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Article

The Relationships among Perceived Value, Intention to Use Hashtags, eWOM, and Brand Loyalty of Air Travelers

by
Haeok Liz Kim
and
Sunghyup Sean Hyun
*
School of Tourism, Hanyang University, Seoul 04763, Korea
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(22), 6523; https://0-doi-org.brum.beds.ac.uk/10.3390/su11226523
Submission received: 27 September 2019 / Revised: 9 November 2019 / Accepted: 11 November 2019 / Published: 19 November 2019
(This article belongs to the Special Issue Influencing Factors of Traveler Loyalty for Destination, Company, and Brand)
Browse Figure
Versions Notes

Abstract

:
This study analyzed the relationships between utilitarian value, hedonic value, intention to use an airline’s social networking service (SNS) hashtag, electronic word of mouth (eWOM), and brand loyalty. A research survey consisting of 220 samples was conducted with respondents who had experience using airline SNS hashtags. Finally, 204 answers were analyzed after excluding 16 unreliable answers. The results show that utilitarian value significantly influenced the intention to use hashtags, while hedonic value, intention to use, and eWOM had no significant effect on brand loyalty. Moreover, the correlation between utilitarian value and intention to use indicated that hashtags had a meaningful impact. However, hedonic value, intention to use, and eWOM were relatively inconsequential. This research ascertained behavioral intention based on previous studies of the theory of perceived value (utilitarian value and hedonic value) and the relationships between each variable. In addition, by analyzing the behavioral intention of customers from an airline perspective, it contributes to a more effective marketing strategy based on social curation. Thus, this research facilitates practical applications by finding a method to improve airline customers’ SNS activity and involving the brand loyalty of its customers.

1. Introduction

At the beginning of the 21st century, blogs became one of the most popular social media formats. People could communicate by posting an article online or providing feedback as readers [1,2].
As the internet environment developed, social network services (SNS) have grown more active due to the increased number of smartphone users. Social media has been known as a catalyst of change that enables immediate global communication and that can leverage technology to share content, opinions, experiences, insights, and media. [3,4]. Additionally, social media has influenced consumer behavior from information acquisition to post-purchase behavior, such as through statements of dissatisfaction [5,6].
This study contributes to existing research on the behavior of consumers on social media by comprehensively examining the ways in which consumers interact with brands in this environment. Research has been conducted on social media and customer loyalty in various fields.
In a previous study, Van Asperen, de Rooij and Dijkmans (2018) studied the association between social media engagement and customer loyalty. This study investigated two dimensions of customer loyalty—affective loyalty and conative loyalty—while distinguishing two types of social media engagement—consuming engagement and contributive engagement. The results showed a partial positive relationship between social media engagement and customer loyalty [7].
Mobile SNS marketing is considered a very important issue in the aviation industry, as high-speed internet on smartphones has become ubiquitous with the development of information technology. Smartphone users can now effortlessly find airline-related information on SNS, thus causing the aviation industry to encourage users to access airline information through social media, as it enables two-way communication between the airlines and their consumers.
In highly competitive environments, industries adopt new marketing strategies so that their new products can appeal to consumers [8]. Social media is playing an important role in this new era of marketing competition.
In recent years, the use of social media platforms as marketing channels has burgeoned due to its ability to reach millions of customers and generate engagement [8,9]. With this expansion of social media marketing channels, consumers must undertake the task of screening out the information they need in a flood of marketing. Both consumers and companies need a way to select information from SNS as well. Most companies recognize the value of a “curation service” as a means of forming a brand relationship with customers, but they cannot attempt a systematic approach in building trust with consumer [10]. Based on these reasons, this study recognizes the importance of “curation services” and aims to analyze the various types of such services that customers have been recently using.
The amount of information transmitted through SNS is rapidly increasing and this type of big data environment, in which an overabundance of data is produced, constitutes an information overload [11]. This vast amount of information is so volatile that it is difficult to know its source over time, as with simple recommendations and search functions [12].
Therefore, in the SNS field, the hashtag (HashTag) function—which helps the user search for interests—is emphasized as an important problem in the development of a social curating mechanism [13,14]. A hashtag allows for the ability to view posts uploaded with the same hashtag if it is posted using the “#” (hash) symbol [6,9,13,15,16]. In major SNS (Facebook, Instagram, and Twitter), the “#” symbol is used to search for desired words and information [13,17]. Today, SNS users also utilize hashtags to make airline information useful.
The purpose of this study was to investigate the influence of airline users’ perceived value on intention to use hashtags and to analyze the relationships between the intention to use hashtags, electronic word of mouth (eWOM), and the brand loyalty of air travelers. In the study by Joun and Koo (2017), the effect of hedonic and utilitarian value on the continued use of hashtags was studied, and its results depicted that perceived value had a significant effect on the intention to use hashtags [13]. Dimitriu and Guesalaga (2017) also studied consumers’ social media brand behaviors and delivered important axioms for segmentation of consumers in the social media environment by dividing them into brand tacit engagement, brad exhibiting, brand patronizing, and brand deal seeking [18].
However, in tourism, there is a lack of understanding of social curation services using hashtags. Recently, research on the use of hashtags to collect and acquire tourist information has grown in relevance [13,19]. The purpose of this study was to investigate the effect of utilitarian and hedonic values on the intention to use a social curriculum based on the perceptual value theory. Furthermore, this study analyzes the effects of social curation and the intention to use hashtags on eWOM and brand loyalty.

2. Literature Review

2.1. Perceived Value (Utilitarian/Hedonic)

Perceived value is defined as the consumer’s overall assessment of a product or service based on their perceptions of what is received and what is given [20,21]. It involves an evaluation of all the services they can receive when purchasing a product [15,22]. The degree of perceived value has a direct effect on the behavior of the user purchasing the product [23]. Zeithaml (1988) argued that perceived values are personal and subjective and consumers perceive them differently depending on their situation [21].
Utilitarian and hedonic constructs are two dimensions of consumers’ attitudes toward intention to buy. Utilitarian constructs are the rational, goal-oriented, and functional responses, while hedonic constructs relate more to immediate and affective responses [24].
Marketing literature often emphasizes the necessity of utilitarian values more inevitable practical properties, potentially including both loss and gain, while the hedonic value is more pleasure-oriented, and empirical attributes only provide profit [2,25]. Chernev (2004) argued that promotion-focused goals are better matched with hedonic value, while a prevention focus is more likely to fit utilitarian value [2,26]. Also, Hong, Lin, & Hsieh (2017) argued that the hedonic and utilitarian values had a significant impact on customers’ intention to continue using the smartwatch [4].

2.2. Social Curation (Hashtags)

Since the late 60s, curation is a term derived mainly from the position of “curator”—which is typically found in the art industry [27]. Social curation means that users collect information about the topics they are interested in, sort them, and then share related content—which they find valuable—with other users [11,28].
A Social Curation Service is a combination of a curation service and social network service (SNS). Thus, it provides value by filtering information from big data [29]. Hashtags are an example of optimization for social curation, because it provides the ability to select keywords that interest you and retrieve the posts containing them, thus maximizing the social curation function [14]. The content creator directly uses the hashtag to recommend filtered content as a social curator. People often use hashtags to search for research or to explore their interests [30].
Joun and Koo (2017) studied the relationship between the positive/negative aspects of the use and satisfaction theory and SNS fatigue factors with the aim of using hashtags—a key function of social curation in obtaining tourism information. The results showed that the use of hashtags had the highest effect on the information behavior related to tourism leisure and that hashtags were a useful tool to obtain tourism-related information. Moreover, they suggested that hashtags have been appropriately used to relieve people’s boredom, loneliness, and tension [13].
Hashtags have been widely adopted by many other popular social media platforms, including Instagram, Facebook, WeChat, and LinkedIn [31]. Consumers use hashtags to search brand names, tag brands, and to engage with brands [30].

2.3. Intention to Use

According to studies in marketing and information management, the success of a product or service is determined by continued use and the consumer’s intention to use the product is determined by satisfaction with its quality and perceived usefulness [32]. Intention to use is the perceived likelihood of a user engaging in a given behavior and the likelihood of the engagement in system use [33].
The relationship among attitudes toward a given behavioral intention to use is evident in the consumer behavior model [34,35]. The mobile use context is defined as people using their mobile device in diverse environments [36]. This indicates that time pressure and location affect the intention to use and attitude [36].
Ayeh, Au, and Law (2013) studied the Technology Acceptance Model (TAM) to find intention to use of travelers’ Consumer-Generated Media (CGM) for travel planning using a Partial Least Squares (PLS) estimation [37]. The study concluded that the hedonic value of using social media, which represents perceived enjoyment, is much more influential in determining travelers’ intention to use Consumer-Generated Media (CGM) for travel planning [37]. Hong, Lin, and Hsieh (2017) studied the relation between consumer innovativeness on perceived value and the continued intention to use smartwatches [24]. They found that the continued intention to use was significantly affected by the hedonic value and utilitarian value of the product. It means that consumer’s behavioral intent to use the smartwatch is directly proportional to its hedonic value and utilitarian value [24]. Integrating the empirical and theoretical backgrounds, the hypotheses are presented as follows.
Hypothesis 1.
Utilitarian value has a positive influence on intention to use hashtags.
Hypothesis 2.
Hedonic value has a positive influence on intention to use hashtags.

2.4. eWOM (Electronic Word of Mouth)

The sharing of content online is considered eWOM [20,38]. E-commerce has become a business strategy and eWOM has been conceptualized with web development [29]. Trusov et al. (2009) argued that the impact of word-of-mouth via social networks is stronger than traditional marketing communications [18,39]. Since eWOM is visual and shared with many people, it is perceived as more potentially dangerous than one-on-one social contact [40]. However, the frequency of individual WOM generation in online social networks positively affects the strength of network relationships with others and the level of mutual trust and influence [41]. Participation in online word-of-mouth activities can reduce social anxiety associated with social ties. Sharing negative experiences warns others not to make similar choices, while positive eWOM can guide people’s purchase decisions [42]. Companies should target consumers with an individualistic self-view to improve WOM activity about their brands and products [12].
Kim (2017) studied the relationships among the valence of a restaurant’s service experience, purchase involvement on consumer motivation, and the intention to engage in eWOM. The study found that highly engaged customers are more willing to offer eWOM regarding negative experiences, and this negative eWOM can significantly influence companies [43]. Based on this theoretical background, the following hypothesis was derived:
Hypothesis 3.
Intention to use hashtags has a positive influence on eWOM.

2.5. Brand Loyalty

According to the American Marketing Association (2004), brands are defined as “a combination of names, terms, signs, symbols, designs or other attributes that are intended to distinguish them from other goods and services with their competitors [44].”
Oliver (1999) defined brand loyalty as “a deeply held commitment to buy or patronize a preferred product or service consistently in the future, thereby causing repetitive same brand or same brand set purchasing, despite situational influences and marketing efforts having the potential to cause switching behavior [45].”
Brands want to increase brand loyalty by creating long-lasting and committed relationships with consumers [46,47,48]. Consumers who are loyal to a particular brand continue to use the product or service provided through their commitment to the brand despite the aggressive marketing of other brands [45]. Brand loyalty entails a psychological commitment to consistently purchase products of the same brand and consistently repurchase or re-sponsor the preferred products in the future [45,49]. In addition, it is defined as a multidimensional concept that includes a positive attitude toward a specific brand, reinforcement of past purchasing experience, and positive feelings—not simply repetitive purchases. A study by Cho, Kyung-hee, and Kim (2005) showed that the expression of customer satisfaction on SNS has a positive effect on airline brand loyalty [50]. Adapting the existing literature review into the brand loyalty context, a hypothesis is presented as follows.
Hypothesis 4.
eWOM has a positive influence on brand loyalty.

2.6. Research Model and Hypotheses

A research model was developed based on the literature review discussed, and Figure 1 shows the proposed model. The hypotheses are composed of four items, relationships among perceived value (utilitarian, hedonic), intention to use, eWOM, and brand loyalty.
Hypothesis 1.
Utilitarian value has a positive influence on intention to use hashtags.
Hypothesis 2.
Hedonic value has a positive influence on intention to use hashtags.
Hypothesis 3.
Intention to use hashtags has a positive influence on eWOM.
Hypothesis 4.
eWOM has a positive influence on brand loyalty.

3. Methods

3.1. Measures

The items of validated measurement were adopted from previous studies [13,18,29,49]. Perceived (utilitarian and hedonic) value used four items from Joun and Koo [24]. Intention to use was measured using items adopted from Wang et al. [32,34,38,51], which includes the overall intention to use (e.g., I will continue to use hashtags). A total of three items were adopted from Kim, Kandampully, and Bilgihan et al. [1,29,39,50] for eWOM, which includes eWOM information (e.g., I tell other people about the positive information, and eWOM information affects my purchase decisions). Lastly, to measure brand loyalty, three items were used from Oliver et al. [6,18,49], (e.g., using hashtags is an important part of my life). At the beginning of the survey, participants were given the definition of social curation as follows:
“Social curation is a form in which a lot of information produced by services such as SNS is automatically filtered through hashtags or keywords entered by the user, and users share additional information by reselecting existing information. A variety of uploaded information are classified into topics of interest, and this information is sorted and organized”.
[13]
Multi-items and five-point Likert scale (from 1 = strongly disagree to 5 = strongly agree) were used to analyze proposed variable in this questionnaire. This study used non-probabilistic sampling based on the researcher’s subjective judgment. Convenience sampling was used in this study, as the population of consumers using hashtags on airline social media is difficult to identify, specific, and of limited availability [11].

3.2. Survey Questionnaire and Data Collection

The survey questionnaire was first conducted as a pilot test with graduate students who use airline social media. The survey was modified based on their feedback, following which it was further developed through feedback and peer reviews in the hospitality field. This study was conducted on customers who have used airline SNS hashtags, considering their behavioral intentions, and perceived value. Data were collected over two months from April 1, 2018, to May 30, 2018. The questionnaire was randomly distributed face-to-face to 220 people who have experience using airline’s SNS hashtag in Hanyang University’s campus, Seoul, South Korea. Given the fact that student market is emerging marketing in tourism industry, a student sample was used for this study [8,52]. Data collection was conducted on consumers who have experience using hashtags of airline social media. After excluding 16 unreliable answers, and the final questionnaire, a sample size of 204 respondents was analyzed. A total 204 valid questionnaires were subjected to the final analysis through the SPSS/Amos Statistics 22.0 statistical package program.

3.3. Sample Characteristics

The survey and data collection describe the respondents’ demographic profile. Table 1 provides the respondents’ demographic profile. From the 220 responses, the final sample (n = 204) included more females than males. Among the participants, 68.1% were female and 31.9% were male. All the respondents were older than 20; 94.6% of the respondents were between 20 and 29 years of age, while 5.4% reported an age of 30-39 years.
Regarding education, 77.5% of respondents had a high school diploma and 18.6% had a bachelor’s degree. A majority of respondents had a high education level; 77.5% had graduated from college, followed by 18.6% being university students, and 3.9% were graduate degree holders. Regarding occupations, 97.1% were students, 1.0% were professionals, 0.5% worked in business, and 1% were employees. Moreover, the majority of respondents (95.1%) reported a monthly income of under KRW 2,000,000; 1.0% reported an income in the range of KRW 2,000,000–2,999,999; and 4.0% reported an income in the range of KRW 3,000,000–4,999,999 and over per month.

4. Results

4.1. Measurement Model

Table 2 shows the reliability for measurement factor analysis. The perceived value mainly divided utilitarian and hedonic values.
As shown in Table 3, the result of average extracted values (AVE) shows that the figures were all above of 0.600 (Utilitarian values= 0.703, Hedonic value = 0.634, Intention to use = 0.778, Electronic word of mouth = 0.695, Brand loyalty = 0.603). Moreover, these figures were greater than the between-construct correlations (squared) (see Table 3), which provided results of the confirmatory factor analysis to show evidence of discriminant validity.
The measurement model was analyzed using a confirmatory factor analysis (CFA). Based on the CFA results, the model estimated an appropriate fit to the data (χ2 = 243.435, df = 125, p < 0.001, χ2/df = 1.947, RMSEA = 0.066, CFI = 0.940, IFI = 0.941, and TLI = 0.918). All the model values were significant (p < 0.01). The assessment of composite reliability (CR) demonstrated that the figures were all above 0.800 (Utilitarian value = 0.903; Hedonic value = 0.873, Intention to use = 0.908, Electronic word of mouth = 0.872, and Brand loyalty = 0.884), which generated the internal consistency within-construct measurement items.

4.2. Structural Model

The result of the structural model are given below in Table 4. The structural model represented an acceptable fit to the data (χ2 = 239.418, df = 114, p < 0.001, χ2/df = 2.100, RMSEA = 0.074, CFI = 0.931, IFI = 0.933, TLI = 0.908) (see Table 4). The proposed impact of perceived value on intention to use, eWOM, and brand loyalty was assessed. The influence of utilitarian value on intention to use (β = 0.360, p < 0.01) was significant. This result supported hypothesis 1. Meanwhile, the path from hedonic value to intention to use (β = 0.101, p > 0.01) was not significant. Consequently, hypothesis 2 was not supported. Additionally, the path from intention to use to eWOM (β = − 0.002, p > 0.05) was not significant. Therefore, hypothesis 3 was not supported. Finally, the path from eWOM to brand loyalty (β = −0.012, p > 0.01) was not significant. Thus, hypothesis 4 was not supported.

4.3. Indirect and Total Impact

The total effect of the variables was evaluated. As reported in Table 3, utilitarian value (β = 0.360, p < 0.05), hedonic value (β = 0.101, p > 0.05), intention to use (β = −0.002, p > 0.05), and eWOM (β = 0.012, p > 0.05) had no significant influence on brand loyalty. This result shows that the intention to use hashtags (R2 = 0.156) is not related to eWOM and brand loyalty.

5. Discussion

5.1. Conclusions

This study analyzed the relationships among perceived value (hedonic and utilitarian value), intention to use, eWOM, and brand loyalty through examining the significance of their consequences. This study investigated the effect of perceived value on the intention to use SNS tags in airlines, along with its effect on eWOM and brand loyalty. This study shows that consumers aged 20–30 have been using hashtags in airline social media. The measure of consumers’ motivation for using the hashtag was derived from previous studies and empirical analyses of existing social media users.
Joun and Koo (2017) studied the relationship between the positive and negative aspects of the use and satisfaction theory and SNS fatigue factors with the aim of applying hashtags—the key function of social curation in obtaining tourism information [13]. Moreover, previous studies indicated that behavioral intentions to use the smart watch is highly relevant to hedonic value and utilitarian value [24]. Thus, based on these existing studies, we proposed a proposed model and established a research hypothesis by introducing a new variable called hash tag intention.
First, perceived value was divided into utilitarian and hedonic values. Utilitarian value (information gathering using hashtags and providing real-time information) had a significant and positive impact on the intention to use hashtags through airline social media. However, the hedonic value (happy, interested, and pleasure) was not related to the behavioral intention to use the hashtags. For example, when consumers used hashtags in SNS, they were not happy, interested, or satisfied. In other words, consumers use SNS hashtags to access practical marketing information about products. These findings also have an important impact on airline marketing. Consumers who appreciate hedonic value have a significantly lower intention to use airline SNS hashtags.
Secondly, the hypothesis that the intention to use an airline’s hashtag has a significant effect on eWOM was rejected. This means that consumers do not directly use SNS hashtags for advertising and publicizing their preferred company online.
Finally, the effect of eWOM on brand loyalty was not significant. It was shown that eWOM activities using hashtags are not closely related to brand loyalty. This study implies that hashtags are SNS activities used by specific demographics. In addition, hashtags are a social curation method that is presently unfamiliar to many. The results of this study found that hypothesis 2, hypothesis 3 and hypothesis 4 did not support Joun and Koo (2017) and Hong, Lin, and Hsieh (2017)’s previous studies.

5.2. Implications for Theory and Practice

This study analyzed consumer behavior with respect to the intention to use hashtags based on the theory of perceived value. To date, research on this theory and the behavioral intention to use had been conducted extensively by many scholars in marketing. This study analyzed consumer behavior by factoring SNS activities of consumers into the theory. It was conducted on consumers who have used SNS in the hospitality industry. In addition, this study is meaningful because it makes consumers familiar with hashtags and their function of “social curation”—which was previously largely unfamiliar.
The theoretical implications of this study were to investigate the relationships between intention to use hashtag, eWOM, and brand loyalty by analyzing consumers’ behavioral intentions based on perceived value theory. This study analyzed the effect of perceived value on consumers’ intention to hashtag by dividing perceived value of consumers into utilitarian and hedonic value. The purpose of this study was to analyze consumers’ behavioral procedures for acquiring the necessary information from social media. This study points out that social media information is plentiful and suggests that consumers use and control selected information through social curation.
The results of this study emphasize that the development of technology and science can be utilized positively in airline social marketing through the benefits of real life. However, only utilitarian value had a significant effect on the intention to use hashtags and consumers using hashtags did not significantly contribute to the electronic word of mouth effect and brand loyalty.
Hypothesis 2 was rejected because consumers using airline social media use hashtags rather than hedonic values to focus on the utilitarian value. Moreover, hypothesis 3 was rejected because consumers using airline social media hashtags did not contribute to brand loyalty through online word of mouth.
A study by Eisingerich et al. (2015) found that the word of mouth on online social sites are different from the traditional word of mouth and recommended marketing face-to-face rather than through Facebook. Thus, hypothesis 3 supports previous studies by Eisingerich et al. (2015).
Beyond the theoretical meaning, the results of this study reveal interesting practical implications for airline marketing managers. In particular, the results show that hedonic value has a negative impact on the intention to use hashtag. Therefore, airline mangers should improve their marketing strategies based on utilitarian information such as information gathering using hashtags and providing real-time information. In particular, the practical implications of this study are as follows.
First, airline social media must understand the consumer behavior through the behavior of airline customers who visit airline brand pages to find and update information. Therefore, airline social media marketing strategies should be updated to reflect this by facilitating customer communication.
Secondly, the two-way communication enabled by social media can help disseminate airline-related information with consumers, who could subsequently provide feedback—potentially improving the airline’s eWOM. Thus, airlines must communicate with customers in real time through SNS and reflect the customer’s opinions.
Third, this study supports hypothesis 1 and recognized that utilitarian value should be emphasized in airline SNS marketing. As a result, airlines need to be aware of the importance of hashtags that consumers often use on Instagram, Facebook, and Twitter. Thus, airline online marketing teams should stop utilizing unnecessary and lengthy commentary-oriented text and promote primarily using pictures and simple text.
Finally, this study suggests that customers should utilize airline social media to reflect their needs and trends. As a result, this study intends to provide practical solutions for brand loyalty plans that improve brand image by building effective social media marketing strategies for airlines.

5.3. Limitations and Future Research

This study has the following limitations. First, the research sample was not general enough because the target population of the questionnaire was limited to the people in their twenties or thirties. As the questionnaire period was only one month, the survey was limited in its demographic scope.
For this study, it was necessary to conduct research on customers who have some experience using airline social media, so the actual age of the users is mostly those in their twenties. In order to reflect opinions of various ages, future research will need to establish a longer survey period.
In addition, this study had a significantly higher proportion of female respondents. Demographic characteristics should be supplemented so that gender can be distributed evenly in future studies. However, the questionnaire of this study was conducted in a short time, so that the sample was not evenly distributed.
Based on these limitations, future research is required to extend and verify the proposed model with different population groups. As the number airline social media users continues to increase, it is also valuable for future research to identify whether airline travelers have tried airline SNS information and used hashtags. Despite the increase in airline customers using social media, there is a lack of research on social media regarding the hospitality industry. Thus, research of behavioral intention between social media and tourism consumers should be actively conducted in the field of hospitality.
Additionally, as technology and science develop, companies immediately adapt and exploit trends. Recently, companies have been using social curation to cope with information overload. The importance of social curation has been emphasized with the increase of consumers using hashtags, but research on social curation is presently uncommon. Therefore, practical research on social curation and hashtags should be pursued academically. The increase in the research on social curation will contribute to the development of the hospitality marketing field by effectively analyzing and utilizing the behavioral intention of SNS users.

Author Contributions

Supervision, Writing, Data Collection—S.S.H.; Writing, Research Design, Data Analysis, Revision—H.L.K.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 11 06523 g001 550
Figure 1. The proposed model.
Figure 1. The proposed model.
Sustainability 11 06523 g001
Table
Table 1. The respondents’ demographic profile.
Table 1. The respondents’ demographic profile.
Sociodemographic VariableNPercentage
GenderMale6531.9%
Female13968.1%
Education levelUnder associate’s degree15877.5
Bachelor’s degree3818.6
Graduate degree and over83.9
IncomeUnder KRW 2,000,00019495.1
KRW 2,000,000–2,999,99921.0
KRW 3,000,000–3,999,99931.5
KRW 4,000,000–4,999,999 and over 52.5
Table
Table 2. Reliability for measurement factors analysis.
Table 2. Reliability for measurement factors analysis.
Factor (α)Construct and Scale ItemsMeanS.D.F.L
Utilitarian valueI use hashtags in SNS to easily see information.3.460.8440.622
Information gathering using hashtags is useful.3.510.7720.865
Hashtags makes it easy to get information.3.640.7600.830
Hashtags are practical as they provide real-time information.3.650.7960.768
Hedonic valueI am happy to see and search for hashtags in SNS.3.180.9510.840
I am very interested in using hashtags.3.200.8940.848
It is a pleasure to search for my interest areas using hashtags in my spare time.3.181.0030.727
Hashtags help me to get access to lots of interesting posts.3.570.8760.670
Intention to use
hashtags		I will continue to use hashtags.3.820.7500.818
I will use hashtags in the future to find information.3.890.7421.018
I will repurchase products using hashtags.3.730.7520.561
eWOMI refer to eWOM information when making a purchase decision.3.201.0130.812
eWOM information affects my purchase decisions.3.200.9490.902
I tell other people about positive information about airlines.3.160.9410.754
Brand loyaltyUsing hashtags is an important part of my life.3.120.9910.881
I have an emotional attachment to this company’s hashtags.2.710.9530.877
I am going to continue to use the company’s hashtags because it is helpful.3.000.985734
Table
Table 3. Results of the confirmatory factor analysis (n = 204).
Table 3. Results of the confirmatory factor analysis (n = 204).
Research Variables12345CRAVE
1. Utilitarian value1.000––––0.9030.703
2. Hedonic value0.311 a
(0.558) b		1.000–––0.8730.634
3. Intention to use0.144
(0.037)		0.091
(0.301)		1.000––0.9080.778
4. eWOM0.053
(0.230)		0.027
(0.164)		0.013
(0.112)		1.000 –0.8720.6950
5. Brand loyalty0.019
(0.139)		0.100
(00.317)		0.061
(0.246)		0.048
(0.219)		1.000 0.8840.603
Note. Goodness-of-fit statistics for the measurement model: χ2 = 243.435, df = 125, p < 0.001, χ2/df = 1.947, RMSEA = 0.066, CFI = 0.940, IFI = 0.941, TLI = 0.918, a Correlations between constructs, b Squared correlations.
Table
Table 4. Results of the structural equation modeling (n = 204).
Table 4. Results of the structural equation modeling (n = 204).
HypothesesPathst-ValuesCoefficientsResult
Hypothesis 1Utilitarian value → Intention to use3.242 **0.306Supported
Hypothesis 2Hedonic value → Intention to use1.5030.131Not supported
Hypothesis 3Intention to use → eWOM−0.025−0.002Not supported
Hypothesis 4eWOM → Brand loyalty−0.174−0.014Not supported
Note. Goodness-of-fit statistics for the structural model χ2 = 239.418, df = 114, p < 0.001, χ2/df = 2.100, RMSEA = 0.074, CFI = 0.931, IFI = 0.933, TLI = 0.908 (* p < 0.05, ** p < 0.01).

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Kim, H.L.; Hyun, S.S. The Relationships among Perceived Value, Intention to Use Hashtags, eWOM, and Brand Loyalty of Air Travelers. Sustainability 2019, 11, 6523. https://0-doi-org.brum.beds.ac.uk/10.3390/su11226523

AMA Style

Kim HL, Hyun SS. The Relationships among Perceived Value, Intention to Use Hashtags, eWOM, and Brand Loyalty of Air Travelers. Sustainability. 2019; 11(22):6523. https://0-doi-org.brum.beds.ac.uk/10.3390/su11226523

Chicago/Turabian Style

Kim, Haeok Liz, and Sunghyup Sean Hyun. 2019. "The Relationships among Perceived Value, Intention to Use Hashtags, eWOM, and Brand Loyalty of Air Travelers" Sustainability 11, no. 22: 6523. https://0-doi-org.brum.beds.ac.uk/10.3390/su11226523

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