DOI QR코드

DOI QR Code

Airline Passenger Repurchase Behavior Intention Model: Moderating Effect of Leisure and Corporate Travel in Korea Market

  • Received : 2023.05.01
  • Accepted : 2023.08.05
  • Published : 2023.08.31

Abstract

Purpose: This research aims to explore the effects of airline's pricing and service quality through service distribution process on repurchasing intention of the air passengers with meditations of passenger satisfaction and airline brand. Research design, data and methodology: This paper particularly focused on employing the moderating effect with two different market segmentations, namely leisure and corporate purpose travelers, in the Korean market. The total sample size of this research is 363 respondents of the general public in Korea. For the methodology of this research, structural equation modeling (SEM) was utilized for the statistical analysis. Results: It figured out that passenger satisfaction is ultimately the most important among variables of price, service quality and repurchase intention for both groups. On the contrary, the relationships, between price and airline brand in both groups, and between airline brand and repurchase intention in the leisure travel only, were not noted as beneficial effects. Conclusions: More noteworthy was that airline brand had a positive influence on repurchase intention in the corporate travel group. Based on this research, the results will deliver the contributions to the commercial airlines in the future.

Keywords

1. Introduction

Traditionally, airlines have kept improving their competitiveness by enhancing market share for the routes operated and reducing costs while maximizing revenue. However, the global aviation-tourism industry has been suffering unprecedented aftereffects by the COVID-19 pandemic. According to the International Air Transport Association (IATA), the airline industry will be able to fully recover its profits and expect overall traveler numbers to reach 4.0 billion in 2024, exceeding pre-COVID-19 levels (103% of the 2019 total) and announced 2022 year to date (YTD) result that air passengers in the year of 2022 have substantially recovered 68.5% of 2019 revenue passenger-kilometers (RPKs) (IATA, 2022). Given the forecast of a return to 2019 levels, at a time when travel demand is rebounding with travel vengeance and more seat capacity or extra available seat kilometers per passenger (ASKs) is added, the enormous growth of both leisure and corporate travels is expected to take place.

Today, the airline industry is becoming more competitive and harder to survive among many competitors, especially with the advent of low cost carriers (LCCs) in the market. Particularly, with market penetrations of domestic and foreign LCCs into Korean aviation industry, and in the fiercer competition environment such as the recent mergers and acquisitions (M&As) application between Korean Air and Asiana Airlines and strategic partnerships like Value Alliance among LCCs in the Asia-Pacific region, the airline industry has been through a market test bed for improving service quality, seamless service distribution and customer satisfaction to meet local passengers’ changed and difficult appetite.

Park et al. (2004) identified the following individual factors - service value, passenger satisfaction, and airline image as having a direct effect on passengers’ behavioral intentions. Furthermore, numerous studies have also shed light on a subject that customer satisfaction in the aviation industry is a very critical requisite, for ensuring an airline business sustainability and long-term relationship with frequent flyer clients through their customer retention measures (Ali et al., 2015; Archana & Subha, 2012; Wu & Cheng, 2013).

To sum up, airline service providers or similar tourism organizations should contemplate sales and marketing tactics to apply more price elastic, improve service quality, make customer-centered service distribution, escalating passenger satisfaction, and maintain behavioral loyalty, which may result in greater profits, such as increasing market share to keep consolidating passenger loyalty (Bowen & Chen, 2001; Dolnicar et al., 2011; Seiders et al., 2005).

Although there have been many previous studies on the aforesaid reciprocal relations in market segments - leisure and/or corporate travel sales, respectively - and similar ones in other industries, the number of papers dealing with the subject is still inadequate. To the best our knowledge and belief, no same research question hitherto has been studied with respect to analyzing passenger’s decision-making process through structural equation modeling’s (SEM’s) moderating effect for leisure and corporate travel purpose in the Korean air transportation industry. Previous scholars were putting the accent on the aviation industry and ascertained the distinguished passenger groups by travel objective solely explaining invariance regarding airline’s type whether it is LCC or full service carrier (FSC) (Lee et al., 2018; Leong et al., 2015) and Chonsalasin et al. (2022) also ascertained a parameter-type model invariance of passenger groups by trip objective in the Thai aviation industry.

Despite the characteristics of passenger travel purpose-derived differences, their research conducted on the subject has showed some similarities and differences as compared with the authors’ study herewith. To fill this gap, our paper establishes the significance of direct or indirect effects of airline’s pricing and service quality on customer behavioral loyalty expressed as passenger’s repurchase intention through the mediations, passenger satisfaction and airline brand. Further, by categorizing two distinguished market segments, leisure and corporate travel purpose, experiencing an air service distribution channel selection and a comparative analysis between the foregoing groups utilizing an analytical method of moderating effect to see if there are any clear disparities in Korean aviation-tourism market.

This makes appreciation of the differences of leisure and corporate travel groups, one of the main determinant attributes of passenger’s decision-making processes, exceptionally indispensable. Therefore, the purpose of this paper is to examine the effects of airline’s pricing and service quality through service distribution process on repurchasing intention of the air passengers with meditations of passenger satisfaction and airline brand. Ultimately, the result of this research can be used as a reference for the airline’s management and the air travel organizations in order to establish effective and practical application to customized sales and marketing strategies and positive passenger experiences locally targeted toward segmented groups organized on the basis of trip objectives.

2. Literature Review

2.1. Leisure and Corporate Travel

In a broader classification of travel purpose by air, it can be divided into either a leisure travel or corporate travel market segment. Holloway (2008) asserted that consumers’ disposition to air travel would grow as their incomes rise, and there is a robust correlation between per capita gross domestic product (GDP) and airline trips per capita. As previous scholars also defined leisure travel as a fundamental disparity between leisure and corporate travelers, relates to their price elasticity of demand and income-elasticity calculations in leisure markets are rather complicated (Dresner, 2006; Holloway, 2008). Furthermore, Doganis (2019) interpreted leisure travel having a different socio-economic characteristic that assists in targeting specific marketing efforts at its subsegment, such as visiting friends and relatives (VFR), as well. In general, the leisure passengers by air tends to be more price-sensitive than corporate or business passengers. Thanks to Korean LCCs’ rapid leaps ever in the pre-pandemic level (+63.0% up from 2015 to 2019) by accommodating this category of passengers, it has ushered the international market expansion by home market air carriers and by foreign air carriers operating to/from Korea market to +53.3% and +35.7% growth from 2015 to 2019, respectively, and it can be also noticeable an upwards curve of trends in overseas cad usage by Koreans, before an abrupt nosedive due to the global pandemic as shown Figure 1 and 2 (KCA, 2023).

OTGHB7_2023_v21n8_69_f0001.png 이미지

Figure 1: Air passengers traffic trend as compared with pre-pandemic years (2015-2019) year-on-year (YoY) in Korea market [Source: Korea Civil Aviation Association (KCA) (2023)]

OTGHB7_2023_v21n8_69_f0002.png 이미지

Figure 2: Trends in overseas card usage by Koreans (Quarterly basis of 2005-2023) [Source: Bank of Korea (BOK) (2023)]

In terms of the corporate travel segment, former researchers analyzed the intrinsic attributes elaborating on the replacement income-elastic calculations to a measure of trade-elasticity, and came to the conclusion that trade causes more influence on corporate travel, and is more dependent upon corporate profits than GDP (Holloway, 2008). Moreover, Taneja (2017) also identified the typical framework of corporate travel as travel managers at corporations that negotiated favorable rates with air suppliers providing various discount level tiers based on the value of the travel undertaken and regarding the corporate travel motivation as it impacts not only the frequency of travel but also the time period of the air trip. On average, corporate travelers catch flights more often, they also make business trips with relatively shorter trip period and that may be linked to the reason why travel managers at corporations emphasize the importance of high frequencies for corporate travelers.

2.2. Price between Passenger Satisfaction and Airline Brand

Airline products are differentiated by a number of essential elements, which can have leverage on pricing decisions. Commonly, scholars explored that price recognition by the consumers can be described as monetary price and behavioral price to look for products and services, ease of use and values evolution (Petrick, 2004). Consumer’s decision-making in the purchasing process is based on what they perceived that prices should be and what prices actually are (Kotler & Keller, 2016). In addition, Choi et al. (2021) predicted that post COVID-19 would change consumption trends as priceoriented which is based on consumer’s economic potential and strengthening of value-oriented consumption trend.

LCCs normally derived customers’ demand from the affordable price of air tickets compared to FSCs. Hence, the price of air tickets is one of the important factors that passengers take into consideration when making their airline selection (Vlachos & Lin, 2014) and the following scholars also showed their insights that ticket price exhibits a significant effect on passenger satisfaction in the new LCC market in China (Pan & Truong, 2018) and fast-growing LCC markets in the Southeast Asia region (Boey et al., 2012). In a similar context, affordable and attractive prices are the satisfying factor for passengers of both LCCs and FSCs (Mikulić & Prebežac, 2011) and Kim et al. (2022) anticipates the appearance of a new cherry-sumers referring strategist customers who consume as frugally as possible to maximize limited resources right after stepping into the endemic in their research.

Furthermore, if consumers recognize the brand as having a higher price but being of similar quality to the competing rival brands, all other things being equal, they should be less willing to purchase the expensive brand and more willing to purchase the affordable brand (Winit et al., 2014). On the other hand, one reason the airline invests money in its brand image and frequent flyer program (FFP) is to strengthen the relationship of customer loyalty and switch the demand from the high value customers dampening the price-elasticity (Holloway 2008). From the above points of view from the previous studies, the following hypotheses are proposed:

H1: Price has a positive impact on passenger satisfaction.

H2: Price has a positive impact on airline brand

2.3. Service Quality between Passenger Satisfaction and Airline Brand

Airlines kept adapting their service standards to suit the dynamic market demands. Service quality can be interpreted as a consumer’s overall impression of the relative efficiency of the organization and its services (Park et al., 2004). Further, an almost innumerable amount of research has been conducted to define different angles in terms of definitions related to service quality, and various methods and dimensions of service quality to verify service providers’ strengths and weaknesses (Bhat, 2012).

Previous research highlighted the importance of the relationships between airline service quality, passenger satisfaction, airline brand and behavioral intentions (Chen, 2008; Chou et al., 2014; Park et al., 2004; Sultan & Simpson, 2000).

In the fierce service industry, therefore, customers play a pivot role in determining the service quality that they experienced and, as for the service quality of a company, the more competitive the environment, the more useful it is as a strategy to continuously provide high quality services rather than price competition (Chang & Yeh, 2002; Chaniago & Mudjiardjo, 2021; Nunkoo et al., 2020). It was also found that the passenger's perception of service quality is positive for the passenger's behavioral loyalty expressed for repurchase intention, and passenger satisfaction is seen as a key to business success (Chonsalasin et al., 2022). Moreover, some previous researchers have argued that in a highly competitive market environment, service quality could exsert intended positive outcomes and found that when consumers experienced quality service, this may result in influencing their behavioral intentions because of the positive awareness and image of the brand (Nadiri et al., 2008; Wu et al., 2011). As such, Chen et al. (2018) developed and examined their empirical model of service quality related to China airline passengers’ repurchase intentions by perceived value and brand awareness of the airline’s service. On the basis of the previous studies, therefore, the following hypotheses are proposed:

H3: Service quality has a positive relationship with passenger satisfaction.

H4: Service quality has a positive relationship with airline brand

2.4. Air Service Distribution

With the arrival of the digital revolution era, the socalled Fourth Industrial Revolution (or Industry 4.0), digital transformation and innovation have been accelerating through industries, and technological advancement in commodity production and sales is being established. In other words, digitalization endeavors are being made to closely identify customer needs and create new business models while inducing technological changes in interfaces, communication, and distribution channels between service providers and consumers, focusing on digital technology bases (Hagberg & Kjellberg, 2020; Mele et al., 2021).

Through the convergence of information and communications technology (ICT), cooperation and coordination among aviation-tourism industry stakeholders for effective air service distribution channels, such as online travel agencies, global distribution systems, direct channels, and travel management companies, by exchanging flight seat availability and passenger information, etc. become important. In particular, in the aviation industry, as the pricing structure of airfare becomes transparent and dynamic due to the dissemination of the internet and changes in the web-based distribution market, the market price declines, resulting in deterioration in airline profitability and fixed costs based on its high structural properties (Taneja, 2016).

Therefore, airlines shall provide differentiated customer experience and value by exposing various aviation products to customers through the new distribution capability (NDC) technology launched by IATA recently, which will turn into a major channel in the future aviation-tourism product sales distribution process, while minimizing costs and providing profitable management (IATA, 2020). Subsequently, air service distribution would make a substantial impact on passenger repurchase intention, as it can affect the overall customer experience and satisfaction with an airline as well.

2.5. Passenger Satisfaction and Repurchase Intention

The customer satisfaction defined by Park et al. (2004) described as a judgement made on the basis of a specific service encounter, and other scholars also clarified that it is the evaluation of the difference between the service anticipated and the actual value after purchasing the products and/or services through distribution channels (Batouei et al., 2020; Monoarfa et al., 2020). In addition, Chonsalasin et al. (2022) underlined that passenger satisfaction is the level of passenger’s favorable empathy regarding products and services offered, evaluated by the appropriateness of the products and service offered. Hence, when passengers experience the actual service quality as surpassing their expectations, these satisfied passengers tend to have repurchase intentions (Nyadzayo et al., 2016). Furthermore, customer satisfaction crucially affects customer trust and product repurchases (Gustafsson et al., 1999). Therefore, passenger satisfaction may have a positive effect on the customer behavioral loyalty represented passenger’s repurchase intention, and they are regarded as major decision-making factors.

Various studies have also found the fact that customer satisfaction in the aviation industry is a very critical element, for ensuring an airline business sustainability and long-term relationship with frequent flyers through their customer retention measures (Ali et al., 2015; Archana & Subha, 2012; Wu & Cheng, 2013). In the highly competitive aviation industry, attracting new customers requires a higher-level of marketing related costs to keep the existing customers in active. Additionally, Taneja (2017) stressed out that three major reasons for an airline to redesign its services around its customers’ satisfaction experience would be passenger trends, big data and analytics, and platform-based collaboration. Such a digital analysis requires the smart and experientially-based services on a personalized and customized basis.

Hence, customer service retention programs should be focused on maintaining the relationship with customers and satisfying them (Thompson, 2005). As such, on the basis of the previous studies, the following hypothesis is proposed:

H5: Passenger satisfaction has a positive impact on repurchase intention.

2.6. Airline Brand and Repurchase Intention

According to Akin (2011), a brand’s identity has various aspects that directly or indirectly affect the customer’s purchase intention. In addition, other scholars identified that brand image is defined as a positive or negative feeling that a consumer possesses about a brand, confidence in the brand, or a psychological framework of the consumer, and is also interpreted as a suit of beliefs that the consumer has about the brand (Armstrong et al., 2014). Low and Lamb (2000) asserted that brand image is a belief about the function and symbol of a brand and is composed of a symbolic, social, and psychological image.

Thus, brand image is important because it can influence customer behavior, preference, and loyalty, which increases airline profit opportunities through purchase intention (Dash & Chakraborty, 2021).

In the same manner, previous studies related to the airline industry have verified that there is a significant influence between airline brand and repurchase intention, which can be related to airline loyalty (Wang & Lee, 2018; Dash et al., 2021). In addition, Jeng (2016) stressed the importance of airline brand credibility influencing consumer purchase intention by raising consumers' decision convenience and enhancing affective commitment. Therefore, airlines also have to be very conscious about their image, goodwill, and brand recognition value (Nadiri et al., 2008; Radovic-Markovic et al., 2017). To maintain a good brand image, airlines should bring various promotional offers and FFPs (Gudmundsson et al., 2002; Radovic-Markovic et al., 2017). Additionally, according to Ekiz et al. (2006), an airline's image comprises of its overall perception, value for money, promotional offers and goodwill which may be explained that repurchase behavior occurs when the customers form a positive attitude toward the product or service that they recognized and purchased. These customers especially those with a high degree of satisfaction are also likely to turn into loyal customers, and they are likely to spend more and unlikely to change air supplier in future purchases (Ranaweera, 2007; Sohaib & Rehman, 2016). As such, on the basis of the previous studies, the following hypothesis is proposed:

H6: Airline brand has a notable influence on repurchase intention.

3. Research Methodology

3.1. Survey Design

Based on the research model shown in Figure 2, nineteen survey items were crafted for a quantitative approach (Saunders et al., 2009). This was achieved by revising and complementing items from previous studies spanning various industries related to the price, service quality, passenger satisfaction, airline brand and repurchase intention as shown in Table 1. All questionnaires were revised to fit the purpose of this study using the 5-point Likert scale and translated into the Korean language with support from two professional translators to clearly articulate the questions for the survey participants. The process of this translation was conducted as per references to ensure that cultural and linguistic equivalency was applied to the scales (Ruvio & Shoham, 2007). A convenient sampling method (Hair et al., 2006), which was based on the non-probabilistic and self-participation sampling method, was applied under the guidelines provided by Tarhini et al. (2016). As such, non-probability sampling method was selected and employed herewith due to its comparable advantages highlighting a quick and efficient data collection, cost saving and obtaining insights into a population of interest. Furthermore, the authors tried to take appropriate measures to minimize the likelihood of common method biases for the improved validity of research findings by adopting careful sample selection, the use of shorter survey questions and scales, and the use of statistical methods to control for theses probable common method biases.

OTGHB7_2023_v21n8_69_f0003.png 이미지

Figure 3: The Research Model

Table1: Questionnaire Items

OTGHB7_2023_v21n8_69_t0001.png 이미지

Three pilot tests were carried out by nine volunteers, and an unspecified majority was used to modify the survey questionnaires.

3.2. Data Analysis and Results

The format of the main survey was constructed using a Google survey program. The survey link was strictly released to the general public via a mostly using Korean social network service (SNS) channel. In four weeks (28 days), 363 completed responses were collected. We used SPSS version 25 for conducting various analyses, including descriptive statistics and internal reliability (Cronbach alpha), and used AMOS version 23 for conducting analyses of confirmatory factor analysis (CFA), including convergent reliability, discriminant reliability, model fit analysis, and SEM path analysis, and to validate the hypotheses (Hair et al., 2011; Leontitsis & Pagge, 2007). A correlation analysis was also carried out to assess the multi-collinearity of the independent variables among the factors and confirm that they were suitable for the SEM analysis (Yamamoto & Onodera, 1999), which was conducted using AMOS version 23.

3.2.1. Descriptive Statistics

Table 2 presents the demographic profile of the 363 survey participating individuals, of which 41.3% were female and 58.7% were male. By age dispersion, the identical portion of 30.6% was found in each of the 40s and 50s age brackets followed by 22.9% from those in their 30s, 12.4% from participants in their 20s and 3.6% from those in their 60s and above, respectively. Among the survey respondents, those who were in their 30s-50s accounted for 84.1% and had a majority of the travel experiences. With regard to academic background, it shows their final education level of 83.8% with a diploma or bachelor’s degree or higher. In terms of annual travel frequencies, single air travel per year was the largest share at 65.8%, 2-4 times air travel per year at 25.1%, 5-7 times air travel per year at 5.2%, over 10 times air travel per year at 3.3% and 8-10 times a year air travel at 0.6%. In terms of travel purpose, the leisure travel with 87.1% surpassed the business travel at 12.9%. In addition to the airlines type of use, the airline usage ratio between FSCs were 58.1% and LCCs were 41.9% accordingly. Remarkably, due to extraordinary market positioning of ten LCCs in Korea market, it is abundantly evident that this situation has been causing excessive competition among them and the result showed a comparatively high ratio of 35.2% of domestic LCCs’ share in a short-answer type question about name(s) of main airlines in use for the participations of this survey.

Table 2: Demographic profile [N: 363]

OTGHB7_2023_v21n8_69_t0002.png 이미지

3.2.2. Confirmatory Factor Analysis (CFA)

Before testing the hypotheses, the measurement model was validated via CFA. For squared multiple correlation (SMC) value screening each questionnaire item, all of the questionnaire items have produced the minimum satisfaction levels of SMC at 0.4 and above which retains the reliability of each questionnaire. To satisfy other internal consistency concerns and maintain reliability, Cronbach’s alpha analysis was also conducted (Cronbach, 1951). As results, all the questionnaire items for Cronbach alpha value were exceeded the recommended level of 0.7 (Santos, 1999), as shown in Table 3.

Table 3: Confirmatory Factor Analysis (CFA)

OTGHB7_2023_v21n8_69_t0003.png 이미지

To analyze correlations within given variables, average variance extracted (AVE) and composite reliability (CR) checks were carried out, as shown in Table 3, if they exceeded 0.5 and 0.7, respectively (Geldhof et al., 2014). The following CR and AVE value pairs were calculated: [0.870 (CR), 0.691 (AVE)] for price, [0.825 (CR), 0.612 (AVE)] for repurchase intention, [0.839 (CR), 0.640 (AVE)] for airline brand, [0.820 (CR), 0.696 (AVE)] for service quality, [0.885 (CR), 0.659 (AVE)] for passenger satisfaction. The values of CR and AVE for all of the variables in this research exceeded the minimum satisfaction level of 0.5 for AVE, 0.7 for CR. Moreover, a discriminant validity check was conducted as shown in Table 4, where a correlation between two specific factors had to be lower than the square root level of the AVE value (Cable & DeRue, 2002).

Table 4: Discriminant Validity

OTGHB7_2023_v21n8_69_t0005.png 이미지

3.2.3. Fit Indices

Fit indices of this model were computed as presented in Table 5. It was found that most of the items of the fit indices for this model were at acceptable levels or close to the acceptable levels. Using CFA, the factors in the absolute fit index reached and exceeded the recommended thresholds with a result of x2 = 408.504, CMIN/DF = 2.623, RMR = 0.030, GFI = 0.935, AGFI = 0.899, and RMSEA = 0.067. The factors in the incremental fit index reached acceptable levels, presenting NFI = 0.942 and CFI = 0.963. The results of the goodness of fit analysis via the CFA process were at acceptable levels with a high level of accuracy. These results indicated that no problems existed in terms of satisfying the acceptance levels of the goodness of fit for CFA.

Table 5: Model Fit Results​​​​​​​

OTGHB7_2023_v21n8_69_t0006.png 이미지

3.2.4. Structural Equation Modelling (SEM) Analysis

The figures of Table 6 and Table 7 present the summary of the proposed research model with the results from the path analysis. Although the hypothesis connecting price to airline brand(LH2), with the values of β = -0.030, SE = 0.043, CR = -0.587, and p = 0.557 (p > 0.05) and the hypothesis connecting airline brand to repurchase intention(LH6), with the values of β = 0.085, SE = 0.069, CR = 1.243, and p = 0.214 (p > 0.05) in the leisure travel segment and the hypothesis connecting price to airline brand(CH2), with the values of β = 0.105, SE = 0.106, CR = 0.694, and p = 0.487 (p > 0.05) in the corporate travel segment were not supported, the remaining hypotheses were all supported. This included the hypothesis connecting price to passenger satisfaction in both leisure and corporate travel, with values of β = 0.200, SE = 0.034, CR = 4.530, p <0.001 and with values of β = 0.401, SE = 0.112, CR = 2.655, p < 0.05, respectively; the hypothesis connecting service quality to passenger satisfaction in both leisure and corporate travel, with values of β = 0.911, SE = 0.093, CR = 11.246, p < 0.001 and with values of β = 0.623, SE = 0.144, CR = 3.263, p = 0.001, respectively; the hypothesis connecting service quality to airline brand in both leisure and corporate travel, with values of β = 0.772, SE = 0.107, CR = 9.145, p < 0.001 and with values of β = 0.604, SE = 0.162, CR = 2.657, p < 0.05, respectively; the hypothesis connecting airline passenger satisfaction to repurchase intention in both leisure and corporate travel, with values of β = 0.787, SE = 0.093, CR = 9.258, p < 0.001 and β = 0.611, SE = 0.183, CR = 3.670, p < 0.001, respectively; the hypothesis connecting airline brand to repurchase intention in solely corporate travel segment, with values of β = 0.632, SE = 0.236, CR = 3.106, and p < 0.05.

Table 6: Path coefficients among variables and hypotheses results of moderating effects for leisure travel

OTGHB7_2023_v21n8_69_t0007.png 이미지

(***p < 0.001, **p < 0.005, *p < 0.05)

Table 7: Path coefficients among variables and hypotheses results of moderating effects for corporate travel

OTGHB7_2023_v21n8_69_t0008.png 이미지

(***p < 0.001, **p < 0.005, *p < 0.05)

A probable portrait for the result of lower correlation between price and airline brand in leisure travel is that local passengers’ appreciation for a variety of airlines selection attributes mainly because of the development of LCCs. On the other hand, a possible depiction for another result of lower correlation between price and airline brand in corporate travel sector is largely attributable to the unique price inelasticity of business travelers and the bilateral corporate contracts and negotiated rates with the pre-determined air carrier(s) regardless of airline brand, respectively, as shown the survey data and path coefficients.

3.2.5. Moderating Effects

The primary purpose of this research is to determine if travel purpose differences exist in the repurchase intention behavior model for airliners’ passengers. Hence, moderating effect analysis was conducted to verify meaningful differences and correlation indices of the two travel purpose groups in the path coefficients of the research model. Based on the study results, the typical air travel groups had some similarities, while they showed clear disparity between the aforementioned two groups. When SEM was individually undertaken for each travel purpose group, therefore, both the leisure travel purpose group and the corporate travel purpose group met the prediction results of the research hypotheses, and the correlation among variables was verified and analyzed to structure the behavioral loyalty of airline customers that led to their repurchase intention.

Notably, for the influence of airline brand, as a mediation, on passenger’s repurchase behavioral intention, there was a substantial difference between leisure and corporate travel. With path coefficients for leisure travel (β 0.085 and C.R. 1.243) and corporate travel (β 0.632 and C.R. 3.106), it was evident that corporate traveler group's prominent loyalty behavioral intention to result in the ultimate agreements of their preferred air carrier(s) was not only due to customer recognition of the higher quality in passenger service but also because of great importance of more amicable attitude and feedback free on the airline brand.

OTGHB7_2023_v21n8_69_f0004.png 이미지

Figure 4: SEM analysis results and moderating effects - both leisure and corporate travel in Korea market​​​​​​​

4. Conclusion and Implications

4.1. Conclusion

This study investigated the moderating effect of leisure and corporate travel on relationships between price, service quality through service distribution and repurchase intention with the mediators of passenger satisfaction and airline brand. The model constancy was also verified by comparative analysis and moderating effect of two groups classified by leisure and corporate purpose traveler group samples.

We sum up the following main points brought out in the result of this study. First, as a result of leisure travel segment of the research model, it was found two variables - price and service quality - affected passenger satisfaction which is a pivotal factor for the repurchase intention, while price had a negative effect on airline brand. Service quality showed a positive influence on both passenger satisfaction and airline brand. Moreover, passenger satisfaction had a comparatively high influence on the passenger behavioral intention, describing a directly proportional correlation between the two variables. As anticipated, the results obtained showed that price made no meaningful influence on airline brand with the price-sensitivity through market entry of LCCs, expanding online travel agency (OTA) and flight aggregator platforms, tour package deals and bundled offerings diagnosed in the previous studies.

Similarly, airline brand which leisure passengers had been mulling over indicated that there was not affiliated with their behavioral loyalty discriminatively, especially during sluggish economic growth amid domestic trilemma, namely the highest household debt, higher commodity prices and exchange rates. On top of that, it is important to note that more contributing elements, e.g., availability of alternative options, changing traveler preferences, influence of online reviews and ratings, and tactical promotions and discounts, are based on the characteristic of leisure travelers and may vary in their impact depending upon the unique market conditions, customer behavior, strategies deployed by airlines.

Second, as a result of the corporate travel segment of this research model, it was also found two variables - price and service quality - affected passenger satisfaction which is a primary element for the repurchase intention, whereas price had an insignificant effect on airline brand with a different reason unlike the result of leisure travel. A possible reason is likely due to the following elements, the price inelasticity of corporate travelers and the prevalence of global/local agreements between companies and airlines regardless of airline brand.

Also, service quality showed a positive influence on both of passenger satisfaction and airline brand in the corporate travel industry. On top of that, unlike leisure travel, both mediations - passenger satisfaction and airline brand - had positive influences on the passenger behavioral intention, representing the importance of corporate clients’ selection criteria for the preferred air carrier through distinct service distribution of corporate’s travel manager and/or Travel Management Companies (TMCs).

4.2. Implications

Subsequently, there are some meaningful takeaways for both academic and managerial implications.

In terms of academic implication, it provided a contribution towards redefining the major factors of the air passenger decision-making process affecting air traveler’s repurchase behavior model from the perspective of integrated FSCs and LCCs of Korean aviation-tourism industry by comparing leisure and corporate travel segments accordingly. This field of research has not been sufficiently studied for the Korean airline industry yet. However, Chonsalasin et al. (2022) had a similar comparative point of view reflecting upon the Thai aviation market, it can be demonstrated to fill the research gaps of precedent research in our different approach by identifying correlations among price, service quality and repurchase intention through the mediations of passenger satisfaction and airline brand in a situation related to decision process of two specific target groups.

Second, in terms of managerial implications, this study conveys significant characteristics of future growth to be considered by airlines management in the new normal. As airline’s products and services via air service distribution, price and service quality have a positive effect on passenger satisfaction and ultimately have a great influence on customer repurchase behavior intention, airlines’ executives should have a different and a second look at their strategy that prioritizes price differentiation policy such as fare branding package, service quality improvement and invigorating customer satisfaction through defined market segments. Accordingly, the airline’s business performance even the commercial viability of airline depends upon how well the management and marketing processes are conducted based on understanding the right market size and segmentation.

Third, service quality has a direct and meaningful effect on the airline brand for both leisure and corporate travel groups, airliners’ decision-makers also need to develop a differentiated customization service strategy. For instances, value-added services and digitally modernized service distribution sales channels especially targeting for premium leisure - e.g. including new subsegments of the Millennials and Generation Z (MZ) young travelers and active silver travelers - and corporate travelers as well. More importantly, the difference between leisure and corporate travel is clearly revealed in relation to customer repurchase intention through the enhancement of airline brand awareness, airline marketers should establish their own brand credibility related sales and marketing strategy via IATA’s distribution standard new distribution capability (NDC), as a B2B/C service distribution channel, effectively and efficiently with more focus on both customer diversification and personalization by travel purpose. By doing so, airlines can enhance customer satisfaction, loyalty, and ultimately, profitability.

In summary, the new normal would be set by who is well prepared for the demands and hidden motives of air travelers.

4.3. Limitations and Future Research

This research had several notable limitations. First, this study was conducted on only the general public who had domestic and foreign travel experiences in Korea. In the future, to generalize the sample, we believe that it will be necessary to include non-Koreans residing in Korea and transit passengers. Second, in order to anticipate customer repurchase behavior intention, more various variables should be contemplated. Above all, it is expected that considering and adding individual air travel consumption tendency in the endemic era would be of great help in developing a customer repurchase behavior intention model.

Third, a total of 363 survey respondents were used, but the number of survey respondents for corporate travel was not relatively large enough. Future studies will be required to investigate extended research with more respondents from corporate travelers.

References

  1. Akin, M. (2011). Predicting consumers' behavioral intentions with perceptions of brand personality: A study in cell phone markets. International Journal of Business and Management, 6(6), 193.
  2. Ali, F., Dey, B. L., & Filieri, R. (2015). An assessment of service quality and resulting customer satisfaction in Pakistan international airlines: findings from foreigners and overseas Pakistani customers. International Journal of Quality & Reliability Management, 32(5), 486-502. https://doi.org/10.1108/IJQRM-07-2013-0110
  3. Archana, R., & Subha, M. V. (2012). A study on service quality and passenger satisfaction on Indian airlines. International Journal of Multidisciplinary Research, 2(2), 50-63.
  4. Armstrong, G., Adam, S., Denize, S., & Kotler, P. (2014). Principles of Marketing. Melbourne, Australia: Pearson Australia.
  5. Bank of Korea (2023, June). Trends in overseas card usage by Koreans. http://www.bok.or.kr/portal/bbs/P0000559/view.do?nttId=10077634&menuNo=200690&pageIndex=2
  6. Batouei, A., Iranmanesh, M., Mustafa, H., Nikbin, D., & Ping, T. A. (2020). Components of airport experience and their roles in eliciting passengers' satisfaction and behavioural intentions. Research in Transportation Business & Management, 37, 100585. https://doi.org/10.1016/j.rtbm.2020.100585
  7. Bhat, M. A. (2012). Tourism service quality: A dimension-specific assessment of SERVQUAL. Global Business Review, 13(2), 327-337. https://doi.org/10.1177/097215091201300210
  8. Boey, T. S., Ekiz, E. H., & Kamarulzaman, Y. (2012). Factors determining choice of full service airlines and low cost carriers: the case of Malaysia. Asia-Pacific Journal of Innovation in Hospitality and Tourism, 1(2), 179-194.
  9. Bowen, J. T., & Chen, S. L. (2001), The relationship between customer loyalty and customer satisfaction. International Journal of Contemporary Hospitality Management, 13(5), 213-217. https://doi.org/10.1108/09596110110395893
  10. Cable, D. M., & DeRue, D. S. (2002). The convergent and discriminant validity of subjective fit perceptions. Journal of Applied Psychology, 87(5), 875-884. https://doi.org/10.1037/0021-9010.87.5.875
  11. Chang, Y. H., & Yeh, C. H. (2002). A survey analysis of service quality for domestic airlines. European Journal of Operational Research, 139(1), 166-177. https://doi.org/10.1016/S0377-2217(01)00148-5
  12. Chaniago, Y. M. Z., & Mudjiardjo, L. A. (2021). The Effect of Service Difference and Logistic Service Quality on Competitive Advantage and Impact on Marketing Performance. International Journal of Innovative Science and Research Technology, 6, 917-924.
  13. Chen, C. F. (2008). Investigating structural relationships between service quality, perceived value, satisfaction, and behavioral intentions for air passengers: Evidence from Taiwan. Transportation Research Part A: Policy and Practice, 42(4), 709-717. https://doi.org/10.1016/j.tra.2008.01.007
  14. Chen, L., Li, Y. Q., & Liu, C. H. (2019). How airline service quality determines the quantity of repurchase intention-Mediate and moderate effects of brand quality and perceived value. Journal of Air Transport Management, 75, 185-197. https://doi.org/10.1016/j.jairtraman.2018.11.002
  15. Choi, K. E., Kim, H. J., & Kang, J. S. (2021). A study on mid- and long-term growth agenda and policy tasks for the tourism industry in the post-COVID-19 era. Korea Culture & Tourism Institute, 3, 106-120. https://doi.org/10.16937/kcti.rep.2021.e44
  16. Chonsalasin, D., Jomnonkwao, S., Chanpariyavatevong, K., Laphrom, W., & Ratanavaraha, V. (2022). Modeling of airline passenger loyalty: A comparison of leisure and business travelers. Research in Transportation Business & Management, 43, 100735. https://doi.org/10.1016/j.rtbm.2021.100735
  17. Chou, P. F., Lu, C. S., & Chang, Y. H. (2014). Effects of service quality and customer satisfaction on customer loyalty in high-speed rail services in Taiwan. Transportmetrica A: transport science, 10(10), 917-945. https://doi.org/10.1080/23249935.2014.915247
  18. Chung, S., Park, J. W., & Lee, S. (2022). The Influence of CSR on Airline Loyalty through the Mediations of Passenger Satisfaction, Airline Brand, and Airline Trust: Korean Market Focused. Sustainability, 14(8), 4548. https://doi.org/10.3390/su14084548
  19. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334. https://doi.org/10.1007/BF02310555
  20. Dash, G., & Chakraborty, D. (2021). Digital transformation of marketing strategies during a pandemic: Evidence from an emerging economy during COVID-19. Sustainability. 13(12), 6735.
  21. Dash, G., Kiefer, K., & Paul, J. (2021). Marketing-to-Millennials: Marketing 4.0, customer satisfaction and purchase intention. Journal of Business Research, 122, 608-620. https://doi.org/10.1016/j.jbusres.2020.10.016
  22. Doganis, R. (2019). Flying off course V: Airline economics and marketing. Oxon, OX, UK: Routledge.
  23. Dolnicar, S., Grabler, K., Grun, B., & Kulnig, A. (2011). Key drivers of airline loyalty. Tourism Management, 32(5), 1020-1026. https://doi:10.1016/j.tourman.2010.08.014
  24. Dresner, M. (2006). Leisure versus business passengers: Similarities, differences, and implications. Journal of Air Transport Management, 12(1), 28-32. https://doi.org/10.1016/j.jairtraman.2005.09.006
  25. Ekiz, H. E., Hussain, K., & Bavik, A. (2006). Perceptions of service quality in North Cyprus national airline, tourism and hospitality industry 2006-new trends in tourism and hospitality management. In: 18th Biennial International Conference. Faculty of Tourism and Hospitality Management, Opatija, 778-790.
  26. Farooq, M. S., Salam, M., Fayolle, A., Jaafar, N., & Ayupp, K. (2018). Impact of service quality on customer satisfaction in Malaysia airlines: A PLS-SEM approach. Journal of Air Transport Management, 67, 169-180. https://doi.org/10.1016/j.jairtraman.2017.12.008
  27. Geldhof, G. J., Preacher, K. J., & Zyphur, M. J. (2014). Reliability estimation in a multilevel confirmatory factor analysis framework. Psychological Methods, 19(1), 72-91. https://doi.org/10.1037/a0032138
  28. Gudmundsson, S. V., de Boer, E. R., & Lechner, C. (2002). Integrating frequent flyer programs in multilateral airline alliances. Journal of Air Transport Management, 8(6), 409-417. https://doi.org/10.1016/S0969-6997(02)00043-1
  29. Gustafsson, A., Ekdahl, F., & Edvardsson, B. (1999). Customer focused service development in practice-a case study at scandinavian airlines system (SAS). International Journal of Service Industry Management, 10(4), 344-358. https://doi.org/10.1108/09564239910282299
  30. Hagberg, J., & Kjellberg, H. (2020). Digitalized Markets. Consumption Markets & Culture, 23(2), 97-109. https://doi.org/10.1080/10253866.2020.1694209
  31. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate Data Analysis (6 th Edition). Upper Saddle River, New Jersey, USA: Pearson Prentice Hall.
  32. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed, a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202
  33. Holloway, S. (2008). Straight and level: Practical airline economics (3rd ed.). Oxon, OX, UK: Ashgate Publishing.
  34. International Air Transport Association (2020, January). Together, Let’s Build Airline Retailing: NDC Program Update. https://www.iata.org/contentassets/6de4dce5f38b45ce82b0db42acd23d1c/ndc-standard-presentation.pdf
  35. International Air Transport Association (2022, March). Air Passenger Numbers to Recover in 2024. https://www.iata.org/en/pressroom/2022-releases/2022-03-01-01/
  36. International Air Transport Association (2022, December). Air Passenger Market Analysis: The year ends on a strong note for the global industry. https://www.iata.org/en/iata-repository/publications/economic-reports/air-passenger-market-analysis---december-2022/
  37. Jeng, S. P. (2016). The influences of airline brand credibility on consumer purchase intentions. Journal of Air Transport Management, 55, 1-8. https://doi.org/10.1016/j.jairtraman.2016.04.005
  38. Kim, N. D., Jeon, M. Y., Choi, J. H., Lee, S. J., Kwon, J. Y., Lee, J. Y., Lee, H. E., Han, D. H., Lee, H. W., & Chu, Y. R. (2022). Trend Korea 2023. Seoul, Korea: Mirae book. 
  39. Korea Civil Aviation Association (2023, January). Aviation Statistics. https://www.airportal.go.kr/knowledge/statsnew/main.jsp#
  40. Kotler, P., & Keller, K. L. (2016). Marketing Management (14th Global Edition). London, UK: Pearson Education.
  41. Lee, C. K., Ng, K. K. H., Chan, H. K., Choy, K. L., Tai, W. C., & Choi, L. S. (2018). A multi-group analysis of social media engagement and loyalty constructs between full-service and low-cost carriers in Hong Kong. Journal of Air Transport Management, 73, 46-57. https://doi.org/10.1016/j.jairtraman.2018.08.009
  42. Leong, L. Y., Hew, T. S., Lee, V. H., & Ooi, K. B. (2015). An SEM-artificial-neural network analysis of the relationships between SERVPERF, customer satisfaction and loyalty among low-cost and full-service airline. Expert Systems with Applications, 42(19), 6620-6634. https://doi.org/10.1016/j.eswa.2015.04.043
  43. Leontitsis, A., & Pagge, J. (2007). A Simulation Approach on Cronbach's Alpha Statistical Significance. Mathematics and Computers in Simulation, 73(5), 336-340. https://doi.org/10.1016/j.matcom.2006.08.001
  44. Low, G. S., & Lamb, C. W. (2000). The Measurement and Dimensionality of Brand Associations. Journal of Product & Brand Management, 9(6), 350-370.
  45. Mele, C., Spena, T.R., Kaartemo, V., & Marzullo, M. L. (2021). Smart Nudging: How cognitive technologies enable choice architectures for value co-creation. Journal of Business Research, 129, 949-960.
  46. Mikulic, J., & Prebezac, D. (2011). What drives passenger loyalty to traditional and low-cost airlines? A formative partial least squares approach. Journal of Air Transport Management, 17(4), 237-240. https://doi.org/10.1016/j.jairtraman.2010.09.005
  47. Monoarfa, T., Usman, O., & Tausyanah, T. (2020). The implication of AIRQUAL and brand credibility on passengers' satisfaction in airlines industry. Management Science Letters, 10(15), 3655-3662. https://doi.org/10.5267/j.msl.2020.6.028
  48. Nadiri, H., Hussain, K., Ekiz, E. H., & Erdogan, S. (2008). An investigation on the factors influencing passengers' loyalty in the North Cyprus national airline. The TQM Journal, 20, 265-280. https://doi.org/10.1108/17542730810867272
  49. Nunkoo, R., Teeroovengadum, V., Ringle, C. M., & Sunnassee, V. (2020). Service quality and customer satisfaction: The moderating effects of hotel star rating. International Journal of Hospitality Management, 91, 102414.
  50. Nyadzayo, M. W., & Khajehzadeh, S. (2016). The antecedents of customer loyalty: A moderated mediation model of customer relationship management quality and brand image. Journal of Retailing and Consumer Services, 30, 262-270. https://doi.org/10.1016/j.jretconser.2016.02.002
  51. Pan, J. Y., & Truong, D. (2018). Passengers' intentions to use low-cost carriers: An extended theory of planned behavior model. Journal of Air Transport Management, 69, 38-48. https://doi.org/10.1016/j.jairtraman.2018.01.006
  52. Park, J. W., Robertson, R., & Wu, C. L. (2004). The effect of airline service quality on passengers' behavioural intentions: a Korean case study. Journal of Air Transport Management, 10(6), 435-439. https://doi.org/10.1016/j.jairtraman.2004.06.001
  53. Petrick, J. F. (2004). The roles of quality, value, and satisfaction in predicting cruise passengers' behavioral intentions. Journal of Travel Research, 42(4), 397-407. https://doi.org/10.1177/0047287504263037
  54. Radovic-Markovic, M., Farooq, M. S., & Markovic, D. (2017). Strengthening the resilience of small and medium-sized enterprises. In: Management, Enterprise and Benchmarking in the 21st Century IV. Presented at the Management, Enterprise and Benchmarking in the 21st Century. Obuda University, Budapest, 345-356.
  55. Ranaweera, C. (2007). Are satisfied long-term customers more profitable? Evidence from the telecommunication sector. Journal of Targeting, Measurement and Analysis for Marketing, 15(2), 113-120. https://doi.org/10.1057/palgrave.jt.5750038
  56. Ruvio, A., & Shoham, A. (2007). Innovativeness, Exploratory Behavior, Market Mavenship, and Opinion Leadership: An Empirical Examination in the Asian Context. Psychology & Marketing, 24(8), 703-722. https://doi.org/10.1002/mar.20180
  57. Santos, J. R. A. (1999). Cronbach's alpha: A tool for assessing the reliability of scales. Journal of Extension, 37(2), 1-5.
  58. Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students. London, UK: Pearson Education.
  59. Schermelleh-Engel, K., Moosbrugger, H., & Muller, H. (2003). Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures. Methods of Psychological Research Online, 8(2), 23-74.
  60. Seiders, K., Voss, G. B., Grewal, D., & Godfrey, A. L. (2005), Do satisfied customers buy more? Examining moderating influences in a retailing context. Journal of Marketing, 69(4), 26-43. https://doi.org/10.1509/jmkg.2005.69.4.26
  61. Sohaib, M., & Rehman, U. A. (2016). Underlying Effect of customer satisfaction on repurchase intentions: mediating role of trust and commitment. European Journal of Business and Management, 8(10), 105-115.
  62. Sultan, F., & Simpson, M. C. (2000). International service variants: airline passenger expectations and perceptions of service quality. Journal of Services Marketing. 14(3), 188-216. https://doi.org/10.1108/08876040010327211
  63. Taneja, N. K. (2016). Looking beyond the runway: Airlines innovating with best practices while facing realities. Oxon, OX, UK: Routledge. https://doi.org/10.4324/9781315107028
  64. Taneja, N. K. (2017). 21st century airlines: Connecting the dots. Oxon, OX, UK: Routledge. https://doi.org/10.4324/9781315107028
  65. Tarhini, A., Teo, T., & Tarhini, T. (2016). A cross-cultural validity of the E-learning acceptance measure (ElAM) in Lebanon and England: A confirmatory factor analysis. Education and Information Technologies, 21, 1269-1282. https://doi.org/10.1007/s10639-015-9381-9
  66. Thompson, B. (2005). The loyalty connection: Secrets to customer retention and increased profits. RightNow Technologies & CRMguru, 18.
  67. Truong, D., Pan, J. Y., & Buaphiban, T. (2020). Low cost carriers in Southeast Asia: How does ticket price change the way passengers make their airline selection?. Journal of Air Transport Management, 86, 101836. https://doi.org/10.1016/j.jairtraman.2020.101836
  68. Vlachos, I., & Lin, Z. (2014). Drivers of airline loyalty: evidence from the business travelers in China. Transportation Research Part E: Logistics and Transportation Review, 71, 1-17. https://doi.org/10.1016/j.tre.2014.07.011
  69. Wang, S. M., & Lee, H. C. (2018). Effects of airline brand attitude on customer satisfaction and intention to reuse. Journal of the Korean Society for Aviation and Aeronautics, 26, 91-100. https://doi.org/10.12985/ksaa.2018.26.4.091
  70. Winit, W., Gregory, G., Cleveland, M., & Verlegh, P. (2014). Global vs local brands: how home country bias and price differences impact brand evaluations. International Marketing Review, 31(2), 102-128. http://dx.doi.org/10.1108/IMR-01-2012-0001
  71. Wu, P. C., Yeh, G. Y. Y., & Hsiao, C. R. (2011). The effect of store image and service quality on brand image and purchase intention for private label brands. Australasian Marketing Journal, 19(1), 30-39. https://doi.org/10.1016/j.ausmj.2010.11.001
  72. Wu, H. C., & Cheng, C. C. (2013). A hierarchical model of service quality in the airline industry. Journal of Hospitality and Tourism Management, 20, 13-22. https://doi.org/10.1016/j.jhtm.2013. 05.001
  73. Yamamoto, K., & Onodera, T. (1999). Structural Equation Modelling by Amos and case analyses. Kyoto, Japan: Nakanishiya Syuppan.