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The determinants of intention to use electronic booking among young users in Thailand.

1. Introduction

Tourism is one of the largest and fastest growing industries worldwide. It helps to support the economic growth and development of many countries, Thailand included. A key engine of the growth of tourism has been the Internet, especially over recent years (Buhalis, 2004). This is because the Internet, along with other information technology (IT), allows information to flow with great efficiency, thus encouraging users to rely on this form of communication for its low cost, security, and accuracy. Without a doubt, the Internet is an extremely important medium in the marketing communication process (Lagrosen, 2005; Law, Qi, & Buhalis, 2010; Lin & Lee, 2010).

The advent of the use of IT applications in the distribution of tourism products has raised the level of sophistication in business practices, not just in terms of effectiveness but also in terms of cost efficiency (Golmohammadi, Jahandideh, & O'Gorman, 2012). This change has come about as a result of the increasing number of online users who are now familiar with using e-commerce and other transactions, which are widely supported by the e-payment system.

The Internet has become more important in Thailand and is now an integral part of everyday life, used for working, communicating, scheduling, and even traveling. Thai travelers use the Internet to search for information in preparing for their travels, book accommodation, arrange transport, choose and book a restaurant, or buy travel-related products such as package tours (Chaiprasit, Jairangprasert, Chomphunut, Naparat, & Jaturapataraporn, 2011). The hotel industry now allows the booking of rooms via the Internet, and online booking has become very important for both domestic and international business and has led to the emergence of online hotel booking companies. Expedia, Priceline, Travelocity, Orbitz, and Booking are well known online booking companies focusing on international business, while Agoda, Hotelsthailand, Sawasdee, and Asia Web Direct are well known online booking companies in Thailand. Hotels also offer online room bookings through their own websites, for example Bangkok Asia Hotel developed its online booking system five years ago to support free independent travelers (FIT) (Boonlert, 2010). Such websites provide full details of the hotels and room rates.

Online hotel booking has been around in Western countries for at least ten years, whereas Thailand has been utilizing it for around eight years. Four- and five-star hotels in Thailand have changed their sales strategies from 80% reliance on agents to the current online booking system. This has resulted in direct room bookings all around the world, and has led to a 40% increase in bookings, which is expected to rise to 60% in the near future. Online hotel booking websites, both international and domestic, are now focusing on Thai travelers and have added the Thai language into their websites. Examples of these are thailand.hotels.com, hotelsthailand.com, agoda.co.th, thaihoteltravel.com, ThaitravelCenter.com, and TripDD.com (Boonlert, 2010).

In order to continue to develop Information and Communications Technology (ICT) in Thailand, the Second ICT Master Plan (2009-2013), consisting of six strategies, was proposed. The sixth strategy focuses on the "use of ICT to build sustainable competitiveness capacity for Thai industries" with an emphasis on the use of ICT in both the strategic manufacturing sector as well as the service sector. One of the objectives is to promote the use of ICT, namely the Internet, e-commerce, online marketing, payment systems, and reservation systems for businesses associated with tourism. This is also in line with the First ICT Master Plan, which placed emphasis on the development of ICT for e-commerce (Ministry of ICT, 2009).

It is clearly evident that the Thai government realizes the importance of the utilization and growth of ICT in tourism, especially in the form of e-commerce. Although more businesses and users have embraced e-commerce and online reservation systems (e-booking), very few studies have been conducted on their usage and adoption especially in the context of a developing country like Thailand. Therefore, this paper proposes two research objectives to address this issue. By undertaking these research objectives, the study will fill in the gaps of research undertaken on e-booking in the context of a developing country.

The two objectives are as follows:

1 To identify the factors and the degree of influence that each factor has on the intention to use e-booking.

2 To identify the factors that have the highest degree of influence on the intention to use e-booking among Thai users.

A literature review of the technology acceptance model (TAM) and e-booking is provided in the next section. This is followed by the research model and hypotheses proposed for this study and the research methodology, which includes instrument development and data collection. An in-depth analysis of the data and results and the conclusions and implications are presented in the subsequent sections.

2. Literature review

2.1. E-booking

E-booking means making a reservation or appointment for a service via the Internet. Landvogt (2004) defines e-booking or online booking engines as tools to store, publish, and update the dynamic data availability and prices, and additionally provide the users with a regular reservation process. Mobile travel booking, as a new way of booking, refers to the consumer using a mobile phone, computer or other portable mobile terminal equipment, through GPRS, 3G, WiFi, and other wireless networks to book air tickets, hotels, resorts and other tourism products or services (Yang, Chu, & Yang, 2006).

The use of the Internet for communicating and transacting with customers has been increasing rapidly in the worldwide tourism and hospitality industry. There has been a rapid increase in online booking in the hospitality and tourism industry, e.g., e-booking of hotel/motel rooms, airline tickets, travel packages, etc., due to the ease of checking information, making inquiries, and making reservations online--in other words, the overall convenience of communicating electronically via the Internet.

E-booking allows service providers to sell or distribute their services both directly to customers or indirectly (via the network or partner distribution channels, such as online travel agents). The adoption of e-booking in the tourism and hospitality industry began and grew rapidly because the nature of its services appeared to fit in well with information technology and its systems (Crnojevac, Gugic, & Karlovcan, 2010). Both sellers and buyers of tourism products find their comfort zones when they use the electronic distribution system for completing their transactions.

Unarguably, online tourism has successfully emerged as a platform that enables direct bookings, electronic payment, Business to Business (B2B) and Business to Consumer (B2C) trading among product marketers, travel agents, resellers, and customers. It has been reported that online booking in the hospitality industry (including hotel/motel, airlines, travel packages, etc.) is rapidly increasing, especially at the lower rate end. Yang et al. (2006) reported that online hotel room bookings had increased six fold from 1999 to 2002 (from $1.1 billion in 1999 to $6.3 billion in 2002). While the e-booking of airline tickets reached about 26% of total annual sales in 2002, online hotel room booking accounted for just half of that proportion--13% of total annual hotel room bookings.

More significantly, the groups who now book online are business travelers and well heeled vacationers who tend to travel more frequently than the average public. Targeting great deals as they do their online searches, such online bookers claim that more often than not they are able to book a hotel room at a much lower rate online compared to traditional phone reservations or traditional travel agents (Yang et al., 2006).

Given the growing number of customers making e-bookings, hospitality businesses need to improve the way they conduct their business operations via the Internet (O'Connor & Frew, 2004). Nowadays, a majority of hotels and airlines depend heavily on websites for direct bookings, either their own website or the websites of travel agencies. It is highly crucial that these organizations make sure that they provide the latest information and offer attractive deals for customers (Almeida, Silva, Mendes, & Oom do Valle, 2012).

While online hotel booking has been around internationally for over ten years, in Thailand it has been popular for around eight years. Hotels in Thailand, especially four- and five-star hotels, have changed their sale strategies to the point where 80% currently use online booking. This has resulted in a 40% increase in sales, which is expected to rise to 60% in the near future. Nowadays, online hotel booking websites, both international and domestic (for example, thailand.hotels.com, hotelsthailand.com. agoda.co.th, thaihoteltravel.com, ThaitravelCenter.com, and TripDD.com), have begun to focus more on Thai travelers and have begun presenting travel information in the Thai language (Boonlert, 2010).

There are several factors that have led to the growth of online bookings in Thailand. There are approximately 17.5 million Internet users in Thailand, and more than 2.5 million of them enjoy online shopping. This number increases every year because online shopping is convenient, secure, and it offers a wide variety of products and services. The online market in Thailand for travel is 10%-20% cheaper than traditional travel agents. Moreover, Thailand's online travel market has undergone rapid growth, averaging a 30% online booking rate increase per year (Manager 360 PRNews, 2012). As a result, Expedia, the world's leading online travel company, has joined with AirAsia and expanded its business in Thailand in 2012 by launching www.expedia.co.th to offer attractive prices for hotels and travel destinations worldwide for Thai travelers (Manager 360 PRNews, 2012).

Considering the number of online transactions, Thailand has the greatest potential for online marketing when compared to neighboring countries such as Malaysia and Singapore. The trend shows consistent growth of online booking in the tourism industry, hence this is an important opportunity for Thailand to focus on and further develop its systems in order to prepare itself for the advent of the ASEAN Economic Community (AEC) in 2015 (Chaiprasit et al., 2011).

2.2. Technology acceptance model

In order to explain the use of information technology systems, researchers initially developed tools that would allow them to measure and analyze the satisfaction level of computer users. Bailey and Pearson (1983) noted that in order to do this researchers needed to turn to psychologists, given their expertise in the study of satisfaction. As a result, the Technology Acceptance Model (TAM) was introduced by Davis (1989) to answer the question as to why users accept or reject a particular technology (Legris, Ingham, & Collerette, 2003).

The TAM was first introduced by Davis in 1989 as an adaption and an extension of the Theory of Reasoned Actions (TRA) (Legris et al., 2003; Roca, Chiu, & Martinez, 2006), which was proposed by Fishbein and Ajzen (1975). The TRA states that a person's belief influences his/her attitude, which then forms a behavioral intention to use the item in question. The attitude-intention-behavior causal chain was then adapted by Davis to predict user acceptance of IT (Hsu & Lu, 2004).

However, the attitude variable was later removed from the TAM model (as shown in Fig. 1) by Venkatesh and Davis (1996) because they considered attitude to be a weak predictor of both behavioral intention to use and actual system use. Taylor and Todd's (1995) research findings also confirmed this to be true (Wu & Wang, 2005). Lederer, Maupin, Sean, and Zhan (2000) and Teo, Lim, and Lai (1999) also dropped the attitude variable from their study to simplify the TAM model. Instead they focused on studying the relationship between perceived usefulness and perceived ease of use on intention to use (Klopping & McKinney, 2004).

The use of TAM by researchers has increased, and TAM has been applied extensively to user acceptance research in the context of different countries and different types of participants, as shown in Table 1. Several meta-analyses performed on TAM have also proved it to be a valid, robust, and powerful model (Bertrand & Bouchard, 2008).

Even though TAM has been applied in different contexts and incorporates different types of participants. Lu, Yu, Liu, and Yao (2003) believe that it should be integrated with other variables or other IT acceptance models. By doing so, TAM's specificity and explanatory utility can be improved.

3. Research model and hypotheses

From the literature review it is evident that TAM needs to be integrated with other variables to make it a stronger model. A comprehensive model that integrates these variables will allow for an understanding of why current users use e-booking and also provide an insight for future users. The research model chosen consists of the TAM model and three variables, namely, image, subjective norm, and perceived value.

3.1. E-booking and the TAM relationship

3.1.1. Perceived usefulness

The TAM states that the behavioral intention of users towards the use of technology is determined by two variables, namely, perceived usefulness and perceived ease of use (Liu, Chen, Sun, Wible, & Kuo, 2010). According to Davis (1989), perceived usefulness is "the degree to which a person believes that using a particular system would enhance his or her job performance" (p. 320). Davis (1989) also states that perceived usefulness has a positive relationship with behavioral intention. A significant number of studies have shown a positive relationship between perceived usefulness and behavioral intention. In her study of electronic mail systems, Szajna (1996) also concluded that perceived ease of use has a positive impact with intention to use. This was again confirmed in a study conducted by Venkatesh and Davis (2000). In another study, on the virtual learning environment of Chinese executive MBA students, Van Raaij and Schepers (2008) concluded that perceived usefulness has a positive relationship with intention to use. Lu et al.'s (2009) study of students' use of instant messaging and Rouibah, Abbas, and Rouibah (2011) study of camera mobile phone shopping also found similar results. Moreover, Van Raaij and Schepers found that perceived usefulness yielded the strongest effect on intention to use.

In the context of e-booking, perceived usefulness refers to the degree to which users feel that using e-booking will be useful for them when making online reservations or online payments. Perceived usefulness therefore is an indicator of whether or not they want to use e-booking, is an important determinant of intention to use, and is an example of extrinsic motivation (Lee, Cheung, & Chen, 2005).

According to Thavornchak and Taratanaphol (2009), perceived usefulness seems to be significant in predicting the intention to buy a domestic airline e-ticket in Thailand. Moreover, respondents appeared to focus on the attributes of accessibility and availability as the most important factors, which have to do with whether the product/service information provided by the company or the seller is easily searchable via the Internet. Such information in this case would include flight information such as schedules, price, promotions, terms and conditions, and any other details regarding flights and services. This seems to be consistent with Lim and Dubinsky (2004), who stated that consumers were likely to buy online those products for which more information was provided. This is probably due to the fact that since customers cannot actually experience the product they intend to purchase, information plays an important role in their decision making. This implies that if the key features and details of an e-ticket are presented online, customers will feel confident in making an online purchase. Therefore this study proposes the following hypothesis:

H1. Perceived usefulness has a positive influence on intention to use.

3.1.2. Perceived ease of use

Perceived ease of use has been defined by Davis (1989) as "the degree to which a person believes that using a particular system would be free of effort" (p. 320). According to Davis (1989), perceived ease of use has a positive effect on perceived usefulness. In their study of online games, Hsu and Lu (2004) concluded that perceived ease of use has a positive relationship with perceived usefulness. This has been supported by the following studies: Calisir and Calisir (2004) in their study of enterprise resource planning systems and Wu and Wang's (2005) study of mobile commerce. Yi et al.'s (2006) study of acceptance of personal digital assistants by healthcare professionals also proved that perceived ease of use exerts a positive relationship towards perceived usefulness. Moreover, Lu, Zhou, and Wang (2009) also found that perceived ease of use has a significant impact on perceived usefulness with regard to instant messaging.

In the context of e-booking, perceived ease of use is defined as the degree to which users feel that e-booking is free of effort and is not difficult to use. If they perceive that it is easy to use, they will also perceive it as being useful to them.

Kamel and Hussien (2004) applied the TAM to evaluate the introduction of the Internet as a platform for business development in the King Hotel in Egypt. Their study concluded that the acceptance level of any technology is fundamentally affected by user perception of ease of use and usefulness. Hence, increasing the perceived ease of use of a technology will increase its perceived usefulness and translate into an increased behavior intention, thereby resulting in a higher margin of acceptance of the technology.

Yang et al. (2006) used the TAM to investigate the factors that predict tourists' intentions to use mobile travel booking. Their results show that perceived ease of use has a positive effect on perceived usefulness while perceived usefulness in turn has a significant effect on behavior intention just as does perceived ease of use. This implies that the more faith tourists have in mobile travel booking, the more likely they will view mobile travel booking as useful. Therefore, mobile travel booking providers should focus on designing both useful and easy-to-use mobile travel booking systems. Thus the following hypothesis is proposed:

H2. Perceived ease of use has a positive influence on perceived usefulness.

Davis (1989) also found that perceived ease of use indirectly affects behavioral intention through perceived usefulness, which means that perceived usefulness mediates the effect of perceived ease of use on behavioral intention (Lu et al., 2009). This was confirmed by several studies that support this claim, notably, Szajna's study on electronic mail systems (1996), Jackson, Chow, & Leitch (1997) study on corporate systems and operating environments, and Gefen's (2003) study of online shoppers. Liu et al. (2010) also concluded that perceived ease of use has a positive impact on intention to use online learning communities. In her study of electronic mail systems, Szajna (1996) also concluded that perceived ease of use has a positive impact on intention to use. This was again confirmed in a study conducted by Venkatesh and Davis (2000).

Thavornchak and Taratanaphol (2009) explored the factors influencing the intention to purchase a domestic airline e-ticket in Thailand. They found that perceived ease of use, perceived usefulness, and perceived risks were related to the intention to buy for e-ticket non-adopters, while perceived ease of use or convenience was the strongest of all factors. This result accords with Roca et al. (2006), who noted that perceived ease of use was significant especially for those who were in the initial stage of learning to use various applications. Eriksson and Strandvik (2009) conducted a field trial to explore factors affecting the adoption of mobile travel reservations and discovered that the major determinants were the value aspect of a packaged tour, price transparency, and ease of use. Therefore the following hypothesis is proposed:

H3. Perceived ease of use has a positive influence on intention to use.

3.2. E-booking and the image, subjective norm, and perceived value relationships

3.2.1. Image

Using subjective norm and image as two additional constructs allows our study to focus on the social characteristics of e-booking users. One of Hofstede's five cultural dimensions is collectivism vs. individualism. According to Hofstede, Thailand received a score of twenty on the individualism dimension, which means that Thailand is a highly collectivist country. The current study would like to understand whether Hofstede's cultural dimension holds true for the use of e-booking among young Thai users (Hofstede, 2001).

According to Moore and Benbasat (1991), image is "the degree to which an individual perceives that use of an innovation will enhance his or her status in his or her social system" (p. 195). This concept of image has been applied to various technology adoption studies and has yielded positive results. In their study of the adoption of wireless Internet services via mobile technology, Lu, Yao, and Yu (2005) revealed that users found image to have an impact on perceived usefulness and were influenced by their social setting. This was also found in the studies of Yi, Jackson, Park, and Probst (2006) on the acceptance of personal digital assistants by healthcare professionals and Zhang, Xunhua, and Gouping (2008) on the adoption and usage of e-mail. Both studies found that image has a positive relationship with perceived usefulness.

Growing numbers of customers now purchase tourism products through websites and perceive that image and usefulness directly affect their purchase intentions (Chiang & Jang, 2007). In their study of behavioral intentions in adopting information technology, Law and Hsu (2006) found that attitudes fully mediate the relationship between perceived image and perceived usefulness, ease of use, and the behavioral intention to use IT with respect to the hotel industry. This implies that image is an important determinant in technology adoption. Yeoman and McMahon-Beattie (2006) predicted that by 2015, the majority of consumers will purchase holidays through the Internet, and that the digital society will change their purchase behavior.

In the context of this study, users may feel that using e-booking is a status symbol and that if they use it, they will somehow gain more prestige and a higher profile among their peers or friends. Thus the following hypothesis is proposed:

H4. Image has a positive influence on perceived usefulness.

3.2.2. Subjective norm

Fishbein and Ajzen (1975) defined subjective norm as "the degree to which an individual perceives that most people who are important to him think he should, or should not, use the system" (p. 302). In their study, Venkatesh and Davis (2000) found that subjective norm has an influence on usage behavior through perceived usefulness. The positive relationship between subjective norm and perceived usefulness was also confirmed in a study conducted by Yi et al. (2006) on the acceptance of personal digital assistants by healthcare professionals. Similarly, Schepers and Wetzels (2006) performed a meta-analysis on microcomputer use and found a significant relationship between subjective norm and perceived usefulness.

Kim, Kim, and Shin (2009) found that subjective norms are the antecedent of perceived usefulness, attitude toward use, and customers' intention to reuse airline B2C eCommerce websites. This implies that customers who frequently shop and purchase air travel-related products from websites of airline companies tend to rely heavily on referents when they make purchases. The result of this study also coincides with that of Buttle and Bok (1996), who studied an online marketing strategy for hotels and the theory of reasoned action. They suggested that subjective norms are an important determinant of perceived usefulness, attitude, and intention as well. In the context of e-booking, users will choose to use it if they believe that people that are important to them, whose opinions they value, and who influence their behavior are using it. Therefore the following hypothesis is proposed:

H5. Subjective norm has a positive relationship on perceived usefulness.

3.2.3. Perceived value

The concept of perceived value is regarded as one of the most important factors in the field of consumer research, especially in the context of shopping behavior. Perceived value can be measured from customer assessment of the quality of the product or the quality of service in conjunction with the perceived cost of the product or service (Bearden & Shimp, 1982). Additionally, perceived value is considered to be an important factor in determining buying behavior of the customers (Dawar & Parker, 1994). There is evidence that higher perceived value can lead to a higher tendency for repeat purchasing behavior and loyalty of the customers (Dodds, Monroe, & Grewal, 1991). To measure perceived value, scholars have suggested using the ratio of perceived quality to the perceived cost of the product or services.

Empirical studies have demonstrated that perceived value leads to purchase intention. Li and Suomi (2007) found that customers' adoption, or rejection of e-services in the airline business is determined by customers' perceived value of these services. Customers will adopt e-services when perceived benefits, such as convenience and time saved, outweigh obstacles such as security risk and doubts as to a site's trustworthiness. A study by Kamtarin (2012) also came up with results that were consistent with empirical studies, namely that behavioral intention is significantly influenced by perceived value. In a much earlier study, Fishbein and Ajzen (1975) stated that customers' positive perceived value of either products or services can lead to a belief in their trustworthiness and result in an intention to commit to a long-term relationship with online retailers.

Wang and Wang (2010) investigated the adoption of mobile hotel reservation services from the perceived value perspective and found that perceived value was a predictor in explaining customer adoption of mobile hotel reservations. In the context of this study, users were more likely to use an e-booking system if they perceived it to be of value. Therefore, the following hypothesis is proposed:

H6. Perceived value has a positive relationship with intention to use.

Ease of use is one of the major factors that can maximize a user's perceived value of a commercial website (Keeney, 1999). Caruso and Westberg (2008) examined how Generation Y consumers perceived the value of online music sites and the relationship between perceived value and purchase intention. Evidence from this research showed that perceived ease of use was found to have a strongly positive correlation with perceived customer value. Furthermore, Alsheikh and Bojei (2012) studied customer perceived value in the context of usage of mobile banking services. They suggested that both usefulness and ease of use of the service delivery are important dimensions of the customer's perceived value, and that when banks are capable of improving these elements, it will benefit the customers. Therefore, as long as service providers offer added benefits to the customer, the customer's perceived value will increase.

Research from Chong, Zhang, Lai, and Nie (2012) revealed that there are three value added characteristics of mobile Internet services, namely informativeness, personalization, and compatibility, which affect perceived value indirectly through usefulness and ease of use. Yang and Peterson (2004) stated that customer satisfaction and perceived product value can contribute positively to consumer loyalty. This contribution is provided through dimensions such as perceived ease of use, customer services, product portfolio, and security/privacy.

Lexhagen (2008) studied customer-perceived value of travel and tourism websites and found that customer-perceived value in the context of information technology may be affected by factors such as customers' previous experiences. Roca et al. (2006) further explained that when the users or consumers already had experiences with a website or when they got accustomed to using one, their perceived ease of use increased. In this study, users will find e-booking easy to use if they perceive it to be of value. Thus, this study proposes the following hypothesis:

H7. Perceived value has a positive relationship with perceived ease of use.

Many studies have found a positive relationship between perceived usefulness and perceived value. A study by Lee and Jun (2007) showed that perceived value of a marketing offer had a significantly positive effect on the perceived usefulness of mobile commerce. Furthermore, in a mobile commerce context the perceived value of a marketing offer was also found to have a significantly positive effect on both the repurchase intention and customer satisfaction. In addition, Kim, Chan, and Gupta (2007) found that usefulness is positively related to perceived value in the context of mobile Internet adoption. They also discovered that in a mobile Internet context the perceived value fully mediates the relationship between usefulness and the adoption intention. Some studies find that perceived usefulness can be used to measure perceived value. Pihlstrom and Brush (2008) pointed out that in marketing literature, usefulness is used to measure one aspect of perceived value.

On the other hand, there are many studies that show the similarity between perceived value and perceived usefulness. According to Shih (2004), perceived usefulness is considered equivalent to perceived value (or perceived benefit) and can be used to measure the effectiveness of e-shopping as perceived by consumers. Keil, Beranek, and Konsynski (1995) supports a notion of perceived value that is similar to the concept of usefulness by utilizing a study by Maher and Rubenstein (1974). The latter examined the factors affecting the adoption of a Monte Carlo simulation program in the area of project selection and found that there was a strong positive correlation between the perceived value of the data that was generated by the model and an individual's willingness to adopt the system.

In the study of customer-perceived value of medical tourism, the Internet has become an especially important tool for marketers and healthcare providers to give information and market a wide variety of healthcare services and products (Bodkin & Miaoulis, 2007). It has been argued that perceived value is greatly impacted by the use of the Internet as a medium for the search and procurement of goods. As a source of information and a means of procuring goods, it has also been argued that the Internet has functional, social, and epistemic value (Cheng, Wang, Lin, Vivek, 2009). In this study, we argue that users will find e-booking to be useful if they perceive it to be of value, according to the following hypothesis:

H8. Perceived value has a positive relationship with perceived usefulness.

Researchers have also attempted to investigate the relationship between image and perceived value. A study undertaken by Ryu, Han, and Kim (2008), conducted on the relationship between the quick-casual restaurant image and perceived value, found that image exerts a positive relationship with perceived value. Hu, Kandampully, and Juwaheer, (2009) also studied the relationship of perceived value and image satisfaction in the hotel industry. Results indicated that creating superior customer value can affect a firm's corporate image. Consequently, developing a good perceived image is the goal of every service provider due to its potential impact on repeat purchasing behavior (Ryu, Lee, & Kim, 2012). This was also confirmed in a study by Milfelner, Snoj, and Korda (2011) in their measurement of perceived value and image and their interrelationship, conducted on hotel services in Slovenia and Italy. They concluded that image has a significant relationship with perceived value. In the context of e-booking, if users believe that image is important then they will perceive it to be more valuable to them. Thus the following hypothesis is proposed:

H9. Image has a positive relationship with perceived value.

Based on the extensive literature review, this study would like to propose the model and the accompanying hypotheses as presented in Fig. 2.

The rationale for proposing so many constructs in this study is that the TAM by itself already makes up three constructs, and without adding the three additional constructs to this study there would be no significant contribution to the literature. Furthermore, previous studies on the TAM have proposed more than six constructs, such as Gu, Lee, and Suh (2009) study on intention to use mobile banking, which proposed twelve constructs, as well as Lee et al.'s (2014) study on individual and system characteristics on enhancing e-learning acceptance, Huang and Liao's (2014) study of augmented-reality interactive technology, and Oh and Yoon's (2014) study of haptic enabling technology. Nine hypotheses were proposed in the present study because many TAM-related studies also proposed more than nine hypotheses in their research models and yielded significant results. Examples of these studies include Gu et al.'s (2009) study on intention to use mobile banking, which proposed sixteen hypotheses, Hong et al.'s (2011) study on digital archives system, which proposed eleven hypotheses, Oh and Yoon's (2014) study of haptic enabling technology, which proposed ten hypotheses, and Shin's (2014) study on cloud services, which proposed twelve hypotheses.

4. Research methodology

4.1. Instrument construction

Questionnaires consisting of measurement scales were developed and modified from previous studies in the context of e-booking. The questionnaire used consisted of two sections. Section one captured the demographics of the users such as gender, academic major, years in college, and monthly income. In section two, participants were asked to indicate their perception towards e-booking by focusing on the following constructs: image, trust, familiarity, perceived value, Internet benefit, perceived performance risk, perceived ease of use, perceived usefulness, intention to use, and usage behavior. The study used the 7-point Likert scale, with 1 indicating "definitely disagree" and 7 indicating "definitely agree." The questionnaire was pre-tested among 20 participants and was modified based on the input received from the participants of the pre-test.

4.2. Data collection

Data were collected from November 2012 to January 2013 from young consumers who were students at a leading university in Thailand. The participants were chosen completely at random. The characteristics of the samples showed variations in majors and years of study. All the respondents had prior experience with using e-booking in hotels and airlines. Of the 1000 questionnaires, 579 were returned and usable, a response rate of 57.9 percent, with no serious issues in terms of missing values, outliers, and distributions. The demographic profile of the participants is summarized in Table 2.

5. Data analysis and results

5.1. Analysis of measurement validity

Prior to testing the proposed model, the authors conducted tests on convergent validity and discriminant validity. According to Hair, Tatham, Anderson, and Black (2006), convergent validity is occurs when some measures exhibit a high correlation with different measures of similar constructs. Convergent validity verifies that the measures (or manifest items) of constructs that theoretically should be related are actually related. Whereas discriminant validity shows that all the constructs can actually be differentiated.

According to Anderson and Gerbing (1988), a good convergent validity exists when the standardized factor loading of each item exceeds 0.40 (Lin & Germain, 2003). The result of the convergent validity verifies that all the observed variables could be converged to each construct appropriately. The data shown above in Table 3 has an acceptable convergent validity.

For discriminant validity, all the AVE values of two constructs are higher than their squared correlation (Fornell & Larcker, 1981). Table 4 demonstrates correlation coefficients and square roots of AVEs, indicating acceptable discriminant validity.

5.2. Model testing results

In this part, the authors provide fit indices of the proposed model, namely, the structural equation model, and a summary of the hypotheses testing. As indicated in Table 5, fit indices provided satisfactory results because the model values were greater than the recommended value, proving the model to be acceptable. The relationship of each construct can be further analyzed and interpreted.

Fig. 3 demonstrates all of the significant relationships among all the constructs, including the coefficients of each relationship. In addition, the values of R2 provided shows how well the predicted constructs were explained by their antecedents.

For hypotheses testing, the results show that all of the proposed hypotheses are supported by the findings (as shown in Table 6). The details of each hypothesis are discussed in the next section.

6. Discussion

6.1. Summary of findings

The study found that perceived usefulness has a positive influence on intention to use (3 = .209, p < 0.001), which is consistent with the findings of Szajna (1996), Venkatesh and Davis (2000), Van Raaij and Schepers (2008), Lu et al. (2009), and Rouibah et al. (2011). It can therefore be interpreted that if users feel that using e-booking is useful they will then have an intention to use it. A positive relationship was also found between perceived ease of use and perceived usefulness ([beta] = .157, p < 0.05). The positive finding between those two is also consistent with previous findings of Hsu and Lu (2004), Calisir and Calisir (2004), Wu and Wang's (2005), Yi et al. (2006), and Lu et al. (2009). Therefore, if the users perceive that the e-booking platform is easy to use, they will also then find it to be useful. Consistent with previous findings from Szajna (1996), Jackson et al. (1997), Venkatesh and Davis (2000), Gefen (2003), and Liu et al. (2010) this study also confirms that perceived ease of use has a significant and positive impact on perceived intention to use ([beta] = .545, p < 0.001). The users' intention to use e-booking is also driven by the ease of use of the platform. If they feel that is it easy to use, they will have an intention to use it. What service providers of e-booking platforms can take from this study is the fact that the users' decision to use an e-booking platform is largely determined by how useful it seems and how easy it is to use. Therefore, service providers should focus on improving these two features and make sure that their platform is useful and easy to use.

The study also found that image has a positive impact on intention to use ([beta] = .177, p < 0.001), as confirmed by previous studies conducted by Lu et al. (2005), Yi et al. (2006), and Zhang et al. (2008). Subjective norm was also found to have a positive relationship with intention to use ([beta] = .121, p < 0.001). Furthermore, it is interesting to note that in this study social characteristics, image, and subjective norm yielded a positive result towards intention to use. It seems that Thai users perceive that using e-booking enhances their status, gives them more prestige, and establishes a higher profile among their friends and peers. Added to that, they will also choose to use e-booking, if they believe that people whose opinions they value are using it. Social status and caring about what other people think of you is not a surprising find, given that, according to Hofstede (2001), Thailand is a highly collectivist country. This means that relationships among people are paramount, which explains why social characteristics and the adoption of e-booking might be related.

A relationship between perceived value and intention to use was discovered in this research as perceived value had a significant and positive relationship on intention to use ([beta] = 0.263, p < 0.001). The findings are supported by previous studies by Byun (2007) and Teerling and Pieterson (2009). Obviously, intention to use e-booking is highly dependent on the level of perceived value by the customers. Service providers should emphasize and promote the value or benefits of their products and services, because it can have the effect of increasing the intention to use. Additionally, this research found that perceived value had a significant and positive influence on perceived ease of use (b = 0.592, p < 0.001) as supported by previous literature from Keeney (1999), Westberg and Caruso (2008), and Alsheikh and Bojei (2012). This suggests that when the customers have a higher perceived value of e-booking, they tend to find it easier to use electronic booking for buying air tickets or booking hotel rooms.

This research also found that a positive relationship existed between perceived value and perceived usefulness, as perceived value had a significant and positive impact on perceived usefulness ([beta] = 0.492, p < 0.001). There are several studies that support this finding, which include Lee and Jun (2007), Kim et al., (2007), Pihlstrom and Brush (2008) and Mudambi and Schuff (2010). Lastly, this research reveals that image had a significant and positive relationship on perceived value ([beta] = 0.241, p < 0.001). Prior research studies, based on a variety of contexts, support this relationship, namely, those by Milfelner et al. (2011), Ozturk and Qu (2008), and Ryu et al. (2008). Helping to support or create a positive image of electronic booking evidently results in a greater perceived value for the customers.

6.2. Academic implications

This study has academic as well as practical contributions. Firstly, the results of the study validate previous TAM findings that perceived usefulness and perceived ease of use as positively related to an intention to use technology. The findings on social norms (namely subjective norm and image) have yielded mixed results in previous studies. This study shows that social norms have a positive relationship with intention to use e-booking. This contradicts Schepers and Wetzels (2006) findings that a positive relationship between subjective norm and intention to use is more likely to be found in studies in Western societies, rather than non-Western societies. This study also found that perceived value has a positive relationship with intention to use. Although the use of the TAM has been undertaken in many previous studies, this study with its focus on Thai consumers, is one of the first to investigate the intention to use e-booking in the context of a developing country. Therefore, other developing countries looking to investigate e-booking usage can use this study as an example or as a baseline model.

6.3. Practical implications

As competition among online booking services becomes increasingly intense, this study offers several practical implications for managers. Online booking businesses need to focus on several factors in order to increase their perceived usefulness to customers. A company should highlight the perceived value of its services because it has the greatest direct influence on perceived usefulness. Secondly, creating the right image of the company and its services will lead to a greater degree of perceived value and perceived usefulness for customers. A company should invest more money in advertising and branding activities to support this positive image. Thirdly, this paper has shown that online booking service providers must consider the importance of perceived value, perceived usefulness, and especially perceived ease of use since it has the highest influence on intention to use for the users. Investment in a friendly user interface is expected to lead to a much greater intention among customers to use online booking services.

In addition, since the results of the study show that ease of use and usefulness are important determinants, e-booking service providers should make sure that the platform for e-booking should focus on ensuring that their customers have an easy to use interface that includes availability of different languages for those who do not read English. They should also emphasize the functions related to the ease of use of the platform, whether it is a desktop or a mobile version of the interface. Also, in terms of usefulness, e-booking service providers should provide on their platforms more information to customers that is related to travel issues, such as directions to destinations, car rental services, and suggested restaurants and tourist attractions. Currently, the Thai government is stepping up its efforts to create and promote the concept of e-tourism in Thailand to local as well as foreign tourists. The empirical evidence from this study can be used to verify the importance of e-booking and to support the government with its efforts in developing the e-tourism platform and infrastructure.

6.4. Limitations and extensions

This study does have some limitations and offers some suggestions of possible extensions that could be added in further studies. The first limitation is that the participants of this study were students, which means the sample is homogenous. Hence the results may not be applicable to other groups of e-booking consumers. The second limitation is that this is a cross-sectional study in which data were collected at one single point in time. A longitudinal study may yield different results as to why consumers use e-booking. Improving upon the limitations of this study and extending this research will add to the literature on e-booking. The first extension would be to identify more variables that affect customer's intention to use e-booking. Secondly, a larger sample size or a more diversified sample could lead to more conclusive results. Thirdly, a qualitative approach would add extra weight to this study, and the introduction of interviews with experts would provide for a more comprehensive framework and an in-depth understanding of the intention to use e-booking.

ARTICLE INFO

Article history:

Received 26 May 2014

Received in revised form

24 November 2014

Accepted 22 December 2014

Available online 14 February 2015

Appendix

Measurement scales:

Constructs    Items

Subjective    SN1: People who influence my behavior think
  Norm          that I should use E-booking.
              SN2: People who are important to me think
                that I should use E-booking.
              SN3: People whose opinions are valued to me
                would prefer that I should use E-booking.

Image         IM1: People who use E-booking have more
                prestige than those who do not.
              IM2: People who use E-booking have a high profile.
              IM3: Using E-booking is a status symbol.

Perceived     PV1: This E-booking is very good value for money.
  Value       PV2: Given its price, this E-booking is economical.
              PV3: This E-booking can be considered a
                favorable purchase.
              PV4: The price of this E-booking is acceptable
                with regard to its quality.
              PV5: The price of this E-booking corresponds
                to its value.

Perceived     PEOU1: My interaction with E-booking is
  Ease of       clear and understandable.
  Use         PEOU2: Interacting with E-booking does not
                require a lot of my mental effort.
              PEOU3: I find E-booking to be easy to use.
              PEOU4: I find it easy to get E-booking to do
                what I want it to do.

Perceived     PU1: Using E-booking improves my performance.
Usefulness    PU2: Using E-booking increases my productivity.
              PU3: Using E-booking enhances my effectiveness.
              PU4: I find E-booking to be useful.

Intention     ITU1: Assuming I had access to E-booking,
  to Use        I intend to use it.
              ITU2: Given that I had access to E-booking,
                I predict that I would use it.
              ITU3: I intend to use E-booking as often
                as needed.
              ITU4: I intend to continue using E-booking
                in the future.


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Veera Bhatiasevi (a), *, Chanin Yoopetch (b)

(a) Business Administration Division, Mahidol University International College (MUIC), Buddhamonthon, Salaya, Nakhon Pathom 73170, Thailand

(b) Tourism and Hospitality Management Division, Mahidol University International College (MUIC), Buddhamonthon, Salaya, Nakhon Pathom 73170, Thailand

* Corresponding author.

E-mail addresses: veera.bha@mahidol.ac.th (V. Bhatiasevi), chanin.yoo@ mahidol.ac.th (C. Yoopetch).

http://dx.doi.org/10.1016/j.jhtm.2014.12.004

Table 1
Countries and types of study participants covered in TAM research.

Variation in      Examples
TAM application

Country           Australia, Cambodia, Canada, China, Finland,
                  France, Hong Kong, Japan, Kuwait, Nigeria,
                  Singapore, Switzerland, Taiwan, Turkey, and
                  USA

Type of Study     Undergraduate and graduate students,
  Participants    knowledge workers, physicians, bank managers,
                  programmer analysts, IT vendors, specialists,
                  computer programmers, Internet users,
                  brokers, and sales assistants.

Source: Chuttur, 2009.

Table 2
Descriptive statistics of the respondents.

Respondent
characteristics                  Frequency   Percentage

Gender
  Male                                236        40.76
  Female                              343        59.24
Years in college
  First year                           11         1.90
  Second year                         241        41.62
  Third year                          219        37.82
  Fourth year                          80        13.82
  More than four years                 28         4.84
Division
  Business administration             424        73.23
  Fine and applied arts                 6         1.04
  Science                              11         1.90
  Social science                        9         1.55
  Tourism and hospitality             129        22.28
Monthly income (in Baht)
  Less than or 5,000                   95        16.41
  5,001-7,500                         115        19.86
  7,501 - 10,000                      136        23.49
  10,001-12,500                        92        15.89
  12,501-15,000                        48         8.29
  More than 15,000                     93        16.06
E-booking type
  Air ticket                          301        51.99
  Hotel room                          278        48.01

Table 3
Item loadings on related factors.

                 Factor                  Cronbach's
Factor   Item    loading   AVE    CR     alpha

SN       SN1     0.86      0.78   0.80   0.91
         SN2     0.92
         SN3     0.86
IM       IM1     0.71      0.63   0.68   0.83
         IM2     0.92
         IM3     0.75
PEOU     PEOU1   0.75      0.63   0.68   0.87
         PEOU2   0.72
         PEOU3   0.87
         PEOU4   0.82
ITU      IU1     0.85      0.68   0.72   0.89
         IU2     0.85
         IU3     0.75
         IU4     0.83
PV       PV1     0.83      0.68   0.72   0.91
         PV2     0.85
         PV3     0.85
         PV4     0.80
         PV5     0.77
PU       PU1      .800     0.66   0.70   0.88
         PU2     0.86
         PU3     0.85
         PU4     0.69

Notes: SN = Subjective Norm; IM = Image;
PEU = Perceived Ease of Use;
IU = Intention to Use; PV = Perceived Value;
PU = Perceived Usefulness.

Table 4
Correlation coefficient matrix and square root of AVEs.

         Number
         of
Factor   Items    SN     IM     PEOU   ITU    PV     PU

SN       3        0.88
IM       3        0.46   0.80
PEU      4        0.31   0.14   0.79
IU       4        0.36   0.19   0.76   0.82
PV       5        0.39   0.24   0.66   0.71   0.82
PU       4        0.43   0.38   0.54   0.63   0.68   0.81

Table 5
Fit indices of the proposed model.

                              Model   Recommended
Fit index                     value   value

Comparative Fit Index (CFI)   0.98    >0.90
Normed Fit Index (NFI)        0.97    >0.90
Non-Normed Fit Index (NNFI)   0.97    >0.90
Root Mean Square Error        0.06    <0.08
  of Approximation
  (RMSEA)
Adjusted goodness-of-fit      0.86    >0.80
  index (AGFI)

Table 6
Summary of hypotheses tests.

Hypothesis   Relationship            Support

H1           PV [left arrow] PEOU    Yes
H2           PEOU [left arrow] ITU   Yes
H3           PV [left arrow] ITU     Yes
H4           PU [left arrow] ITU     Yes
H5           IM [left arrow] PV      Yes
H6           PEOU [left arrow] PU    Yes
H7           PV [left arrow] PU      Yes
H8           SN [left arrow] PU      Yes
H9           IM [left arrow] PU      Yes
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Author:Bhatiasevi, Veera; Yoopetch, Chanin
Publication:Journal of Hospitality and Tourism Management
Article Type:Report
Geographic Code:9THAI
Date:Jun 1, 2015
Words:10665
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