The Influence of Website Quality on Online Purchase Intentions on Agoda.Com with E-Trust as a Mediator

In e-commerce market, there is no physical interaction between buyers, sellers, and payments. The confidence to buy online e-trust can raise or lower the perceived risk and security issues, so e-trust is crucial for the success of e-commerce companies, such as Agoda.com. The sorting of online businesses is vital to avoid losses when doing the online business transaction, such as by looking at the quality of the website and the company's ability to provide e-trust. The methods used in this research were quantitative and causal. The research sample was collected using non-probability sampling method which was purposive sampling by taking 200 respondents. Data analysis techniques used SEM (Structural Equation Modeling).The conclusion shows the existence of a significant influence on the website's quality towards e-trust, and e-trust on the online purchase intentions. Moreover, there is an insignificant impact on the quality of the site towards online purchase intentions.


INTRODUCTION
The development of the Internet and World Wide Web today has increased very rapidly, especially for electronic transactions (Salo & Karjaluoto, 2007). There is no doubt of e-commerce market share experiencing rapid growth in Indonesia. With the number of Internet users reached 88,1 million, soar 16,2 million from 71,9 million, or in other words, has a penetration of 34,9%. From these data, it can be said that the number of Internet users in Indonesia is around 30% of the total Indonesia population, which turns the e-commerce market into a gold mine that is very tempting for people who can see the potential in the future (Mitra, 2015).
E-commerce has a positive impact on the tourism industry. Web technology in this sector is expanding the scope of transactions online travelers (Dedeke, 2016). Tourism and hospitality industry currently requires a competitive advantage to face the competition; one way to develop a competitive advantage is the use of information technology (Law et al., 2009). In hospitality services, the Internet has become an essential part of the hotel operations and also become one of market research and surveys, the website can identify the strengths and weaknesses of an organization (Herrero et al., 2015). Research on information and design website is needed in the tourism industry, and its influence on purchase intention (Dedeke, 2016). Website Quality is the overall excellence or effectiveness of a website in conveying messages intended for audiences and viewers (Wang et al., 2015). Website quality is a web conformance with the expectations of stakeholders (Canziani & Welsh, 2016). Website design is a critical determinant in achieving the quality of services offered to consumers (Hasanov & Khalid, 2015). In this research, website quality uses three sub-variables, which are functional, usability, and security and privacy (Wang et al., 2015;Ali, 2016).
Website quality has an important role in developing purchase intention. An excellent website quality would increase customers purchase intention (Ali, 2016). Online purchase intentions is the willingness and desire of customers to participate in online deals, including the process of evaluating the website quality and products information (Wang et al., 2015). Online purchase intention is the desire of consumers to buy a product or service within a specific site (Ha et al., 2014). Purchase intention in online hotel booking is the desire of consumers to book rooms through a website (Lien et al., 2015). It is important for hoteliers to determine the factors that influence purchase intention at this stage of the prepurchase (Lien et al., 2015). The level of purchases will increase if positive purchase intention is more powerful than the weak intention (Shaouf et al., 2016). Based on the results of a survey conducted by Nielsen Global Survey of e-commerce, it is found that travel services are the most widely planned by consumers to purchase online. About half of Indonesian consumers, which is 55%, plans to buy airline tickets online, while 46% of them plans to book hotel and travel agencies (Lubis, 2014). Chou et al. (2015) stated that a good website did not guarantee an increase in e-trust. In the online travel industry, Indonesia is estimated to become the largest market for hotels and flights in Southeast Asia by 2015. Nevertheless, there are several challenges that must be addressed by the government and other interested parties, such as aspects of logistics and connectivity, the complexity of payment, market readiness, fraud and cyber security (Setiawan, 2016). Internet users continue to increase, but the majority of them do not conduct transactions via online. They are reluctant to provide information for online payments because they do not trust e-commerce (Kim et al., 2011). Distrust is a problem that must be solved by e-commerce companies regarding infrastructure and payment system. E-commerce companies must be able to convince their prospective customers to shop online, especially for young people as the target market, who are generally very aware of the technological development. If an e-commerce company can provide a sense of comfort in shopping online and provide a payment system that can be used by many people, it can be expected that more people in Indonesia would not hesitate to shop, either using the credit card or debit card (Wang et al., 2015). Nilashi et al. (2016) stated that the attributes of a quality website could affect consumers' trust to an agent. Purchase intention is influenced by consumers trust and perspectives towards the usefulness of website. In contrast, research conducted by Lien et al. (2015) showed that the impact of trust on the purchase intention was not significant.
Trust is central to human behavior, which is called a truism. In addition, this realization runs deep in the human psyche (Sharma, 2013). Trust is a recommendation tool that can assist consumers in making better decisions (Nilashi et al., 2016). Thus, building trust is a very crucial key in e-commerce (Yousafzai et al., 2003). The main feature of the relationship between buyer and seller is trust (Lien et al., 2015). E-trust is a multi-dimensional construction with two interrelated components, beliefs (perceptions of competence, benevolence, and integrity of the vendor), and intentions to believe (a willingness to rely on the vendor) (Othman et al., 2013). In addition ,the most important trust in a relationship is a trust relationship between human beings and machines or online systems (Salo & Karjaluoto, 2007). The components of trust are confidence as well as expectations and willingness to accept the risk (Chek & Ho, 2016). Trust is a very important in an online environment, particularly in the payment and privacy (Salo & Karjaluoto, 2007). This research uses threedimensional of trust, namely integrity, benevolence, and abilities (Wang et al., 2015;Chek & Ho, 2016).
The Internet allows potential guests to gather information about the hotel facilities. Moreover, the guests can compare hotel rooms without having to contact the hotel or travel agents, and they can also prepare itineraries (Runfola et al., 2013). Agoda.com is one of e-commerce companies that are engaged in hotel services. Agoda.com serves a variety of information about hotels needed by tourists in a persuasive and attractive manner. According to Alexa. com (2015), Agoda.com is ranked 578 in the most visited websites in the world. The high percentage of visitors Agoda.com in Indonesia can be proof that Agoda.com is considered trusted by Internet users in Indonesia as their travel agent, even though Agoda. com is not a local company. E-trust that is needed in making purchases on Agoda.com is quite huge because Agoda.com only accepts payment by credit card, Paypal, and American Express. Additionally, Agoda. com also has branch offices in Indonesia. In online transactions, there is no physical interaction between buyers, sellers, and payments. Unobservant buyers could have suffered from loss, for example, swindled by the seller. This can happen to all Internet users anytime and anywhere. Therefore, the confidence to proceed an online purchasing (e-trust) can raise or lower the perceived risk and security issues, which makes e-trust crucial for the success of e-commerce companies. Therefore, sorting online businesses is required to avoid losses when conducting online business transactions. One way to sort companies is to see the quality of the website and the company's ability to give confidence for customers (e-trust) because the quality of the website and e-trust may affect the purchase intentions. The intention of behaving is the very first thing a person indicated before deciding to behave. The key to success in e-business is trust and security when making transactions (Srinivasan, 2004). Trust and purchase intentions have a direct relationship which is assumed to be positive (Ha et al., 2014). Trust is a factor that affects the purchase intention for e-commerce and the tourism industry. This means that the greater the confidence, the greater their intention to use them (Ponte, Carvajal-Trujillo, & Escobar-Rodríguez, 2015).
This research is expected to provide benefits for (1) the provider of an online travel agent, which is to provide information on how to manage the website and boost the confidence of consumers when transacting, and (2) Internet users, which is to provide information in online transactions.
Based on the descriptions that have been stated above, this research has several questions, which are: (1) does website quality influence e-trust on agoda. com? (2) does e-trust influence online purchase intentions on agoda.com? (3) does website quality influence online purchase intentions on agoda.com?
The aim of the research is as follows: (1

METHODS
The methods used in this research are quantitative and causal. The population in this research is internet users who have reserved a hotel room through Agoda.com. The number of samples in this research refers to Tebachinick and Fidell (Latan, 2012) that recommended the number of samples had to meet for the estimation of Structural Equation Modelling (SEM) around 10 times the parameters to be estimated. Moreover, the research sample is conducted with non-probability sampling method which is purposive sampling by taking 200 respondents. Data analysis techniques used is SEM.
In general, two types of SEM are already widely known that covariance-based structural equation modelling (CB-SEM) and partial least squares path modelling (PLS-SEM) or often called as the variance or component-based structural modelling.
PLS is a structural equation analysis based variants that can simultaneously perform testing at the same measurement model testing structural models. The measurement model is used to test the validity and reliability, while the structural models are used to test causality (hypothesis testing predictive models). However, in its development, there are three types of SEM by adding generalized and structured component analysis (GSCA) (Latan, 2012).

RESULTS AND DISCUSSIONS
Respondents' characteristics are required to determine the background of the respondents. Those characteristics can also be used as input for an explanation of the results. They can be seen in Table 1.  Table 1 shows that the majority of the respondents of the research is younger than 25 years old (53%), females, SMA/SMK graduates, and students. Moreover, the outer model is to assess the validity and reliability of the model. The testing itself is conducted by using the Smart PLS 2.0 Software. The model for the Outer Model test is presented in Figure 2. Figure 2 shows that all indicators in this research have a factor loading value > 0,5. In the early stages of research, the development of value measurement scale of factor loading is 0,5 to 0,6 considered as sufficient (Ghozali, 2011). It shows that all the indicators in this research meet the test of convergent validity. In addition to convergent validity test, all indicators have a higher factor loading value toward the construct than factor loading value to another construct. Therefore, it can be said that all indicators have met the test of discriminant validity.
Moreover, a test is performed to determine the reliability of each construct. It is conducted by looking at the value of composite reliability of each construct. In addition to that, to meet a good reliability value, it is suggested that the composite reliability value is > 0,7. Table 2 will show the values of composite reliability and Cronbach's alpha in this research.
According to Table 2, the whole construct in the research has composite reliability value above 0,7. It means that all of the constructs are reliable. Next, the structural model (inner model) testing is also done by using the R-square value of the endogenous latent constructs and t-count on each exogenous latent variable towards endogenous latent constructs.    The path coefficient value or inner model describes the level of significance in hypothesis testing. The coefficient or inner models scores indicated by the value of the T-statistic should be above 1,64 for the one-tailed hypothesis. Table 3 will show more details about the supported hypothesis. Based on the result of tcount in Table 3, it is revealed that both relationships between website quality towards e-trust and e-trust towards online purchase intentions have t-count value < 1,6. It means there is a significant influence resulted in H1 and H2 being rejected. Meanwhile, the relation between website qualities towards online purchase intentions has tcount < 1,64. It implies that the relationship is insignificant. As a result, H3 is accepted. Moreover, the researchers also conduct the calculations by using R-square value to determine how much the endogenous latent variable is affected by the exogenous latent variables. The calculation results listed in Table 4.
In Table 4, it can be seen that R-square value for the endogenous latent variables of e-trust in the structural model has a value of 0,741. It means that the exogenous variables website quality affect the e-trust by 74,1. Meanwhile, 25,9% of them are influenced by external factors other than those variables. The endogenous latent variables of online purchase intention in this structural model have a value of 0,501. It can be inferred that the exogenous latent variable website quality and e-trust affect the endogenous latent variable online purchase intentions by 50,1%. The rest 49,9% is influenced by other variables.

CONCLUSIONS
Based on the findings of the research, several points can be concluded. First, website quality influences 18,276 or 74,1% towards e-trust. The results indicate that there is a positive and significant influence of website quality towards e-trust on Agoda. com. This means that the higher the quality of the website is, the higher the user's trust will be. Moreover, the perceived risk in e-commerce is higher, so trust is necessary for retailers online than offline retailers (Pappas, 2016;Chek & Ho, 2016). Similarly, e-trust affects 3,306 or 46,1% towards the online purchase intentions. It shows there is a positive and significant influence of e-trust towards online purchase intentions on Agoda.com website. Meanwhile, website quality only influences 0,157 or 0,1% of online purchase intentions. It shows that website quality does not give any significant influence on online purchase intentions on Agoda.com website.
Second, since the quality of Agoda.com website significantly affects the e-trust of the Agoda.com consumer, Agoda.com should maintain and improve its website quality to improve the e-trust as well as the online purchase intentions of its visitor. In the website variable quality, the indicator F1 has received the lowest result among the other items. Therefore, Agoda.com is expected to add more information on hotel reservation. For example, information can be how to book a hotel room from Agoda.com website.
For the research regarding this topic, it is suggested to employ Covariance Based SEM (CB-SEM) in analyzing the data supported by Lisrel or Amos as the statistic software used to calculate the data. The use of CB-SEM is necessary because the standardization in CB-SEM is higher compared to PLS. Next, the other suggestion is to make a comparison on website quality, e-trust, and online purchase intentions on several websites such as Traveloka, Tiket.com, Pegipegi, Misteraladin, Trivago, Booking. com, and others. By doing a comparison research, it may strengthen the website quality on e-trust and online purchase intentions, and e-trust towards online purchase intentions in the process.