Academy of Marketing Studies Journal (Print ISSN: 1095-6298; Online ISSN: 1528-2678)

Research Article: 2020 Vol: 24 Issue: 4

E-Tourism: How Customers Intention to use be Affected?

Anthony Tik-Tsuen WONG, Caritas Institute of Higher Education

Abstract

E-tourism has a significant value in travel industry. It provides one more choice for customers in going for a trip. More and more customers are willing to use it. However, the opaqueness and unrealistic of the Internet are concerned by users. Therefore, this study aims to identify the factors affecting the Hong Kong customers to decide to use E-tourism for their trips as well as the degree of influences of different factors. Technology acceptance model (TAM) is adopted in this study. Besides, additional factors including perceived value, trust and perceived risk are added to the model for further exploration. Both quantitative and qualitative studies were conducted. The result shows that perceived ease of use has the largest degree of influence in affecting Hong Kong customers’ purchase intention in using E-tourism. The empirical results of this study support the usual relationship among perceived ease of use, which drives the consumer intention to use E-tourism. The result shows perceived ease of use positively affects intention to use, perceived ease of use positively affects perceived usefulness, perceived value positively affects perceived usefulness, trust positively affects perceived usefulness and trust negatively affects perceived risk. Moreover, the result also shows that perceived usefulness does not significantly influence the intention to use and the relationship between perceived risk and intention to use is not significant. Managerial implications in the development of tourism websites like E-tourism website owners can focus more on user-friendliness.

Keywords

E-tourism, TAM, Trust, Intention to Use.

Introduction

The achievements in the information and communication technologies (ICT) domain change undeniably the practices, the business strategies, and also the industry structurally (Porter, 2001). In recent years, the Internet has become a new channel for the commercialization of products conventionally sold through traditional outlets (Hernández et al., 2009). As a matter of fact, purchasing online travel products has become the most successful business in e-commerce (Kim et al., 2007). According to Internationale Tourismus-Börse Berlin (ITB) World travel trends report in 2013, the Internet has now clearly established itself as the main place to buy travel with 54% of bookings, well ahead of travel agencies which have slipped to 24% in 2012. More and more people have gradually accepted the changes brought by the Internet to people’s living habits and lifestyles. With the combination of tourism and ICT, tourism has an emerging e-commerce sector called E-tourism. E-tourism is the use of the Internet to establish business relations with tourism-related products. The products or services involved include flight reservations, hotel reservations, car rentals and so on. The development of E-tourism is especially obvious in developing countries.

Tourism is an important industry in Hong Kong. It helps support the economic growth and development of Hong Kong. With the rapid development of information and communication technology, travel websites become widely used nowadays. There are many travel websites providing booking and comparison (search aggregator) of hotels and air tickets services such as “Trivago”, “Hotels Combined” “Expedia” and “Agoda”. More and more Hong Kong travelers are using those websites instead of going to traditional travel agencies. Although the opaqueness and unrealistic of the Internet are concerned by users, most of them would still prefer to use the travel websites. There should be some factors behind it, they may be convenience, security and price. This research identifies the factors affecting the Hong Kong customers to decide to use the travel websites for their trips. Furthermore, this research finds out the degree of influences of different factors to purchase intention. The factors behind are very important for E-tourism and even all the online transactions as the owners can understand what and how the customers are thinking. After that, they can build a reliable and trustable website for their E-tourism business.

Literature Review

To study the factors that affect Hong Kong customers’ purchasing intention in E-tourism, it would be rational to adopt an already examined and well-developed model.

Technology Acceptance Model (TAM)

TAM is a model that used to assess user’s acceptance of technology, which is measured by the external variable, perceived usefulness, perceived ease of use toward the intention to use (Davis, 1989). The result showed that perceived usefulness and perceived ease of use have positive effect toward the intention to use. In this study, the main part of the factors is based on the TAM. Figure 1 shows the TAM.

Figure 1 Technology Acceptance Model

E-tourism

Internet, technology and globalization have contributed to the emergence of a new economy. The old economy relies on the logic of industrial management, and the new economy is based on the logic of information management and the information industry (Kotler, 2009). The "E" abbreviation indicates the degree of electronisation of online platforms and represents the electronic markets where the e-business meets e-consumers, e-government, e-partners and other e-business from IT platforms.

There is no doubt that the products or services on the electronic platform are provided by travel agencies or intermediaries. The travel website is the form that electronic travel place presents only. During the pre-internet period, the undertakers from the touristic domain did not have other choices but to base on the touristic agents’ capacity of intermediation and also on the tour-operators’ capacity (Condratov, 2013). With the diversification of consumer demand of travelers and the rise of online travel agencies (OTAs), traditional travel agencies cannot only rely on low prices to attract consumers (Long et al., 2017). However, for OTAs, the website plays an important role in providing travel information, enabling customers to make reservations, meet the needs of visitors and meet their expectations (Liao et al., 2017). Besides, OTAs are just a part of the E-tourism industry, and also includes attractions website, official travel sites and so on (Cao & Yang, 2016). Comprehensive information provision has made travel websites increasingly important and the most frequently visited online source of information for travelers (Chiou et al., 2011), thus undermining the role of traditional travel agencies (Vijoli et al., 2016). As a platform for e-commerce, the website has four core functional values: transaction incubation, transaction negotiation, transaction formation and transaction management (Chu et al., 2007). This means that the website provides participants and hosts with basic information processing capabilities to facilitate the negotiation of business transactions. And when the transaction is finalized, the participant pays through authentication and sends the product to the purchaser. This is the ability to coordinate multiple interconnected activities online. They can be used to assist in the management of online business processes for the integration, integration, optimization and control of e-business processes. E-tourism as a carrier website and tourism as a recipient of the combination is inseparable. Therefore, E-tourism is the electronisation of all aspects of tourism through information and communication technologies, including publishing products, research travel information, tourism advertising and promotion on social media, pre-sales and after-sales service, booking travel products and making payments (Sion & Mihălcescu, 2016).

Intention to Use

Intentions can be defined as desires, wishes, willingness or self-instructions to behave in a certain way and the motivational factors that influence one’s behavior (Ajzen, 1991). Intentions indicate how hard a person is willing to try and how much of effort a person is planning to use in order to perform a behavior. The stronger intention to engage in a behavior, the more likely a behavior will be performed. Behavioral intention is an indication of the readiness of an individual to perform a given behavior. It is assumed to be an immediate preceding of a behavior (Omotayo & Adeyemi, 2018).

Perceived Ease of Use

According to a research done by Bhatiasevi & Yoopetch (2015) in Thailand, perceived ease of use has a significant and positive impact on perceived intention to use. The users’ intention to use E-tourism is also driven by the ease of use of the platform. If they feel that it is easy to use, they will have an intention to use it.

Another research done by Sin et al. (2012) in Malaysian states that perceived ease of use has a significant effect on the users’ online purchase intention through social media. They suggest that users may tend to buy online through social media if the processes of using social media in terms of ordering and delivering products or services are simple and easy to understand. It positively affects the purchase intention through online social media.

Though, there are some research shows opposite result. A research done by Wong (2017) in Hong Kong confirms that the perceived ease of use in online shopping is negatively related to repurchase intention. A similar research done by Gong et al. (2013) in China finds out that perceived ease of use generates a non-significant parameter estimate. Base on the review on the above research, this research proposes the following hypothesis.

H1: Perceived ease of use positively affects intention to use.

According to the research done by Wong (2018) in Hong Kong, the relationship between perceived ease of use and perceived usefulness is statistically significant and positive. Bhatiasevi & Yoopetch (2015) in Thailand has a similar result that a positive relationship is found between perceived ease of use and perceived usefulness. Therefore, if the users perceive that the E-tourism platform is easy to use, they will also find it to be useful. Therefore, this research proposes the following hypothesis.

H2: Perceived ease of use positively affects perceived usefulness.

Perceived Value

Perceived value is considered to be an important factor in determining the buying behavior of the customers (Dawar & Parker, 1994). It is the basis for all marketing activities (Morar, 2013). Dodds et al. (1991) considered perceived value is positively correlated with repurchase behavior and customer loyalty. Customer perceived value is the next source of competitive advantage (Woodruff, 1997). The ability of companies to provide superior value to customers was seen as one of the most successful competitive strategies.

Although there is no clear definition of perceived value, this research considers that the concept of perceived value shows an interaction between a consumer and a product (Sánchez-Fernández & Iniesta-Bonillo, 2007). Iglesias & Guillen (2004) considered perceived value is an exchange between what is received and what is given. Value is reflected in the monetary sacrifice in the process of service and product consumption (Cronin et al., 2000; Einhorn & Hogarth, 1981; Kahneman & Tversky, 1979). Some scholars argue that perceived value is a trade-off between quality and price (Bolton & Drew, 1991). Instead, more palatable is Monroe’s views. Monroe (1990) considers value as the benefits of consumers perceive in the purchased product or service, relative to the sacrifice they perceive by paying the price for the product.

The nature of perceived value is complex and multi-dimensional (Sánchez-Fernández & Iniesta-Bonillo, 2007). Consumers’ perception is divided into two parts: benefit and sacrifice. For the benefit component -what a consumer receives when he or she acquires a product, includes quality, psychological benefits (Zeithaml, 1988), economic and social benefits (Grewal et al., 1998; Cronin et al., 2000). The other part is the sacrifice. Sacrifice is not just the sacrifice of money (Ravald & Gronroos, 1996). It also includes time, energy, risk, opportunity and other factors (Grewal et al., 1998; Cronin et al., 2000). As defined by Zeithaml (1988), perceived value results from the personal comparison of the benefits obtained and personal sacrifices made after the purchase act has been done. However, this concept is a very subjective and personal (Parasuraman et al., 1985) because one-dimensional structure has problems of too narrow and simplistic a perception of what the customer might experience (Zeithaml, 1988; Bolton & Drew, 1991).

In general, there are five dimensions of value concept: society, emotion, function, cognition and condition (Sheth et al., 1991). Some researchers use multi-dimensional methods such as functional dimension and emotional dimension to building perceived value (Woodruff, 1997; Sweeney & Soutar, 2001; Sanchez et al., 2006). Functional value is the utility formed by reducing the perceived cost of consumers (Sweeney & Soutar, 2001). Besides, Zeithaml (1988) also considered in order for the consumers to purchase particular services or to buy again specific products, these have to be delivered with value, either by incorporating benefits or by reducing sacrifices. Therefore, perceived usefulness is considered equivalent to perceived value (or perceived benefit) and often used to measure the effectiveness of e-shopping as perceived by consumers (Shih, 2004). As a tool to search for information, buy goods and communicate with each other, the Internet is considered to have functional, social and cognitive value (Cheng et al., 2009). In the context of Internet use, usefulness is positively correlated with perceived value (Kim et al., 2007). Thus, this study proposes the following hypothesis.

H3: Perceived value positively affects perceived usefulness.

Trust

Trust is a factor that be proposed as an external variable in TAM in this study. Trust is not just between people but also between user and the computer system, as far as the online shopping agency (Lee & Turban, 2001). Previous research has found that trust is taken as a vital part in affecting customers’ purchasing intention online (Salo & Karjaluoto, 2007). Most of them have found that trust has a positive relationship with perceived usefulness.

In recent year, online purchasing has become more and more common in the business world. Trust is a critical issue that aware by different scholars. The relationship between trust and perceived usefulness is being explored. Previous research has shown that trust has a significant effect towards perceived usefulness as stated in the TAM (Gefen et al., 2003). So, the following hypothesis is proposed in this research.

H4: Trust positively affects perceived usefulness.

Security is one of the concerns by users when it comes to online purchasing. Previous result found that customer will hesitate if they feel that the website is uncertain and risky (McKnight et al., 2002). Another research has also found that trust is directly affecting perceived risk negatively (Van der Heijden et al., 2003). As risk affected the intention to use in purchasing (Wong, 2018), the factors that affect risk are vital in this study. So, the following hypothesis is proposed in this research.

H5: Trust negatively affects perceived risk.

Perceived Usefulness

Perceived usefulness is defined as the degree in which a person believes that using a particular system would reinforce his or her job performance (Davis, 1989). A significant number of empirical studies have shown that perceived usefulness has a positive impact on online purchase intention. Kucukusta et al. (2015) concluded that perceived usefulness has a positive impact for Hong Kong customers using E-tourism. Another study by Renny et al. (2013) also concludes that perceived usefulness has a positive impact towards online airlines ticket purchase, which is a part of E-tourism. By summarizing the positive impacts of perceived usefulness on using E-tourism, the following hypothesis is proposed.

H6: Perceived usefulness positively affects intention to use.

Perceived risk

Perceived risk was extended from psychology by Bauer (1960). From the research of Zhang & Hou (2017), it is believed that uncertainty affects the purchasing decision of customers, which is the initial concept of perceived risk (Zhang & Hou, 2017). It is defined as the extent for a potential buyer who is uncertain about the consequences of buying, using, or disposing of a purchasing. This shows two relevant aspects of perceived risk, which are uncertainty and consequence (Wong, 2018).

Perceived risk has been conceptualized at multiple levels of specificity. Park et al. (2004) have taken an intermediate approach and divided the multiple dimensions of risks according to product or service like functional loss, financial loss, time loss, opportunity loss and those related to online transaction such as security, privacy and nonrepudiation (Gong et al., 2013).

Prior research has indicated that high confidence and low perceived risk increase the intention to use of online significantly (Gong et al., 2013). In general, a number of studies including research done by Jarvenpaa et al. (1999), Tan (1999) and Miyazaki & Fernandez (2000) that addressed the negative relationship between perceived risk and the intention of customers to shop online, which includes E-tourism. Based on the above studies, the following hypothesis is proposed.

H7: Perceived risk negatively affects intention to use.

Research model

Base on the literature review and hypotheses proposed, the research model is proposed as shown in Figure 2. There are six constructs and seven hypotheses in the model which aims to study the factors affecting Hong Kong customers’ purchase intention in using E-tourism.

Figure 2 Research Model

Methodology

Sampling and Data Collection

The target population of this research is the people who have experience in using E-tourism. With a short period of time, the convenience sampling technique is used to facilitate the collection of the empirical data and reach the population. To apply this technique, online questionnaires were distributed to the respondents through different social media such as Facebook and Instagram. A total number of 157 completed questionnaires were collected and all of them are invalid responses. It is similar to the research of Sundarraj & Manochehri (2011) in online purchase intention context which the collected data is 145. The qualitative interview has also been done to enhance the significance of the result of the online questionnaire.

Questionnaire Design

The questionnaire was designed as simple as possible in order not to consume respondents so much time as to increase the response rate. For the above purpose, open-ended questions were avoided while close-ended questions were adopted because they require shorter response and answering time. In the questions asking for the respondents, five-point Likert Scale is adopted which the range of the scale is from (1) “Strongly Disagree” to (5) “Strongly Agree”.

Measurement Items

Table 1 shows all the measurement items and the corresponding sources for this study. A few modifications had been made for some wording in the measurement items. For example, the measurement items of intention to use were adapted from the research of Xia & Hou (2016) and their research studied the “Yuebao”, an online service. Their questionnaires were adopted because of the similarity but a few modifications had been made, which the word “Yuebao” was changed into “online tourism website” in order to make the measurement items in line with the focus of this study as well as to keep the original meaning.

Table 1 Measurement Items
Constructs Measurement items Reference
Perceived ease of use PE1. Learning to operate a tourism website is easy Wong, 2017
  PE2. A tourism website is flexible to interact with  
  PE3. My interaction with a tourism website is clear and understandable  
  PE4. It is easy to become skillful at using a tourism website  
  PE5. A tourism website is easy to use  
Perceived value PV1. A tourism website is very good value for money. Bhatiasevi & Yoopetch, 2015
  PV2. Given its price, a tourism website is economical  
  PV3. A tourism website can be considered a favorable purchase  
  PV4. The price of a tourism website is acceptable with regard to its quality  
  PV5. The price of a tourism website corresponds to its value  
Trust T1. I would be willing to provide information like my name and phone number to a tourism website McKnight et al. 2002
  T2. I would be willing to share the specifics of my legal issue with a tourism website  
  T3. I would feel secure in using a tourism website  
Perceived usefulness PU1. Using a tourism website improves my performance Yoopetch, 2015
  PU2. Using a tourism website increases my productivity  
  PU3. Using a tourism website enhance my effectiveness  
  PU4. I find a tourism website to be useful  
Perceived risk PR1. I do not perceive any risk by sharing my personal information concerning using a tourism website Wong, 2018
  PR2. I am confident that others cannot tamper with information concerning on a tourism website  
  PR3. I believe that advanced technology can certainly provide the desired security for my information using a tourism website  
  PR4. I do not think that my information will get stolen whenever I using a tourism website through online  
Intention to use IU1. I have used or will start using a tourism website soon Xia & Hou, 2016
  IU2. I intend to continue using a tourism website in the future  
  IU3. I am willing to provide my credit card information to a tourism website  

Statistical Analysis Methods

Structural equation modeling (SEM) technique is especially suitable for the analysis with small or medium sample sizes (Lee et al., 2007). The sample size of this study was 157 participants, which was a medium sample size. Moreover, SEM supports in studying the relationships among a model with multiple independent and dependent constructs simultaneously (Gerbing & Anderson, 1988) which are required in this research. Therefore, SmartPLS 3.0 (Ringle et al., 2015) was used in this study as the statistical software for SEM.

Before the hypotheses path testing, reliability and validity test were performed. For the validity testing, the factor loading of exploratory factor analysis (EFA) and the square root of average variance extracted (SRAVE) were used to evaluate the convergent and discriminant validity of the constructs of this study respectively while Cronbach’s alpha, composite reliability (CR) and average variances extracted (AVE) were assessed for the reliability testing (Chang et al., 2013; Wong, 2018).

Data Analysis

Characteristics of the Sample

Table 2 shows the demographic variables of the research. There is almost equal proportion of male and female. Majority of respondents are between 18 and 24 years old who have experience in using E-tourism.

Table 2 Characteristics of the Sample
    Frequency Percentage
Gender Male 75 47.8%
  Female 82 52.2%
Age Under 18 4 2.5%
  Between 18-24 91 58%
  Between 25-34 40 25.5%
  Between 35-44 16 10.2%
  45 or above 6 3.8%

Validity Testing

Table 3 shows the factor loading result of exploratory factor analysis. A total of six components were extracted from the exploratory factor analysis. All of the measurement items had factor loading more than 0.7 except measurement items PE3 (0.655) and IU3 (0.629). In order to ensure the validity of the data, those two measurement items, PE3 and IU3, were removed as well as all the responses of these two measurement items in the questionnaires.

Table 3 Original Factor Loading
  PE PV T PU PR IU
PE1 0.733          
PE2 0.763          
PE3 0.655          
PE4 0.727          
PE5 0.729          
PV1   0.797        
PV2   0.772        
PV3   0.792        
PV4   0.829        
PV5   0.707        
T1     0.860      
T2     0.910      
T3     0.873      
PU1       0.776    
PU2       0.783    
PU3       0.809    
PU4       0.712    
PR1         0.895  
PR2         0.798  
PR3         0.814  
PR4         0.881  
IU1           0.874
IU2           0.849
IU3           0.629

After analysing the data that measurement items PE3 and IU3 were removed, the result of the factor loading is shown in Table 4. Each of the questionnaire items is loaded into one and only one component with factor loading more than 0.7.

Table 4 Factor Loading After Removing PE3 and IU3
  PE PV T PU PR IU
PE1 0.754          
PE2 0.780          
PE4 0.752          
PE5 0.743          
PV1   0.797        
PV2   0.772        
PV3   0.792        
PV4   0.829        
PV5   0.707        
T1     0.860      
T2     0.910      
T3     0.873      
PU1       0.771    
PU2       0.783    
PU3       0.814    
PU4       0.714    
PR1         0.896  
PR2         0.795  
PR3         0.816  
PR4         0.881  
IU1           0.905
IU2           0.883

Fornell & Larcker (1981) indicated that the discriminating validity can be measured by the square root of average variance extracted (SRAVE) of each construct and the correlation coefficient among the constructs. Discriminating validity exists when the SRAVE is greater than the correlation coefficient among the other constructs. Table 5 shows that the SRAVE extracted were greater than the correlation coefficients among the other constructs, indicating that adequate discriminating validity existed among constructs in this study.

Table 5 Srave
Constructs Perceived ease of use Perceived risk Perceived usefulness Perceived value Intention to use Trust
Perceived ease of use 0.757          
Perceived risk 0.242 0.848        
Perceived usefulness 0.495 0.484 0.771      
Perceived value 0.501 0.518 0.562 0.780    
Intention to use 0.560 0.241 0.430 0.436 0.894  
Trust 0.342 0.673 0.531 0.584 0.352 0.881

Reliability Testing

Cronbach’s alpha tests were conducted to measure the level of consistency among the items in each variable extracted by factor analysis (Hair et al., 2005). Table 6 shows that the six constructs having a Cronbach’s alpha value ranging from 0.749 to 0.859 which are greater than the threshold of 0.7 as recommended by Hair et al. (2005). Besides, as shown in Table 6, all the composite reliabilities (CR) are more than 0.7 and the average variances extracted (AVE) exceeds the value of 0.5. Those results surpass the reference thresholds as recommended by Bagozzi & Yi (1988) and Kline (2005). The results indicate that the data have an acceptable internal consistency and the measuring scales which are reliable for further analysis.

Table 6 Reliability Testing
Constructs Cronbach’s alpha CR AVE
Perceived ease of use 0.753 0.843 0.574
Perceived value 0.839 0.886 0.609
Trust 0.857 0.913 0.777
Perceived usefulness 0.773 0.854 0.595
Perceived risk 0.869 0.911 0.720
Intention of use 0.746 0.888 0.799

Hypotheses Path Testing

The seven hypotheses in this research were tested by SmartPLS 3.0. From the result in Table 7, it indicates that five hypotheses are supported and two hypotheses are not supported.

Table 7 Summary of Path Relationships
Hypothesis Path Path coefficient P value Result
H1 Perceived ease of use ? intention of use 0.460 0.000 Accept
H2 Perceived ease of use ? perceived usefulness 0.266 0.002 Accept
H3 Perceived value ? perceived usefulness 0.261 0.002 Accept
H4 Trust ? perceived usefulness 0.282 0.000 Accept
H5 Trust ? perceived risk 0.673 0.000 Accept
H6 Perceived usefulness ? intention of use 0.181 0.068 Reject
H7 Perceived risk ? intention of use 0.042 0.616 Reject

Hypotheses H1 and H2 have p values less than 0.05 which show that perceived ease of use significantly affects intention of use and perceived usefulness respectively. Their relationships are positive since their path coefficients are in positive value. The strength of path dependence between perceived ease of use and intention of use is moderate whilst between perceived ease of use and perceived usefulness could be said as weak. The relationship between perceived value and perceived usefulness as hypothesized in H3 is significant, positive and not strong. The two hypotheses about trust in H4 and H5 are tested to be significant and positive to perceived usefulness and perceived risk respectively. Especially for hypothesis H5 with path coefficient as 0.673 which could be interpreted as relatively strong relationship. It is not surprise in the online environment especially consumers are using E-tourism in booking air tickets, hotels, and other transportation, higher trust of those E-tourism platforms will lower the consumers’ risks in using these platforms. The testing of the last two hypotheses (H6 and H7) related to the ultimate dependent variable: intention to use, shows that this dependent variable is not significant related to perceived usefulness and perceived risk with p values greater than 0.05. They show that in order to attract the consumers to use E-tourism platforms, easier use of interface might be more critical to lower risk and whether the website is useful or not.

Analysis of the Model

The results of the model are shown as in Figure 3. It shows that the R2 of perceived usefulness is 0.431, which means that the relationship from perceived ease of use, perceived value and trust to perceived usefulness is not so strong. Also, the R2 of intention to use is 0.346, it is not strong especially there is an insignificant relationship between perceived ease of use and perceived usefulness to intention to use. Furthermore, the R2 of perceived risk is 0.53, which means a medium relationship from trust to perceived risk.

Figure 3 Results of the Research Model

Results and Discussion

Perceived Ease of Use

After analysing the data, the result shows that there is a positive relationship between perceived ease of use and intention to use, which is similar to the findings of Ku (2009), and Mohammad et al. (2013). The former one stated that students’ beliefs on using the online learning system as easy to use, had a direct effect on their attitude toward using online learning system; the later one stated that perceived ease of use of web-based learning of students had a significant and direct influence the intention to use web-based learning. This may be an effect of the characteristics of students that were more willing and having higher ability to learn and understood the benefits of using online features. However, there was a research contradicted with the result of this study. Gong et al. (2013) stated that perceived ease of use was not found to be a predictor of Chinese consumers’ online shopping intention. The reason is that there may be other factors having a greater influence than ease of use towards intention to use in China. They are lacking of safe and efficient online payment mechanism, low download speed and data transfer rate, low credit card usage and transaction volume, mindset of “Never make a purchase until you have compared three shops”, word of mouth by group orientation, time-saving, lower price, and wide selection. Qualitative interview also indicated that convenience is one of the factors to choose a tourism website. Therefore, E-tourism website owners should build a user-friendly interface. For example, they can build fine and simple instead of complex and intricate web pages, eliminate duplicate web pages and provide a site map.

The results also show that perceived ease of use positively affects perceived usefulness. The research of Surachman (2013) showed that if the developed mobile library technology made it easier for the user, then the user will increasingly feel the benefits, and will affect the assessment of the usefulness of mobile library. Though there was a research by Park et al. (2018) suggested that perceived ease of use had no effect on information technology usage and may not remain an issue if the technology is useful. It suggested that the reason was people no longer feel difficult to use information technology and the reluctance to learn will be lesser as the usage became more common in modern life. That meant perceived ease of use would be less meaningful in predicting future use because an individual got accustomed to a system as the user gaining the experience of using it. The reason that it is different from this research could be the focus of that research is intranet of restaurant industry, which means that internal and private usage comparing with public usage will have different concerns.

Perceived Value

This study finds a relationship existed between perceived value and perceived usefulness in which perceived value has a positive impact on perceived usefulness. There are several studies that support this finding, which include (Lee & Jun, 2007; Kim et al., 2007; Pihlström & Brush, 2008; Mudambi & Schuff, 2010). Customers would be willing to use E-tourism if they found that it is more useful compared to the traditional way. Laukkanen (2007) found additional value and potential value could improve customer satisfaction, thus further improve customer perceived value. For example, the additional value can be the addition of a customer review area. Customers could search for more information about the products from other customers’ reviews. Previous research by Kumar & Benbasat (2006) has shown that the mere presence of customer reviews on a website could improve customer perception of the website. Reviews are perceived as helpful to customers and have greater potential value to companies, including increased sales (Chen et al., 2008; Chevalier & Mayzlin, 2006; Clemons et al., 2006; Ghose & Ipeirotis, 2006). Although customer will make different consumption based on information from customer reviews, the information from customers’ review helps the customers make decisions.

According to the qualitative interview, most of interviewees will read comments. They consider the information from the comments that can help them to make a decision. A reason is that there are many photos in the comment area, many consumers grade the products or services and share their experiences. Then, customers will use that information to compare whether the products or services satisfy their expectations or arouse their interest. Therefore, the website owners can improve the perceived value by increasing the additional value, thus improve the usefulness of the website. The website owners can create additional value, especially functional value, such as the number of available rooms in real time. This can help customers quickly find out which hotels having vacancies and book in some emergency situations. Nowadays, customer's private customized service is popular, the website owners can launch a private tour guide service. Tour guides can be professional guides, locals or even international students. People can enjoy the local customs and practices, and avoid the inconvenience of some cultural differences. This can be a conglomerate service, instead of just providing services such as booking hotels, renting cars, and purchasing air tickets.

Trust

The results of this study find that trust is positively affecting perceived usefulness. It is different from the previous research by Cheung et al. (2008) that was about the adoption of online opinions in online communities. Their research found that there was no significant relationship between perceived usefulness and trust. This reflects that the relationship between trust and usefulness is very dependent on the customer. Many factors may contribute in it and the situation towards trust is very complicated. It is not easy to make a conclusion that trust is really positively or negatively affecting the perceived usefulness. The research by Wong (2017) also found there was not a significant relationship between the trust and the perceived usefulness, but the research also indicated that trust was a very complicated contrast in research. The findings in the qualitative interview also show that different interviewees also had different views toward the usefulness. The factors concerned by interviewees include brand image, reality, price and time-consuming.

The results also show that there is a negative relationship between trust and perceived risk. This result is similar to the findings by Amaro & Duarte (2015). Their research conducted a similar study about the consumers’ intention to purchase travel online. Also, it had the same result with the study of Van der Heijden et al. (2003) which is about the contribution from technology and trust prospective. However, the results contradict with the research by Wong (2017) and Jarvenpaa et al. (2000) that there was no significant relationship between trust and perceived risk. The reason may be the awareness of people toward the security on the Internet was not at a high level in the previous time. With the improvement of the information technology, people can access to the Internet easily. With the application of big data, people’s online information may be easily misused and stolen easily. With this trend, people become more and more concern about the risk. So the result is different due to the improvement of technology.

Intention to Use

Moreover, this study finds that perceived usefulness does not significantly influence the intention to use. It is consistent with the study by Muda et al. (2016) that perceived usefulness did not influence Gen Y’s online purchase intention in Malaysia. On the other hand, the result is differed from the research of Moslephour et al. (2018) which stated that perceived usefulness had a significant impact on online purchase intention for Taiwanese online consumers. The reason is the online consumers in different cities or countries were affected by different aspects. For Hong Kong people, they may concern more in perceived ease of use rather than perceived usefulness when using E-tourism. It also means that Hong Kong people who perceived E-tourism as a useful tool may not tend to use them for purchase. Qualitative interview also indicated that Hong Kong customers will consider other factors in using E-tourism like price and convenience. Therefore, technology innovation should not be the major concern for companies who developing E-tourism. They should focus more on other aspects like user-friendliness in order to attract more new customers in Hong Kong.

Finally, this research finds that the relationship between perceived risk and intention to use is not clear. It differs from the study by Jordan et al. (2018) which showed that the lower perception of risk will increase online purchase intentions. However, the result is consistent with the study by Muda et al. (2015) that perceived risk did not influence Gen Y’s online purchase intention in Malaysia. Another research by Wei et al. (2018) also indicated that the perceived risk has no significant effect on consumers’ online purchasing intention in China. It reflects that Hong Kong online consumers are like other Asian cities or countries. Although they have awareness of Internet security, they still tend to use the Internet because of the benefits brought from it. Even though they know that there are risks like identity theft and invasion of privacy when surfing the Internet including using E-tourism, they will ignore them because they rely on the Internet too much. It also matches the result collected by the qualitative interview that they would choose to ignore the risk because of its convenience. Therefore, it is important to increase the precaution in online security to avoid Internet risks.

Limitations and Recommendations

Although this research studies the factors affecting Hong Kong customers’ purchase intention in using E-tourism, it is subject to four restrictions. First and foremost, the scope of the research is not large enough. The result found in this study may be just able to apply on the E-tourism but different electronic platforms may have different results due to different factors concerned. Further research could be conducted to compare the result of different studies in factors affecting Hong Kong customers’ purchase intention in using different kinds of electronic platform. Second, the questions in the online questionnaire are adopted from the previous research which had done the pilot test to test the reliability. However, in this research, no pilot test was done again after changing the wording of the questions because of, first the changes were believed not too much whilst second, the validity and reliability of the past questionnaires were quite high. However, the respondents of this study might misunderstand some of the wording in the questionnaire and give a different response from their understanding which might lead to possible bias affecting the results. Future studies are suggested to have a pilot test in order to ensure the validity and reliability of the questionnaires if wording is changed. Third, the background of the sample of the qualitative method is similar because of using convenience sampling. Convenience sampling approach might collect data from respondents with similar experience so that their responses may be close to each other. It then causes some bias of the qualitative results as the sample did not represent the opinions from other backgrounds. Further research could be conducted in which the sampling approach covers more respondents with different backgrounds, such as different ages, occupations and education level. Last but not the least; the result may be applicable in Hong Kong only. Although the results are similar to previous research conducted in Asia, different countries or cities will still have different factors to concern due to the difference in cultures or politics. Scholars can have further studies in E-tourism in other Asian countries like Japan, or even in western countries for comparison of findings.

Conclusion

This study had examined the factors affecting the purchase intention of Hong Kong customers in using E-tourism. Three constructs of TAM have been used as the core structure of the model for this study; they are perceived usefulness, perceived ease of use and intention to use. Besides, additional constructs including trust, perceived risk and perceived value have been added as the extension of the model. Seven hypotheses were proposed in which five are supported and two are not supported according to the statistical analysis. The results of this study finds that the relationships between perceived ease of use and intention to use, perceived ease of use and perceived usefulness, perceived value and perceived usefulness, trust and perceived usefulness, and trust and perceived risk are significant. On the other hand, the result also shows that the relationships between perceived usefulness and the intention to use, and perceived risk and intention to use are not significant. Researchers might be inspired by this study and perform further research of TAM regarding the E-tourism in Hong Kong. Finally, this study contributes to significant managerial implications in developing tourism websites and advance the service they provided.

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