Participating anonymous online student communities and university brand relationship outcomes

Abstract

Besides official social pages of organizations, the anonymous online consumer communities are emerging phenomena. Participating these communities may affect the relationship between consumers and brands. Focusing on the higher education context, where consumers and brands have strong relationship, this work examines the impact of participating “Confessions pages”- the anonymous community on the brand relationship outcomes. Quantitative data were collected from 480 university students in Ho Chi Minh city who have followed Confessions pages. Findings indicate that online interaction propensity in university confessions page and attitude toward confessions page have no relationship with brand relational outcomes while higher education involvement has significant impact on satisfaction and image. The research explores the effect of anonymous online communities on brand and provide suggestions for universities to deal with this emerging phenomenon.

Keywords:

• anonymous online communities
• student satisfaction
• university image
• student loyalty
• student trust

JEL Classification:

• M31
• I23
• P46

PUBLIC INTEREST STATEMENT

Participating on social media is prevalent in our daily life. University students, of the young generation, actively communicate on the social pages and discuss about every aspect of their lives, including the university-related topics. In order to improve the service quality and maintain the brand image of the university, university managers need to understand what students discuss about and how this activity influences the relationship between the university and its students. This research focuses on the anonymous online student communities (the Confessions pages) and investigates the impacts of the community engagement on the brand relationship outcomes. The research explores the effect of anonymous online communities on brands and provides suggestions for universities to deal with this emerging phenomenon.

1. Introduction

Social media is currently a primary platform of human communication (Alves et al., 2016). People in a variety of age use social media in daily basis and receive a wide range of information regarding their brands or consumption experience. Social media usage has transformed the nature of relationships among brands and their consumers, as the brands cannot control all information related to their images (Gensler et al., 2013). Besides the positive messages from online brand communities, consumers also participate negative discussions which possibly have negative impacts on the brand images (Dessart et al., 2020; Kristal et al., 2018). Much attention has been paid to social media engagement of consumers towards brands, from the two extremes, brand community (Brodie et al., 2013) and anti-brand community (Dessart et al., 2020), as brand love and brand hate. However, lack of research has been conducted to explore such online communities which lie in the middle of this continuum, as the community discussions with parody and pranks can be called “brand play” (Kristal et al., 2018). Focusing on the anonymous online student communities, this research explores such a “brand play” community, as the discussions on the communities are not clearly positive or negative about the brand and organization. This type of communities is especially popular for the credence-based services in which the consumers are highly involved with the brands and the consumers have lack ability to evaluate the quality of service (Girard & Dion, 2010). Because of the high involvement with the service, consumers are not clearly satisfied or dissatisfied with their experience. It depends on the particular cases, so that their communications on social media are also varied according to different situations.

Higher education is classified as a credence-based service, when most of consumers, as university students, have one-off decision to enter the university, and then spend a few years for their study (Le, Robinson et al., 2019; Moogan et al., 1999). Sometimes they are unhappy with their experience, but they are unlikely to quit. Social media is a channel for their chats and discussions regarding the student life (Fagerstrøm & Ghinea, 2013; Le, Dobele et al., 2019). Besides the official social pages or groups established by universities, the anonymous online student communities are increasingly popular. In Vietnam, students are familiar with confessions pages of universities (Son et al., 2021). Confession pages are pages on social media sites like Facebook or standalone websites which are generally used for students to anonymously post their confessions, secrets or basically their thoughts, complaints about their universities without everyone knowing their identity by sending what they want to post to that page (Son et al., 2021). The content of these posts is easily accepted to be posted by the page administrators, who are also anonymous. Many posts would influence university stakeholders, including current and potential students, so that it has significant impacts on the brand and relationships of the universities. This research aims to explore the impact of such anonymous online student communities on the university brand, by examining the influence of engagement on such communities and higher education on the university brand relationship outcomes.

This study begins with a literature review conceptualizing the social media engagement; its determinants and potential outcomes might have on the university—student relationship then focuses and reviews existing the relationship among factors. The next section presents the hypotheses that lead to a conceptual model for this research. The methodology shows the sample and methods of data collection and analysis. The most important of the study is the results, discussion and conclusion including the theoretical contribution, managerial implications and limitations and suggestions for future research.

2. Literature review

2.1. The determinants and relationship outcomes of community engagement

Online interaction propensity, attitude towards online community participation and product involvement are individual-related determinants of community engagement (Brodie et al., 2011; Dessart, 2017; Vivek et al., 2012). Online interaction propensity (OIP) is defined as the degree of a person’s willingness to interact with others in either online platforms or offline meeting, and not all people perform the same level of propensities to communicate (Wiertz & De Ruyter, 2007). Although OIP is relatively under-researched, it is the focus of some previous studies. For instance, Blazevic et al. (2014) investigated the interactivity side of social media and promoted the concept of General Online Social Interaction Propensity (GOSIP). They defined GOSIP as a trait-based individual difference in the predisposition to join online discussions. GOSIP displays the probability that a person will intentionally participate in an online interaction. Thus, OIP is an individual-level factor that captures individual predisposition to interact with other people or join online discussions in online communities (Blazevic et al., 2014; Dessart, 2017).

Attitude towards online community participation reflects the level that a consumer does favor or does not favor participating in the online communities (Wu & Chen, 2005). This concept was proposed from the theory of planned behavior (TPB) of Ajzen (1991). The theory is a well-known approach in social psychology that has been used successfully in hundreds of contemporary applied studies (e.g., Armitage & Conner, 2010) and a foundation for many studies on the relationship between attitude toward behavior and behavioral intention, such as Bagozzi and Dholakia (2006), Krueger et al. (2000), and Pelling et al. (2009). TPB defined attitude toward the behavior as the degree to which one has a favorable or unfavorable assessment of the behavior in question, before truly form an intention to do the behavior. Because online community participation is a behavior, attitude toward online community participation is defined as the degree to which one has a positive or negative appraisal or evaluation of the participation on the online communities, aligning with the notion of Dessart (2017). Hence, attitude towards online community participation is an individual-level factor that displays individual evaluation of participating on the online communities.

When it comes to product involvement, this concept has been a primary center of interest in consumer research literature for the past 20 years. The construct of involvement is the “perceived relevance of the object based on inherent needs, values, and interests” (Zaichkowsky, 1985). While involvement is a cognitive, affective, or motivational construct indicating state of mind (Smith & Godbey, 1991), or perceived personal relevance, it is not viewed as a behavior (Bloch & Richins, 1986; Celsi & Olson, 1988; Zaichkowsky, 1985). Product involvement is considered as an important dimension of engagement (Vivek et al., 2012).

Community engagement has the influence on the consumer brand relationship outcomes including the brand trust, brand commitment, and brand loyalty (Algesheimer et al., 2005; Brodie et al., 2011). The three determinants comprising online interaction propensity, attitude toward participation and product involvement are proposed to have impacts on the outcomes of consumer brand relationships. Fernandes and Moreira (2019) validated that “the effects of consumer brand engagement on brand loyalty, directly or indirectly through satisfaction, are stronger for emotional relationships’’. Nonetheless, brand image is an outcome of brand community participation (David et al., 2008; Keller, 1993). Thus, brand image and consumer satisfaction are outcomes of community participation. Hence, we proposed that those individual-related determinants of community engagement will have direct effects on the two relationship outcomes including customer satisfaction and brand image.

2.2. The proposed research model

In the context of this research in which investigating the anonymous online community, online interaction propensity and attitude towards online community participation can be transformed into online interaction propensity in university confessions page (OIPCP), attitude towards participating in university confessions pages (APCP). Nevertheless, as all business concepts and theories can contemporarily be applied in higher education sector (Tuan, 2012). University can recently be seen as brand providing a product called higher education and students have become customers. Therefore, we adapt product involvement into higher education involvement. As a result, online interaction propensity in university confessions page, attitude towards online community participation in university confessions page and higher education involvement rationally impact student satisfaction and university image, which will be examined in our study as the following hypotheses:

H1: OIPCP has a direct influence on student satisfaction.

H2: OIPCP has a direct influence on institution image.

H3: APCP has a direct influence on student satisfaction.

H4: APCP has a direct influence on institution image.

H5: Higher education involvement has a positively direct influence on student satisfaction.

H6: Higher education involvement has a positively direct influence on institution image.

In the higher education aspect, student loyalty may refer to both the period when a student enrolls courses and the period after they graduate (Helgesen & Nesset, 2007). As pointed out by Schlesinger et al. (2016), loyalty is not restricted to the period during which students are formally enrolled in courses at their university. Former students can help the university to improve and promote the image and reputation (Nguyen & LeBlanc, 2001), the loyalty of former students can also be highly important for educational institutions (Helgesen & Nesset, 2007).

The definition of trust has evolved over time (Schlesinger et al., 2016). Trust are relationship marketing constructs that are well acknowledged in the literature. It is a key variable for enhancing a relationship’s scope (Schlesinger et al., 2016). In service contexts, trust has been acknowledged as an important factor for developing customer loyalty (Ball et al., 2004; Chaudhuri & Holbrook, 2001; Garbarino & Johnson, 1999; Sirdeshmukh et al., 2002). Morgan and Hunt (1994) also defined trust as confidence of one party in the reliability and integrity of its exchange partner, which has been supported by a variety of contemporary studies from (Adidam et al., 2011; Ghosh et al., 2001; Helen & Ho, 2011; Hennig-Thurau et al., 2001; Sampaio et al., 2012) Figure 1.

Figure 1. The proposed research model

Satisfaction is widely acknowledged as a major driver of customer retention and loyalty (Fornell et al., 1996; Oliver et al., 1997). Satisfaction can be defined as the cumulative experience of the students with the university, which has been shaped over time and leads to students’ emotional evaluation of the brand (Ghorbanzadeh et al., 2020). Moreover, according to Schlesinger et al. (2016), the result revealed that satisfaction is one of the antecedents of the alumni loyalty in the context of higher education. In the meantime, Ganesan (1994) points out that satisfaction increases perceptions of credibility and benevolence of the other party, which is trust. Several previous papers indicated that satisfaction could lead to trust, namely Flavián et al. (2006) and Loureiro et al. (2014). In education, a research conducted by Rojas-Méndez et al. (2009) is unique in reporting such a relationship. Based on these theories, the hypothesis hold for student satisfaction is as below:

H7: Student satisfaction has a positive impact on student loyalty.

H8: Student satisfaction has a positive impact on student trust.

Institutional image is an important construct for university students (Nguyen & LeBlanc, 2001; Schlesinger et al., 2016). In prior studies, university image is the indirect antecedent of the loyalty, determined by the work of Schlesinger et al. (2016) and Alhaddad (2015). Similarly, Chiou and Droge (2006) validated that a trustworthy image can increase loyalty. Apart from that, Alhaddad (2015) also supports the notion that brand image has a positive effect on brand trust. In the meantime, Palacio et al. (2002) and Clemes et al. (2007) showed the finding to shade the light for the influence of overall image on satisfaction. Therefore, hypotheses regarding university image are proposed as in below:

H9: University image has a positive influence on student satisfaction.

H10: University image has a positive influence on student loyalty.

H11: University image has a positive influence on student trust.

3. Methods

3.1. Sample and data collection

A quantitative approach has been conducted to examine and analyze the data set collected from the respondents of a questionnaire survey. This survey is in the form of both pen-and-paper and web-based questionnaires, targeting university students who follow universities’ confession pages. Students who carried out the survey came from various universities. The chosen universities were among the most popular universities in Ho Chi Minh city and all universities are considered to have a large number of students experiencing confessions pages. The online survey was implemented via Google Form links shared on Facebook. The offline survey is hard-copy questionnaires collecting responses from random university students in four university campuses and an event in the Youth Culture House of Ho Chi Minh City. Before distributing printed questionnaires to get responses, the survey conductors asked respondents whether they follow their university’s confessions pages or interact with those pages. All the participants in the research were completely voluntary and all questionnaires, both online and offline, were returned with a total of 480 respondents used for data analysis. The sample characteristics are presented in Table 1. There are 298 females (62%) and 182 males (38%) respondents. All respondents are from large universities in Ho Chi Minh City. The major of study reflects the distribution of major in reality, in which half of the respondents are studying business and economics (45%).

Table 1. Sample characteristics

	Units	Percent
GENDER
Male	182	37.92%
Female	298	62.08%
AGE
18	94	19.58%
19	107	22.29%
20	99	20.63%
21	141	29.38%
22	27	5.63%
23 and above	12	2.50%
ACADEMIC STANDINGS
Freshman	103	21.46%
Sophomore	123	25.63%
Junior	85	17.71%
Senior	169	35.21%
GPA RANGE
Not yet	80	16.67%
Lower than 2.0	6	1.25%
From 2.0 to lower than 2.5	29	6.04%
From 2.5 to lower than 3.0	47	9.79%
From 3.0 to lower than 3.5	168	35.00%
From 3.5 to lower than 3.75	87	18.13%
From 3.75 to 4.0	28	5.83%
Others	35	7.29%
UNIVERSITY
Ho Chi Minh City University of Technology, VNUHCM	41	8.54%
Hoa Sen University	63	13.13%
International University, VNUHCM	148	30.83%
Ho Chi Minh City University of Science, VNUHCM	101	21.04%
University of Economics and Law, VNUHCM	31	6.46%
Others	96	20.00%
MAJOR OF STUDY
Business and Economic	215	44.79%
Engineering	89	18.54%
Natural Science	96	20.00%
Social Science and Law	30	6.25%
Others	50	10.42%
LIVING AREA
Ho Chi Minh City	436	90.83%
Others	44	9.17%

3.2. Measures and pretest

There are seven measurement scales for constructs including OIPCP, APCP, Higher Education Involvement, Student Satisfaction, University Image, Student Loyalty, and Student Trust. The first three antecedents, student trust and student loyalty were measured using the scales adapted from Dessart (2017), while the measurement scale of university image was adapted from Schlesinger et al. (2016). Student satisfaction was measured by the scale developed by Fornell (1992) and supported by Palacio et al. (2002) and Schlesinger et al. (2016).

In the beginning of the questionnaire, screening questions ensure that only participants who follow confessions pages or interact with the post on these pages could carry out the questionnaires. Moreover, the definition for every concept were carefully described for respondents to fully understand the concepts and answer the question from the same perspective. The remaining part of the questionnaire was structured to follow the order of examined constructs. The final section was about to collect participants’ demographic information. Pilot test was conducted with one academic staff and ten Vietnamese university students to ensure the language, translation and the questions were well understood.

4. Data analysis and results

In the first stage of measurement validation, principal component factor analysis indicates that the eigenvalues of all factors are greater than one. All factor loadings are high, and there are no significant cross-loadings with the Varimax rotation method. Before conducting the path analyses to test the hypotheses, a confirmatory factor analysis (CFA) using AMOS 22 was performed to analyze the reliability and validity of constructs measured by multi-item scales. Maximum likelihood (ML) estimation was employed to estimate the parameters and the overall fit index of the measurement model. The measurement model consisted of OIPCP, APCP, Higher Education Involvement, Student Satisfaction, University Image, Student Loyalty, and Student Trust on University. All constructs’ Average Variance Extracted indices (AVE) were higher than 0.5. The overall fit indices of the measurement model, as reported in Table 2, indicating a good model fit (Fornell & Larcker, 1981; MacKenzie et al., 2011), and all of the factors satisfied the conditions for reliability and validity (Hair et al., 2006).

Table 2. Measurement model

Code	Measures	Factor loading
	Online Interaction Propensity in University Confession Pages (OIPCP) (α = 0.834; AVE = 0.56; CR = 0.84)
OIP1	I am someone who enjoys interacting with like-minded people in online confession page(s)	0.710
OIP2	I am someone who likes actively participating in online confession page(s)	0.799
OIP3	I thoroughly enjoy exchanging ideas with others via online confession page(s)	0.760
OIP4	In general, I like to get involved in online confession page(s)	0.719
	Attitude Toward Online Community Participation in University Confession Pages (APCP) (α = 0.817; AVE = 0.60; CR = 0.82) (* = reversed scales)
ATTR2	I think that participating in online confession page(s) is foolish*	0.798
ATTR4	I think that participating in online confession page(s) is harmful*	0.789
ATTR5	I think that participating in online confession page(s) is punishing*	0.740
	Higher Education Involvement (α = 0.810; AVE = 0.70; CR = 0.82)
HEI1	Higher education matters to me	0.728
HEI2	Higher education is very important to me	0.938
	Student Satisfaction (α = 0.894; AVE = 0.74; CR = 0.90)
SAT1	My decision to choose this university was correct	0.868
SAT2	My experience in this university has satisfied my expectations	0.814
SAT3	In general, I am satisfied with my decision to attend this university	0.897
	University Image (α = 0.795; AVE = 0.51; CR = 0.75)
IMA1	I have always had a good impression of this university	0.801
IMA2	In my opinion, this university has a good image in the minds of consumers	0.614
IMA3	Overall, I have a positive image of this university	0.712
	Student Loyalty (α = 0.883; AVE = 0.67; CR = 0.89)
LOY1	If I were faced with the same choice again, I would still choose the same university	0.861
LOY2	If I had to apply for advanced courses or postgraduate courses, this university would be my first choice	0.704
LOY3	If somebody asked me, I would definitely recommend this university	0.855
LOY4	If the opportunity arose, I would make positive comments of this university to family and friends	0.853
	Student Trust (α = 0.879; AVE = 0.66; CR = 0.85)
TRU1	I trust my university	0.892
TRU3	My university is an honest university	0.722
TRU4	My university is safe	0.806
Model Fit indices: Chi-square = 400.831, df = 184, p = .000, Chi-square/df = 2.178, Goodness of Fit Index (GFI) = 0.929; Tucker Lewis Index (TLI) = 0.957, Normed Fit Index (NFI) = 0.939, Comparative Fit Index (CFI) = 0.966 and Root Mean Square Error of Approximation (RMSEA) = 0.050
N = 480; α = Cronbach’s Alpha; AVE = Average Variance Extracted; CR = Composite Reliability.

Table 3 shows the results of path analysis using structural equation modelling (SEM). CFI, NFI, GFI, TLI were all greater than 0.9 and RMSEA was smaller than 0.06 (Hu & Bentler, 1999), which implies an appropriate fit for the model. Among the eleven direct hypothesised relationships, the SEM results indicated three non-significant relationships, as reported in Table 3. Three non-significant hypothesized relationships included the impact of OIPCP on University Image and Student Satisfaction and the impact of APCP on Student Satisfaction. Hence, the hypotheses H1, H2, H3 were not supported.

Table 3. Results of path analysis

	Casual Path	Std. Estimates	Significance		Support
H1	Online Interaction Propensity → Student Satisfaction	0.087	0.044	Insig.	Not Supported
H2	Online Interaction Propensity → University Image	0.062	0.257	Insig.	Not Supported
H3	Attitude Toward Confessions → Student Satisfaction	0.023	0.598	Insig.	Not Supported
H4	Attitude Toward Confessions → University Image	0.151	**	Sig.	Supported
H5	Higher Education Involvement → Student Satisfaction	0.126	**	Sig.	Supported
H6	Higher Education Involvement → University Image	0.341	***	Sig.	Supported
H7	Student Satisfaction → Student Loyalty	0.811	***	Sig.	Supported
H8	Student Satisfaction → Student Trust	0.586	***	Sig.	Supported
H9	University Image → Student Satisfaction	0.671	***	Sig.	Supported
H10	University Image → Student Loyalty	0.143	**	Sig.	Supported
H11	University Image → Student Trust	0.374	***	Sig.	Supported
Model Fit indices: Chi-square = 425.620, df = 191, p = .000, Chi-square/df = 2.228, Goodness of Fit Index (GFI) = 0.924; Tucker Lewis Index (TLI) = 0.955, Normed Fit Index (NFI) = 0.935, Comparative Fit Index (CFI) = 0.963 and Root Mean Square Error of Approximation (RMSEA) = 0.051
N = 480; *** significant at the 0.001 level, ** significant at the 0.01 level

According to the results, APCP was reported to have a significantly positive influence on University Image (β = .151, p < .01). Thus, H4 is supported. Next, Higher Education Involvement was verified to have a significantly positive effect on Student Satisfaction (β = .126, p < .01), and on University Image (β = .341, p < .001), which supported H5 and H6. Likewise, Student Satisfaction also indicated positive significant influences on Student Loyalty (β = .811, p < .001), and Student Trust (β = .586, p < .001), confirming the hypothesis H7 and H8. These strong relationships show that Student Satisfaction is the key factor to build up a strong brand relationship. The influence Student Satisfaction has on Student Loyalty is stronger than that on Student Trust. Last, University Image was shown to have positive significant influences on Student Satisfaction (β = .671, p < .001), Student Loyalty (β = .143, p < .01), and Student Trust (β = .374, p < .01), verifying the hypothesis H9, H10 and H11. University Image has the greatest effect on Student Satisfaction, then on Student Trust and lastly on Student Loyalty.

5. Discussion

Online Interaction Propensity, Attitude Toward Online Community Participation, and Higher Education Involvement are three constructs that capture individual predispositions toward the online community (Dessart, 2017). Applying these constructs into the context of anonymous online community in higher education results indicates that participating confession pages would not impact the brand relationship outcomes. According to the empirical results, OIPCP has no influence on either Student Satisfaction or University Image. Although students expose and interact with the confession pages and anonymously discuss about experience with the universities, it is unlikely to change their satisfaction or their perceived image of university.

APCP influences University Image but not Student Satisfaction. This means both participation and attitude toward confession page would not increase or decrease the satisfaction of students. It is different from the anxiety of university managers that the confession pages would damage all the efforts and quality they bring to students. One of the reasons should be because the posts and discussions on confessions pages are diversified, not only the negative feedbacks about universities (Son et al., 2021). Moreover, students who engage in the anonymous online communities might be also the groups who highly engage in the activities of their universities. Therefore, they are not easily influenced by the posts on these communities. This is also consistent with the significant effects of Higher Education Involvement. Higher Education Involvement has significantly positive influences on University Image and Student Satisfaction. These results are in line with the support of David et al. (2008) who proved the positive influence of product involvement on brand image.

Along with the above relationships, the inter-relationship of four relational outcome variables in the Higher Education context was tested. Those variables have been examined for years but without the presence of online communities. In our study, the online community was considered when examining Student Satisfaction, University Image, Student Loyalty, and Student Trust. The results are consistent with previous studies on the influences of Student Satisfaction on Student Loyalty and Student Trust (Schlesinger et al., 2016). The impacts of University Image on Student Satisfaction and Student Trust were also supported by the findings. Meanwhile, our results oppose previous studies that confirmed the influence of University Image on Student Loyalty.

6. Implications for theory and practice

Social media are currently the major platform of human communication. Besides the online brand or fan communities of normal products or services, online communities of students have been popular (Le, Dobele et al., 2019). University mangers are difficult to manage the discussions on these platforms, especially the anonymous online communities. This is among the first research to explore the impact of these phenomena on the university brand relationships. The findings of this research contribute to the literature of brand and social media engagement in two aspects. First, anonymous online community is a special type of online brand communities, with lack of attention in previous studies. Beside the brand communities (Brodie et al., 2013) and anti-brand communities (Dessart et al., 2020), this research explores another type of consumer community. Second, this research contributes to the literature of online community in higher education context. As higher education is a credence-based service (Moogan et al., 1999), a context with some special consumer and institution characteristics.

Considering the online communities and communication are recently important to the integrated marketing communication strategies of firms and organizations, this research provides insights for marketers to understand the impact of online engagement in the context of such a special online community. Since the results show that OIPCP and APCP do not influence Student Satisfaction, University Image, interaction of students on these pages does not change the satisfaction of the students and the university image they perceive. Therefore, in terms of relationship marketing, the anonymous online communities of students would not decrease the evaluation of students on the university quality and image. University managers can consider the online anonymous communities like confessions pages as an external channel to observe and understand more about their consumers. Universities do not need to restrict students from creating, operating, and interacting with online communities such as confessions pages. Universities should invest in developing the involvement of students in the official and informal activities with the universities, as involvement was proved as an important factor to university brand relationship.

7. Limitations and future research directions

In our study, the confessions pages in Vietnamese higher education context are applied as the sample of anonymous online community, which might limit the generalization of research because the content of confessions pages may be unique and could not represent the phenomena of anonymous online communities. Thus, further studies on the same topic should investigate diversified forms of anonymous brand community. Data can be collected in different countries, in order to capture how culture can influence the students in terms of participating such online anonymous communities.

Acknowledgements

This research is funded by International University - VNUHCM under grant number T2019-04-BA

Additional information

Funding

This research is funded by International University - VNUHCM under grant number T2019-04-BA

Notes on contributors

Tri D. Le

Tri D. Le has research interests in word-of-mouth, higher education marketing, online engagement. His works have been published in journals such as Journal of Consumer Behaviour, Studies in Higher Education, and Marketing Intelligence and Planning.

Linh Le

Linh Le and Quynh Phan are research assistants at International University, VNU-HCM, Vietnam. Their research interests are online communities and brand engagement.

Quynh Phan

Linh Le and Quynh Phan are research assistants at International University, VNU-HCM, Vietnam. Their research interests are online communities and brand engagement.

Khoa T. Tran

Khoa T. Tran is the President of International University, a member of Vietnam National University at Ho Chi Minh city (VNU-HCM), Vietnam. He completed his doctorate degree in Marketing and International Business at Western Sydney University, Australia. His research interest includes corporate branding and behavioral studies on business management. His works have been published in journals such as Sustainability, Administrative Sciences, Entrepreneurship and Sustainability Issues.

Phuong Nguyen

Phuong Nguyen is a lecturer and researcher of International University, VNU-HCM. He earned his Ph.D in Development Administration at NIDA, Thailand. His major research focuses on public policy, sustainability, and corporate strategy.