Using an Online Travel Agency When Booking A Hotel in China: The Impact of Trust, Perceived Risk and Perceived Benefit on Purchase Intention Abstract With the rapid development of China's network science and technology, Chinese e- commerce is also becoming increasingly more developed. More people can easily buy and book tourist products through the electronic B2C platform, including hotel reservations, purchasing tickets, and other travel-related items. When an online travel agency website is generated, integrated information of many hotels can be accessed to help customers find the hotels they need faster and more conveniently. Although this brings benefits to users, it also includes some risk. This paper intends to show that perceived risk has a significant negative impact on purchase intention, including financial risk, product/service risk, time risk and information risk. Perceived benefits such as price benefit, convenience benefit and selection benefit, have a significant positive effect on purchase intention. However, there is no significant effect between trust and purchase
Transcript
Using an Online Travel Agency When Booking A Hotel in China: The Impact of Trust, Perceived Risk and
Perceived Benefit on Purchase Intention
AbstractWith the rapid development of China's network
science and technology, Chinese e-commerce is also becoming increasingly more developed. More people can easily buy and book tourist products through the electronic B2C platform, including hotel reservations, purchasing tickets, and other travel-related items. When an online travel agency website is generated, integrated information of many hotels can be accessed to help customers find the hotels they need faster and more conveniently. Although this brings benefits to users, it also includes some risk. This paper intends to show that perceived risk has a significant negative impact on purchase intention, including financial risk, product/service risk, time risk and information risk. Perceived benefits such as price benefit, convenience benefit and selection benefit, have a significant positive effect on purchase intention. However, there is no significant effect between trust and purchase intention. In addition, perceived risk and perceived benefit have a significant negative and positive impact on trust, respectively. These research results can help hotel businesses and online travel agencies better understand customer needs, in order to provide better products and services.Keywords: Purchase intention, trust, perceived risk and perceived benefit.
1.IntroductionIn recent years the living standard of the
Chinese people has shown constant improvement. China's tourism economy has achieved rapid growth. At the same time, the rapid development of China's network science, technology, and e-commerce has also become increasingly developed. More and more people can easily access and book tourist products through the electronic B2C platform, including hotel reservations, ticket purchases and other travel-related needs.
Figure 1: MAU in the first quarter of 2018
The above figure shows that the market for online accommodations in China is still very large, but the online cost is increasing. According to the latest data released by Trustdata, more than 75 million users per month had booked a hotel online by the first quarter of 2018, and an increasing number of people chose to subscribe through mobile terminals.The convenience of travel
arrangements has been greatly improved, but it has also brought with it perceived risks. Based on past literature models, the authors discussed the impact of perceived benefits, trust, and perceived risk on customers’ purchase intentions under the circumstances of booking hotels through online travel agencies. These research results can help hotel businesses and online travel agencies better understand customer needs in order to provide better products and services
Based on this context, the purpose of this study is to understand the impact of trust, perceived benefit and perceived risk on purchase intention. And the researcher will also study the impact of perceived risk and perceived benefit on trust. These research results can help hotel businesses and online travel agencies better understand customer needs in order to provide better products and services. For consumers, the results can help hotels hotel and online travel agency better improve their products and services, and customers will benefit eventually.
2.Literature Review2.1 Purchase Intention
Intention is the subjective probability of a person to engage in a particular action. The consumer's behavior intention is the decision before the result of the behavior, and it is the explanation of the behavior process. According to the research and summary of Darley et al. (2010), the authors found five stages in the process of customer purchase. Dewey (1910) first proposed the five buying stages in 1910: problem/need recognition, information search, evaluation of
alternatives, purchase decision and post-purchase behavior.
The purchase intention would be in the stage of the purchase decision. Studies by Schiffman and Kanuk (2005) show that the higher the purchase intention, the higher the likelihood of the consumer to buy products. The willingness to buy is an important factor in predicting the actual purchase behavior; this has also been verified in hotels and tourism (Bai, et al. 2008; Park & Brown, 2011). From this, the researcher finds that understanding factors influencing hotel reservation intention plays a vital role in hotel management. In this study, the researcher will define purchase intention as follows: When booking hotels online, users tend to purchase the hotel room through the online travel agency.
2.2 TrustTrust is one of the core characteristics of the
relationship between buyers and sellers. Trust has always been the subject of studies by researchers in the area of social exchange relations (Wu et al. 2010). Kim et al. (2008) advanced the concept that due to the inherent characteristics of internet shopping, consumers always have some risks. They are eager to speculate about future uncertainty and others' behavior.
Moorman, et al. (1993) use "a willingness to rely on an exchange partner in whom one has confidence" to define trust. Using the combination of the above two definitions, the author comes to this conclusion: The combination of the above two definitions (Morgan and Hunt 1994) leads to a conclusion that trust exists when one party has confidence in an exchange partner’s reliability and
integrity. This definition of trust has also become the most widely used and most recognized definition by scholars. All of them emphasize the importance of confidence. Thus, trust in this study means a willingness to rely on an online travel agency when customers have confidence in that agency’s reliability and integrity.
2.2.1 Trust & Purchase IntentionSichtmann (2007) and Comegys et al. (2009)
found that trust for the company has a positive impact on the willingness to purchase.Lewis et al (1998) demonstrated that trust is the main concern for many consumers. For those who plan to travel, trust in an online website leads to a higher likelihood that they will purchase from the website. Previous studies related to online purchase have argued that trust in the online store positively influences the consumer’s intention to purchase from the online store. While consumers need to rely on the information provided by the hotel purchasing website, they also need to trust the website itself.
Study of Mansour et al. (2014) has shown that the more customers trust websites and the lower the perceived risk of online trading, the greater the customer's willingness to buy on the site. So the researcher put forward the hypothesis:
Hypothesis 2. Trust has a positive impact on online hotel purchasing intention.
may be regarded as invisible products, because consumers are not directly linked to the goods they are purchasing. (Peterson et.al 1997) Particularly in
the category of experiential products like hotels, people are even more susceptible to perceived risk. Perceived risk plays an important role when buying online (Bhatnagar and Ghose 2004; Jiuan Tan 1999), because in this setting consumers will feel insecure about their purchase decisions.
In the context of online shopping, Forsythe et al. (2006) studied the factors that measure perceived benefits and perceived risks. They define perceived risk in online shopping as a subjective understanding of the consumer’s potential loss in online shopping. In this study, the researcher will define perceived risk as follows: Under the circumstances of booking a hotel through an online travel agency, the consumer's subjective perception of potential loss from purchasing online.
2.3.1 Perceived Risk & Purchase IntentionPerceived risk theory has been used to explain
consumer behavior in decision-making since the 1960s. Mitchell (1999) argues that perceived risk is powerful in explaining consumer behavior because consumers are more likely to avoid mistakes rather than maximize purchasing utility. Previous studies have shown that there is a relationship between the risk perception of new shopping channels and the choice of the channel (Bhatnagar et al. 2000). Although consumers feel the risk in most purchase decisions, non-store purchase decisions tend to have higher levels of perceived risk.
Under the environment of the social network Facebook, Leeraphong and Mardjo (2013) studied the impact on purchase intention between social trust and risk and proved a significant impact of perceived risk and trust on purchase intention. Kim et al. (2008) developed a theoretical framework
describing the trust-based decision-making process a consumer uses when making a purchase from a given site. The article confirms that perceived risk and trust have a significant effect on purchase intention in an e-commerce environment. Chang and Wu (2012) attempt to elaborate the consequences of perceived risk by taking the moderating effects of decision-making style (i.e. involvement vs. heuristics) into account in the context of online shopping. Their findings indicate that perceived risk toward the website/product influences purchasing intention through cognition and affect-based attitudes. At the same time, perceived risk toward the website/product also influences purchasing intention directly.
Based on the above literature review, we can consider that perceived risk has a negative impact on the purchase intention. Hence, the following hypothesis is developed.
Hypothesis 1. Perceived risk has a negative impact on purchase intention.
Hypothesis 1a. Financial risk has a negative impact on online hotel booking intention.
Hypothesis 1b. Product/Service risk has a negative impact on purchase intention.
Hypothesis 1c. Time risk has a negative impact on purchase intention.
Hypothesis 1d. Information risk has a negative impact on purchase intention.
2.3.2 Perceived Risk & TrustScholars have provided different views
regarding the relationship between risk and trust. Researchers identified four types of relationships (Gefen 2000; Lim 2003). In the first type, perceived risk regulates the relationship between consumer
trust and purchase intention In the second relationship, the perceived risk is preceded by the consumer's trust. In the third relation, trust precedes perceived risk. The fourth relationships between the two factors are not recursion.
The most of studies in the e-commerce situation support second relationships, for example: Corbitt et al. (2003) studied the impact of organizational reputation, relative advantage, and perceived risk on perceived service quality, trust and behavioral intentions of customers toward adopting e-services. They created an online B2C (business to consumer) perception trust model and believe that perceived risk has a negative impact on perceived trust. Similarly, Corritore et al. (2003) identifies a number of key factors related to trust in the B2C context and demonstrates that risk perception affects the consumer’s trust in online shopping. Lien et al. (2015) evaluates and validates the impacts of perceived technology and perceived risk on online trust and how online trust is related to online purchase intention. The findings reveal that perceived technology and perceived risk are positively related to online trust; online trust is positively related to online purchase intention. Therefore，the research hypothesis is as follows:
Hypothesis 3. Perceived risk has a negative impact on trust.
2.4 Perceived BenefitMany scholars have proven that the perceived
benefits of the purchase are one of the most important factors that affect the customer's purchase intention. The perceived benefit-of-
buying construct is often applied to normal shopping behaviors.
When Chandon et al. (2000) studied a benefit congruency framework of sales promotion effectiveness, they defined perceived benefit as beliefs about the positive outcomes associated with a behavior in response to a real or perceived threat. And Tingchi Liu et al. (2013) also use this definition of perceived benefit to study consumer group buying behavior in the online purchase scenario.
Forsythe et al. (2006) studied the development of scales to measure the perceived benefits and risks associated with online shopping. They defined the perceived benefit of shopping online as the consumer’s subjective perception of gain from shopping online.
In this study, perceived benefit will be defined as follows: Under the circumstances of booking a hotel through an online travel agency--the consumer's subjective perception of potential gain from purchasing online.
2.4.1 Perceived Benefit & Purchase IntentionIn the online environment, there are not many
articles to study perceived benefit. The author will collate the literature of perceived benefit, and explore the relationship between perceived benefit and online purchase intention.
In an early stage, Kim (2008) studied the relationship between perceived benefit and purchase intention in the business-to-customer (B2C) internet commerce environment. In the context of the B2C economy, they established the trust-based customer decision-making model and
confirmed that perceived benefit had a significant impact on purchase intention.
Tingchi Liu et al. (2013) compared the differences between consumers' group buying behaviors. They studied the effect of three types of perceived benefit—price, convenience, and recreational--on consumers' group buying behavior, and ultimately demonstrated that every item of perceived benefit has a significant positive impact on consumers' group buying behavior.
When Du (2009) studied the relationship between perceived risk, perceived benefits, perceived value, and purchase intention, he created a perceived value based online customer's purchase intention model and found that perceived benefit has a positive effect on both perceived value and purchase intention.
Thus, the researcher proposes that:Hypothesis 4. Perceived benefit has a
positive impact on purchase intention.Hypothesis 4a. Price benefit has a positive
impact on purchase intention.Hypothesis 4b. Convenience benefit has a
positive impact on purchase intention. Hypothesis 4c. Selection benefit has a
positive impact on purchase intention
2.4.2 Perceived Benefit & Trust There are few articles to discuss the
relationship between perceived benefit and trust. Some scholars do not discuss the relationship between them even if they study the two variables at the same time. For example, Kim (2008) only focused on the relationship between perceived benefit and purchase intention and the relationship between trust and purchase intention when
studying consumer decision-making in the online B2C market, but that study did not discuss the relationship between perceived benefit and trust. In addition, Tingchi Liu et al. (2013) also studied the relationship between perceived benefit and customer attitude as well as the relationship between trust and customer attitude when studying consumers' group buying behavior. The relationship between trust and perceived benefit was not discussed.
The researcher found few articles which discuss the problem. Siegrist (2000) studied a causal model, explaining the acceptance of gene technology, and finally demonstrated that perceived benefit has a significant positive impact on trust. Loureiro (2013) research examines the interrelationships of trust, brand awareness/associations, perceived quality and brand loyalty in building internet banking brand equity. Scholars have used perceived risk and perceived benefit as the important indicators for testing and measuring trust. In this study, scholars have confirmed that perceived benefit has a significant positive impact on trust.
The researcher proposes the following hypotheses:
Hypothesis 5. Perceived benefit has a positive impact on trust.
2.5 Conceptual FrameworkAccording to the literature, the relationship
between the variables was understood and the decision ultimately made to use the following model for research and learning. The model consists of variables: they are perceived risk, perceived benefit, trust, and purchase intention,
with purchase intention as a dependent variable influenced by the other three factors and the relationship between perceived risk and perceived benefit as an independent variable. In addition, perceived benefit effects trust. The researcher will also test the relationship between perceived risk and trust. All these three independent variables affect dependent variable purchase intention.
Figure 2: Various structure
3.MethodologyThe objective of this research is to study the
impact of perceived risk, perceived benefit and trust on customers’ online purchasing hotel intentions. A quantitative method was chosen in this study. A questionnaire was used to collect primary data from a sample of customers who are using or used to use the online travel agency to book a hotel. This paper forms the questionnaire on the basis of combing the theories of predecessors and combining the research models of many scholars.
The questionnaire has 5 sections. Section 1 is demographic, asking the personal background of our target group. Section 2-5 is based on the variables of this study. It consists of perceived risk, trust, perceived benefit and online purchasing hotel intentions.
3.1 Population & SampleBased on the latest data from Trustdata, CNNIC
and China Commercial Industry Research Institute, the scholar calculated that the number of users using online booking tourism products was 397.72 million.
Figure 3: Users Age Analysis
According to the Trustdata 2018 research report above, the figure shows that the age of online users booking travel related products is between 21 and 50 years of age. Therefore the age of the target user in this article is between 21 and 50 years.
According to the above data, the researcher calculates the population of this article as 338,962,560.
The sample size calculated by way of the population is 338,962,560; the determined
standardized score is 95%; and the level of acceptable error is 5%. Final sampling size should be 400 persons, which means that 400 valuable questionnaires will be collected.
3.2 Data CollectionConsidering the factors such as time and labor
cost, the data collected in this paper is primarily based on network questionnaire distribution and recovery using the Chinese survey website www.wjx.cn. The questionnaire adopts the method of the nearest sample survey--first friends--and then adopts the method of snowball sampling to spread the questionnaire throughout the popular Chinese social network platform, thereby ensuring the wide scope of the survey. WeChat, QQ, Microblog, Online Community, and Web are the main channels for the dissemination of online questionnaires.
4.Data Analysis4.1 Reliability Statistics
At the beginning 61 questionnaires were collected for reliability analysis. The results of Cornbach’s alpha were as follows: The author got a high Cornbach’s Alp. The reliability of the questionnaire was very good, so the collection process was begun. The result of the reliability analysis of the valid 465 sample questionnaires is shown in Table 4.1. As the alpha value of all variables is greater than 0.9 the results are very good, indicating that the reliability of this questionnaire is very high. Therefore, its structure is reasonable.
4.2. Demographic CharacteristicT According to the analysis and research of the
third chapter, the researcher selected users aged 21 to 50 years old as the research objects. The researcher set the following two screening questions to ensure that interviewees are the research objectives of this paper.
A total of 510 questionnaires were collected, and only 465 valid questionnaires were left after screening.
4.3 The Level of Agreement AnalysisTable 4: Analysis of the agreement level
VARIABLE
NO QUESTION Me
an SD
PR
Financial Risk
1 I don't worry about waste of money when I purchase the hotel room(s) on this site
3.79 .838
2 I think my credit card information is safe when I purchase the hotel room(s) on this site
3.94 .935
3 I believe I might not get overcharged if I purchase the hotel room(s) on this site
3.71
1.009
4 It's not going to happen to me that I can't stay in the hotel I have already booked
3.61 .954
Total3.76
.804
Product/ Service
Risk
5 It's not going to happen to me that I cannot get the right hotel room
3.97 .873
6 It's not going to happen to me that I cannot get the room as good as expected
3.68
1.155
7 It is not hard to judge the quality of hotel over the Internet
3.80
1.293
Total 3.82
1.006
Time
Risk
8 It is not difficult to find a right hotel through this site 4.03
1.054
9 It may not require a lot of time to communicate with the hotel receptionist
3.94
1.011
10
The operation process of this site will not take too much time
3.82
1.035
Total3.93
0.942
Information
Risk
11
The personal information that I provide on this site is secure
3.60
1.064
12
The monetary information that I provide on this site is well protected
3.80 .905
13
This site will not use unsuitable methods to collect my personal data
3.62
1.106
Total3.67
0.906
Total3.79
.850
Trust
14 I believe in the information that this site provides. 3
.921
.00015
This site is genuinely concerned about its customers.
3.70
1.042
16 This site gives me the impression that it is reliable 3
.611
.247
Total3.74
.983
PB
Price Benefit
17 I often get the discount price of the hotel on this site 3
.941
.19518 The price listed on this site is inexpensive 3
.571
.24419 I can get vouchers from this site 3
.83 .891
Total3.787
.980
Convenience Ben
20 Use this site can save time for comparing hotels 3
.801
.14121
I can purchase the hotel room(s) wherever I want 3.92
1.315
efit
22
It’s convenient to purchase room through all kinds of online payment channels
3.81 .996
Total 3.84
1.067
Selection
Benefit
23 I can get hotel information online easily 3
.991
.00324 This site offers me a wide array of hotel options 3
.891
.325
25
The feedback mechanism of the website (such as user reviews) can help me understand the real situation of the hotel better
3.96
1.283
Total3.95
1.141
Total3.86
.850
Purchase Intention
26
I am willing to purchase the hotel room(s) on this site.
3.63
1.058
27 I am willing to recommend this site to my friends. 3
.601
.12728 I am willing to make another purchase from this site 4
.111
.335
Total3.78
1.095
In order to facilitate participants’ choice of answers, the author adds negative words to all the original questions regarding perceived risk. In order to verify the hypothesis proposed in Chapter 2, the author will revise the value of the title "perceived risk". As the author explains in Chapter 3, the researcher will adjust the results in the SPSS software by "transform". Click on the "Record into same variables" option under "Transform". Add all the items about perceived risk to "variables". After clicking the "Old and New Values" option, there will be a setup interface to replace the old value with the new value. The old value "1" is changed to the
new value "5"; the old value "2" changes to the new value "4"; the old value "4" changes to the new value "2"; and the old value "5” changes to the new value “1”. The value of "3" is the same. After setting up, all the values of items of perceived risk will be exactly the opposite. The table below shows the adjusted agreement level of perceived risk.
Table 4.12: Analysis of the agreement level of perceived risk
VARIABLE NO. QUESTION Mea
n SD
Financial Risk
1 I don't worry about waste of money when I purchase the hotel room(s) on this site
2.21 .838
2I think my credit card information is safe when I purchase the hotel room(s) on this site
2.06 .935
3 I believe I might not get overcharged if I purchase the hotel room(s) on this site
2.29 1.009
4 It's not going to happen to me that I can't stay in the hotel I have already booked
2.39 .954
Total 2.24 .804
Product/ Service
Risk
5 It's not going to happen to me that I cannot get the right hotel room
2.03 .873
6It's not going to happen to me that I cannot get the room as good as expected
2.32 1.155
7 It is not hard to judge the quality of hotel over the Internet
2.20 1.293
Total 2.18
1.006
Time Risk
8 It is not difficult to find a right hotel through this site
1.97 1.054
9 It may not require a lot of time to communicate with the hotel receptionist
2.06 1.011
10 The operation process of this site will not take too much time
2.18 1.035
Total 2.07
0.942
Information Risk
11 The personal information that I provide on this site is secure
2.40 1.064
12 The monetary information that I provide on this site is well protected
2.20 .905
13 This site will not use unsuitable methods to collect my personal data
The above data table shows the coefficient of this regression model, in which Standardized Coefficients is the path coefficient. The Standardized Coefficients of financial risk, product/service risk, time risk, and information risk
are -0.221, -0.043, -0.067 and -0.595. The Sig. of FR and IS were 0.000 and 0.000 respectively, which shows that the influence of FR and IS variables on purchase intention is significant. And the VIF values of FR and IS are 5.240 and 7.858 respectively--all below 10-- which basically shows that there is no Collinearity between independent variables.
This result confirms the following two hypotheses of the researcher:
Hypothesis 1a. Financial risk has a negative impact on purchase intention.
Hypothesis 1d. Information risk has a negative impact on purchase intention.
However, Sig. of product/service risk and time risk were 0.528 and 0.243 respectively, both of which were greater than 0.05, indicating that PI of these two variables had no significant effect. So the following two hypotheses of the researcher were rejected:
Hypothesis 1b. Product/Service risk has a negative impact on purchase intention.
Hypothesis 1c. Time risk has a negative impact on purchase intention.
4.4.2 Second complex regression model: The impact of price benefit, convenience benefit and selection benefit on purchase intention
Table 7: Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t Sig.
Collinearity Statistics
BStd. Error Beta
Tolerance VIF
1 (Consta
nt)
-.181 .071 -2
.553
.011
PB .408 .032 .366 12.89
4
.000 .313 3.196
CB .322 .046 .314 7.059
.000 .127 7.866
SB .299 .044 .312 6.747
.000 .118 8.493
a. Dependent Variable: Purchase Intention
The above data table shows the coefficient of this regression model, in which Standardized Coefficients is the path coefficient. The Standardized Coefficients of price benefit, convenience benefit, and selection benefit are 0.366, 0.314 and 0.312 respectively. The Sig. of price benefit, convenience benefit and selection benefit were 0.000, 0.000 and 0.000 respectively, which shows that the influence of price benefit, convenience benefit, and selection benefit variables on purchase intention was significant. The VIF values of price benefit, convenience benefit, and selection benefit are 3.196, 7.866 and 8.493 respectively--all below 10--which basically shows that there is no Collinearity between independent variables.
This result confirms the following three hypotheses of the researcher:
Hypothesis 4a. Price benefit has a positive impact on purchase intention.
Hypothesis 4b. Convenience benefit has a positive impact on purchase intention.
Hypothesis 4c. Selection benefit has a positive impact on purchase intention
4.4.3 Third complex regression model: The impact of perceived risk and perceived benefit on purchase intention
The above data table shows the coefficient of this regression model, in which Standardized Coefficients is the path coefficient. The Standardized Coefficients of perceived risk and perceived benefit are -0.605 and -0.356 respectively. The Sig. of perceived risk and perceived benefit were 0.000 and 0.000 respectively, which showed that the influence of perceived risk and perceived benefit on purchase intention was significant. The VIF values of perceived risk and perceived benefit are 3.403, and 3.403 respectively--all below 10--which basically shows that there is no Collinearity between independent variables.
This result confirms the following two hypotheses of the researcher:
Hypothesis 3. Perceived risk has negative impact on trust.
Hypothesis 5. Perceived benefit has positive impact on trust.
4.4.4 Forth complex regression model：The impact of perceived risk, perceived benefit and Trust on
The above data table shows the coefficient of this regression model, in which Standardized Coefficients is the path coefficient. The Standardized Coefficients of perceived risk, perceived benefit, and trust are 0.224, 0.706 and 0.053 respectively. The Sig. of perceived risk and perceived benefit were 0.000 and 0.000 respectively, which shows that the influence of perceived risk and perceived benefit on purchase intention iss significant. The VIF values of perceived risk and perceived benefit are 5.902 and 4.267 respectively--all below 10--which basically shows that there is no Collinearity between independent variables.
This result confirms the following two hypotheses of the researcher:
Hypothesis 1. Perceived risk has a negative impact on purchase intention.
Hypothesis 4. Perceived benefit has a positive impact on purchase intention.
However, Sig. of Trust is 0.165, which is greater than 0.05, indicating that trust had no significant effect on purchase intention. This means the following hypothesis was rejected:
Hypothesis 2. Trust has a positive impact on purchase intention.
4.5 Summary of Hypothesis
Table 10: The summary for all hypothesisNo. Hypothesis Sig. Conclusion ResultH1 Perceived risk has
negative impact on purchase intention. 0.000
Negative
relatedsignificantly
Accept
H1a
Financial risk has negative impact on purchase intention. 0.000
Negative
relatedsignificantly
Accept
H1bProduct/Service risk has negative impact on purchase intention.
0.528 No effects Reject
H1cTime risk has negative impact on purchase intention.
0.243 No effects Reject
H1d
Information risk has negative impact on purchase intention. 0.000
Negative
relatedsignificantly
Accept
H2Trust has positive impact on purchase intention.
0.165 No effects Reject
H3
Perceived risk has negative impact on trust. 0.000
Negative
relatedsignificantly
Accept
H4 Perceived benefit has positive impact on
0.000 Positive Accept
purchase intention. relatedsignificantly
H4a
Perceived benefit has positive impact on trust. 0.000
Positive
relatedsignificantly
Accept
H4b
Price benefit has positive impact on purchase intention. 0.000
Positive
relatedsignificantly
Accept
H4c
Convenience benefit has positive impact on purchase intention. 0.000
Positive
relatedsignificantly
Accept
H5
Selection benefit has positive impact on purchase intention. 0.000
Positive
relatedsignificantly
Accept
5.ConclusionA total of 500 questionnaires were collected,
and only 465 valid questionnaires were left after screening. Of the 500 people surveyed, 486 said they had used an online travel agency, accounting for 97.2 percent of the total. People aged between 21 and 40 are the significant group who use websites to book hotels. The target population of this study is Chinese users aged 21 to 50 who use online travel agencies. The final number of valid people is 465, or 465 valid questionnaires.
After a multiple regression analysis of the hypotheses, the results are summarized as follows. The results show that perceived risk (beta = -0.224, P=0.000 < 0.001) has a significant negative impact on purchase intention, which verifies
Hypothesis 1 proposed by the author. Four variables in the measurement dimension of perceived risk, which are financial risk (beta = -0.221, P=0.000 < 0.001); product/service risk (beta = -0.043, P=0.528 > 0.05); time risk (beta = -0.067, P=0.243 > 0.05); and information risk (beta = -0.595, P =0.000< 0.001). Only two variables showed a significant negative impact on purchase intention. Hypothesis 1a and Hypothesis 1d are verified. Hypothesis 4b and Hypothesis 4c are rejected.
According to the results of the study perceived benefit (beta = -0.706, P=0.000 < 0.001) has a significant negative impact on purchase intention, which verifies Hypothesis 4 proposed by the author. There are three variables in the measurement dimension of perceived risk, which are price benefit (beta = 0.336, P=0.000 < 0.001); convenience benefit (beta = 0.314, P=0.000 < 0.001); and selection benefit (beta = 0.312, P =0.000< 0.001). All three variables showed a significant positive impact on purchase intention. Hypothesis 4a, Hypothesis 4b and Hypothesis 4c are all confirmed.
The results of the study on the effect of trust on purchase intentions show that trust (beta = -0.052, P=0.165 > 0.05) has no significant impact on purchase intention.
In addition, the results show that PR has a significant negative impact on trust (beta = -0.605, P=0.000 < 0.001). PB has a significant positive effect on trust (beta = 0.356, P=0.000 < 0.001).
The results show that perceived risk has a significant negative impact on purchase intention. This result is similar to the research of Kim et al. (2008), which shows that perceived risk is a very important factor affecting customers' purchase intention in the online environment. Our research shows that in category of impact of perceived risk on purchase intention, financial risk and information risk are the two that customers care most about. This is also closely related to the rapid development of science and technology. As hacker technology continues to increase in effectiveness the risk of online information exposure becomes higher. When booking a hotel, customers must fill in detailed personal information and payment information, including credit card information. Once the information is obtained illegally by hackers it can cause incalculable economic and personal losses to consumers. Therefore, whether it is a hotel or an online travel agency, the online protection wall must be strengthened. Sellers need to improve their IT systems to enhance the safety awareness of buyers; this will affect consumers’ willingness to buy online. Hotels and websites should secure customer information properly to ensure protection from fraud. Providing a Network Security Tester certificate can enable customers to feel a certain degree of security of personal information, and effectively reduce some perceived risks.
5.1.2 Perceived BenefitThe results show that perceived benefit has a
significant positive effect on purchase intention. This result is consistent with many previous studies, such as Kim et al. (2008) and Tingchi Liu
et al. (2013), whose research found similar results. It is not difficult to discover that when customers consider booking hotels online they pay great attention to the profitability of this purchase behavior. The customer’s expectations in regard to price, convenience, or multiple benefit options are significant factors affecting purchase intentions.
The website needs to seek price benefits from hotels in order to provide customers with the most favorable price. The website can provide membership mechanisms and other special privileges for frequent users. This can enhance the loyalty of users. Second, the website can begin with the customer's point of view, explore the customer's needs, and provide easier search methods. Thirdly, users may attach great importance to hotel resources owned by the website. Website managers need to have a clear understanding of each destination and integrate as many hotel resources as possible.
5.1.3 TrustThe results show that although trust does have
a certain effect on purchase intention, it is not a significant effect. This is inconsistent with the findings of Kim et al. (2008) in online shopping research, but is consistent with the findings of Lien et al. (2015). The latter study is also concerned with online hotel reservations. In the online shopping environment, consumers attach great importance to the trustworthiness of the website; however, in the case of an online travel agency, the customer's trust of the website does not have a great impact on purchase intention. Customers may be more interested in the integrity of the hotel. Customers' trust in the hotel and their trust
in the online travel agency should be discussed separately.
At the same time, in conjunction with our research, researchers found that in today's advanced network era users have numerous ways to safeguard their rights. Customers can defend their rights and express their dissatisfaction more easily than before. In today’s era of user-generated content users need not rely solely on traditional media channels to voice their opinion. The internet provides consumers with more convenient means to safeguard their rights.
5.2 Limitation & Future Research5.2.1The relationship between perceived risk and
trustAccording to the literature review mentioned in
the second chapter, scholars have been controversial regarding the relationship between perceived risk and trust at this time. There are four kinds of relations. In the first type, perceived risk regulates the relationship between consumer trust and purchase intention. In the second relationship, the perceived risk is preceded by the consumer's trust. In the third relation, trust precedes perceived risk. The fourth relationships between the two factors are not recursion.
In this study, the author combines various factors such as the research background of each article, and puts forward a hypothesis based on the second relationship: Customers' perceived risk has a negative impact on trust. Finally, this hypothesis is verified. Future research can do a systematic and complete research on relationship between perceived risk and trust.
5.2.2 Trust & Purchase intentionIn the case of online travel agencies, the
author studies the effect of trust on purchase intentions. It is shown that although trust does have some effect on purchase intention, this is not a significant effect. After reviewing the previous literature, the author finds that this paper discusses only trust toward the online travel agency websites, but does not discuss trust toward hotels. Future researchers can do a separate survey of these two trusts and may find different results.
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