Next Article in Journal
Deconstructing the Overtourism-Related Social Conflicts
Next Article in Special Issue
Topic Modeling of Online Accommodation Reviews via Latent Dirichlet Allocation
Previous Article in Journal
What Teachers Think and Know about Education for Sustainable Development and How They Implement it in Class
Previous Article in Special Issue
Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 12
Issue 4
10.3390/su12041691
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Effect of Social Media Usage Characteristics on e-WOM, Trust, and Brand Equity: Focusing on Users of Airline Social Media

by
Eun Ju Seo
1,
Jin-Woo Park
2,* and
Yu Jin Choi
3
1
International Service Office Incheon, Asiana Airlines, Incheon 22382, Korea
2
School of Business, Korea Aerospace University, Goyang-si 10540, Korea
3
Airport Industry Technology Research Institute, Incheon International Airport Corporation, Incheon 22384, Korea
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(4), 1691; https://doi.org/10.3390/su12041691
Submission received: 6 January 2020 / Revised: 21 February 2020 / Accepted: 21 February 2020 / Published: 24 February 2020
(This article belongs to the Special Issue Sustainable Tourism in the Social Media and Big Data Era)
Browse Figures
Versions Notes

Abstract

:
Brand equity is a valuable intangible asset for companies, yet is increasingly difficult in managing in an era with hard to control social media. The purpose of this study was to investigate the effect of social media usage characteristics on electronic word-of-mouth (e-WOM), trust, and brand equity by dividing the characteristics to personality, social, and information. A survey was administered to 430 respondents who had experience of using airline social media and the collected data was analyzed using structural equation modeling. The results showed that the personality and informational characteristics from social media usage had statistically significant effects on e-WOM. It was found that the e-WOM had significant effects on trust and also on brand awareness. The trust was shown to have a statistically significant effect on brand awareness and brand image. Therefore, this study categorizes social media usage characteristics into three characteristics: personality characteristics, social characteristics, and information characteristics, and each of these usage characteristics present a strategy to improve actual brand equity of airline through e-WOM and trust in empirical methods. The findings of this study are expected to provide fundamental data for the development of strategies related to airline social media. In addition, this study has implications for suggesting to improve brand equity through e-WOM and trust.

1. Introduction

Social media is a space that allows consumers to discuss freely exchanged opinions. These interactions between consumers in social media are fundamentally changing the communication between brands and customers [1,2]. Social media has dramatically changed the process for how brand contents is created distributed and consumed, and has made it possible for the brand images created by marketers to be delivered online via consumers [2,3,4]. Social media is also fundamentally changing the way consumers acquire the information they want, how they buy products, and how they discuss social issues and pursue social change.
In the past, the public mostly relied on the service of travel products offered by travel agencies for overseas trips, but nowadays, the range of choices for travel destinations, hotel reservations, and flight ticket purchases have become diversified and subdivided through social media and the Internet. There has been a rapid increase in the number of cases where travel plans are set up, flight tickets are purchased, and hotel rooms are reserved through various travel information delivered through social media. In addition, information can be viewed and shared at any time or place so people are making faster decisions while preparing for overseas trips.
According to Socialbakers’ statistics on usage levels of social media in the aviation industry based on Facebook fans as of June 2019, Qatar Airways has the world’s largest number of fans, at 14 million followed by KLM with about 13 million. Compared to foreign cases, the usage of social media in marketing and the awareness of its importance in Korean airlines seem to be very low, considering the small size of fans (Asiana Airlines 570,000, Jeju Air 500,000, and Eastar Airlines 470,000). Thus, the use of social media by airlines in Korea is limited compared to that of overseas airlines. Major Korean airlines have official social media accounts, but their activities and marketing are less active than overseas. The use of airline social media by passengers is likely to increase continuously and so will the importance of social media in airline marketing.
Unlike other industries, the products of the airline industry consist of seats and service, which are material and intangible as comprehensive service ones, so there are no leftover stocks and the produced amount cannot be controlled. Even if products are not made or sold, it carries a unique characteristic where a definite amount of expense is spent, so it is important to attract potential customers through different marketing activities and, in the long term, enhance brand values. Seo and Park [5] examined the influence of corporate social media activities on customer response through brand equity in the social media marketing aspect of the airline industry. Studies on social media have been being actively conducted, however few studies have been conducted that systematically characterize the use of social media [6,7,8,9,10]. In particular, there is still a lack of research on how the use of social media can have an effect on corporate performance. This study shows that the characteristics of personality, social, and information characteristics in terms of users of social media examined the impact on companies through electronic word-of-mouth (e-WOM). The studies to identify the factors in characteristics of airline social media usage and how those characteristics affect airlines are likely to provide very important implications for developing strategies related to airline social media. The purpose of this study was, therefore, to analyze empirically the effects of the characteristics of airline social media usage on electronic word-of-mouth (e-WOM), trust, and brand equity.

2. Theoretical Background

“Media” is a collective term for tools that mediate human communication [11]. Social media is a concept that encompasses social network services (SNSs) such as Facebook, Twitter, and LinkedIn that share the connections formed through registered personal profiles [12] and is one of the interactive media that has enhanced the function of producing and sharing contents, in addition to the network function of existing SNS [13]. Richter and Koch [14] defined social media as “an online application, platform, and media that facilitate the interaction, collaborative work, and contents sharing”. The marketing activities using social media provide companies with the opportunities to build individual relationships with consumers and to reach closer to them [15]. Social media studies in the tourism industry may be divided, by their perspectives, into consumer and supplier ones, or, by the variables, into ones to identify the prerequisites for using social media and the impact of social media [16,17]. The e-WOM in social media varies depending on the personality characteristics of individual users, social networks, and information characteristics provided. This study, following the findings of previous studies, defines social media usage characteristics as personality, social, and information ones.
The study of personality characteristics centers on predictions of consumer reactions and behaviors in specific consumption situations and has been actively performed in the field of consumer behaviors and consumer psychology [18]. In the field of personality psychology, researchers have studied to discover universal and important characteristics that can distinguish individual differences in human personality, and there are various theories of physiological and developmental aspects of personality characteristics [19,20]. Although the theoretical and methodological underpinnings of the Big Five model are not completely without dispute [21], it is regarded as acknowledging at least some of the essential aspects of personality [22].
Neuroticism is defined as a “measurement of controlling emotion and feeling” [22]. A low level of neuroticism indicates easy control of feelings, while a high level includes acute sensitivity, nervousness, and concern [23]. Extroversion is the positive emotions and feelings that occur in social situations. Those who have low Extroversion (Introversion) tend to be shy and respond in an introversive fashion when meeting or socializing with people [18]. Openness to Experience is an attitude to novel experiences. Those who have a high level of openness are curious, creative and innovative, while those who have a low level show a clear preference for being customary and consistent, and practical and traditional [24,25]. Agreeableness is a concept meaning trust, concern, and generous sentiment toward others or the degree of maintaining a comfortable and harmonious relationship with others. This trait is expressed as trust, empathy, and is contrasted with cynicism, disrespect, and hostility [26]. Conscientiousness refers to the individual tendency to keep rules, norms, principles, and others of the organization. Higher Conscientiousness is associated with stronger self-restraint, ambition, and hard-work [27], and a stronger willingness to complete a task [28].
All members of society may build trust within relationships with their families, work colleagues, neighborhoods, and community groups, and through these social networks, increase their quality of life and reach social achievement. Social capital is formed through these interpersonal or intergroup relationships, a concept that has been studied in many disciplines related to social networks, trust, mutual cognition, and emotional support [29,30,31,32]. Bridging social capital refers to a human network created through voluntary engagement in relationships between individuals from different backgrounds and enables connections between employers regardless of race, gender, occupation, income, and religion [31]. Structural holes are created between members who are not tangled with each other based on interest. Such members do not have a direct relationship and provide a variety of non-overlapping information to each other, and are thus likely to acquire useful new information and knowledge [33]. In contrast, a social network composed of people with similar backgrounds and characteristics, such as family and friends, is referred to as bonding social capital. This relationship is closely linked by sticky emotion, providing emotional support and practical assistance to each other [34]. In this kind of relationship, members are linked by strong internal ties, deep trust, mutual dependence, and active emotion [35]. Bridging social capital is helpful for smooth social activities, while bonding social capital strengthens one’s identity and is essential for complementary relationships [36].
Information can be defined as data where analyzed or contextualized messages are conveyed and differences follow depending on the recognition of the recipients [37], and due to the recent development of social media, the public can approach information more freely so it results in the production and delivery of information that is incomparably massive in quantity compared to the past [38]. The information quantity signifies the actual amount of information [39,40], and it has mostly been researched in two aspects, including the number of choices or the amount of information that is provided for each decision [41]. The information credibility is the most fundamental element of the personal persuasion process [42] and can be defined as the extent to which the recipients recognize that the origin of information has knowledge, skills, and experience related to the product or service and will provide unbiased opinions and objective information [43]. The information quality is the extent to which the corresponding information helps a decision maker in evaluating a product or service and defined as the usefulness of the information in decision-making [44].
e-WOM has long been regarded as an influential marketing tool [45] and social media is recognized as the best platform for e-WOM [46,47]. E-WOM is similar to the traditional offline WOM in that it is an interactive communication process for exchanging experiences and information about products or services, while differing from offline WOM in that it is based on the Internet [48]. e-WOM is generally defined as the act of meeting and sharing opinions with each other on the Internet and exchanging the ratings for services [49,50,51], which provide usability, accessibility, and persistence for information that were unavailable in traditional offline WOM [52]. Consumers search for information posted by people who have used a product or service they are planning to purchase in attempts to reduce fear or anxiety about failures by verifying relevant information [53]. The information disseminated through these WOMs tends to be accepted as fair and unexaggerated one [54]. WOM is very important because it shapes consumers’ attitudes toward brands [55]. e-WOM considers positive WOM as expressed in customers’ willingness to recommend the product to others in this study.
Trust is a concept that plays an important role in social and economic interactions in which uncertainty and dependence exist and have been widely studied in various social sciences [56]. Robinson [57] argued that trust is the expectation and belief future behaviors of others will be favorable or, at least, non-hostile. In contrast with these definitions of trust in terms of emotion or psychological state, there are other definitions from the behavioral perspective. Mishra [58] defined trust as a party’s willingness to be vulnerable to another party based on the belief that the other party is competent, open, concerned, and reliable. Trust is basically defined as taking risks, and in some situations, choosing one option in spite of the possibility of loss by others [59]. Consequently, trust has two components as the confident expectations of the brand’s reliability and good intentions to the brand even in unexpected problems [60]. Trust in service providers is an essential factor in determining the quality of successful relationships [61] and is an important variable in forming relationships with customers [62].
The groundwork for customer-based brand equity (CBBE) was set in the early 1990s by Aaker [63] and Keller [64,65] and has received ample attention in many different fields. Keller [64] insisted that customer-based brand equity occurs when the customer is familiar with the brand, and this gives the customers a favorable, powerful, and/or unique memory about the brand image. Keller [64], accordingly, defined brand equity as the customer’s response to brand knowledge and presented the components of brand equity as brand awareness including brand recall, brand recognition, and brand image including the type, preference, strength, and uniqueness associated with the brand. Brand equity may be, therefore, defined as a measure of the favorable outcome in a market that would not have occurred if the product or service had no such brand. Brand equity is formed when customers are aware of the brand and have a unique and positive image associated with the brand [63]. Therefore, brand equity is an important intangible asset of a company and is a higher level of concept than other concepts related to the brand, such as brand love or brand loyalty. In previous studies [66,67], the influence of brand love and brand loyalty on brand equity as parameters were conducted.
Brand awareness is often regarded as a fundamental concept of brand equity because it is an important starting point and the basis of forming brand loyalty by familiarity with a brand generated by brand awareness [68]. Aaker [69] defines brand awareness as a concept that represents the degree to which consumers perceive a brand differently from other brands, and Keller et al. [70] explained that brand awareness is the ability of potential customers to recognize and recall a particular brand in a product category. Brand awareness refers to the consumer’s ability to identify a brand under different environmental conditions, that is, the ability to remember a brand [71], which forms the basis for building an image, attitude, and trust in the brand and is a very important concept in that it is the first step in the purchase where a product or service is included in the consumer’s consideration sets. Brand awareness, therefore, plays a role in providing consumers with confidence in the quality of products with the brand [72].
Brand image is a positive or negative feeling that a consumer has about a brand, confidence in the brand, or a psychological structure of the consumer, and is defined as a set of beliefs that the consumer has about the brand [73]. Low and Lamb [74] insisted that brand image is a belief about the function and symbol of a brand’ and is composed of a symbolic, social, and psychological image. Dobni and Zinkhan [75] defined brand image as logical or emotional perception reflecting the brand association of the consumer. The positive brand image is made possible by a marketing program that connects strong, favorable, and unique associations with the brand in the memory of the consumer and may be generated by, in addition to the information controlled by the marketing manager, various channels such as the direct experiences of consumers, opinions, and WOM of other consumers [65]. Brand image is composed of a combination of physical, emotional, and psychological elements of the consumer, and is created by combining associations with the brand [64].
Consumers with different personalities may respond differently to an identical product or service [76]. Noh et al. [77] examined the influence of WOM by inputting personality traits of users using online in their 20–30s as situation variables. Ju and Suh [78] examined consumer commitment to an online shopping-mall and its effects on WOM intention and reported that the Big Five Personality traits (excluding Openness) had a significant effect on WOM intention through commitment. Bachrach et al. [79], in their study on Facebook and personality factors, investigated the personality, Facebook profile, network size, photos, and number of events and reported that Extroversion was the strongest predictor of WOM intention and followed by Neuroticism, Openness, Conscientiousness, and Agreeableness. This study, based on these previous studies, developed the following hypothesis about the effect of personality characteristics of social media usage of consumers.
Hypothesis 1 (H1).
The personality characteristics of social media usage have a significant positive effect on e-WOM.
The management of e-WOM through social media has a complicated structure inevitably because the users as consumers simultaneously produce the value and meaning of marketing information [80]. It was also suggested that this variable should be measured and expanded at the individual and social levels because the consumers, in e-WOM processes, jointly produce and share social capital [81]. Ellison et al. [12] investigated whether offline social capital is generated also through online tools and demonstrated that SNS plays a role in shaping and maintaining social capital accumulated through relationships between people. Lee [82] studied, focusing on the comparison between Facebook and Twitter, the e-WOM behaviors and demonstrated that the bridging and bonding social capitals had a significant effect on e-WOM where the former had a stronger effect. This study, based on these previous studies on social characteristics, developed the following hypotheses about the effect of social characteristics of social media usage of consumers.
Hypothesis 2 (H2).
The social characteristics of social media usage have a significant positive effect on e-WOM.
Information and consumers have significant effects on e-WOM [83]. As has already been demonstrated in several studies, greater amounts of online reviews lead to more information that consumers acquire about the product or service, resulting in more pervasive e-WOM and higher sales [83,84,85,86]. Wen [87] set online information characteristics as accuracy, vividness, and neutrality in the study on the effect of e-WOM information characteristics on WOM acceptance, WOM spread, and purchase intention by product type, and reported that the accuracy of the information had effects on WOM acceptance, and consequently on WOM spread and purchase intention. In a study measuring the effect of tourism e-WOM information quality and reliability and community interaction on the usefulness of WOM and the WOM effect, it was found that the information quality and information reliability had a positive effect on WOM [88]. This study, based on these previous studies, developed the following hypothesis about the effect of the information characteristics of social media usage of consumers.
Hypothesis 3 (H3).
The information characteristics of social media usage have a significant positive effect on e-WOM.
WOM forms the attitude of consumers toward a brand [55] and the information disseminated through WOMs tends to be accepted as fair and unexaggerated [54]. e-WOM may have a stronger effect compared to offline WOM in some situations. e-WOM is regarded as a reliable and fair source of information, shaping consumer expectations, affecting attitudes, purchasing decisions, and post-evaluation [89]. Ladhari and Michaud [90] studied the influence of e-WOM on hotel booking intentions, attitudes, trust, and website rating, and demonstrated that more positive WOM for hotels has an association with higher trust in hotels. Cha [91] studied the development of a communication paradigm model for the e-WOM of restaurant information and argued that positive e-WOM builds confidence in the sender. Bickart and Schindler [45] investigated Internet forums and reported that Power Blogs act as leaders in online oral communication and that consumers trust information gained from Power Blogs more compared to those from typical company websites, resulting in some effect on brand evaluation.
The most important feature of social media is that users, without constraint on time and place, directly produce and consume desired content. This means that more active and vigorous participation of consumers than company-led one-way communication is possible, and such participation is likely to have strong effects on consumers’ awareness and attitudes toward the brand. The recommendation to other consumers about their experiences after online purchasing or using products or services is a typical process of e-WOM in this digital age and has been continuously expanded [92].
The studies on the relationship between e-WOM and brand equity factors have been performed continued in the service field. Yim [93] demonstrated that e-WOM had a significant effect on brand awareness in a study of family restaurant brands. Kim [94] confirmed that positive WOM activities of marketing communication in the relationship between marketing communication and service brand equity factors had a positive effect on brand awareness and brand image. Godey et al. [6] investigated luxury brands’ social media marketing efforts and demonstrated that e-WOM influenced brand awareness and brand image by classifying the e-WOM as a social media marketing factor. In the aviation industry field, Lee [95] conducted a study on the influence of WOM activities on brand image and brand awareness. This study, based on these previous studies, developed the following hypothesis about the effect of e-WOM.
Hypothesis 4 (H4).
The e-WOM has a significant positive effect on trust.
Hypothesis 5 (H5).
The e-WOM has a significant positive effect on brand awareness.
Hypothesis 6 (H6).
The e-WOM has a significant positive effect on brand image.
According to Forunier et al. [96], as with people engaging with each other in everyday life, consumers engage in personal relationships with the brands they purchase. The trust is part of the brand and consumer relationship and is one of the most influential factors in actual online consumption. Trust is the willingness to trust in, rely on, and exchange with others and, in the situation of dangerous and uncertain services, is a valuable factor for successful long-term relationships [97]. Consumers have a rigid characteristic of not participating in behaviors that they consider to be worthless [98]. Trust is formed through the entire process of recognizing, purchasing, using, and experiencing the brand and is an interaction between consumer and brand at equal positions. Kim et al. [99], in their study on hospital service, argued that brand equity could be formed through customer satisfaction, trust, and commitment, and had a positive effect on improving the overall image of the hospital. Han et al. [100] studied brand equity, brand reputation, and brand trust, and reported that brand awareness had a positive effect on brand trust through brand reputation. Fatma et al. [101], in a study of company reputation and brand equity through company social responsibility activities, found a significant effect of trust on brand equity. Loureiro [102] investigated the brand equity and demonstrated that trust has a positive effect on brand awareness. This study, based on these previous studies, developed the following hypothesis about the effect of trust.
Hypothesis 7 (H7).
The trust has a significant positive effect on brand awareness.
Hypothesis 8 (H8).
The trust has a significant positive effect on brand image.

3. Methodology

The purpose of this study was to identify the influence of personality, social, and information characteristics of social media usage on brand equity through e-WOM and trust. For the purpose, the empirical analysis method using structural equations was performed and, as shown in Figure 1, the research model is presented.
The questionnaire used in this study was prepared by conducting a preliminary survey based on existing literature studies, supplementing, and revising. The items of the questionnaire were classified into personality characteristics (15), social characteristics (8), information characteristics (9), e-WOM (3), trust (3), brand awareness (3), and brand image (3). A total of 44 items were asked. Royse [103] compared the pros and cons of quantitative research and qualitative research, and while quantitative research secures objectivity through theory-based research results, qualitative research overly depends on subjective judgment and the research results show a lack of objectivity. Therefore, this study started research about social media characteristics and the theoretical background of e-WOM and gathered structured questionnaires as the data in order to identify a universal law. In addition, the demographic characteristics and airline usage were also asked. The survey scale was the Likert five-point scale, with five being very true and one being not at all. The survey was conducted on Koreans who had experience of using airlines using the convenience sampling method, from Aug. 11 to Sep. 15, 2017. In this study, non-probabilistic sampling was used. This is a common technique in social science and statistical research. Based on the probability sampling method, there are advantages including how it is relatively easy to carry out a very difficult investigation and useful to quickly comprehend certain trends [104]. Sampling was difficult to investigate because we chose a specific target. The investigation took about a month. The statistical analysis method of this study is considered very appropriate. Non-probability sampling methods have been used in various fields for longer than probability sampling, and the use of non-probability sampling methods is increasing. Non-probability sampling methods are widely used in research and research fields [105].
The random sampling method was applied in this study to ensure internal consistency and solve sample selection bias-related issues. In order to obtain a genuine response, the researcher collected a sample with data by conducting a face-to-face survey. Through this process, a total of 450 questionnaires were distributed and 442 of them were collected. After excluding twelve ones with missed or inappropriate data, 430 questionnaires were used in the final analysis. This is because when the data is systematically lost due to omission, the results may not characterize the population and also be affected by validity and reliability [106]. The items of the questionnaire are shown in Table 1.
This study, to identify characteristics of passengers who have experience using airline social media, analyzed data using the SPSS 21.0 program and AMOS 20.0 program, which have been widely used as statistical packages of social sciences. The frequency analysis was conducted to identify the characteristics of the sample, and confirmatory factor analysis was performed to further analyze the validity of the measurement model. The secondary forms of concepts that are composed of sub-factors were each analyzed by confirming factor analysis to verify the internal validity and then converted to the primary form. In addition, Using Cronbach’s α, by scales, the refinement of the scale was carried out. The concentration and discriminant validity were verified, and the hypothesis of this study model was verified through structural equations.

4. Empirical Analysis

The valid samples of this study are 430 subjects, and Table 2 shows the demographic characteristics of the subjects. The females were somewhat higher, with n = 235(54.7%) and males were n = 195 (45.3%). The most frequent age group was n = 159 (37.0%) for 31–40 years old and followed by n = 149 (34.6%) for 21–30, n = 75 (17.4%) for 41–50 years old, n = 30 (7.0%) for 51 years old or older, and n = 17 (4.0%) for younger than 20 years old. This confirmed that those in their 20s and 30s who are active in social and economic activities are the main generations of using social media. The distribution of airlines that subjects have experience of using social media showed n = 188 (43.7%) for Korean Air, n = 154 (35.8%) for Asiana Airlines, n = 72 for low-cost domestic airlines (16.7%), n = 11 for foreign airlines (2.6%), and n = 5 (1.2%) for foreign low-cost airlines (1.2%), indicating that major airlines are focusing on SNS as part of their marketing strategy.
As the results of confirmatory factor analysis to verify the single-dimensionality, conceptual validity and reliability of the measurement items are shown in Table 3. The Squared Multiple Correlations (SMC) value of all the measured items except Image 2 appeared to be 0.5 or more, and the standardized factor loadings of the measured items were 0.7 or more, ensuring the concentration validity [108]. In addition, all Cronbach’ α values were more than 0.7, ensuring content validity. For the result of confirmatory factor analysis for each item, χ2 = 552.814, df = 168, CMIN/DF = 3.291, p = 0.000, GFI = 0.889, NFI = 0.890, IFI = 0.920, CFI = 0.920, RMR = 0.04, and RMSEA = 0.073, indicating that the research model of this study is fit.
To test the hypotheses of this study, the structural equation model analysis was performed. The estimated fit and path coefficient of the structural model were χ2 = 688.229, df = 178, CMIN/DF = 3.866, p < 0.001, GFI = 0.863, AGFI = 0.822, RMR = 0.062, CFI = 0.894, TLI = 0.875, and RMSEA = 0.082, indicating a satisfactory level of fitness when compared with the general criteria. The structural model presented in this study is considered as appropriate, and the hypothesis testing results are presented in Figure 2.
Among the characteristics of social media usage, only personality and information characteristics are showed significant influence on e-WOM. In particular, it was confirmed that the information characteristics showed more influence than the personality characteristics because the information characteristics were β = 0.472 and C.R. = 5.598 (p < 0.001). In other words, if the information quantity, reliability, and quality of airline social media are good, it can be seen that they leave a positive review online. However, social characteristics were found to have no significant effect on e-WOM. The relationship between e-WOM and brand equity (brand awareness, brand image) yielded different results. The e-WOM had a significant effect on brand awareness, but not on the brand image. The hypothesis that e-WOM has a significant effect on trust was supported with β = 0.562 and C.R. = 10.036 (p < 0.001). The relationship between trust and brand equity was found to be statistically significant. The influence of trust on brand awareness amongst brand equity was β = 0.492, CR = 7.241 (p < 0.001), and it was displayed as β = 0.91 and CR = 12.263 (p < 0.001) for brand image, supporting both H7 and H8. Accordingly, this shows that brand image is built through trust. The explanatory power was 38.8% and 77.6%, respectively.

5. Conclusions

The purpose of this study was to investigate the influence of social media usage characteristics on brand awareness and brand image of brand equity through e-WOM and trust. Through previous studies, social media usage characteristics were derived into personality characteristics (Openness, Conscientiousness, Extroversion, Agreeableness, and Neuroticism), social characteristics (bridging social capital and bonding social capital), and information characteristics (information quantity, Reliability, and quality). The results of this study are consistent with the previous studies in a large context [90,101,109], but the differences are shown according to the characteristics of the samples and the market situation [7,82,88].
In order to present the empirical results, a survey of 430 passengers with experience using airline social media was analyzed. First, personality characteristics among social media usage characteristics were found to have a significant effect on e-WOM. Airlines should apply customers’ social media activities and online conversations to understand customer preferences and also manage customer data. Protection of personal information is an important issue for this, but the future lies in ensuring that airlines can use social media data and convert them into actionable insights that will yield closer relationships with customers through greater personalization. For this to be achieved, airlines are required to make a significant investment in resources and professional training, especially with regards to the application of social media data. Second, the social characteristics of social media did not have a significant effect on e-WOM. This means that the personality or disposition of the individual affects the e-WOM, but the social connection or cohesion does not affect the e-WOM in relation to the characteristics of the airline’s use of social media. It may be interpreted that any distortions or intentions due to social relationships have no effects on the e-WOM. Third, the information characteristics of social media have a significant effect on e-WOM. Contrary to social characteristics, and information characteristics have a close effect on e-WOM. This indicates that the higher quality, reliability, and amount of information are associated with a more active role of e-WOM. Accordingly, the airlines should reinforce the functions of the links for the information in the technical aspect and also deliver news through various social media channels and constantly provide events in order to attract interest from potential customers. Plenty of high quality and reliable information should be provided to customers, both quickly and actively, to strengthen the sales strategies of direct sales without distributors. Fourth, e-WOM has a significant effect on trust, suggesting that the more positive WOM about the airline in social media is associated with higher trust in that airline. Many studies have already demonstrated how important trust is to brands and consumer relationships, which gives directions on how airlines should use social media marketing. Fifth, e-WOM had a significant effect on brand awareness, but not on brand image, indicating that the e-WOM does not directly change the image of airline brands, but has a direct effect on brand awareness. It was also found that the building of trust using e-WOM may have an effect on brand image. Lastly, trust has a significant effect on both brand awareness and brand image of brand equity. Trust has already been shown to be a decisive factor in boosting brand equity and that brand equity has a direct bearing on consumer purchase intentions. This shows that e-WOM generated through the use of social media has a significant impact on airline brand equity through trust.
The airline industry is a part of the service division that plays an important role in the tourism and air transport industry and shows consistent growth through technological and economic development. However, the emergence of a mega carrier due to the merger between former airlines and the market share of low-cost carriers is causing fierce competition in the industry. Airlines need new ways to create competitive advantage and various strategies are required in order for the airlines to attract and maintain more customers. Based on the circumstances, the following is the significance of this study. This study focused on investigating the application of social media in the airline industry in regard to how this particular field turned to the researches done by other industries due to the lack of research about social media targeted on the airline industry. This study analyzed the influence of the users’ personality characteristics, social characteristics, and information characteristics on e-WOM, trust, and brand equity in respect of social media application. The study provides an academic base on social media in the airline industry henceforward.
The following is a suggestion for the specific practice. First, the importance of social media marketing should be recognized and dedicated personnel and division should be designated to focus on social media marketing. Second, social media marketing that customers can join should be implemented and attention should be provided to the data collection and management of the users. Third, various reliable information should be provided and marketing activities should be executed to activate e-WOM and create differentiation that is worthy of gaining trust as well as construct brand equity that can make way for cognitive and emotional experiences to the consumers.
As a result, this study suggests that companies should consider customers’ personality characteristics for social media marketing activities and also apply the information quantity, reliability, and quality to make e-WOM active and gain trust. The marketing manager and decision maker should make investments to consistently collect and analyze data in order to learn customers’ personal tastes and preferences, and if sufficient amount of information and credible data are provided to the customers through social media, then significant synergy effect can be expected to construct advanced brand equity. Therefore, the result of this study provides support to establish operational strategies as to how airline companies should give attention to social media marketing activities and conduct research about the strategies of the application measures along with the methods that should be applied to build positive word-of-mouth online and reliability about the company.
The limitations of this study and future research subjects are as follows. First, the survey was conducted only on Korean passengers of domestic airlines and lacked representativeness of the sample. That 7.9% of the surveys were included using foreign airline social media is insignificant. In the future, comprehensive studies should be conducted on foreign cases and airlines. Second, the definition of e-WOM was studied as a positive meaning, so it could display preponderance in the research. It is anticipated for future research to consider the directivity of e-WOM and the differences that follow the varied characteristics. Third, although empirical studies demonstrated that social media marketing activities have a significant effect on e-WOM or trust, there is a lack of studies on how these results affect to make the actual profit or management performance of companies. The overcome of these limitations in future studies is expected to be greatly helpful not only to aviation companies but also to marketers in all areas concerned with social media marketing strategies and decision-making. The results of this study confirm how social media usage characteristics affect brand equity through e-WOM and trust, and demonstrate the importance of using social media in corporate activities of airlines. Despite the limitations of this study, it theoretically and statistically was confirmed that results will have great significance in future social media research directions, and proposals for airline operation strategies will be of practical help to management.

Author Contributions

Conceptualization, E.J.S. and J.-W.P.; methodology, E.J.S., J.-W.P. and Y.J.C.; data collection and analysis, E.J.S. and Y.J.C.; supervision of the research, J.-W.P.; writing-original draft, E.J.S.; writing-review & editing E.J.S., J.-W.P. and Y.J.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Gallauter, J.; Ransbotham, S. Social Media and Customer Dialog Management at Starbucks. MIS Q. Exec. 2010, 9, 197–212. [Google Scholar]
  2. Kaplan, A.M.; Haenlein, M. Users of the World, Unite! The Challenges and Opportunities of Social Media. Bus. Horizons 2010, 53, 59–68. [Google Scholar] [CrossRef]
  3. Kietzmann, J.; Hermkens, K.; McCarthy, I.; Silvestre, B.S. Social Media? Get Serious! Understanding the Functional Building Blocks of Social Media. Bus. Horizons 2011, 54, 241–251. [Google Scholar] [CrossRef] [Green Version]
  4. Hanna, R.; Rohm, A.; Crittenden, V.L. We’re All Connected: The Power of the Social Media Ecosystem. Bus. Horizons 2011, 54, 265–273. [Google Scholar] [CrossRef]
  5. Seo, E.-J.; Park, J.-W. A Study on the Effects of Social Media Marketing Activities on Brand Equity and Customer Response in the Airline Industry. J. Air Transp. Manag. 2018, 66, 36–41. [Google Scholar] [CrossRef]
  6. Godey, B.; Manthiou, A.; Pederzoli, D.; Rokka, J.; Aiello, G.; Donvito, R.; Singh, R. Social Media Marketing Efforts of Luxury Brands: Influence on Brand Equity and Consumer Behavior. J. Bus. Res. 2016, 69, 5833–5841. [Google Scholar] [CrossRef]
  7. Alan, A.K.; Kabadayı, E.T. The Effect of Personal Factors on Social Media Usage of Young Consumers. Procedia Soc. Behav. Sci. 2016, 235, 595–602. [Google Scholar] [CrossRef]
  8. Su, C.C.; Chan, N.K.; Chao, C.S.; Keung, C.N. Predicting Social Capital on Facebook: The Implications of Use Intensity, Perceived Content Desirability, and Facebook-Enabled Communication Practices. Comput. Hum. Behav. 2017, 72, 259–268. [Google Scholar] [CrossRef]
  9. Kim, B.; Kim, Y. College students’ Social Media Use and Communication Network Heterogeneity: Implications for Social Capital and Subjective Well-Being. Comput. Hum. Behav. 2017, 73, 620–628. [Google Scholar] [CrossRef]
  10. Erkan, I.; Evans, C. The Influence of EWOM in Social Media on consumers’ Purchase Intentions: An Extended Approach to Information Adoption. Comput. Hum. Behav. 2016, 61, 47–55. [Google Scholar] [CrossRef]
  11. Kim, J.T. Media and Man. Communication books; SEL: Seoul, Korea, 1998. [Google Scholar]
  12. Boyd, D.M.; Ellison, N. Social Network Sites: Definition, History, and Scholarship. J. Comput. Commun. 2007, 13, 210–230. [Google Scholar] [CrossRef] [Green Version]
  13. Safko, L.; Brake, D. The Social Media Bible: Tactics, Tools and Strategies for Business Success; Wiley: New York, NY, USA, 2009. [Google Scholar]
  14. Richter, A.; Koch, M. Social Software-Status Quo and Zukunft, Fak. Fur Informatik; University der Bundeswehr München: Munich, Germany, 2007. [Google Scholar]
  15. Kelly, L.; Kerr, G.; Drennan, J. Avoidance of Advertising in Social Networking Sites. J. Interact. Advert. 2010, 10, 16–27. [Google Scholar] [CrossRef]
  16. Leung, D.; Law, R.; Van Hoof, H.; Buhalis, D. Social Media in Tourism and Hospitality: A Literature Review. J. Travel Tour. Mark. 2013, 30, 3–22. [Google Scholar] [CrossRef]
  17. Zeng, B.; Gerritsen, R. What Do We Know about Social Media in Tourism? A Review. Tour. Manag. Perspect. 2014, 10, 27–36. [Google Scholar] [CrossRef]
  18. Costa, P.T.; McCrae, R.R. The Revised NEO Personality Inventory (NEO-PI-R); SAGE Publications: Southend Oaks, CA, USA, 2012; pp. 179–198. [Google Scholar] [CrossRef]
  19. Min, K. Personality Psychology; Bobmunsa: Paju, Korea, 2002. [Google Scholar]
  20. Liu, D.; Campbell, W.K. The Big Five Personality Traits, Big Two Metatraits and Social Media: A Meta-Analysis. J. Res. Pers. 2017, 70, 229–240. [Google Scholar] [CrossRef] [Green Version]
  21. Block, J. The Five-Factor Framing of Personality and Beyond: Some Ruminations. Psychol. Inq. 2010, 21, 2–25. [Google Scholar] [CrossRef]
  22. Hughes, D.J.; Rowe, M.; Batey, M.; Lee, A. A Tale of Two Sites: Twitter Vs. Facebook and the Personality Predictors of Social Media Usage. Comput. Hum. Behav. 2012, 28, 561–569. [Google Scholar] [CrossRef] [Green Version]
  23. McCrae, R.R.; Costa, P.T., Jr. The Five-Factor Theory of personality; Guilford Press: New York, NY, USA, 2008. [Google Scholar]
  24. John, O.P.; Srivastava, S. The Big Five Trait Taxonomy: History, Measurement, and Theoretical Perspectives. In Handbook of Personality: Theory and Research; Pervin, L.A., John, O.P., Eds.; Guilford Press: New York, NY, USA, 1999; pp. 102–138. [Google Scholar]
  25. Ryan, T.; Xenos, S. Who Uses Facebook? An Investigation into the Relationship Between the Big Five, Shyness, Narcissism, Loneliness, and Facebook Usage. Comput. Hum. Behav. 2011, 27, 1658–1664. [Google Scholar] [CrossRef]
  26. Costa, P.T.; McCrae, R.R. The Five-Factor Model and the NEO Inventories. Oxf. Handb. Personal. Assess. 2009, 299–322. [Google Scholar] [CrossRef]
  27. McCrae, R.R.; Costa, P.T., Jr. Personality in Adulthood; Informa UK Limited: Colchester, UK, 2003. [Google Scholar] [CrossRef]
  28. Chan, D.; Schmitt, N. Situational Judgment and Job Performance. Hum. Perform. 2002, 15, 233–254. [Google Scholar] [CrossRef]
  29. Adler, P.S.; Kwon, S.-W. Social Capital: Prospects for a New Concept. Acad. Manag. Rev. 2002, 27, 17–40. [Google Scholar] [CrossRef]
  30. Lin, N. Social Capital: A Theory of Social Structure and Action; Cambridge University Press: New York, NY, USA, 2002. [Google Scholar]
  31. Etzioni, A.; Putnam, R.D. Is Bowling Together Sociologically Lite? Bowling Alone: The Collapse and Revival of American Community. Contemp. Sociol. A J. Rev. 2001, 30, 223. [Google Scholar] [CrossRef]
  32. Williams, D. On and Off the ’Net: Scales for Social Capital in an Online Era. J. Comput. Commun. 2006, 11, 593–628. [Google Scholar] [CrossRef] [Green Version]
  33. Burt, R.S. The Contingent Value of Social Capital. Adm. Sci. Q. 1997, 42, 339. [Google Scholar] [CrossRef]
  34. Steinfield, C.; Ellison, N.; Lampe, C. Social Capital, Self-Esteem, and Use of Online Social Network Sites: A Longitudinal Analysis. J. Appl. Dev. Psychol. 2008, 29, 434–445. [Google Scholar] [CrossRef]
  35. Briggs, X.D.S. Brown Kids in White Suburbs: Housing Mobility and the Many Faces of Social Capital. Hous. Policy Debate 1998, 9, 177–221. [Google Scholar] [CrossRef]
  36. Wilken, R. “Bonds and Bridges: Mobile Phone Use and Social Capital debates.” Mobile Communication: Bringing Us Together and Tearing Us Apart; Transaction Publishers: New Brunswick, NJ, USA, 2011. [Google Scholar]
  37. Ahituv, N.; Riley, H.N.; Neumann, S. Principles of Information Systems for Management; McGraw-Hill Professional: Columbus, OH, USA, 1993. [Google Scholar]
  38. A Thelwall, M.; Buckley, K.; Paltoglou, G. Sentiment Strength Detection for the Social Web. J. Am. Soc. Inf. Sci. Technol. 2011, 63, 163–173. [Google Scholar] [CrossRef] [Green Version]
  39. Chewning, E.G.; Harrell, A.M. The Effect of Information Load on Decision makers’ Cue Utilization Levels and Decision Quality in a Financial Distress Decision Task. Account. Organ. Soc. 1990, 15, 527–542. [Google Scholar] [CrossRef]
  40. Eppler, M.J.; Mengis, J. The Concept of Information Overload: A Review of Literature from Organization Science, Accounting, Marketing, MIS, and Related Disciplines. Inf. Soc. 2004, 20, 325–344. [Google Scholar] [CrossRef]
  41. Chen, Y.-C.; Shang, R.-A.; Kao, C.-Y. The Effects of Information Overload on consumers’ Subjective State towards Buying Decision in the Internet Shopping Environment. Electron. Commer. Res. Appl. 2009, 8, 48–58. [Google Scholar] [CrossRef]
  42. Wathen, C.N.; Burkell, J. Believe It or Not: Factors Influencing Credibility on the Web. J. Am. Soc. Inf. Sci. Technol. 2002, 53, 134–144. [Google Scholar] [CrossRef] [Green Version]
  43. Pan, X.; Ratchford, B.T.; Shankar, V. Can Price Dispersion in Online Markets Be Explained by Differences in E-Tailer Service Quality? J. Acad. Mark. Sci. 2002, 30, 433–445. [Google Scholar] [CrossRef]
  44. Chen, C.C.; Tseng, Y.-D. Quality Evaluation of Product Reviews Using an Information Quality Framework. Decis. Support Syst. 2011, 50, 755–768. [Google Scholar] [CrossRef]
  45. Bickart, B.; Schindler, R.M. Internet Forums As Influential Sources of Consumer Information. J. Interact. Mark. 2001, 15, 31–40. [Google Scholar] [CrossRef]
  46. Canhoto, A.; Clark, M. Customer Service 140 Characters at a Time: The users’ Perspective. J. Mark. Manag. 2013, 29, 522–544. [Google Scholar] [CrossRef]
  47. Erkan, I. The Influence of Electronic Word of Mouth in Social Media on Consumers’ Purchase Intentions. Ph.D. Thesis, Brunel University, London, UK, June 2016. [Google Scholar]
  48. Katz, E.; Lazarsfeld, P.F.; Roper, E. Personal Influence: The Part Played by People in the Flow of Mass Communications; Routledge: London, UK, 2017. [Google Scholar]
  49. King, R.A.; Racherla, P.; Bush, V.D. What We Know and Don’t Know About Online Word-of-Mouth: A Review and Synthesis of the Literature. J. Interact. Mark. 2014, 28, 167–183. [Google Scholar] [CrossRef]
  50. Yoon, S.J. A Social Network Approach to the Influences of Shopping Experiences on e-WOM. J. Elec. Comm. Res. 2012, 13, 213–223. [Google Scholar]
  51. Barreto, A.M. The Word-of-Mouth Phenomenon in the Social Media Era. Int. J. Mark. Res. 2014, 56, 631–654. [Google Scholar] [CrossRef]
  52. Cheung, C.M.; Lee, M.K. What Drives Consumers to Spread Electronic Word of Mouth in Online Consumer-Opinion Platforms. Decis. Support Syst. 2012, 53, 218–225. [Google Scholar] [CrossRef]
  53. Pitta, D.A.; Fowler, D. Online Consumer Communities and Their Value to New Product Developers. J. Prod. Brand Manag. 2005, 14, 283–291. [Google Scholar] [CrossRef] [Green Version]
  54. Mourali, M.; Laroche, M.; Pons, F. Antecedents of Consumer Relative Preference for Interpersonal Information Sources in Pre-Purchase Search. J. Consum. Behav. 2005, 4, 307–318. [Google Scholar] [CrossRef]
  55. O’Cass, A.; Grace, D. Service Brands and Communication Effects. J. Mark. Commun. 2004, 10, 241–254. [Google Scholar] [CrossRef]
  56. Gefen, D.; Drexel University. Customer Loyalty in E-Commerce. J. Assoc. Inf. Syst. 2002, 3, 27–53. [Google Scholar] [CrossRef]
  57. Robinson, S.L. Trust and Breach of the Psychological Contract. Adm. Sci. Q. 1996, 41, 574. [Google Scholar] [CrossRef]
  58. Mishra, A.K. Organizational Responses to Crisis; Trust in Organizations: Sage, CA, USA, 1996. [Google Scholar]
  59. Luhmann, N. Familiarity, Confidence, Trust: Problems and Alternatives. In Trust: Making and Breaking Cooperative Relations; Basil Blackwell: Oxford, UK, 2000; pp. 94–107. [Google Scholar]
  60. Ballester, E.D.; Munuera-Alemán, J.L. Does Brand Trust Matter to Brand Equity? J. Prod. Brand Manag. 2005, 14, 187–196. [Google Scholar] [CrossRef] [Green Version]
  61. E Swan, J.; Bowers, M.R.; Richardson, L.D. Customer Trust in the Salesperson. J. Bus. Res. 1999, 44, 93–107. [Google Scholar] [CrossRef]
  62. Jang, H. A Comparative Study on the Structutal Interactionns Among Customer Satisfaction, Trust, Loyalty Based on Types of Internet Shopping Mall. J. Global Acad. Mark. Sci. 2007, 17, 23–49. [Google Scholar]
  63. Aaker, D.A. Measuring Brand Equity Across Products and Markets. Calif. Manag. Rev. 1996, 38, 102–120. [Google Scholar] [CrossRef]
  64. Keller, K.L. Conceptualizing, Measuring, and Managing Customer-Based Brand Equity. J. Mark. 1993, 57, 1–22. [Google Scholar] [CrossRef]
  65. Keller, K.L. Brand Synthesis: The Multidimensionality of Brand Knowledge. J. Consum. Res. 2003, 29, 595–600. [Google Scholar] [CrossRef]
  66. Sallam, M.A.; Wahid, N.A. The Effects of Satisfaction and Brand Identification on Brand Love and Brand Equity Outcome: The Role of Brand Loyalty. Eur. J. Bus. Soc. Sci. 2015, 4, 42–55. [Google Scholar]
  67. Machado, J.C.; De Carvalho, L.V.; Azar, S.L.; André, A.R.; Dos Santos, B.P. Brand Gender and Consumer-Based Brand Equity on Facebook: The Mediating Role of Consumer-Brand Engagement and Brand Love. J. Bus. Res. 2019, 96, 376–385. [Google Scholar] [CrossRef] [Green Version]
  68. Sen, S. The Effects of Brand Name Suggestiveness and Decision Goal on the Development of Brand Knowledge. J. Consum. Psychol. 1999, 8, 431–455. [Google Scholar] [CrossRef]
  69. Shocker, A.D.; Aaker, D.A. Managing Brand Equity. J. Mark. Res. 1993, 30, 256. [Google Scholar] [CrossRef]
  70. Keller, K.L.; Parameswaran, M.G.; Jacob, I. Parameswaran, and Isaac Jacob. Strategic Brand Management: Building, Measuring, and Managing Brand Equity; Pearson Education: London, UK, 2011. [Google Scholar]
  71. Percy, L.; Rossiter, J.R. A Model of Brand Awareness and Brand Attitude Advertising Strategies. Psychol. Mark. 1992, 9, 263–274. [Google Scholar] [CrossRef]
  72. Heo, J.H. The Effects of Brand Awareness, Perceived Service Quality and Physical Environment on Congruity and Purchase Intention: Focusing on Coffee Shop. Master’s Thesis, Sejong University, Seoul, Korea, 2012. [Google Scholar]
  73. Kotler, P.; Armstrong, G. Principles of Marketing; Pearson Education: London, UK, 2010. [Google Scholar]
  74. Low, G.S.; Lamb, C.W. The Measurement and Dimensionality of Brand Associations. J. Prod. Brand Manag. 2000, 9, 350–370. [Google Scholar] [CrossRef]
  75. Dobni, D.; Zinkhan, G.M. In Search of Brand Image: A Foundation Analysis. Adv. Consum. Res. 1990, 17, 110–118. [Google Scholar]
  76. Ajzen, I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
  77. Noh, J.-E.; Choi, Y.-S.; Choi, S.-D. The Impact of Tourism Information Characteristics and Information Seeker Personality Variables on Word-of-Mouth Effects Throughout the Online Environment: Focusing on Internet Users in the Age Groups of the 20s and 30s. J. Tour. Sci. 2016, 40, 43–62. [Google Scholar] [CrossRef]
  78. Ju, H.; Suh, H. Relationships Among Personality, Commitment and Word-of-Mouth Insertion in Online Shopping. Glob. E-Bus. Assoc. 2015, 16, 29–50. [Google Scholar]
  79. Bachrach, Y.; Kosinski, M.; Graepel, T.; Kohli, P.; Stillwell, D. Personality and Patterns of Facebook Usage. In the 3rd Annual ACM Web Science Conference; Association for Computing Machinery (ACM): New York, NY, USA, 2012; pp. 24–32. [Google Scholar] [CrossRef]
  80. Wang, T.; Yeh, R.K.-J.; Chen, C.; Tsydypov, Z. What Drives Electronic Word-of-Mouth on Social Networking Sites? Perspectives of Social Capital and Self-Determination. Telemat. Inform. 2016, 33, 1034–1047. [Google Scholar] [CrossRef]
  81. Chung, N.; Koo, C. The Use of Social Media in Travel Information Search. Telemat. Inform. 2015, 32, 215–229. [Google Scholar] [CrossRef]
  82. Lee, S.N. The Study on the Effect of Personal Characteristics, Interpersonal Influence and Social Capital on Online Word of Mouth on SNS: Mainly about Comparison between Facebook and Twitter. Master’s Thesis, Hanyang University, Seoul, Korea, June 2013. [Google Scholar]
  83. Knoll, J. Advertising in Social Media: A Review of Empirical Evidence. Int. J. Advert. 2015, 35, 266–300. [Google Scholar] [CrossRef]
  84. Bowman, D.; Narayandas, D. Managing Customer-Initiated Contacts with Manufacturers: The Impact on Share of Category Requirements and Word-of-Mouth Behavior. J. Mark. Res. 2001, 38, 281–297. [Google Scholar] [CrossRef]
  85. Duan, W.; Gu, B.; Whinston, A.B. Do Online Reviews Matter? — An Empirical Investigation of Panel Data. Decis. Support Syst. 2008, 45, 1007–1016. [Google Scholar] [CrossRef]
  86. Liu, Y. Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue. J. Mark. 2006, 70, 74–89. [Google Scholar] [CrossRef]
  87. Wen, X. The Effect of the Characteristic of Online Word-of -Mouth on Word of Mouth Acceptance, Word of Mouth Spread and Purchase Intention. Master’s Thesis, Kyung Hee University, Seoul, Korea, Suwon, Korea, 2015. [Google Scholar]
  88. Kim, N.; Kim, M.H. The Impact of Tourism e-WOM Information Characteristics and Community Interactivity on E-WOM Information Usefulness and e-WOM Effects. Korea Serv. Manag. Soc. 2010, 11, 17–44. [Google Scholar]
  89. Litvin, S.W.; Goldsmith, R.E.; Pan, B. Electronic Word-of-Mouth in Hospitality and Tourism Management. Tour. Manag. 2008, 29, 458–468. [Google Scholar] [CrossRef]
  90. Ladhari, R.; Michaud, M. EWOM Effects on Hotel Booking Intentions, Attitudes, Trust, and Website Perceptions. Int. J. Hosp. Manag. 2015, 46, 36–45. [Google Scholar] [CrossRef]
  91. Cha, S.M. Developing Word-of-Mouth(WOM) Communication Paradigm Model of Restaurant Information. Master’s Thesis, Yonsei University, Seoul, Korea, 2006. [Google Scholar]
  92. Sénécal, S.; Nantel, J. The Influence of Online Product Recommendations on consumers’ Online Choices. J. Retail. 2004, 80, 159–169. [Google Scholar] [CrossRef]
  93. Yim, S.H. Research on Influence to Brand Equity and Revisit Intention by On/Off-Line Word of Mouth: Based on Family Restaurant Brands. Master’s Thesis, Tourism Kyung Hee University, Seoul, Korea, Suwon, Korea, 2009. [Google Scholar]
  94. Kim, J.-W. The Relation Between of Marketing Communication and Service Brand Equity. J. Korea Contents Assoc. 2008, 8, 150–163. [Google Scholar] [CrossRef] [Green Version]
  95. Lee, S.H. The Effects of Airline Marketing Communications on Brand Knowledge and Core Customer-Based Brand Equity. Ph.D. Thesis, Sejong University, Seoul, Korea, 2012. [Google Scholar]
  96. Fournier, S.; Dobscha, S.; Mick, D.G. Preventing the Premature Death of Relationship Marketing. Harv. Bus. Rev. 1997, 76, 42–51. [Google Scholar]
  97. Moorman, C.; Deshpandé, R.; Zaltman, G. Factors Affecting Trust in Market Research Relationships. J. Mark. 1993, 57, 81–101. [Google Scholar] [CrossRef] [Green Version]
  98. Moorman, C.; Zaltman, G.; Deshpande, R. Relationships Between Providers and Users of Market Research: The Dynamics of Trust Within and Between Organizations. J. Mark. Res. 1992, 29, 314–328. [Google Scholar] [CrossRef]
  99. Kim, K.H.; Kim, K.S.; Kim, D.Y.; Kim, J.H.; Kang, S.H. Brand Equity in Hospital Marketing. J. Bus. Res. 2008, 61, 75–82. [Google Scholar] [CrossRef]
  100. Han, S.H.; Nguyen, B.; Lee, T. Consumer-Based Chain Restaurant Brand Equity, Brand Reputation, and Brand Trust. Int. J. Hosp. Manag. 2015, 50, 84–93. [Google Scholar] [CrossRef]
  101. Fatma, M.; Rahman, Z.; Khan, I. Building Company Reputation and Brand Equity through CSR: The Mediating Role of Trust. Int. J. Bank Mark. 2015, 33, 840–856. [Google Scholar] [CrossRef]
  102. Loureiro, S.M.C. The Effect of Perceived Benefits, Trust, Quality, Brand Awareness/Associations and Brand Loyalty on Internet Banking Brand Equity. Int. J. Electron. Commer. Stud. 2013, 4, 139–158. [Google Scholar] [CrossRef] [Green Version]
  103. Royse, D. Research Methods in Social Work. Cengage Learning, 5th ed.; Thomson Learning: Belmont, CA, USA, 2008. [Google Scholar]
  104. Given, L. The SAGE Encyclopedia of Qualitative Research Methods. SAGE Encycl. Qual. Res. Methods 2008. [Google Scholar] [CrossRef]
  105. Baker, R.; Brick, J.M.; Bates, N.A.; Battaglia, M.; Couper, M.P.; Dever, J.A.; Gile, K.J.; Tourangeau, R. Summary Report of the AAPOR Task Force on Non-Probability Sampling. J. Surv. Stat. Methodol. 2013, 1, 90–143. [Google Scholar] [CrossRef]
  106. McKnight, P.E.; McKnight, K.M.; Sidani, S.; Figueredo, A.J. Missing Data: A Gentle Introduction; Guilford Press: New York, NY, USA, 2007. [Google Scholar]
  107. Goyette, I.; Ricard, L.; Bergeron, J.; Marticotte, F. e-WOM Scale: Word-of-mouth Measurement Scale for e-services Context. Can. J. of Adm. Sci./Rev. Can. Sci. De l’Adm. 2010, 27, 5–23. [Google Scholar] [CrossRef]
  108. Song, J.J. SPSS/AMOS Statistical Analysis Method; 21C: Paju, Korea, 2015; ISBN 978-898-468-618-2. [Google Scholar]
  109. Augusto, M.; Torres, P. Effects of Brand Attitude and EWOM on consumers’ Willingness to Pay in the Banking Industry: Mediating Role of Consumer-Brand Identification and Brand Equity. J. Retail. Consum. Serv. 2018, 42, 1–10. [Google Scholar] [CrossRef]
Sustainability 12 01691 g001 550
Figure 1. Research model.
Figure 1. Research model.
Sustainability 12 01691 g001
Sustainability 12 01691 g002 550
Figure 2. Results of testing hypotheses. * p < 0.05, *** p < 0.01.
Figure 2. Results of testing hypotheses. * p < 0.05, *** p < 0.01.
Sustainability 12 01691 g002
Table
Table 1. Questionnaire items.
Table 1. Questionnaire items.
VariableItemRelated Studies
Personality
Characteristics
of Social
Media Usage		NeuroticismAlan, A. K., and Kabadayı, E. T. (2016) [7]
I have calm characteristics.
I am emotionally stable.
I do not become angry easily.
Extroversion
I am extroversive.
I am enthusiastic.
I am active.
Openness
I like new kinds of experience.
I like change.
I am creative.
Agreeableness
I am kind.
I am generous.
I like emotional interaction with others.
Conscientiousness
I am sincere.
I am trustworthy.
I have habits of readiness and strict.
Social
Characteristics
of Social
Media Usage		Bridging Social CapitalSu, C. C., and Chan, N. K. (2017). [8];
Kim, B., and Kim, Y. (2017). [9]
Airline social media makes me to be interested in news,
Airline social media makes me to be curious about another world.
Airline social media makes me to want to try something new.
Airline social media makes me to be attention to people who think differently from me.
Bonding Social Capital
Airline social media is a good candidate to be recommended for airline usage and travel information.
Airline social media advises me in making important decisions about airline usage and travel information
Airline social media is helpful in solving problems related to airline usage and travel information.
Airline social media is helpful when airline usage and travel information are sought in a hurry.
Information
Characteristics
of Social
Media Usage		Information QuantityErkan, I., and Evans, C. (2016). [10]
media.Airline social media has a high amount of information.
Social media has high amount of information about airlines.
Many people post much information about airline on social
Information Reliability
I think that the information on airline social media is credible.
I think that the information on airline social media is accurate.
I think that the information on airline social media is influential.
Information Quality
I think that the information on airline social media is easy to understand.
I think that the information on airline social media is certain.
I think that the quality of information on airline social media is excellent in general.
e-WOMI will post positive comments about this airline on my social media.Goyette, I., Ricard, L., Bergeron, J., and Marticotte, F. (2010). [107]
I will recommend to use this airline through my social media.
I will recommend to use this airline to my social media acquaintances.
TrustThis airline is reliable.Delgado--Ballester, E., and Munuera--Alemán, J. L. (2005). [60]
I think that this airline does not hide the important information I needs to know.
I believe this airline respects its promises.
Brand Equity Brand AwarenessGodey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R., and Singh, R. (2016). [6]
I can always recognize this airline brand.
I am familiar with this airline characteristic.
I remember this airline logo certainly.
Brand Image
This airline is a leading one in their industry.
I have an impressive experience of this airline.
The airline is a customer-centered company.
Table
Table 2. Demographic characteristics of subjects.
Table 2. Demographic characteristics of subjects.
VariableFrequency (n)Percentage (%)
GenderMale19545.3
Female23554.7
AgeUnder 21174.0
21–3014934.6
31–4015937.0
41–507517.4
51 and Over307.0
Purpose of Using AirlineWork or Business347.9
Tour and Vacation36785.3
Education and Meeting92.1
Visiting Friend and Relatives153.5
Others51.2
Social Media UsageAsiana Airlines15435.8
Korean Air18843.7
Foreign Airlines112.6
Domestic Low-Cost Airlines7216.7
Foreign Low-Cost Airlines51.2
Frequency of Using Airlines per Year114934.6
2–316337.9
4–57717.9
6–7143.3
8–971.6
10 and Over204.7
Total Respondents430100%
Table
Table 3. Results of confirmatory factor analysis.
Table 3. Results of confirmatory factor analysis.
ConstructsVariableSMCRegression
Coefficient
(C.R.)		S.C.Rα
Characteristics
of
social Media		PersonalityNeu.0.4171.357(6.287)0.5530.734
Ext.0.5351.489(5.971)0.657
Ope.0.4201.000(Fix)0.561
Agr.0.7111.997(6.955)0.843
Con.0.6011.765(6.897)0.775
SocialBridging0.6240.939(16.688)0.790.830
Bonding0.8091.000(Fix)0.899
InformationQuantity0.4460.799(15.351)0.6680.828
Reliability0.7871.000(Fix)0.887
Quality0.720.941(21.416)0.848
TrustTrust 10.5191.000(Fix)0.720.834
Trust 20.6741.294(15.689)0.821
Trust 30.7351.25(16.178)0.857
e-WOMe-WOM10.6811.000(Fix)0.8250.908
e-WOM20.8751.163(23.663)0.935
e-WOM30.751.051(21.767)0.866
Brand EquityAwarenessAwe. 10.6171.000(Fix)0.7860.820
Awe. 20.5531.096(14.985)0.743
Awe. 30.6541.204(16.135)0.809
ImageImage 10.4610.929(12.91)0.7290.663
Image 30.5321.000(Fix)0.679
Note: α = Cronbach’ α S.C.R = Standardized C.R.

Share and Cite

MDPI and ACS Style

Seo, E.J.; Park, J.-W.; Choi, Y.J. The Effect of Social Media Usage Characteristics on e-WOM, Trust, and Brand Equity: Focusing on Users of Airline Social Media. Sustainability 2020, 12, 1691. https://doi.org/10.3390/su12041691

AMA Style

Seo EJ, Park J-W, Choi YJ. The Effect of Social Media Usage Characteristics on e-WOM, Trust, and Brand Equity: Focusing on Users of Airline Social Media. Sustainability. 2020; 12(4):1691. https://doi.org/10.3390/su12041691

Chicago/Turabian Style

Seo, Eun Ju, Jin-Woo Park, and Yu Jin Choi. 2020. "The Effect of Social Media Usage Characteristics on e-WOM, Trust, and Brand Equity: Focusing on Users of Airline Social Media" Sustainability 12, no. 4: 1691. https://doi.org/10.3390/su12041691

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop