UNDERSTANDING CUSTOMERS E-LOYALTY IN THE AIRLINE INDUSTRY: A CASE STUDY OF VIETNAM AIRLINES COMPANY LIMITED

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1 I J A B E R, Vol. 13, No. 5, (2015): UNDERSTANDING CUSTOMERS E-LOYALTY IN THE AIRLINE INDUSTRY: A CASE STUDY OF VIETNAM AIRLINES COMPANY LIMITED Van T. T. Bui 1, Phuong V. Nguyen 1,*, Dung T. Pham 2 and Kien T. Mai 1 Abstract: Vietnam Airlines, the largest state-own company in the airline industry of the country, is providing e-ticket purchase to reduce its operations costs and to bring other benefits in terms of efficiency. However, online business is currently at the starting phase in this emerging market, while the operation is still burdened by the traditional selling methods in overhead running cost terms. Therefore, this study aims to give an overview of customers E-satisfaction, E-trust, and E-loyalty to evaluate the current online business of Vietnam Airlines Company. A Partial Least Squares Structural Equation Modeling (PLS-SEM) approach is used to analyze our research model of the relationships among e-service quality factors with E-satisfaction and E-trust, and how these two factors impact on E-loyalty. With the sample size of 182 using bootstrapping resampling technique, our findings show that E-satisfaction has a larger impact than E-trust on E-loyalty. Besides the positive effects of Ease of Use, Responsiveness and Price Perception on E-satisfaction, E-trust is positively affected by Assurance. Price Perception is the strongest determinant of E-satisfaction, which implies that customers purchasing e-tickets tend to focus on price during their shopping process. The implications and suggestions are given based on these statistical evidence, and along with the in-depth interviews conducted with the participation of Vietnam Airlines managers and experts. Through the case study of Vietnam Airlines, this paper enables other local airline companies or online companies to replicate by looking at two aspects of online shopping, providing customer insights and company insights. Keywords: E-satisfaction, E-trust, E-loyalty, Vietnam Airlines, online services 1. INTRODUCTION Vietnam is the fastest growing Internet country in the region and among the countries with the highest growth rates in the world. During the last 10 years, Internet users in Vietnam have multiplied by 120. There are more than 32 million Vietnamese using the Internet in In the meantime, Vietnam has caught up the level of Internet use with other emerging economies. With the Internet growth, the e-commerce in Vietnam has also developed rapidly. For the airlines, the benefits 1 School of Business, International University, VNU - HCMC, Vietnam 2 Vietnam Airlines Company Limited * Correspondence author: nvphuong@hcmiu.edu.vn

2 3040 Van T. T. Bui, Phuong V. Nguyen, Dung T. Pham and Kien T. Mai of Internet use for purchasing e-tickets are fundamental to know customers better and to reduce the distribution costs of the airlines industry. Therefore, online commercialization has driven the electronic boarding card, online selection of seats and increased market share through the improvement of online performance and satisfaction with the website (Harison and Boonstra, 2008). Thus, for the firms, it is fundamental to enhance their customers loyalty to their websites. With the development of online booking, airlines can reduce cost and increase productivity as well Overview of e-commerce in Vietnam With the development of Internet users, online trading and banking become popular with people. Table 1 shows the statistics of Internet users in Vietnam in 2013 and the estimates of 2015 statistics. Internet users in Vietnam are having a strong growth and expected to reach the number of 45% of population in 2015, from the rate of 36% in Average expenditure per user is 120 USD and climbs up to 150 USD in During the period from 2013 to 2015, the revenue from the online market is expected to increase double and achieve value of around 4 billion USD in Despite the recession in Vietnam economy recently, information technology and e-commerce have kept moving forward in a high speed. It is more likely to have a considerable impact on marketing and sales, changing the traditional methods of distribution and transaction in Vietnam. Table 1 Statistics of Internet user in Vietnam 2013 Estimate 2015 Population 90 million 93 million % Internet user 36% 45% Annual online expenditure each person 120USD 150 USD % Internet user for online purchasing 57% 70% (high) 65% (average) 60% (low) Estimate revenue from online B2C 2.2 Billion USD 4.3 billion USD (high) 4.08 billion USD (average) 3.7 billion USD (low) (Source: Vecita, Vietnam E-commerce Report 2013) Vietnam has a great potential chance to pursue a sustainable development strategy. Thousands of companies are investing in the online trading, making it the main channel distribution, especially in travel enterprises and airlines. In fact, there are a lot of advantages for customers while they purchase tickets online. Some websites show a big promotion, but also increase price at the same time, so the price of a product after being discounted may be higher than that bought in offline stores.

3 Understanding Customer s E-Loyalty in the Airline Industry 3041 Other reasons were the problems of delivery (38% of opinions) and personal privacy risks (31%), which could be harmful to customer trust in online purchasing. Trust and satisfaction are important in e-commerce; therefore, if customers do not believe in the service quality of a website, they may never come back to that webpage again. Moreover, technical characteristics of a website, Ease of Use and Web design, are concerned. Thus, they are important topics for conducting research, thereby making improvement. We can see that price, quality of product, ease-of use of website, design, and so forth have considerable impacts on customer behaviors. Hence, to build up a successful website, we need to find out the impact of service quality towards customer behaviors Overview of airline industry Owning the local market with 90 million people, Vietnam has a lot of potential conditions to develop airline industry. Hanoi and Ho Chi Minh City (HCMC) are expected to emerge as busy trading and travel hubs in the region and the world, which explains why Vietnamese government maintains the huge public investment in transportation infrastructure. Besides, Vietnamese transportation operation is perceived inefficient in comparison with other countries in the South-East Asian region. Impacted strongly by subsidized mechanism, rail transportation has a slow change progress. In fact, the ticket system of rail transportation is mainly practiced manually with few applications of modern technology. Since Vietnamese middle class is expanding, the demand for air travel is starting to increase, opening a new market for low-cost airline. More people choose aviation for long and medium journeys in Vietnam because of its safety and time saving ability. Furthermore, airfare and costs have a trend to drop down due to the fierce competition of low-cost airlines and the result of increasing effective management. Mr. Dinh La Thang, Minister of Transportation Ministry, stated that rail fare from Ho Chi Minh City to Hanoi is 1.9 million VND, even higher than low-cost airfare with only 1.2 million VND. Instead of traveling 30 hours by train, passengers only need 3-4 hours taking a flight from Ho Chi Minh City to Hanoi. With this advantage, Vietnamese people obviously prefer to travel by air. There are three domestic airline companies in Vietnam: Vietnam Airlines (VNA), Jetstar Pacific and Vietjet Air. VNA is the national flag carrier acting as the largest airline company in Vietnam. VNA had 63.2% of market share in domestic market and 40.7% in the international outbound market. Founded in 1993, VNA, the state-owned company in aviation industry has a well-known reputation in Vietnam. It has developed the online trading and reservation through the website since Similar to other airline online services, VNA mainly provides information, promotion programs and reservation service on the website; with which customers can easily access the webpage and book their tickets online. In the domestic market, VNA is facing the competition from Vietjet Air

4 3042 Van T. T. Bui, Phuong V. Nguyen, Dung T. Pham and Kien T. Mai and Jetstar Pacific. While VNA is a leader in the market with 63.2% of the shares domestically, VietJet currently has 24.9% of the shares. Jetstar Pacific was ranked third with 11.9%. With the rapid development and strong financial power, Vietjet Air has continually increased the frequency, airplanes and operation in Vietnam. It can be said that the air domestic market is the battlefield between VNA (full service airline) and Vietjet Air (low-cost airlines). Airline companies are facing significant challenges in covering running costs and gaining profits at the same time. In the competition between travel agencies, traditional airlines, and low-cost carriers, it has become essential to adopt smart solutions to reduce costs; this is especially true in the industry with a long-term growth like travel industry. To due with these matters, VNA has a strategy to reduce the impact of their own traditional distribution of selling tickets (through ticket offices and sales agents, which results in overhead running costs). They realized that the trend of ticket distribution in the world shall be online in the virtual environment. However, it is hard to keep current customers using VNA service because of cultural and other existing obstacles. On their way to pursue this new trend, the main challenge is designing a site that is attractive right at the first view and interesting enough for customers to repeat the visits (Kassim 2010). Besides website impression, it is important make customers feel their desire fulfilled when using services, resultsing in customers satisfaction. Therefore, the Board of Director of VNA needs to find ways improving online services, increasing the number of loyal customers and contributing to the increase in revenue. Based on the current needs, this study is conducted to measure e-satisfaction and e-loyalty of online customer of VNA. Online services, such as flight booking, selecting seats, web check-in, and, more importantly, buying tickets are all considered essential for airline companies to succeed. Accordingly, it is important to gain a better understanding about behaviors of travelers when completing online travel arrangements. The airlines have taken the greatest advantage of the growth in online tickets; online ticket sales is accounting of 26.7 % of the total sales in the world (Sita 2011). However, the revenue coming from online sales of VNA has only taken around 9% of total revenue. The number is limited compared with the average number of 26.7% of airlines industry in the world. In spite of effectiveness and cost saving, online distribution of VNA contributes the lowest to revenue as a method of distribution. Ticket sales agent and VNA ticket office are two main channels that solve all problems and complaints of passengers about ticket regulations. With the growth of online and agent distribution, ticket office is contributing to 11% revenue of VNA and has the trend to reduce the scope. Although online services role is increasing in the sales of VNA, increasing quality of e-services by establishing customer value and satisfying customers needs has not been highly considered in VNA. In fact, understanding the loyalty and its

5 Understanding Customer s E-Loyalty in the Airline Industry 3043 relationship is crucial for making corporate development. From this reality, the research How quality of online service and price impact on E-loyalty of VNA customers is conducted to provide a fully accurate and systematic overview of this service. The research is designed to solve mentioned problems by collecting and analyzing relevant information of VNA online services. We find that the most important e- service quality, information and price dimensions are initially investigated and identified to achieve E-loyalty. After studying the literature, such as Price Perception, Ease of Use, Information Quality, Responsiveness, Customization, and Assurance were investigated and then their impacts on customers satisfaction and E-trust were measured. Due to limitation of time and resource, this research cannot reach all aspects of online services of VNA in Vietnam while it only focuses on scope in Ho Chi Minh City. The study was executed through two phrases: (1) Quantitative and (2) Qualitative. From the current context of VNA, quantitative investigation by distributing surveys is carried out to analyze the level of correspondence of the conceptual model in the current practice. As the objective to find out the relationship between exogenous variables to E-loyalty, structural equation modeling (SEM) statistical methods are applied with partial least squares approach (PLS SEM method) is used in this research. The software Smart-PLS is used to analyze the collected data and conceptual model, with the sample size of 182 respondents. After having the data analysis, author conducts an in-depth interview of 11 experts in VNA and industry. By the interview, author can have more opinions, which is valuable for author making recommendation. The remainder of this paper is organized as follows: Section 2 is the discussion of previous literature about e-service quality, information quality, price perception, e-trust, e-satisfaction, and e-loyalty. Section 3 presents the research methodology as well as the research results. Section 4 provides the discussion of findings and practical implications. Finally, section 5 follows the conclusion of the study. 2. LITERATURE REVIEW AND HYPOTHESES 2.1. Concepts (1) E-service quality. Bitner (1990) defined service quality as the impression of customer for the relative superiority of a service provider. Service quality demonstrates the comparison of customers between expectations and the performance of enterprises. From this point of view, e-service quality is the judgment of customers toward quality of services in the virtual environment (Santos, 2003). There are various research dimensions concerned with service quality. In tourism and leisure industry, Ho and Lee (2007) made a set of five dimensions information, functionality, security, responsiveness, customer relationship. Park and Gretzel (2007) identified six dimensions fulfillment,

6 3044 Van T. T. Bui, Phuong V. Nguyen, Dung T. Pham and Kien T. Mai ease of use, security, visual, responsiveness and information. In e-commerce settings, Ribbink (2004) proposed the set of five dimensions of e-service quality Ease of Use, Responsiveness, Personalization or Customization, and Assurance. We can see that there are some similar factors in the previous researches such as Security, Responsiveness, Ease of Use. Based on the model of Ribbink (2004), this research measures online service quality through four dimensions Ease of Use, Responsiveness, Personalization or Customization, and Assurance. Ease of Use. Ease of Use is an important dimension of service quality (Dabholkar, 1996) and is decisive for customer satisfaction, because the effectiveness of using the service is enhanced (Xue and Harker, 2002). Ease of Use would provide better experience of website contents so that it can play an important role in developing customer s satisfaction and loyalty (Luis et al., 2008). It is crucial to improve customers feeling with providing online service in all the times and locations (Gerrard & Cunningham, 2003). Reibstein (2002) asserted some aspects such as functionality, accessibility of information, ease of ordering and navigation. Ribbink (2004) mentioned the Ease of Use such as accessibility, navigation, friendliness. Customization. There is also empirical support that Customization is a dimension of service quality (Ennew and Binks, 1996). Fornell (1996) mentioned Customization as a quality indicator measuring how well a product fits a customer s personal requirements and is the vital element to forecast the demand of customers. Responsiveness. As a component of service quality, Responsiveness measures the ability of company to take action and offer instant service when customers get problems (Zeithaml et al., 2002). Understanding customer requirements and developing the service based on responsive feedback enhances service satisfaction and also trusts (Gummerus et al., 2004). For detail, Ribbink (2004) mentioned Responsiveness such as a quick reply, willing to feedback and easy to contact. Santiago et al. (2012) also measured Responsiveness including two items, including a quick and straightforward reply. Assurance. Ribbink (2004) asserted that Assurance is always concerned with e-service quality and includes security and privacy. Security concerns the problem losing important information about the customer for third parties (e.g. information of credit card or bank account details), whereas privacy relates to the concern about the wrong purpose using of personal information by marketers (Milne and Rohm, 2000). For detail, Ribbink (2004) mentioned th e Assurance such as private information, trustworthiness, secure.

7 Understanding Customer s E-Loyalty in the Airline Industry 3045 (2) Information Quality. Information Quality is the dimension referring to the quality of the information provided on the website. The accuracy, comprehensiveness, and newness of the website content are important characteristics in the battle of online competition among e-ticketing providers, as well as other forms of online services. In the academic view of information quality, there are four types of information quality, which are intrinsic, contextual, representational, and accessibility information quality. (Wang & Strong, 1996, Jarke & Vassiliou, 1997, Delone & McLean, 1992). (3) Price Perception. Price Perception is an important element in evaluating a consumer s pre-purchase decision. Specifically, consumers tend to consider the relevant relationship between price and their expectations by comparing it with their previous experiences. Price perception is the degree to which a consumer engages in comparative shopping and that he or she intends to get the best price. The pervasive influence of price is due, in part, to the fact that the price cue is present in all purchase situations and, at a minimum, represents to all consumers the amount of economic outlay that must be sacrificed in order to engage in a given purchase transaction. Perceived strictly in this way, price represents the amount of money that must be given. Price is surely a strong motive to attract the customers. (4) E-trust. E-trust is defined as a consumer s conviction and belief regarding the behavior intention of an online seller, who must react in accordance with the e-shopper s interests, be honest in the transactions and deliver the services requested (Kim et al. 2009). ) Previous studies have identified E-trust as honesty, integrity (Moliner et al. 2007) and competence (Flavian et al. 2006). The degree to which the customer s confidence that the airline s web site will fulfil the obligations set forth in an exchange, and will not take advantage of the information shared (Gundlach & Murphy, 1993, Koppius et al., 2005). Trust in the website is important; wrong purpose use of personal information, unauthorized use of credit card information, loss of data privacy or unauthorized transactions are some popular problems that may happen while using the Internet (Gefen et al (5) E-satisfaction. Customer satisfaction is one of the most important dimensions to measure the success of marketing plans and strategy. Online satisfaction may also be defined as the contentment of the customer while purchasing online service (Anderson and Srinivasan, 2003). (6) E-loyalty. E-loyalty brings a high rate of customer retention and reduced cost for recruiting new customers who lead to long-term profitability to the online retailer. Flavian et al. (2006) asserted that online loyalty, or E-loyalty, has been defined as a consumer s intention to buy from only one web site and not to change buying decision to others. In another study of E-loyalty, Cyr et al. (2005)

8 3046 Van T. T. Bui, Phuong V. Nguyen, Dung T. Pham and Kien T. Mai proposed E-loyalty as intention to revisit a web site or to consider purchasing from it in the future. Previous research has shown that the antecedents of E- loyalty are E-trust, E-satisfaction, e-service quality, Price Perception and many other variables concerned (Ribbink, 2004, Flavian et al. 2006; Cyr et al. 2008) Proposed research model E-loyalty in airline travel and its framework have not been developed widely, especially in Vietnam. In the previous research, (Herrmann, Xia, Monroe, and Huber, 2007; Huber, Herrmann, and Wricke, 2001), relationships linked to pricing focus on product quality, performance, and consumer satisfaction that matches an expectation of price for a product or service. In the airline industry, research of Athiyaman (2002) which assumes that Price Perception has the strong impact on satisfaction. Therefore, we develop the proposed research model as presented Figure 1, based on model of Ribbink (2004) combined with the Information Quality and Price Perception factors. Figure 1: Proposed Research Model 2.3. Hypotheses Base on the studied model suggested and the theory of service quality of many authors as discussed above, the majority of studies have suggested that four components of e-service quality, Information Quality and Price Perception influence on E-satisfaction and E-trust, which in turn also influence positively and indirectly on E-loyalty. From the assumptions in the proposed model, the research hypotheses are given as follows:

9 Understanding Customer s E-Loyalty in the Airline Industry 3047 H1a: Assurance has a positive impact on E-trust of VNA customer. H1b: Ease of Use has a positive impact on E-trust of VNA customer. H1c: Information Quality has a positive impact on E-trust of VNA customer. H1d: Responsiveness has a positive impact on E-trust of VNA customer. H1e: Customization has a positive impact on E-trust of VNA customer. H2a: Assurance has a positive impact on E-satisfaction of VNA customer. H2b: Ease of Use has a positive impact on E-satisfaction of VNA customer. H2c: Information Quality has a positive impact on E-satisfaction of VNA customer. H2d: Responsiveness has a positive impact on E-satisfaction of VNA customer. H2e: Customization has a positive impact on E-satisfaction of VNA customer. H3: Price Perception has a positive impact on E-satisfaction of VNA customer. H4: E-satisfaction has a positive impact on E-loyalty of VNA customer. H5: E-trust has a positive impact on E-loyalty of VNA customer. H6: E-satisfaction has a positive impact on E-trust of VNA customer. This study seeks to explain how customer E-loyalty may be demonstrated by E-service Quality, Price Perception, E-trust, and E-satisfaction. It is combined and developed the existing model of Ribbink (2004). Besides that, the framework seeks to find out the E-loyalty in the travel in Vietnam, which has been not thoroughly investigated. 3. METHODOLOGY AND RESULTS 3.1. Sampling method and sample size This research used the convenience sampling method with the participation of 182 customers using online service of VNA via both online survey and hardcopy survey. To ensure the reliability of the research, the sample size requirement is greater than 100 and greater than the number of variables multiple by 5 (Hair et al., 2006). In this research, there were 40 representative indicators. Thus, the sample size of this research should be greater than 200 if Covariance-based Structural Equation Modelling is applied. However, the sample size is not as large when Partial Least Squares - Structural Equation Modelling technique is used to analyze; therefore, 182 observations are suitable for the validity of the analyzed data and could be smaller (Hair et al., 2013). Measurement scale and key components denotation are presented in the appendix Data analysis At first, we conduct a pilot test with 80 respondents to detect weaknesses in questionnaire design and instrumentation (Cooper and Schindler, 2011). Obviously,

10 3048 Van T. T. Bui, Phuong V. Nguyen, Dung T. Pham and Kien T. Mai before officially spreading the survey, pilot test helps us know whether all the questions are easy to understand and easy for respondents to answer or not, then we use their feedbacks to revise the questionnaires consistent with the Vietnamese context. During the data collection process, we receive a great support from 20 Vietnam Airline agents to help us to distribute the questionnaire to their customers. We delivered more than 250 samples. However, we received only 182 valid samples. We implemented the following analyses: descriptive statistics, reliability, factor analysis, and structural equation modeling in the partial least square approach The descriptive statistics Table 2 shows respondents gender, age, education and income is showed below: Table 2 Demographic information Frequency Percent (%) Gender Male Female Age Under From From 40 to Income Under 5mil From 5mil to 10mil From 10mil to 15mil Above 15mil Education University Post-university High School Total Among 182 respondents, there are 54.9% females and 45.1% male from different age and income level. Therefore, these respondents could partly reflect the differences in perception, feelings, and psychology. Based on the table, the percentage of female respondents is approximately equal to the percentage of male respondents, so the research shows a balance in genders. Regarding with the age of customers, the majority of respondents are in the range of 20 to 40 years old (more than 80%). People between 40 and 60 years old are counted for 18.1%. The smallest proportion group is under 20. This could reflect the financial condition of each income group as well as different traveling purposes. Regarding income, most of the respondents (41.8%) have monthly income from 5 million VND to 10 million VND. Followings are 24.2% of respondents earn from million VND each month and 26.9% of respondents earn more than 15 million per month. The income segment has been objectively categorized and respondents are randomly chosen. In addition, in terms of education, nearly 70% of respondents have

11 Understanding Customer s E-Loyalty in the Airline Industry 3049 university degrees, and 28% have a post-university degree. From the data, we could conclude that the majority (approximately 98%) of people who took this survey and used online service of VNA have University degree and only 2% completed their high school programs without continuing on the university degree Reliability Test and Factor Analysis Firstly, Cronbach s alpha is used to test whether each item of each factor is reliable or not. Internal consistency reliability is applied to assess consistency of an individual s performance from item to item and item homogeneity. In order to test internal consistency reliability of measurement, this study uses method evaluating Cronbach s alpha index. Many professionals suggested that an alpha score of 0.6 is generally acceptable (Peterson, 1994; Slater, 1995). In addition, some studies also indicated that the accepted rule for Cronbach s alpha extensionally: alpha > 0.9: Excellent, >0.8: Good, > 0.7: Acceptable, >0.6: Questionable, >0.5: Poor, and <0.5: Unacceptable (Kline, 1999; George & Mallery, 2003). In SPSS, Corrected Item-Total Correlations are monitored to determine the degree to which each item correlates with the total score. Field (2005) and Pallant (2007) showed that values less than 0.3 indicate that the item is measuring something different from the whole scale. The Cronbach s alpha if deleted is evaluated to determine the effect of removing items from each sub-scale (Lemmens, 2010). The item whose Cronbach s alpha if an item deleted is larger than the overall Cronbach s alpha, and corrected item-total correlation is less than 0.3 will be discarded from the variable list. Table 3 illustrates all key indicators to test the reliability. After calculating, obviously, the Cronbach s alpha of all constructs is over 0.6; moreover, the Corrected Item-Total Correlation values of those items are all greater than 0.3 (Pallant, 2011). Therefore, all the items are reliable and preferable, except for the item RPS3, which has the correlated value lower than 0.3. After the Reliability Test, we found that all items are available to proceed the next step: Partial Least Square analysis. In this step, the internal consistency of measurement is tested by Composite Reliability statistics, with the purpose to ensure the measurement of each factor by overcoming the possible limitation of Cronbach s alpha analysis Partial Least Square analysis In CB-SEM method, an exploratory factor analysis (EFA) should be taken before confirmatory factor analysis (CFA) to observe the factorial validity and SEM model fit is analyzed as the last one. However, with PLS method, a researcher could basically conduct CFA test and use different statistical evidence to check the factorial validity of the data, as the assumptions and statistical proof of two approaches are different. As suggested by Gaskin (2014), model specification is the first step in this approach. Configure the model should be done before running a PLS analysis. Formative and reflective factors need to be appropriately identified.

12 3050 Van T. T. Bui, Phuong V. Nguyen, Dung T. Pham and Kien T. Mai Table 3 General statistical results Construct Cronbach s Correlated Std AVE Model loading Value Range Deviation Range range Ease of Use ( ) Information Quality ( ) Responsiveness ( ) Customization ( ) Assurance ( ) Price Perception ( ) E-satisfaction ( ) E-trust ( ) E-loyalty ( ) A careful establishment of indicators is a must, because factorial validity establishing tests for reflective indicators and formative indicators will have different approaches. In our model, reflective constructs are used; PLS-SEM is suitable for this situation, and no special method for formative constructs needs to be considered. After the step of model configuration, Construct Validity of Reflective Constructs is established. Establishing validity and testing the entire path model occurs in one pass using PLS by running a bootstrap of the model using 200 (or more) resamples. As suggested by Hair (2013), bootstrapping of 5000 is necessary to generate a PLS-SEM result. In doing so, we performed a confirmatory factor analysis (CFA) that was executed as part of the PLS run. We first established convergent validity for the reflective constructs by checking whether the measurement items were loaded with significant values on their theoretical constructs. All of our reflective indicators were significant at the 0.05 level on this test. We then examined the values of the outer model loadings (an estimation of how much a particular indicator loads onto a construct in the model). All of the outer loadings were significant at the 0.05 level. These results indicate strong convergent validity in our model for the constructs, which are reported in Table 3. SmartPLS also offers a measurement model table (to a pattern matrix) with the inner model loadings Convergent validity Average Variance Extracted (AVE) as a criterion of convergent validity Convergent validity signifies that a set of indicators represents one and the same underlying construct, which can be demonstrated through their unidimensionality. Fornell and Larcker (1981) suggest using the AVE value of at least 0.5 indicates sufficient convergent validity, meaning that a latent variable is able to explain more than half of the variance of its indicators on average (e.g., Götz, Liehr-Gobbers, & Krafft,

13 Understanding Customer s E-Loyalty in the Airline Industry ). AVE of all factors is presented in Table 3. AVE values of all factors are larger than 0.5, which signifies that the set of indicators reached convergent validity Discriminant validity In PLS path modeling, two measures of discriminant validity have been put forward: The Fornell Larcker criterion and the crossloadings. Fornell & Larcker (1981) postulate that a latent variable shares more variance with its assigned indicators than with any other latent variables. Variables should be greater than the latent variable s highest squared correlation with any other latent variable. They also suggest that the square root of AVE in each latent variable should have the value larger than other correlation values among the latent variables to confirm the discriminant validity. Table 4 reports the results from checking discriminant validity. Table 4 Fornell-Larcker Criterion Analysis for Checking Discriminant Validity ASR CTM ELY EOU ESF ETR IQ PPC RPS ASR CTM ELY EOU ESF ETR IQ PPC RPS The latent variable ELY s AVE is found to be ; hence, its square root becomes This number is larger than all correlation values in the column of ELY (lowest value at , highest value at ) and also larger than those in the row of ELY (0.527 and ). Similar observation is also made for the latent variables ASR, CTM, EOU, IQ, ESF, ETR, PPC, and RPS. The results indicate that discriminant validity is well established Structural Equation Modeling (SEM) PLS-SEM index In our model, the constructs are reflectively measured, so all PLS-SEM method used in this research is for reflective constructs only. At this stage, we conduct SEM technique for the full model, which is the measurement model and the structural model. The criterion of meaningful factor loading was set to 0.4 (Tsoukatos and Rand, 2006). When loading all items in the model through SmartPLS, the author eliminates the items affecting in each factor which has the value lower than 0.4, since it shows the indicators are not suitable enough to explain for the proposed factors. After removing the items out of the model, the data are reloaded. The following table is the result of CFA. Each factor is identified by self-

14 3052 Van T. T. Bui, Phuong V. Nguyen, Dung T. Pham and Kien T. Mai grouped indicators. The subtraction of items with the largest number in the row and the second largest one needs to be greater than 0.2. The coefficient of determination, or R squared, is for the E-loyalty variable. This means that the e-customer satisfaction and E-trust moderately explain 41.8% of the variance in E-loyalty. Besides that, the coefficient of determination for E- trust and E-satisfaction is and This means that four dimensions of the e-service quality (Assurance, Customization, Responsiveness, and Ease of Use), Information Quality, and Price Perception explain 45.4% of the variance in E-trust and 56.4% in E-satisfaction. Table 5 shows detailed information about the overview statistics of PLS-SEM analysis. R-squared shows the explanation power mentioned above. Composite Reliability is larger than 0.7 Hair et al. (2013) tells researchers the same meaning of what Cronbach s alpha tells about the internal consistency of the measurement, but it can overcome the weakness of Cronbach s alpha in terms of PLS-SEM analyzing technique. Table 5 Overview Statistics Composite Reliability R-Squared Communality ASR CTM ELY EOU ESF ETR IQ PPC RPS All these factors have Composite Reliability larger than 0.7, in addition with the Cronbach s alpha results analyzed with the software SPSS version 21.0 gives a perfect view at the measurement of the factors. The unreliability on the side of the questionnaire was somehow successfully avoided Significant level (Bootstrapping) PLS-SEM does not assume the data is normally distributed, which implies that parametric significance tests used in regression analyses cannot be applied to test whether coefficients such as outer weights and loadings are significant. Instead, PLS-SEM relies on a nonparametric bootstrap procedure to test coefficients for their significance. After reviewing the path coefficient for the inner model, we can explore the outer model by checking the T-statistic as showed in Table. As presented in Table 6, all of the Outer Statistics T-Statistics are larger than 1.96 so we can say that the outer model loadings are highly significant.

15 Understanding Customer s E-Loyalty in the Airline Industry 3053 Bootstrapping is a basic term in econometrics, in which an original sample is used to draw into a specific quantity of subsamples with replacement. In this case, after each draw of random observation, the process starts back from the sampling population to come to the next draw. Because of this randomness, some observations could be chosen several times; some may not be chosen even once. The results, therefore, are slightly changed after each time a bootstrapping resampling technique is performed. However, as our observation, the result remains the same due to the fact that the change in statistical data is not significant. As suggested by Gaskin (2014), bootstrapping of 5000 is suitable for PLS. In this study, the bootstrapping of 5000 is conducted by PLS. The t values can be compared with the critical values from the standard normal distribution to decide whether the coefficients are significantly different from zero. The critical values for significance levels of 1% (a = 0.01) and 5% (a = 0.05) probability of error are 2.57 and 1.96, respectively (two-tailed test). Using a two-tailed t-test with a significance level of 5%, the path coefficient will be significant if the T- statistics is larger than The below table is the summary of our research results, which clearly state the relationships presenting in the proposed model. T-statistics of Hypothesis H1b, H1c, H1d, H1e, H2a, H2c, H2e are not significant because these T-statistics are smaller than 1.96, provided the confidence interval of 95%. Therefore, we reject these hypotheses, which implies that Ease of Use, Information Quality, Responsiveness, Customization do not have a significant impact on E-trust of VNA customer; in other words, these factors do not make customers trust the site. In terms of E-satisfaction, we also conclude that Assurance, Information Quality, and Customization and E-satisfaction do not have a significant impact on E-satisfaction of VNA customers; from which we could draw a conclusion suitable to the research context is that the changes in those factors could not lead to the changes in how customers feel satisfied with the online services VNA provides. Meanwhile, the T-statistics of Hypothesis H1a, H2b, H2d, H3, H4, H5, and H6 are significant (larger than 1.96). We can conclude that only Assurance have a positive and significant impact on E-trust of VNA customer. Ease of Use, Responsiveness and Price Perception have positive and strongly significant impacts on E-satisfaction of VNA customer. Both E-trust and E-satisfaction have positive and significant impact on E-loyalty of VNA customer with T-value accordingly 3 and The appearance of an interesting fact is that E-satisfaction has stronger impact than E-trust in the relationship with E-loyalty needs a careful consideration; the impact level of E-trust on E-loyalty is 0.22, while this statistic is 0.51 with E- satisfaction (more than double). The behavior of customers can be explained in the next chapter after these data are reviewed in accordance with the interview results.

16 3054 Van T. T. Bui, Phuong V. Nguyen, Dung T. Pham and Kien T. Mai Table 6 T-Statistics and Path Coefficients (Inner Model) Hypothesis Content T Statistics Path coefficient Result H1a Assurance (E-service quality) has a positive impact on E-trust of VNA customer Accepted H1b Ease of Use (E-service quality) has a positive impact on E-trust of VNA customer Rejected H1c Information Quality (E-service quality) has a positive impact on E-trust Rejected of VNA customer H1d Responsiveness (E-service quality) has a positive impact on E-trust of Rejected VNA customer H1e Customization (E-service quality) has a positive impact on E-trust of Rejected VNA customer H2a Assurance (E-service quality) has a positive impact on E-satisfaction Rejected of VNA customer H2b Ease of Use (E-service quality) has a positive impact on E-satisfaction Accepted of VNA customer H2c Information Quality (E-service quality) has a positive impact on Rejected E-satisfaction of VNA customer. H2d Responsiveness (E-service quality) has a positive impact on E-satisfaction Accepted of VNA customer H2e Customization (E-service quality) has a positive impact on E-satisfaction Rejected of VNA customer. H3 Price Perception has a positive impact on E-satisfaction of VNA customer Accepted H4 E-satisfaction has a positive impact on E-loyalty of VNA customer Accepted H5 E-trust has a positive impact on E-loyalty of VNA customer Accepted H6 E-satisfaction has a positive impact on E-trust of VNA customer Accepted

17 Understanding Customer s E-Loyalty in the Airline Industry 3055 Assurance does not only play as a key factor affecting E-loyalty, but is the strongest one in this research. This somehow reflects exactly the reality that the feeling of being secured is the one thing customers need to consider putting their trust on an online service. Customers behaviors are explained in the next chapter to give a suitable solution to improve E-trust among these people. On the side of E-satisfaction, Price Perception leaves the strongest impact with the path coefficient value of 0.3. Those come to a conclusion that VNA customers tend to consider price most during purchasing process; and their satisfaction mainly is the result of a good perception of the price of VNA. There is also an important thing that no researcher could ignore that E-satisfaction does effect on E-trust, and in our statistical evidence, the path coefficient value is This relationship implies that if a customer is satisfied with the online service, they are more likely to trust the website; thereby feeling more loyal to the service. 4. DISCUSSION AND IMPLICATIONS To have an overview about characteristics of the websites in Vietnam, some indepth interviews were conducted with some experts in industry. The interviewees are the manager or senior staff working in VNA and its agents. They have worked in travel industry for a long time and have the viewpoint to develop this industry. The interview concentrated in the main questions regarding with independent factors (Ease of Use, Information Quality, Assurance, Customization, Responsiveness and Price Perception). The contents of questions are mainly focused the individual evaluation in these factors, present the problem, and recommend several possible solutions. The result of data analysis shows that there is a positive and direct association of E-satisfaction and E-trust with E-loyalty for online service of VNA. This finding is consistent with the theory of Ribbink (2004) about the relationship between E- satisfaction, E-trust and E-loyalty in e-commerce setting. Taking into account the results, it can be seen that E-loyalty is constructed by two factors: E-satisfaction attracts customers and E-trust creates the confidence for customers. Based on path correlation, E-satisfaction has the stronger impact on E-loyalty than E-trust. To build up E-loyalty, E-satisfaction and E-trust need to be established first and create the good customer s perception, especially in virtual environment. However, E- satisfaction and E-trust are also dependent on its own antecedents (e.g. Price Perception, Ease of Use, Customization, Assurance, Information Quality), which should be taken into account when considering their relationship to loyalty. Customer s trust is important to the website; thus, they are important to the development of Business-to-Consumer (B2C) e-commerce in Vietnam. In the process of booking online, the customers hesitate whether they should provide information to pay online. If they never make online payment, it can prevent people to choose the products or services online. Customers usually get worried if there

18 3056 Van T. T. Bui, Phuong V. Nguyen, Dung T. Pham and Kien T. Mai is a trouble happening in payment, especially in Vietnam where risks could be concerned with the legal systems and bank systems. Fraud websites could be created to disappear after collecting money from customers. It can be said that the virtual transaction is not well managed in Vietnam and the customers are facing many risks. As VNA is a strong brand name acting as the national flag carrier of the country, Vietnamese people seem to believe in VNA reputation. It creates the competitive advantage for website VNA. In fact, with the good security and data protection system for customers, VNA keeps enhancing the trust of customers. In fact, most opinions show that they can believe the security online system of VNA. However, E-satisfaction is proven to play a more important role in deciding E- loyalty. As the online service of VNA has just been in its first stage, which needs a lot of effort and improvement if they want to turn e-ticketing into their main distribution to reduce current burdened costs. To do this, Price, Responsiveness, and Ease of Use are three critical factors, especially Price. In the Vietnamese airline industry, there are not only whole-package airline companies, but also brands famous for cheap tickets, such as Jet Star, Air Asia. Price discounts in specific periods are suggested since Price Perception has the strongest impact. The data results also show that only one component of service quality Assurance has the positive and direct impact on E- trust. This result fits with other studies about the factor Assurance from Ribbink (2004), Dianne (2008), and Mustafa I. Eid (2013). These can be explained by the online context in Vietnam e-commerce market. Since the fast-paced development of Internet, people sell and buy over the Internet easily; however, the trust over these purchasing methods is hard to gain due to the fact that e-commerce websites are more likely to review the personal information of customers as well as phishing. On the other hand, VNA has built its reputation over a long period of time and is the Representative National Airline Company that has the strongest power in Vietnam Airline industry. Therefore, its online service is assured although it is the new applied method of e-ticketing. This factor, Assurance, is obviously the most important determinant of E-trust. If VNA knows this strength, especially in the period of airplane crisis after continuous accidents In Malaysia Airlines (2014), the development strategy over this period needs to base on this factor; thereby raising customers trust and win in the battles of with cheap airline ticketing brands. Ease of Use impacts directly on E-satisfaction and indirectly on E-loyalty. Ease of Use is important for new customers to understand the website. In general, the website is easy to use and have a good navigation for customers. To make online booking, people only need to click and choose the suitable items. However, VNA should investigate to improve the website simple and easy-to-use more, especially for new customer. Most opinions in in-depth interview show that the website of VNA has the structure similar with other websites in industry. Some main functions can be listed including online reservations, online check in, information supply,

19 Understanding Customer s E-Loyalty in the Airline Industry 3057 etc. Regarding with the online booking procedure; VNA website is also similar with other websites in industry. When the users fill in the requested blank and follow all the instructions, they can make reservation compatible with their demand. Furthermore, Ease of Use brings customers the feelings of total control when they know what to do based on the clear interface of the website, and what to do next. This feeling is crucial due to the fear of losing money in online transaction. As the in-depth interview results, the interface of VNA website is not as attracted as other websites, because of national policies when designing and using word phrases. The balance between rules, regulations, and customers demands need to be carefully discussed. Responsiveness has a significant relationship with the customer satisfaction in the website. Most of opinions show that VNA has consumers are interested in getting with offline distribution (ticket offices, telephone centers, ticket sales agents) to solve the problem arising. Although Responsiveness is important to service quality and VNA respect the passenger feedback and take into consideration for improving VNA services, at this time VNA has not had the online support 24/24 for tickets purchased on the website. Regarding to the complaint handling process, VNA can take time to investigate the problem happening and in some case the Responsiveness may not be quick as expected by customers. Online Responsiveness of VNA is not highly appreciated by customers. Most respondents in the survey have the high education (undergraduate degree and above). They have the ability to approach the Internet and have a lot of choice before making decisions. Through the in-depth interview, it shows that website of VNA has lots of information about the various and different services. Customers can book more services (infants, stretcher, special meal and so forth) compatible with their demand. However, the website only describes the information, conditions and contacts to book the service. Currently, VNA has not allowed passengers book service via website. In case customers need to book service, they have contacted an agent or a ticket office of VNA. It is because VNA needs full information from customers and provides consultation before ordering service. In the future, VNA website is expected to bring ancillary service to customers with more information to customers. Price plays an important role in making the decision. Through the in-depth interview, interviewees show that price has the strong significant to E-satisfaction of customers. Through the in-depth interviews, most experts also think that price is important in the online environment. Analysis from Google also shows that the typical traveler uses 22 websites to research a trip, compare price before booking (Harteveldt, 2012). With the transparent information in the Internet, people can choose the best services with the lowest price. In the travel industry, there are usual promotions in the low season which boost the ability to travel of customers and fill up the empty seats in the airplane. In the in-depth interview, there are