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Article

Understanding the Repurchase Intention of Premium Economy Passengers Using an Extended Theory of Planned Behavior

by
Jun Hwan Kim
and
Hyun Cheol Lee
*
School of Business, Korea Aerospace University, Goyang-si 10540, Korea
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(11), 3213; https://doi.org/10.3390/su11113213
Submission received: 3 May 2019 / Revised: 3 June 2019 / Accepted: 5 June 2019 / Published: 10 June 2019
(This article belongs to the Special Issue Service Quality in Leisure and Tourism)
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Abstract

:
This study investigates the repurchase intention of passengers who have experienced premium economy class. To achieve the research purpose, we examine the relationship among psychological factors, perceived price, perceived service quality, perceived value and repurchase intention using a research model extended from the theory of planned behavior (TPB). The survey data were collected both airside and landside at two major Korean international airports from 382 passengers who used premium economy class. The results show that the repurchase intention of passengers is influenced by the attitude, perceived behavioral control, and perceived value derived from price and service quality; repurchase intention is not influenced by the subjective norm. These findings will enable air carriers to better understand the intention of premium economy passengers with respect to psychological and service value perspectives. They can also be used to improve marketing capabilities and the sustainable profitability of premium economy service.

1. Introduction

Increasing competition in the air transportation industry has spurred airlines to endeavor to provide better flight environments, and premium economy class has appeared as one of those efforts. Premium economy class is a step up from standard economy class, and it has rapidly become prevalent due to passenger demand [1]. Passengers regard air transportation as part of the travel experience and seek comfortable flights in that experience, and as such, premium economy class is increasing in popularity [1]. Also, unfavorable economic conditions such as the financial crisis in 2008 have encouraged business travelers to consider changing their seats to premium economy class [2]. According to Carlson Wagonlit Travel and Travelport [3], the number of passengers in first and business classes decreased while that of passengers in premium economy class increased by up to 157% on average for three years from 2015 to 2017 in Singapore. This trend is expected to continue, and recent studies have confirmed that demand for premium economy service has further growth potential [1,2,4].
Despite the gradual growth of this service, there are not many related studies regarding this topic [1,2]. Within the restricted number of published research results, most studies have focused on investigating the willingness to pay for seat comfort including extra seat width, pitch and legroom (see, e.g., [5,6,7]) rather than examining the relationship between passenger psychological factors, value and behavioral intention. However, in order to enhance marketing capabilities and the sustainable profitability of premium economy service, it is important to identify factors that affect passenger purchase intention and reflect such factors in airline marketing and operational strategies. The repurchase intention of customers is strongly related to customer loyalty, and integrated forms of customer loyalty are essential to business sustainability [8]. In the present study, our research model uses the theory of planned behavior (TPB) to investigate the repurchase intention of premium economy passengers. The TPB model is a widely used methodology in air transportation and tourism research to understand psychological factors that affect the intention of customers [9,10,11,12,13,14].
We also explore the effects of perceived value regarding repurchase intention by assuming that the perceived value of the premium economy service is derived from price and service quality [15,16,17,18,19]. From the demand side, Hugon-Duprat and O’Connell [1] observe that premium economy service has grown as a result of a compromise between conflicting values: Conservative consumption caused by the economic downturn and the desire for comfortable travel experiences. Kuo and Jou [2] explain that the primary purpose for airlines to introduce premium economy class, from the supply side, is to attract travelers who want higher service quality as well as a reasonable price. There is also another reason passengers’ might be willing to pay a premium price for the service. The fare price of business class from New York to London, as an example, is around 17 times more expensive than that of standard economy class [20]. By contrast, the price of premium economy class is about three times more expensive than that of standard economy. Therefore, there is a considerable possibility that passengers who hesitate to purchase first or business class due to high prices will switch to premium economy class. In terms of needs for higher comfort and service quality, the International Air Transport Association (IATA) Annual Review [21] reported that 85% of passengers preferred higher and more customized services and they were ready to spend their money on these services. This shows that passengers desire high service quality, and they are likely to use premium economy class. Accordingly, we simultaneously consider two variables—service quality and price—while examining the effect of perceived value regarding repurchase intention.
In summary, we use the TPB model to investigate psychological factors in passenger repurchase intention. In particular, we add perceived value to the TPB model while assuming that the value is influenced by price and service quality. In the literature on tourism and airline services, some studies have simultaneously considered the service value factors and individual factors of the TPB model, including attitude and subjective norm [22,23,24,25]. However, thus far, few studies using the entire TPB model have examined the behavioral intention of travelers while simultaneously considering the relationship among price, service quality and value. Based on this extended TPB model, we investigate the direct effects of major factors enclosed in the research model. Ultimately, the purpose of this study is to answer the following research questions (RQs).
  • RQ 1. Which factors directly motivate repurchase intentions for premium economy service?
  • RQ 2. What is the magnitude of the direct impact of critical factors?
The remainder of this paper is structured as follows. Section 2 introduces the basic explanation of premium economy class and related studies. Section 3 explains the theoretical framework of the TPB model with service evaluation variables to support the proposed research model and develops hypotheses. All hypotheses are established by thoroughly reviewing the relevant literature. Section 4 determines the relationship between variables and tests the hypotheses. We also evaluate the validity, reliability and goodness of fit to test the structure of the proposed research model. Section 5 discusses the findings, implications, and future usability of research results. Finally, Section 6 summarizes and concludes this study.

2. Literature Review

2.1. Premium Economy Class

Premium economy class is a mid-level class between economy and business class, introduced by Eva Air and Virgin Atlantic in the early 1990s. Refer to the detailed features in Table 1. Premium economy class is a relatively new airline service that has grown significantly over the last few years. Within the past three years, three major air carriers in the US (DL, AA and UA) began offering premium economy service, and premium economy class has also continued to grow in the Southeast Asian aviation market [26]. At present, 46 airlines provide premium economy service in the world [27], and a considerable number of airlines plan to introduce the service in the near future, especially for long haul flights [2]. These endeavors have benefitted both passengers and airlines. For passengers, the premium economy cabin provides a new option for more comfortable travel experiences at relatively low prices. According to Vink et al. [28], comfort plays a key role in the flight experience and is positively related to future repurchase decision making. In their research, the wide legroom and comfortable seats were strongly associated with the overall comfort of passengers during the flight, and these seat-related comfort factors were rather affordable options in the premium economy class. Thus, a premium economy cabin can be a competitive alternative for business or first class travelers, as well as for leisure travelers who are willing to pay slightly more for comfort [1]. For air carriers, premium economy service makes it possible to manage their services efficiently with limited seat space [1] and to gain a better reputation [29]. As a result, the premium economy service can contribute to increases in airline revenues and price dispersion [7,30]. Although very few studies have analyzed the willingness to pay for premium economy class [2] and the rationale for implementing premium economy class [1], there are still few airline-specific research studies that have examined the overall value of premium economy and the determinants that influence customer purchase intentions.

2.2. Theoretical Background and Hypotheses Development

2.2.1. Theory of Planned Behavior

The theory of planned behavior (TPB) is an extension of the theory of reasoned action [32]. In TPB, an individual’s intention is assumed to be an indicator of the effort or willingness to act, and a strong predictor of actual behavior [32,33]. According to Ajzen [32], personal intention is affected by three psychological factors—attitude, subjective norm and perceived behavioral control (PBC). TPB has been recognized as one of the most prominent theories to understand and predict individual behaviors in various fields such as the food industry [34,35,36], the tourism and hospitality industry [37,38,39] and the acceptance of mobile technology [40]. TPB has also contributed to analyzing passenger intention in aviation industry research, including for low cost carrier (LCC) choice behaviors [10,41], environmental issues [42,43] and safety issues [11].
In TPB, attitude refers to the degree of favorable or unfavorable evaluation toward a specific behavior, which is developed from the belief that the performance of that behavior is likely to lead to a positive or negative outcome [32]. Attitude is developed through past experiences or information, and it represents a general tendency toward a product or service [39]. When the result of a behavior is predicted positively, a favorable attitude is formed, and it strengthens the intention to perform the behavior [32]. In the tourism industry, the influence of traveler attitude regarding intention has been demonstrated in multiple studies [44,45,46,47], and there are also a few studies on the air transport industry [10]. Liou [48] demonstrated that passenger attitude had a positive effect on in-flight shopping intention, and Buaphiban and Truong [10] showed that passenger intention to select LCCs was positively related to attitude. Therefore, we hypothesize that attitude toward premium economy service has a positive effect on the repurchase intention of the premium economy passenger.
Subjective norm is defined as an individual’s psychological tendency to act in response to the expectations of a person or people that influence him/her [32] and can represent social pressure in a broad sense. The impact of the subjective norm on behavioral intention has been well documented in many research topics, including food consumption [36,49,50] and the hospitality industry [51,52,53]. For air travelers, the subjective norm affects passenger decision-making with respect to airline and destination selection [9,39]. In particular, Kim, Kim and Shin [54] examined the reuse of airline websites for B2C e-commerce and found that the subjective norm had a significant impact on passenger intention to reuse. Also, Buaphiban and Truong [10] demonstrated the positive effect of the subjective norm on LCC passenger intention. Therefore, we hypothesize that the subjective norm has a positive effect on the repurchase intention of the premium economy passenger.
PBC refers to the perceived ease or difficulty in performing a specific behavior [32], and it consists of diverse factors that include time, money and information. PBC is an added component in the theory of reasoned action to address a situation in which a behavior is incompletely controlled [55]. According to Ajzen [32], PBC is similar to the self-efficacy suggested by Bandura [56]. Based on the meaning of self-efficacy, the ease of a behavior is a very important factor in performing a given behavior, and it can affect an individual’s decision-making and emotional response [56,57]. For some behaviors, even if a person has a positive attitude and feels social pressure, he/she cannot possess a behavioral intention without sufficient money or knowledge, which is represented by PBC. In this vein, a specified degree of PBC is required to consume the premium economy service. Ajzen [32] suggests that a person with strong PBC is likely to have a positive intention, and we thus hypothesize that PBC has a positive effect on the repurchase intention of the premium economy passenger. Based on the theoretical background discussed above, three hypotheses are established.
Hypothesis 1 (H1).
Attitude positively influences the repurchase intention of the premium economy passenger.
Hypothesis 2 (H2).
Subjective norm positively influences the repurchase intention of the premium economy passenger.
Hypothesis 3 (H3).
Perceived behavioral control positively influences the repurchase intention of the premium economy passenger.

2.2.2. Relationship between Service Evaluation Variables and Behavioral Intention

Perceived price is defined as a monetary or non-monetary (e.g., time, effort) sacrifice from the customer’s perspective [16,58]. In the purchasing process, customers usually compare objective and reference prices and make a decision based on their perception [16,59]. Related studies have demonstrated that a customer’s perception toward price is one of the most significant factors in changing the customer’s behavior [60], decision making [15,16] and customer loyalty [61]. In particular, according to Zeithaml [16], perceived price directly influences the customer’s value perception. In tourism research, Sánchez et al. [62] suggested four functional values—installation, professionalism, perceived quality and perceived price—that affect the perceived value of customers who purchase tourism products. Among the four values, they found that perceived price had the greatest impact on perceived value. In the airline industry, prior studies have emphasized the impact of price in ticket purchasing, with results revealing that an acceptable price positively affects passengers’ perceived value [63,64]. Based on the previous literature, we hypothesize that perceived price positively influences perceived value.
Perceived service quality is explained as a quality level of service determined by customer judgment [16]. Previous studies have suggested that service quality is a strong influencer in the customer decision process [65,66] and is useful to predict perceived value [66,67]. In the air transport industry, perceived service quality refers to the overall performance of a particular airline from the passenger’s perception, including in-flight entertainment, kindness of the cabin crew, seat comfort and so forth. Many researchers have emphasized that service quality is an important factor for airlines to survive [68,69,70,71] and to increase the perceived value of passengers [72,73]. In general, passengers who use or plan to use a premium economy service are likely to expect improved service quality over standard economy class. As a result, we hypothesize that perceived service quality has a positive effect on the perceived value of passengers. In this study, we evaluate the service quality of premium economy class in terms of seat comfort, in-flight service and the overall evaluations of passenger perceptions.
Perceived value refers to a comprehensive evaluation of customers regarding a service based on their experience [16]. In general, perceived value is based upon perceived price and perceived service quality [74]. The trade-off relationship between perceived price and perceived quality is the most important factor when customers make a purchase decision. In previous studies, researchers emphasized this relationship and found that both variables could influence customers’ perceived value. For example, according to Thaler [75], when customers made their decision to buy a product or service, they compared the objective price with their reference price while considering its quality, and their purchase was made when the product (or service) had a valuable utility. The utility represented by perceived value played a critical role in understanding customers’ purchasing behavior [75]. From a similar point of view, Kashyap and Bojanic [17] asserted that perceived value was measured through an assessment of the trade-off relationship between price and quality, and the customer’s value provided a summary of the overall experience. Chang and Wildt [15] demonstrated that perceived price and perceived quality led to perceived value, and the perceived value motivated the purchase intention of customers. In addition, Petrick [76] found that perceived value could affect the decision to revisit the same destination or repurchase similar products. In the tourism and aviation management fields, many studies have demonstrated that perceived value has an impact on customer’s behavioral intention [77,78,79,80,81] and that the price and service quality of air carriers significantly affects the purchase decisions of customers and their perceived value [82,83]. In particular, Chen, Li and Liu [84] found that a passenger’s perceived value had a critical impact on repurchase intention, and Yang et al. [73] also asserted that a passenger’s repurchase intention was essentially based on perceived value. Because premium economy class passengers pay more and expect higher service quality, their perceived value through price and quality is expected to be a crucial factor in their repurchase intention. The TPB is open to adding additional variables [32], and proper additional constructs might improve the predictive power of the TPB [85]. Therefore, perceived price, perceived service quality and perceived value are added as external variables, and three hypotheses are established based on the theoretical background. Figure 1 represents the proposed research model.
Hypothesis 4 (H4).
Perceived price positively influences the perceived value of premium economy passenger.
Hypothesis 5 (H5).
Perceived service quality positively influences the perceived value of premium economy passenger.
Hypothesis 6 (H6).
Perceived value positively influences the repurchase intention of premium economy passenger.

3. Methodology

Data Collection and Analytical Method

The survey data were collected both airside and landside in two major Korean international airports—Incheon and Gimpo—from 11 to 26 February 2019. Items on the questionnaire were designed based on the related literature discussed above. The questionnaire was pre-tested by 30 people and revised properly to ensure content validity. The questions were refined based on interviewers’ feedback and opinions regarding the questionnaire. Using the 30 samples, the Cronbach’s alpha values were obtained and ranged from 0.752 to 0.878, exceeding the recommended value. The finalized version of the questionnaire was composed of eight questions for demographic and travel-related characteristics, and 21 questions for seven constructs. In the seven parts used for construct measurements, parts 1 to 3 measured the three psychological factors of the TPB, parts 4 to 6 examined the perceived price, perceived service quality and perceived value, respectively, of the premium economy class, and part 7 investigated the repurchase intention of the passengers. All questionnaire items were measured using a 5-point-Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). The survey was conducted face-to-face with passengers who had experienced premium economy service at least once. A total of 382 usable responses were collected. Because premium economy service accounts for the smallest portion of the seating capacity in an airline service despite its strong tendency toward growth (e.g., 6% for Singapore Airlines [86]), about 40% of the survey data were collected airside at airports (with assistance from those airports) to increase the sample sizes and expedite sampling speed. Demographic and travel-related information is displayed in Table 2. There were slightly more males (56%) than females (44%), and the majority of respondents ranged in age from 20–29 (30%) and 30–39 (35%). In addition, most respondents (65%) had experienced premium economy service within one year from the moment they responded to the survey.
We statistically examined whether the collected data were representative of the air travel population. Compared to the 2018 Global Passenger Survey (n = 10,408) conducted by the IATA [87], this sample was good at representing the demographic characteristics of the global air travel population. We conducted paired sample t-tests for the critical demographic variables (i.e., age and gender portions) between sample and population groups and there was no statistically significant difference in the critical demographics between groups. Refer to the test results summarized in Table 3.
Figure 2 shows the home regions of the respondents and the airlines they experienced. The left panel indicates the home regions of airlines. The Asian region consists of eight airlines in seven countries—BR (Taiwan), CI (China), CX (Hong Kong), CZ (China), NH (Japan), OZ (Korea), SQ (Singapore) and VN (Vietnam). Europe includes eight airlines in eight countries—AF (France), AY (Finland), AZ (Italy), BA (United Kingdom), KL (The Netherlands), LH (Germany), LO (Poland) and SU (Russia). The Americas contain four airlines in two countries—AA (US), AC (Canada), DL (US) and UA (US). Oceania includes two airlines in two countries—NZ (New Zealand) and VA (Australia). The right panel shows the home regions of the respondents. Asia includes six countries—China, Japan, Korea, the Philippines, Singapore and Thailand. Europe includes six countries—France, Germany, Greece, Italy, Russia and the United Kingdom. The Americas contain three countries—Brazil, Canada and the US. Oceania includes one country—Australia.
Before testing hypotheses in the research model, we conducted one-way ANOVA tests for seven constructs to determine whether there was any statistically significant difference in average Likert ratings between the groups with different demographic and travel-related characteristics. From the test results, we were able to find a statistical difference between the income levels (in PBC and perceived price), period of most recent experience (in repurchase intention), and home regions of airlines (in attitude and repurchase intention). From the further statistical tests for all possible combinations of two groups, passengers who earn more than $4000 a month indicated a more positive PBC and perceived price for premium economy service. Customers who have experienced the service within 6 months reported a more positive repurchase intention. Also, passengers using airlines housed in Asia and Oceania indicated a more positive attitude and repurchase intention. However, we could not find any statistical difference between the gender, travel purpose, occupation, and home regions of respondents based on the ANOVA. Refer to the one-way ANOVA test results summarized in Table 4.
In this study, we used structural equation modelling (SEM), which describes the relationship between observed variables and test hypotheses [88]. We also employed Cronbach’s alpha coefficient [89] to assess reliability through internal consistency. Internal consistency is a concept that determines whether all items in the questionnaire measure the same attribution or configuration, and high internal consistency can prove proper reliability [90]. The data analysis was performed using IBM SPSS AMOS 24 [91].

4. Results

4.1. Measurement Model

A confirmatory factor analysis (CFA) was performed to assess the construct and test the validity and reliability of the measurement model. Before performing the CFA, we checked normality for the Likert scales using skewness and kurtosis criteria, and the normality assumption was satisfied [92]. Convergent validity is evaluated by using standardized factor loading and the average variance extracted (AVE). To ensure convergent validity, all factor loadings should be greater than 0.70 and the AVE should be greater than 0.50 [93]. The factor loadings of the items in our research model varied from 0.754 to 0.945, and all AVEs exceeded the recommended threshold, ranging between 0.688 and 0.810. The outcomes satisfied the proper degree of convergent validity. The model reliability was evaluated via composite reliability and Cronbach’s alpha. It is recommended that the composite reliability should exceed 0.7 and the proper value for Cronbach’s alpha should also exceed 0.7. As shown in Table 5, all composite reliability values exceeded 0.95 (except for one, which came to 0.949). The Cronbach’s alpha values ranged from 0.869 to 0.943, exceeding the recommended value. The results satisfied the proper degree of reliability. Discriminant validity was assessed by comparing AVEs to the square of inter-construct correlations. All squared values of inter-construct correlation should be lower than the AVE values [93]. As shown in Table 6, all AVE values exceeded the square values of inter-construct correlation, and this ensured discriminant validity.

4.2. Strucural Model

The structural model analysis consists of checking the model fit and testing the hypotheses. The results show that almost all of the goodness of fit indicators are included in their acceptable ranges except the GFI value [94]: χ 2 = 495.240 (df = 171, p = 0.000); GFI = 0.895 (recommended > 0.90); CFI = 0.953 (recommended > 0.95); NFI = 0.930 (recommended > 0.90); χ 2 /df = 2.896 (recommended < 3); RMSEA = 0.071 (recommended < 0.08). The results suggest that the research model fits well. The results of the hypothesis tests are summarized in Table 7. H1 and H3 are supported, but H2 is not supported. This shows that among the three psychological factors of the TPB model, attitude and PBC positively influence the repurchase intention of the premium economy passenger while subjective norm does not; standardized coefficient of attitude = 0.449 (p < 0.001), standardized coefficient of PBC = 0.204 (p < 0.001), standardized coefficient of subjective norm = 0.113 (p = 0.161). This suggests that positive attitude and a high PBC value can increase the intention to repurchase premium economy class.
H4, H5 and H6 are all supported. That is, the perceived price and perceived service quality are statistically significant, and they positively influence perceived value; standardized coefficient of perceived price = 0.306 (p < 0.001), standardized coefficient of perceived service quality = 0.600 (p < 0.001). Among the variables affecting repurchase intention, perceived value has the most significant influence—standardized coefficient is 0.469 (p < 0.001). The results suggest that positively perceived price and quality increase passengers’ perceived value, and passengers who believe that premium economy service provides a valuable experience have a positive repurchase intention. Figure 3 depicts the results of the relationships among all the constructs.

5. Discussion

5.1. Impact of Psychological Factors in TPB Regarding Repurchase Intention

The results of this study show that passenger attitude and PBC have a positive effect on the repurchase intention of premium economy passengers. Attitude is the second most significant motivator (0.449) among the components of the proposed TPB model. This result indicates that if passengers have positive thoughts and emotions toward premium economy class, they will be more likely to choose premium economy service as their travel mode. PBC also has a positive effect on repurchase intention for premium economy class (0.204), indicating that a passenger’s intention to repurchase that class will increase when the passenger feel that he/she can control the relevant conditions when using premium economy class. The slightly more expensive fare level of premium economy class (compared to that of standard economy class) prompts passengers to consider their financial capabilities, which is potentially a critical PBC attribute [95]. Therefore, passengers who believe that the premium economy class fare is affordable will be more likely to choose that class.
Subjective norm does not have a significant impact in this study. This suggests that premium economy passengers are less sensitive to external recommendations and tend to voluntarily decide whether to use the service. To understand this result, it should be noted that premium economy class is the least common airline service with respect to the capacity volume and time duration in which the service has been introduced. To be influenced by subjective norm, a passenger should obtain prior recommendations or information from people around him/her while having experienced premium economy service. However, premium economy seats account for a very restricted portion of total airline seats and only a small number of air carriers operate premium economy service despite the increasing trend. Also, premium economy class is currently applied to specific aircrafts and long-haul routes with limited resources. As a result, premium economy service is still not as prevalent as other services, and, in addition, the related information is not as widespread as the information for other classes. Because the number of passengers that have experienced the service is still not large compared to the number of airline passengers, it is relatively difficult to gain information or recommendations from individuals who have experienced premium economy class.

5.2. Impact of Service Evaluation Variables Regarding Repurchase Intention

In this study, both perceived price and service quality have a positive impact on perceived value, and perceived value is the most influential factor in predicting a passenger’s intention to repurchase. The results are consistent with previous studies that have shown that perceived value is an antecedent in understanding behavioral intention [15,16,66,77] and that perceived value is influenced by price and quality [16,64,83]. The results show that premium economy passengers evaluate price and service quality simultaneously through their experience, and their intention to repurchase will increase when they think premium economy service is well worth experiencing. Perceived service quality is almost twice as important as perceived price while having an impact on the perceived value of premium economy passengers. This finding indicates that premium economy passengers would consider service quality first when evaluating the overall value of premium economy service. The finding is consistent with previous studies that have emphasized the effect of service quality on a customer’s value [77,78]. Perceived price also demonstrates a positive effect on the perceived value of premium economy passengers. The results suggest that if a passenger thinks that the fare for premium economy class is affordable, the passenger will be more likely to recognize the value of the service.

5.3. Practical Implications

Despite successful applications of the premium economy service class, there is a paucity of studies regarding premium economy class in the air transport literature. Within the restricted selection of previous research, most studies have focused on the rationality of premium economy class implementation and customer willingness to pay [1,2]. On the contrary, research regarding the behavioral intention of passengers has not been significantly carried out thus far. By proposing an extended TPB model, this study endeavors to comprehend the premium economy passenger’s perception and psychological factors that influence the intention to repurchase.
As the demand for premium economy class increases, an appropriate design and continuing improved updates for the service are very important to enhance the sustainable profitability of airlines. In fact, continuous improvements should be carried out as a prerequisite for service sustainability. This study offers some managerial implications for airlines to strengthen the repurchase intention of the premium economy passenger. Perceived value has the most significant impact on the repurchase intention of the premium economy passenger while being simultaneously affected by price and service quality. Thus, airlines should design and deliver their premium economy class to enable passengers to feel that they are treated with respect, as well as to feel satisfied from boarding to deplaning. For example, cabin crews should strive to instantly resolve inconveniences to maintain a proper degree of service quality. At the same time, a strategic balance between service quality and price is needed to create higher value. When pricing, it is certainly natural to consider acceptable price ranges from the passenger point of view to encourage continuous purchases. Through such efforts, airlines can convey the impression that passengers will encounter a more valuable flight experience in relation to the price they pay for that service experience. In terms of TPB variables, the attitude and PBC had significant impacts on repurchase intention. Therefore, airlines should deploy marketing strategies to improve their reputations and convey favorable images to passengers. Also, airlines should provide reasonable prices and offer active promotions to elicit the passenger belief that the selection of premium economy class is totally within their control. Such efforts would sustain passengers’ intention to repurchase premium economy class, and they might also increase customer loyalty. A strongly unified structure of customer satisfaction and loyalty guarantees business sustainability [8].

6. Summary and Conclusions

The increasing demand for more comfortable travel options has prompted airlines to strive to offer higher service quality at lower prices and thereby increase competitiveness. Premium economy class represents one of these efforts to balance the trade-off between two essential values—quality and price. Although air carriers have successfully implemented the premium economy class, the (re)purchase intention of premium economy passengers has not been frequently investigated in the related literature. Our research proposed an extended TPB model by adding perceived value derived from perceived price and perceived service quality as external variables to investigate passenger perception. Although there are some research results that simultaneously consider the service value factors and individual factors of the TPB model such as attitude and subjective norm, very few studies have combined service value factors into the entire TPB model while examining the behavioral intention of travelers in tourism and airline service research. Based on the proposed TPB model, we were able to determine the major motivators of passenger repurchase intentions and estimate the magnitude of the direct impact of those motivators. The results show that both perceived price and perceived service quality can increase perceived value, and high perceived value can strongly influence repurchase intention. Among the TPB variables, attitude and PBC also have a positive effect on repurchase intention, whereas the effect of subjective norm is not statistically significant.
The proposed model was tested by using face-to-face surveyed data from 382 passengers who had experienced premium economy class. Because we collected data from respondents and airlines from a diverse range of countries (16 traveler nationalities and 19 airline nationalities), the data might exclude the effect of cultural and social characteristics from specific regions. Also, the data covers almost half (22 among 46) of the airlines that currently offer premium economy class despite the dominance of Asia and Europe.
According to Hugon-Duprat and O’connell [1], premium economy class has shown steady growth while standard economy class is stagnant. To realize the competitive advantages of premium economy class, Kuo and Jou [2] highlighted that airlines need to understand the factors that affect a traveler’s choice to select premium economy class. To ensure sustainable profitability and manageability, it is important to analyze passenger perceptions and determine the psychological motivators that influence decision-making. The findings of this study can help practitioners to specifically understand the relationship between factors that have a positive impact on repurchase intention. Also, the findings can provide insights for airlines to increase customer loyalty and develop their premium economy class as a sustainable service. In addition, the proposed research model was well structured to sufficiently explain the repurchase intentions of passengers while producing suitable values for model validity, reliability and goodness of fit.
We finalize this study by stating a few research limitations. First, because we have evaluated service quality through only three attributes (i.e., seat comfort, in-flight service and overall service quality), it is necessary to expand the number and/or coverage of service quality attributes to provide more precise measurements. Second, we have defined that subjective norm, which has been proved to be statistically insignificant, was influenced by familiar relationships such as family and friends in this study. However, if we stretch the meaning of the variable to encompass a wider scope of social pressure [32], the range of referents affecting subjective norm would also be widened to unspecified individuals in society as well as individually close relationships to better understand the effect of social influence. In this vein, future studies using social media and big data are highly recommended. For instance, Jailivand and Samiei [96] conducted an empirical study with tourists who had used travel reviews as an information source and found that electronic word of mouth (eWOM) could influence all TPB variables. Although lots of studies have looked at the tourism and hotel businesses using online reviews (see, e.g., [97,98,99,100,101,102], and the references therein), research in the air transportation industry still has substantial growth potential [103,104,105,106]. Finally, we investigated the repurchase intention of only experienced passengers in this study. It is plausible to examine passenger purchase intention while dealing with the general public, including unexperienced customers, as another future avenue of research.

Author Contributions

Conceptualization, J.H.K. and H.C.L.; methodology, J.H.K. and H.C.L.; software, J.H.K.; validation, J.H.K. and H.C.L.; formal analysis, J.H.K. and H.C.L.; investigation, J.H.K. and H.C.L.; resources, H.C.L.; data curation, J.H.K.; writing—original draft preparation, J.H.K. and H.C.L.; writing—review and editing, J.H.K. and H.C.L.; visualization, J.H.K.; supervision, H.C.L.; project administration, H.C.L.

Funding

This research received no external funding.

Acknowledgments

The authors would like to thank Taejin Shin at Incheon international airport and Min-chul Jeong at Gimpo international airport for their special assistance in surveys.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hugon-Duprat, C.; O’Connell, J.F. The rationale for implementing a premium economy class in the long haul markets—Evidence from the transatlantic market. J. Air Transp. Manag. 2015, 47, 11–19. [Google Scholar] [CrossRef]
  2. Kuo, C.W.; Jou, R.C. Willingness to pay for airlines’ premium economy class: The perspective of passengers. J. Air Transp. Manag. 2017, 59, 134–142. [Google Scholar] [CrossRef]
  3. Carlson Wagonlit Travel. Available online: https://news.carlsonwagonlit.com/pressreleases/cwt-slash-travelport-research-premium-economy-a-hot-ticket-for-singapore-business-travelers-2547807 (accessed on 26 April 2019).
  4. Doganis, R. Flying off Course: Airline Economics and Marketing, 4th ed.; Routledge: London, UK, 2010; ISBN 0415447372. [Google Scholar]
  5. Balcombe, K.; Fraser, I.; Harris, L. Consumer willingness to pay for in-flight service and comfort levels: A choice experiment. J. Air Transp. Manag. 2009, 15, 221–226. [Google Scholar] [CrossRef]
  6. Espino, R.; Martín, J.C.; Román, C. Analyzing the effect of preference heterogeneity on willingness to pay for improving service quality in an airline choice context. Transp. Res. Part E Logist. Transp. Rev. 2008, 44, 593–606. [Google Scholar] [CrossRef]
  7. Lee, D.; Luengo-Prado, M.J. Are passengers willing to pay more for additional legroom? J. Air Transp. Manag. 2004, 10, 377–383. [Google Scholar] [CrossRef]
  8. Eklof, J.A.; Westlund, A. Customer satisfaction index and its role in quality management. Total Qual. Manag. 1998, 9, 80–85. [Google Scholar] [CrossRef]
  9. Ruiz-Mafe, C.; Sanz-Blas, S.; Hernandez-Ortega, B.; Brethouwer, M. Key drivers of consumer purchase of airline tickets: A cross-cultural analysis. J. Air Transp. Manag. 2013, 27, 11–14. [Google Scholar] [CrossRef]
  10. Buaphiban, T.; Truong, D. Evaluation of passengers’ buying behaviors toward low cost carriers in Southeast Asia. J. Air Transp. Manag. 2017, 59, 124–133. [Google Scholar] [CrossRef]
  11. Chang, Y.C. Cabin safety behavioral intentions of passengers with reduced mobility. J. Air Transp. Manag. 2012, 25, 64–66. [Google Scholar] [CrossRef]
  12. Cheng, S.; Lam, T.; Hsu, C.H. Testing the sufficiency of the theory of planned behavior: A case of customer dissatisfaction responses in restaurants. Int. J. Hosp Manag. 2005, 24, 475–492. [Google Scholar] [CrossRef]
  13. Quintal, V.A.; Lee, J.A.; Soutar, G.N. Risk, uncertainty and the theory of planned behavior: A tourism example. Tour. Manag. 2010, 31, 797–805. [Google Scholar] [CrossRef]
  14. Teng, Y.M.; Wu, K.S.; Liu, H.H. Integrating altruism and the theory of planned behavior to predict patronage intention of a green hotel. J. Hosp. Tour. Res. 2015, 39, 299–315. [Google Scholar] [CrossRef]
  15. Chang, T.Z.; Wildt, A.R. Price, product information, and purchase intention: An empirical study. J. Acad. Mark. Sci. 1994, 22, 16–27. [Google Scholar] [CrossRef]
  16. Zeithaml, V.A. Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. J. Mark. 1988, 52, 2–22. [Google Scholar] [CrossRef]
  17. Kashyap, R.; Bojanic, D.C. A Structural analysis of value, quality, and price perceptions of business and leisure travelers. J. Travel Res. 2000, 39, 45–51. [Google Scholar] [CrossRef]
  18. Oh, H. Price fairness and its asymmetric effects on overall price, quality, and value judgments: The case of an upscale hotel. Tour. Manag. 2003, 24, 387–399. [Google Scholar] [CrossRef]
  19. Beneke, J.; Flynn, R.; Greig, T.; Mukaiwa, M. The influence of perceived product quality, relative price and risk on customer value and willingness to buy: A study of private label merchandise. J. Prod. Brand Manag. 2013, 22, 218–228. [Google Scholar] [CrossRef]
  20. The New York Times. Available online: https://www.nytimes.com/2018/11/09/travel/how-much-are-you-willing-to-pay-for-a-few-extra-inches-of-legroom.html (accessed on 26 April 2019).
  21. IATA Annual Review 2017. Available online: https://www.iata.org/publications/Documents/iata-annual-review-2017.pdf (accessed on 26 April 2019).
  22. Gardiner, S.; King, C.; Grace, D. Travel decision making: An empirical examination of generational values, attitudes, and intentions. J. Travel Res. 2013, 52, 310–324. [Google Scholar] [CrossRef]
  23. Zhu, G.; Sangwan, S.; Lu, T.J. A new theoretical framework of technology acceptance and empirical investigation on self-efficacy-based value adoption model. Nankai Bus. Rev. Int. 2010, 1, 345–372. [Google Scholar] [CrossRef]
  24. Zhu, G.; So, K.K.F.; Hudson, S. Inside the sharing economy Understanding consumer motivations behind the adoption of mobile applications. Int. J. Contemp. Hosp. Manag. 2017, 29, 2218–2239. [Google Scholar] [CrossRef]
  25. Ozturk, A.B.; Nusair, K.; Okumus, F.; Hua, N. The role of utilitarian and hedonic values on users’ continued usage intention in a mobile hotel booking environment. Int. J. Hosp. Manag. 2016, 57, 106. [Google Scholar] [CrossRef]
  26. CAPA. Available online: https://centreforaviation.com/analysis/reports/premium-economy-thai-airways-considers-joining-the-growing-trend-428540 (accessed on 26 April 2019).
  27. SeatGuru. Available online: https://www.seatguru.com/charts/premium_economy.php#key (accessed on 26 April 2019).
  28. Vink, P.; Bazley, C.; Kamp, I.; Blok, M. Possibilities to improve the aircraft interior comfort experience. Appl. Ergon. 2012, 43, 354–359. [Google Scholar] [CrossRef] [PubMed]
  29. Niţă, M.F.; Scholz, D. Business opportunities in aircraft cabin conversion and refurbishing. J. Aerosp. Oper. 2011, 1, 129–153. [Google Scholar] [CrossRef]
  30. Cui, Y.; Orhun, A.Y.; Duenyas, I. How price dispersion changes when upgrades are introduced: Theory and empirical evidence from the airline industry. Manag. Sci. 2018. [Google Scholar] [CrossRef]
  31. Skytrax. Available online: https://www.worldairlineawards.com/worlds-best-airline-premium-economy-class-2018/ (accessed on 26 April 2019).
  32. Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
  33. Sheppard, B.H.; Hartwick, J.; Warshaw, P.R. The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. J. Consum. Res. 1988, 15, 325–343. [Google Scholar] [CrossRef]
  34. Kassem, N.O.; Lee, J.W.; Modeste, N.N.; Johnston, P.K. Understanding soft drink consumption among female adolescents using the Theory of Planned Behavior. Health Educ. Res. 2003, 18, 278–291. [Google Scholar] [CrossRef] [Green Version]
  35. Tarkiainen, A.; Sundqvist, S. Subjective norms, attitudes and intentions of Finnish consumers in buying organic food. Br. Food J. 2005, 107, 808–822. [Google Scholar] [CrossRef] [Green Version]
  36. Shah Alam, S.; Mohamed Sayuti, N. Applying the Theory of Planned Behavior (TPB) in halal food purchasing. Int. J. Commer. Manag. 2011, 21, 8–20. [Google Scholar] [CrossRef]
  37. Bianchi, C.; Milberg, S.; Cúneo, A. Understanding travelers’ intentions to visit a short versus long-haul emerging vacation destination: The case of Chile. Tour. Manag. 2017, 59, 312–324. [Google Scholar] [CrossRef]
  38. Kim, Y.; Han, H. Intention to pay conventional-hotel prices at a green hotel—A modification of the theory of planned behavior. J. Sustain. Tour. 2010, 18, 997–1014. [Google Scholar] [CrossRef]
  39. Lam, T.; Hsu, C.H. Predicting behavioral intention of choosing a travel destination. Tour. Manag. 2006, 27, 589–599. [Google Scholar] [CrossRef]
  40. Pedersen, P.E. Adoption of mobile internet services: An exploratory study of mobile commerce early adopters. J. Organ. Comput. Electron. Commer. 2005, 15, 203–222. [Google Scholar] [CrossRef]
  41. Borhan, M.N.; Ibrahim, A.N.H.; Miskeen, M.A.A.; Rahmat, R.A.O.K.; Alhodairi, A.M. Predicting car drivers’ intention to use low cost airlines for intercity travel in Libya. J. Air Transp. Manag. 2017, 65, 88–98. [Google Scholar] [CrossRef]
  42. van Birgelen, M.; Semeijn, J.; Behrens, P. Explaining pro-environment consumer behavior in air travel. J. Air Transp. Manag. 2011, 17, 125–128. [Google Scholar] [CrossRef] [Green Version]
  43. Davison, L.; Littleford, C.; Ryley, T. Air travel attitudes and behaviours: The development of environment-based segments. J. Air Transp. Manag. 2014, 36, 13–22. [Google Scholar] [CrossRef] [Green Version]
  44. Hsu, C.H.; Cai, L.A.; Li, M. Expectation, motivation, and attitude: A tourist behavioral model. J. Travel Res. 2010, 49, 282–296. [Google Scholar] [CrossRef]
  45. Lee, T.H. A structural model to examine how destination image, attitude, and motivation affect the future behavior of tourists. Leis. Sci. 2009, 31, 215–236. [Google Scholar] [CrossRef]
  46. Um, S.; Crompton, J.L. Attitude determinants in tourism destination choice. Ann. Tour. Res. 1990, 17, 432–448. [Google Scholar] [CrossRef]
  47. Jalilvand, M.R.; Samiei, N.; Dini, B.; Manzari, P.Y. Examining the structural relationships of electronic word of mouth, destination image, tourist attitude toward destination and travel intention: An integrated approach. J. Destin. Mark. Manag. 2012, 1, 134–143. [Google Scholar] [CrossRef]
  48. Liou, J.J. Consumer attitudes toward in-flight shopping. J. Air Transp. Manag. 2011, 17, 221–223. [Google Scholar] [CrossRef]
  49. Al-Swidi, A.; Mohammed Rafiul Huque, S.; Haroon Hafeez, M.; Noor Mohd Shariff, M. The role of subjective norms in theory of planned behavior in the context of organic food consumption. Br. Food J. 2014, 116, 1561–1580. [Google Scholar] [CrossRef]
  50. Kim, H.Y.; Chung, J.E. Consumer purchase intention for organic personal care products. J. Consum. Market. 2011, 1, 40–47. [Google Scholar] [CrossRef]
  51. Han, H.; Hsu, L.T.J.; Sheu, C. Application of the theory of planned behavior to green hotel choice: Testing the effect of environmental friendly activities. Tour. Manag. 2010, 31, 325–334. [Google Scholar] [CrossRef]
  52. Hsu, M.S. A study of internship attitude, subjective norm, perceived behavioral control, and career planning of hospitality vocational college students. J. Hosp. Leis. Sport Tour. Educ. 2012, 11, 5–11. [Google Scholar] [CrossRef]
  53. Kaushik, A.K.; Agrawal, A.K.; Rahman, Z. Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents. Tour. Manag. Perspect. 2015, 16, 278–289. [Google Scholar] [CrossRef]
  54. Kim, H.B.; Kim, T.T.; Shin, S.W. Modeling roles of subjective norms and eTrust in customers’ acceptance of airline B2C eCommerce websites. Tour. Manag. 2009, 30, 266–277. [Google Scholar] [CrossRef]
  55. Ajzen, I. Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. J. Appl. Soc. Psychol. 2002, 32, 665–683. [Google Scholar] [CrossRef]
  56. Bandura, A. Self-efficacy: Toward a unifying theory of behavioral change. Adv. Behav. Res. Ther. 1978, 1, 139–161. [Google Scholar] [CrossRef]
  57. de Vries, H.; Dijkstra, M.; Kuhlman, P. Self-efficacy: The third factor besides attitude and subjective norm as a predictor of behavioural intentions. Health Educ. Res. 1988, 3, 273–282. [Google Scholar] [CrossRef]
  58. Lichtenstein, D.R.; Bloch, P.H.; Black, W.C. Correlates of price acceptability. J. Consum. Res. 1988, 15, 243–252. [Google Scholar] [CrossRef]
  59. Dickson, P.R.; Sawyer, A.G. The price knowledge and search of supermarket shoppers. J. Mark. 1990, 54, 42–53. [Google Scholar] [CrossRef]
  60. Keaveney, S.M. Customer switching behavior in service industries: An exploratory study. J. Mark. 1995, 59, 71–82. [Google Scholar] [CrossRef]
  61. Anuwichanont, J. The impact of price perception on customer loyalty in the airline context. J. Bus. Econ. Res. 2011, 9, 37–50. [Google Scholar] [CrossRef]
  62. Sánchez, J.; Callarisa, L.; Rodríguez, R.M.; Moliner, M.A. Perceived value of the purchase of a tourism product. Tour. Manag. 2006, 27, 394–409. [Google Scholar] [CrossRef]
  63. Yu, S.F. Price perception of online airline ticket shoppers. J. Air Transp. Manag. 2008, 14, 66–69. [Google Scholar] [CrossRef]
  64. Liu, C.H.S.; Lee, T. Service quality and price perception of service: Influence on word-of-mouth and revisit intention. J. Air Transp. Manag. 2016, 52, 42–54. [Google Scholar] [CrossRef]
  65. Zeithaml, V.A.; Berry, L.L.; Parasuraman, A. The behavioral consequences of service quality. J. Mark. 1996, 60, 31–46. [Google Scholar] [CrossRef]
  66. Cronin, J.J.; Brady, M.K.; Hult, G.T.M. Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. J. Retail. 2000, 76, 193–218. [Google Scholar] [CrossRef]
  67. Parasuraman, A.; Grewal, D. The impact of technology on the quality-value-loyalty chain: A research agenda. J. Acad. Mark. Sci. 2000, 28, 168–174. [Google Scholar] [CrossRef]
  68. Chen, F.; Chang, Y. Examining airline service quality from a process perspective. J. Air Transp. Manag. 2005, 11, 79–87. [Google Scholar] [CrossRef]
  69. Chou, C.C.; Liu, L.J.; Huang, S.F.; Yih, J.M.; Han, T.C. An evaluation of airline service quality using the fuzzy weighted SERVQUAL method. Appl. Soft Comput. 2011, 11, 2117–2128. [Google Scholar] [CrossRef]
  70. Ostrowski, P.L.; O’Brien, T.V.; Gordon, G.L. Service quality and customer loyalty in the commercial airline industry. J. Travel Res. 1993. [Google Scholar] [CrossRef]
  71. Park, J.W.; Robertson, R.; Wu, C.L. The effect of airline service quality on passengers’ behavioural intentions: A Korean case study. J. Air Transp. Manag. 2004, 10, 435–439. [Google Scholar] [CrossRef]
  72. Woo, M. Assessing customer citizenship behaviors in the airline industry: Investigation of service quality and value. J. Air Transp. Manag. 2019, 76, 40–47. [Google Scholar] [CrossRef]
  73. Yang, K.C.; Hsieh, T.C.; Li, H.; Yang, C. Assessing how service quality, airline image and customer value affect the intentions of passengers regarding low cost carriers. J. Air Transp. Manag. 2012, 20, 52–53. [Google Scholar] [CrossRef]
  74. Woodruff, R.B. Customer value: The next source for competitive advantage. J. Acad. Mark. Sci. 1997, 25, 139. [Google Scholar] [CrossRef]
  75. Thaler, R. Mental accounting and consumer choice. Mark. Sci. 1985, 4, 199–214. [Google Scholar] [CrossRef]
  76. Petrick, J.F. The roles of quality, value and satisfaction in predicting cruise passengers’ behavioral intentions. J. Travel Res. 2004, 42, 397–407. [Google Scholar] [CrossRef]
  77. Chen, C.F. Investigating structural relationships between service quality, perceived value, satisfaction, and behavioral intentions for air passengers: Evidence from Taiwan. Transp. Res. Part. A Policy Pract. 2008, 42, 709–717. [Google Scholar] [CrossRef]
  78. Chen, C.F.; Chen, F.S. Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists. Tour. Manag. 2010, 31, 29–35. [Google Scholar] [CrossRef]
  79. Fu, Y.; Liu, X.; Wang, Y.; Chao, R.F. How experiential consumption moderates the effects of souvenir authenticity on behavioral intention through perceived value. Tour. Manag. 2018, 69, 356–367. [Google Scholar] [CrossRef]
  80. Kim, Y. Assessing the effects of perceived value (utilitarian and hedonic) in LCCs and FSCs: Evidence from South Korea. J. Air Transp. Manag. 2015, 49, 17–22. [Google Scholar] [CrossRef]
  81. Ponte, E.B.; Carvajal-Trujillo, E.; Escobar-Rodríguez, T. Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents. Tour. Manag. 2015, 47, 286–302. [Google Scholar] [CrossRef]
  82. Pan, J.Y.; Truong, D. Passengers’ intentions to use low-cost carriers: An extended theory of planned behavior model. J. Air Transp. Manag. 2018, 69, 38–48. [Google Scholar] [CrossRef]
  83. Rajaguru, R. Role of value for money and service quality on behavioural intention: A study of full service and low cost airlines. J. Air Transp. Manag. 2016, 53, 114–122. [Google Scholar] [CrossRef]
  84. Chen, L.; Li, Y.Q.; Liu, C.H. How airline service quality determines the quantity of repurchase intention—Mediate and moderate effects of brand quality and perceived value. J. Air Transp. Manag. 2019, 75, 185–197. [Google Scholar] [CrossRef]
  85. Conner, M.; Abraham, C. Conscientiousness and the theory of planned behavior: Toward a more complete model of the antecedents of intentions and behavior. Personal. Soc. Psychol. Bull. 2001, 27, 1547–1561. [Google Scholar] [CrossRef]
  86. CAPA. Available online: https://centreforaviation.com/analysis/reports/sias-premium-economy-attractive-for-corporate-travel-422884 (accessed on 26 April 2019).
  87. IATA Global Passenger Survey 2018. Available online: https://www.iata.org/publications/store/Pages/global-passenger-survey.aspx (accessed on 26 April 2019).
  88. Lomax, R.G.; Schumacker, R.E. A Beginner’s Guide to Structural Equation Modeling, 2nd ed.; Lawrence Erlbaum Associates: Mahwah, NJ, USA, 2004; ISBN 0805840176. [Google Scholar]
  89. Cronbach, L.J. Coefficient alpha and the internal structure of tests. Psychometrika 1951, 16, 297–334. [Google Scholar] [CrossRef] [Green Version]
  90. Streiner, D.L. Starting at the beginning: An introduction to coefficient alpha and internal consistency. J. Pers. Assess. 2003, 80, 99–103. [Google Scholar] [CrossRef]
  91. Arbuckle, J.L. Amos (Version 24.0) [Computer Program]; IBM SPSS: Chicago, IL, USA, 2016. [Google Scholar]
  92. Kline, R. Structural Equation Modeling, 3rd ed.; Guilford: New York, NY, USA, 2011. [Google Scholar]
  93. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  94. Hair, J.F.; Anderson, R.E.; Tatham, R.L.; Black, W.C. Multivariate Data Analysis; Prentice-Hall: Upper Saddle River, NJ, USA, 1998. [Google Scholar]
  95. Sahni, A. Incorporating perceptions of financial control in purchase prediction: An empirical examination of the theory of planned behavior. In Advances in Consumer Research; Allen, C.T., John, D.R., Eds.; Association for Consumer Research: Provo, UT, USA, 1994; Volume 21, pp. 442–448. [Google Scholar]
  96. Jalilvand, M.R.; Samiei, N. The impact of electronic word of mouth on a tourism destination choice. Internet Res. 2012, 22, 591–612. [Google Scholar] [CrossRef]
  97. Archak, N.; Ghose, A.; Ipeirotis, P.G. Deriving the pricing power of product features by mining consumer reviews. Manag. Sci. 2011, 57, 1485–1509. [Google Scholar] [CrossRef]
  98. Berezina, K.; Bilgihan, A.; Cobanoglu, C.; Okumus, F. Understanding satisfied and dissatisfied hotel customers: Text mining of online hotel reviews. J. Hosp. Mark. Manag. 2016, 25, 1–24. [Google Scholar] [CrossRef]
  99. Mankad, S.; Han, H.S.; Goh, J.; Gavirneni, S. Understanding online hotel reviews through automated text analysis. Serv. Sci. 2016, 8, 124–138. [Google Scholar] [CrossRef]
  100. O’connor, P. Managing a hotel’s image on TripAdvisor. J. Hosp. Mark. Manag. 2010, 19, 754–772. [Google Scholar] [CrossRef]
  101. Vermeulen, I.E.; Seegers, D. Tried and tested: The impact of online hotel reviews on consumer consideration. Tour. Manag. 2009, 30, 123–127. [Google Scholar] [CrossRef]
  102. Sparks, B.A.; Browning, V. The impact of online reviews on hotel booking intentions and perception of trust. Tour. Manag. 2011, 32, 1310–1323. [Google Scholar] [CrossRef] [Green Version]
  103. Gitto, S.; Mancuso, P. Improving airport services using sentiment analysis of the websites. Tour. Manag. Perspect. 2017, 22, 132–136. [Google Scholar] [CrossRef]
  104. Lim, J.; Lee, H.C. Comparisons of service quality perceptions between full service carriers and low cost carriers in airline travel. Curr. Issues Tour. 2019. [Google Scholar] [CrossRef]
  105. Martin-Domingo, L.; Martín, J.C.; Mandsberg, G. Social media as a resource for sentiment analysis of Airport Service Quality (ASQ). J. Air Transp. Manag. 2019. [Google Scholar] [CrossRef]
  106. Nam, S.; Ha, C.; Lee, H.C. Redesigning In-Flight Service with Service Blueprint Based on Text Analysis. Sustainability 2018, 10, 4492. [Google Scholar] [CrossRef]
Sustainability 11 03213 g001 550
Figure 1. Theoretical research model.
Figure 1. Theoretical research model.
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Figure 2. Regionality distribution of survey data. The left and right panels indicate the home regions of airlines and the home regions of the respondents, respectively.
Figure 2. Regionality distribution of survey data. The left and right panels indicate the home regions of airlines and the home regions of the respondents, respectively.
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Figure 3. Research model results (*** p < 0.001).
Figure 3. Research model results (*** p < 0.001).
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Table
Table 1. Comparisons of seat sizes and additional services between premium and standard economy classes of the top-five premium economy services [31].
Table 1. Comparisons of seat sizes and additional services between premium and standard economy classes of the top-five premium economy services [31].
AirlineSeat ClassPitchWidthAdditional Service
NZPremium Economy41~4218.5~20Free additional baggage
Extended dining menu service
Standard Economy31~3317.1~17.8
QFPremium Economy38~4219~20.5Priority boarding, Free self-serve bars
Extensive wine service
Standard Economy31~3217~17.5
SQPremium Economy3819~19.5Priority boarding, Private storage space
Individual reading light
Standard Economy32~3417.5~19
LHPremium Economy38~3918~19Free additional baggage, Welcome drink
Fine china tableware and personal water
Standard Economy31~3217.1~18.2
AFPremium Economy38~4018~19Individual reading light, Priority boarding
Free additional baggage, Free airport lounge
Standard Economy31~3417~18
Note: The table was created using data from the official websites of corresponding airlines and seatguru.com.
Table
Table 2. Demographic and travel-related information (n = 382).
Table 2. Demographic and travel-related information (n = 382).
AttributeSubgroup CategoriesSample NumberPercentage (%)
GenderMale21556%
Female16744%
Age10–19123%
20–2911530%
30–3913235%
40–496016%
50–594211%
≥60215%
Purpose of travelLeisure18649%
Business8121%
Visit friends and relatives5414%
Others6116%
OccupationCompany employee14738%
Private business5514%
Student7319%
Professional257%
Housewife113%
Government employee236%
Others4813%
Monthly incomeLess than $10006316%
$1000–2000215%
$2001–300011029%
$3001–40008322%
More than $400010527%
Period of most recent experience Within 6 months16343%
Within 6 months~1 year8422%
Within 1~2 years6417%
Within 2~3 years287%
Over 3 years4311%
Table
Table 3. Paired sample t-tests for age and gender portions between sample and population groups.
Table 3. Paired sample t-tests for age and gender portions between sample and population groups.
GenderAge
PopulationSample PopulationSample
mean0.5000.500mean0.1650.167
variance0.0340.007variance0.0060.017
observations22observations66
correlation1 correlation0.869
df1 df5
t-statistics−3.97 × 10−16 t-statistics−0.055
p-value 1 p-value 0.958
Table
Table 4. One-way ANOVA tests for constructs between groups with different income levels, period of most recent experience, and home regions of airlines. Highlighted values denote statistical significance (p-value < 0.05) and do not support the null hypothesis ( H 0 : μ 1 = μ 2 = ⋯ = μ k ).
Table 4. One-way ANOVA tests for constructs between groups with different income levels, period of most recent experience, and home regions of airlines. Highlighted values denote statistical significance (p-value < 0.05) and do not support the null hypothesis ( H 0 : μ 1 = μ 2 = ⋯ = μ k ).
ATSNPBCPPPSQPVRI
M_INC
Less than $1000 (n = 63)3.853.613.573.573.693.653.70
$1000–2000 (n = 21)3.523.373.293.143.543.513.22
$2001–3000 (n = 110)3.803.493.683.363.653.683.70
$3001–4000 (n = 83)3.953.663.903.533.853.903.87
Over $4000 (n = 105)3.783.663.993.643.633.563.65
F-statistics1.0210.8173.9652.8351.1092.3041.165
p-value0.3960.5150.0040.0240.3520.0580.170
P_MRE
Within 0.5 year (n = 163)3.973.703.843.603.813.783.92
Within 0.5~1 year (n = 84)3.713.563.703.383.613.663.50
Within 1~2 years (n = 64)3.733.483.823.433.573.593.62
Within 2~3 years (n = 28)3.773.523.493.393.703.633.56
Over 3 years (n = 43)3.603.403.743.523.533.543.47
F-statistics2.2141.1730.9371.2921.8201.1043.199
p-value0.0670.3220.4420.2730.1240.3550.013
A_HR
Asia (n = 176)3.893.693.823.483.773.633.81
Europe (n = 130)3.653.433.683.493.633.623.52
Americas (n = 65)3.773.553.703.563.473.653.58
Oceania (n = 11)4.423.914.153.583.973.674.27
F-statistics3.4672.3201.1690.2012.5070.0263.126
p-value0.0160.0750.3210.8960.0590.9940.026
Note: AT = attitude; SN = subjective norm; PBC = perceived behavioral control; PP = perceived price; PSQ = perceived service quality; PV = perceived value; RI = repurchase intention; M_INC = monthly income; P_MRE = period of most recent experience; A_HR = home region of airlines.
Table
Table 5. Construct reliability and convergent validity.
Table 5. Construct reliability and convergent validity.
ConstructItemFactor LoadingAVEComposite ReliabilityCronbach’s Alpha
Attitude1. I have a positive perception toward the premium economy class.0.8890.7690.9710.906
2. I think traveling in premium economy class would be fun.0.888
3. I think traveling in premium economy class would be relaxing.0.850
Subjective Norm1. My friends or relatives would support my use of premium economy class.0.8620.7470.9600.909
2. People who are important to me would prefer that I use premium economy class.0.860
3. People whose opinions I value would prefer that I use premium economy class.0.903
Perceived Behavioral Control1. If I want to use premium economy class, it would be easy.0.8250.6880.9490.885
2. I have enough resources and knowledge to use premium economy class.0.877
3. Using premium economy class is not difficult for me.0.850
Perceived Price1. The price of premium economy class is reasonable.0.8570.7260.9670.869
2. The price of premium economy class is appropriate for my consumption level.0.880
3. The price of premium economy class is acceptable.0.754
Perceived Service Quality1. The in-flight service (e.g., meals and entertainment) in premium economy class is good.0.8230.7450.9610.885
2. Premium economy class seats are wide and comfortable0.843
3. The overall service quality of premium economy class is satisfactory.0.870
Perceived Value1. Premium economy class offers value.0.8930.7410.9730.879
2. The overall value of premium economy class is high.0.854
3. I gain more than what I sacrifice from using premium economy class.0.795
Repurchase Intention1. I am willing to use premium economy class again.0.9010.8100.9710.943
2. I will positively consider repurchasing premium economy class.0.945
3. I will recommend premium economy class to other people.0.917
Table
Table 6. Square inter-construct correlations and average variance extracted (AVEs). AVEs are highlighted in the top diagonal of the matrix, and the square inter-construct correlations are presented diagonally under the AVEs. All inter-construct correlations are significant at the 0.05 significance level.
Table 6. Square inter-construct correlations and average variance extracted (AVEs). AVEs are highlighted in the top diagonal of the matrix, and the square inter-construct correlations are presented diagonally under the AVEs. All inter-construct correlations are significant at the 0.05 significance level.
1234567
1. AT0.769
2. SN0.7230.747
3. PBC0.4960.3940.688
4. PP0.1790.2020.2630.726
5. PSQ0.1730.1200.0650.3150.745
6. PV0.2920.2300.1140.4060.6160.741
7. RI0.6510.5300.4240.3410.2740.5100.810
Table
Table 7. Hypothesis tests.
Table 7. Hypothesis tests.
HypothesisStructural Coefficientt-Valuep-ValueResult
H1: Attitude → Repurchase intention0.4494.796***Supported
H2: Subjective norm → Repurchase intention0.1131.4010.161Not supported
H3: PBC → Repurchase intention0.2043.777***Supported
H4: Perceived price → Perceived value0.3065.864***Supported
H5: Perceived service quality → Perceived value0.60010.565***Supported
H6: Perceived value → Repurchase intention0.46911.617***Supported
Note: *** p < 0.001.

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Kim, J.H.; Lee, H.C. Understanding the Repurchase Intention of Premium Economy Passengers Using an Extended Theory of Planned Behavior. Sustainability 2019, 11, 3213. https://doi.org/10.3390/su11113213

AMA Style

Kim JH, Lee HC. Understanding the Repurchase Intention of Premium Economy Passengers Using an Extended Theory of Planned Behavior. Sustainability. 2019; 11(11):3213. https://doi.org/10.3390/su11113213

Chicago/Turabian Style

Kim, Jun Hwan, and Hyun Cheol Lee. 2019. "Understanding the Repurchase Intention of Premium Economy Passengers Using an Extended Theory of Planned Behavior" Sustainability 11, no. 11: 3213. https://doi.org/10.3390/su11113213

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