had visited Vietnam more than three times, and 22.9% were tourists who had visited the second time, from this result, it can be said that most of the respondents of this research have certain experience for traveling to Vietnam, they have certain knowledge about the price, destinations, living standard, or tourism service of the Vietnamese, they probably had better plan for their current trip, and they started to give strictly evaluation or review to the products or service that they experienced more than once, this also meant that most of the results from the given questionnaire are highly valuable and reliable. It is mentioned that occupation, income, nationality and travel experience can be demonstrated as one‟s social life, personality, psychology and culture which become factors that affect one‟s buying decision (Bhasin, 2016). Elements of the personal background characteristics, such as Age & Life, cycle stage, occupation, income, lifestyle, personality, can affect their own making decision process on purchasing a product or service, known as demographics factors (Kotler, 2000).

“The usage of the internet” section revealed information about tourists‟ habit in using the internet for travel purpose. 100 percent of the respondents said that they use the internet and it becomes as one of their habits whenever they want to go for a trip. It did reveal that the two most popular virtual communities for the tourists nowadays are TripAdvisor.com and Trivago.com. From this result, the business strategy person or the marketers can easily plan on the marketing campaign for their products or services on these two popular virtual communities. It has the same meaning with the research of Gretzel et al. (2007) that the tourists‟ opinion on online travel review sites as TripAdvisor.com were the most often used

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source of information. 95.2 percent said that they agree the information from the virtual community are helpful for their trip, the tourists today more and more rely on the internet in making purchasing decision or searching information for their needs, this also meant that the internet, as well as the virtual community, are the very powerful tools for businesses, especially for the tourism businesses. This finding has the same outcomes with the study of Sigala (2007) that recommendation or review from friends or relatives has a huge impact on the tourists' travel decision-making process, and with the study of Mandala LCC. (2010) that 90% of the respondents do trust recommendation from their friends, 300% more likely to buy when recommended by friends, 1000% more likely to buy deal after seeing their friends purchased it. It did reveal that the tourists‟ habit of using the internet for travel search did increase the impact on the tourists‟ behavior on purchasing decision on tourism products. The collected and analysis data from this section tried to indicate and insist the important role of the internet in purchasing decision on tourism products.