The impact of social media marketing and brand credibility on higher education institutes’ brand equity in emerging countries

ABSTRACT

Social media marketing facilitated prospective students to communicate and collaborate to gather information relevant to higher education institutions and their respective brand equity. More complex and dynamic models focusing on customer-based brand equity often lack empirical support in higher education sectors, particularly from more than one country. Drawing from the elaboration likelihood model, this study empirically investigated how higher education institutions can develop brand equity using social media marketing. The quantitative findings from 936 undergraduates from Sri Lanka and Vietnam indicated social media marketing influences the brand equity of higher education institutions through brand credibility. Taking into the comparison between two emerging countries, Vietnamese students are more concerned about brand credibility through social media marketing activities to form brand equity compared to their Sri Lankan counterparts. The findings provide some practical implications for educational marketers to promote their higher education institutions.

KEYWORDS:

• Social media marketing
• brand equity
• brand credibility
• emerging countries
• higher education

Introduction

In the competitive environment where higher education institutions (HEIs) expand globally, HEIs in many countries have focused on branding in which they foster effective and meaningful dialogues about HEI’s brand values to prospective students (Nguyen et al. 2020). To differentiate themselves in the marketplace, HEIs branding activities are developed around their strong brand equity which shows the credibility and capability of their services deliver to prospective students (Mclaughlin, Mclaughlin, and Mclaughlin 2018). Brand equity enables HEIs to enhance brand awareness in order to attract students, recruit high-caliber staff, gain higher market shares, and differentiate themselves from their competitors (Mourad, Meshreki, and Sarofim 2020).

Figure 1. A proposed theoretical model.

In particular, emerging Asian countries also acknowledged the importance of branding as they are increasingly becoming the emerging education hubs (Panda et al. 2019). Higher education (HE) sectors in emerging Asian countries witnessed an unprecedented expansion to meet the growing demand from domestic and international students (Anabila 2020). So, HEIs in emerging Asian countries are trying to differentiate themselves while developing branding strategies to attract prospective students (Yousaf, Mishra, and Bashir 2020). Although Asian HEIs’ administrators recognize the need for branding to distinguish themselves from competitors, HEIs in emerging Asian countries still struggle with their branding strategies to reach out to targeted prospects (Sobaih et al. 2016). There are relatively few studies that empirically explain the specificities of the brand equity development process in HE sectors. Attempts to understand this phenomenon more holistically have, so far, resulted in models which are purely conceptual or lack empirical support in the Asian market.

Recently, there is a high adoption rate of social media by the younger generation (Liu et al. 2021). It was estimated that over 90% of prospective students use social media (Aldahdouh, Nokelainen, and Korhonen 2020). As such, marketing activities on social media have become particularly important for HEIs to connect with prospective students (Lacka and Wong 2019). Whilst social media marketing is well established in emerging Western countries, a comparative analysis of the factors that motivate customers in emerging countries is lacking in the literature (Choi et al. 2019). What remains unclear is how social media marketing and brand credibility create and enhance brand equity for HEIs.

In this paper, we empirically test the relationship between the multi-dimensionality aspect of the customer-based brand equity (CBBE), with other marketing constructs in the HE sector, comprising two emerging countries of Sri Lanka, and Vietnam. Using the Elaboration likelihood Model as the theoretical foundation (Figure 1), we argue that marketing activities on social media create a significant impact on the HEIs’ brand credibility while reducing the uncertainty, to enhance brand equity. This offers a comprehensive understanding of the driving factors for HEIs’ brand equity in two emerging Asian countries of Sri Lanka, and Vietnam. The findings provide a valuable resource in the preparation of the HEIs’ branding and marketing strategies, through social media campaigns.

Theoretical framework and model development

Brand equity of higher education institutions

Marketing for HEIs is arguably more difficult than marketing activities for tangible products due to the unique characteristics of the HE industry that result in the existence of a high-perceived risk associated with the purchase (Zhang and Li 2019). Characteristics of intangibility, heterogeneity, inseparability, and perishability entail a higher level of uncertainty of the outcome of the delivered HE service (Posselt 2018). Although prospective students evaluate various factors to assess the HEIs’ quality, it is hard for HEIs to demonstrate the quality and consistency of HEIs’ brand promise delivery until students are enrolled and experience HEIs’ services (Sharabati, Alhileh, and Abusaimeh 2019). This issue creates difficulties for both HEIs (to convince prospectives for the high-quality education service) and prospective students (to select high price education service as a risky decision) (Endo, De Farias, and Coelho 2019).

Moreover, the trends in global student mobility contribute to a rapidly evolving market in international education, which, in turn, creates new opportunities, challenges, and an increasingly competitive higher education environment (Feng and Horta 2021). Lu, Scholz, and Nguyen (2018) argue that institutions with extensive experience in offering courses offshore or by distance education tend to develop global brands in order to be more effective in the international market. HEIs targeting overseas students to their home campuses might need to find ways to increase their brand credibility and equity globally (Lomer, Papatsiba, and Naidoo 2018). Hemsley-Brown and Goonawardana (2007) claims that consistent brand positioning delivery help HEIs to maintain their competitiveness in the global marketplace. By standardizing activities across international markets and linking other enterprise functions to support the overall branding effort, HEIs can achieve better brand equity (Feng and Horta 2021)

To overcome these challenges, HEIs try to strengthen their brand equity as an indicator of education quality offerings. Brand equity refers to ‘a set of brand assets and liabilities linked to a brand, its name, and symbol that add to or subtract from the value provided by a product or service to a firm and/or to that firm’s customers’ (Aaker and Equity 1991, 15). Brand equity is the added value with which a given brand endows a product; thus, rendering the development of a strong brand is imperative for organizational strategic thinking (Farquhar, 1989). In the HE industry, brand equity can be demonstrated through the professionalism of teachers/lecturers (inseparability and heterogeneity in their skills and the way they interact with the audience) (Lovelock and Jochen 2007), the reputation and history of the HEIs in the marketplace (Panda et al. 2019), location (Haffner et al. 2018), the high-quality available courses that HEIs can offer and have the expertise (Rambe and Moeti 2017), the supporting and operation systems to run education services (Mourad, Meshreki, and Sarofim 2020), and the physical facilities to support learning experiences (Fearon et al. 2018).

Brand equity is potentially a major element that influences the HE customer’s selection process as it acts as a risk reliever as well as a differentiation tool (Carvalho, Brandão, and Pinto 2020). HEIs try to establish positive brand equity to (a) enhance the HEI brand awareness among the stakeholders (Dennis et al. 2017), (b) attract many students (Lim, Jee, and De Run 2018), (c) enable the HEIs to recruit high-caliber faculty and administrators (Mourad, Meshreki, and Sarofim 2020), (d) differentiate themselves from rival new and existing HEIs (Perera, Nayak, and Nguyen 2020), and (e) gain a higher market share (Chee et al. 2016). However, the determinants of the CBBE in HE markets have received limited attention. The branding literature offers no prior research examining the issues and factors that are important for developing strong HEI brand equities (Endo, De Farias, and Coelho 2019). Developing and managing brand equity in the HE markets facilitates the HEIs to signal the quality service of the providing institution (Mourad, Meshreki, and Sarofim 2020). Thus, this research adopts an empirical model developed by Lassar, Mittal, and Sharma (1995). The adopted framework was developed by integrating the models of Aaker and Equity (1991) and Keller (1993) and synthesizing the HE services characteristics that determine brand equity, with the conceptualized dimensions of the brand equity: social image, performance, attachment, trustworthiness, and value.

The driving factors of CBBE: brand credibility and social media marketing

In the realm of intense competition, credible brands could trigger positive outcomes in the creation of brand value (Park, Im, and Kim 2018), and increase the purchase intention (Brunner, Ullrich, and De Oliveira 2019). Brand credibility refers to the customers’ perception of the brand’s perceived ability, motivation, and willingness to provide accurate and truthful information and deliver what the brand promises to its customers (Bougoure et al. 2016). Brand credibility is assessed through the holistic exposure of the customers to the brand across pre-purchase behaviour (Dwivedi, Nayeem, and Murshed 2018). Furthermore, in today’s digital and interactive age, real-time information influences a brand’s credibility (Pinem et al. 2019). It is intricately linked to high perceived brand value (Chakraborty and Bhat 2018), thereby improving customers’ perception of the brand attributes (Chin, Isa, and Alodin 2019). Similarly, higher brand credibility exerts a substantial effect on customers’ brand choice intention (Martín-Consuegra et al. 2018), influences the perception of high quality (Pecot et al. 2018), and low information searching cost (Fan et al. 2019). If the trustworthiness and expertise are not managed correctly, it can lead to brand rejection (Sun et al. 2019). In a service setting, brand credibility provides many benefits for the firms including high relationship equity (Mills, Pitt, and Ferguson 2019), reduced perceived risk (Busser and Shulga 2019), and positive change in customers’ purchasing and consumption behaviour (Chin, Isa, and Alodin 2019), which forms stronger ties between customers and the brand (Kashif et al. 2018).

Moreover, in developing branding strategies, HEIs are increasingly using social media to share, communicate, and collaborate with the students (Nguyen et al. 2020). The use of social media as a marketing channel has expanded in recent years, driven by the ability to reach millions of customers with brand-related content and engage them in conversations (Lacka and Wong 2019). Social media marketing (SMM) refers to the usage of social media networking sites for executive marketing activities effectively (Alawadhi and Al-Daihani 2019). The most prominent reason why social media has become an important communication tool in HEIs’ marketing landscape is its ability to protect HEIs within the competitive environment, and connect with the target audience instantly (Peruta and Shields 2018). In developing branding strategies, HEIs are increasingly using social media to share, communicate, and collaborate with the students (Nguyen et al. 2020). Social media facilitates the prospective students to receive a better understanding of the HEI including HEI reputation, education service, and quality, the course relevances, and HEIs’ lecturing member profiles (Rambe and Moeti 2017; Fearon et al. 2018). These factors influence the prospective students and other social media users to make their final decision of choosing HEI (Baker 2018). Despite the increased perceived risks of adopting social media in higher education marketing, HEIs seem to appreciate the benefits of using social media for marketing and overcome any negative feelings to be ‘good HEI’ (Manca 2020).

In order to create and exchange information about the brands with target customers, SMM is developed in two forms user-generated content (UGC) and firm-generated content (FGC) (Raji, Mohd Rashid, and Mohd Ishak 2018; Müller and Christandl 2019). UGC is the ‘media content created or produced by the general public, rather than paid professionals and primarily distributed on the Internet’ (Hollebeek and Macky 2019, 503) whereas FGC is considered ‘the content created by marketers on official brand pages on social media channels’ (Colicev, Kumar, and O’Connor 2019, 102). Brand-related UGC motivates prospective students to develop positive feelings toward the brands (Hwang and Kim 2015). Students tend to search for information and advice from others on social media to develop their favorable attitudes toward enhancing brand equity. Besides, FGC also enables consumers to evaluate HEIs against competitive HEIs to enhance brand equity (Colicev, Kumar, and O’Connor 2019).

In particular, during the Covid19 pandemic, social media marketing of HEIs is more important than ever (Lee, Ng, and Bogomolova 2020). HEIs are unlikely to organize traditional offline marketing events, experience days, school visits, face to face consultations to promote the HEIs (Dutta 2020). Marginson (2020a) noted that the effect of this pandemic created a negative impact on international higher education and student mobility which brought substantial financial challenges to universities and countries that depend on international students’ tuition. Moreover, the lockdown situation due to Covid19 changes prospects’ consumer behaviours. they visit social media platforms more frequently for the desire for social interactions, advice seeking, and updating the Covid19 situations (Sobaih, Hasanein, and Abu Elnasr 2020). To follow this tendency, HEIs have to increase the usage of social media for academic matters and marketing communication (Sobaih, Hasanein, and Abu Elnasr 2020). On one hand, using social media help HEIs to maintain high-quality education service delivery continuously with respective interested parties for academic matters (Dutta 2020). On the other hand, the increased usage of social media platforms such as Facebook, LinkedIn, and Instagram for marketing purposes can highlight their brand performance, and increase brand awareness among prospective students (Mason et al. 2021). Accordingly, many HEIs in Asia have creatively responded to the same challenges and started to pivot to a new era of education (Joaquin, Biana, and Dacela 2020). Universities in China have built and consistently improved the usage of social media for various types of online education (Mok et al. 2021). Similarly, Universities in Indonesia, Thailand, and Vietnam have shifted their focus to online platforms for both marketing and teaching activities (Yang and Huang 2021).

Theoretical background: elaboration likelihood model

Elaboration Likelihood Model (ELM) has been applied in the field of social media and electronic word-of-mouth (eWOM) (Cyr et al. 2018; Shahab, Ghazali, and Mohtar 2021) focusing on how marketers can influence consumers’ attitudes towards the brand through persuasive situations, such as online communities, blogs, and online marketing contents (Cyr et al. 2018). ELM suggests that social media users have a series of elaboration approaches to process available messages using cognitive thinking (the central route) or/and just following simple clues (the peripheral route) to make decisions (Goh and Chi 2017). When recipients have both the motivation and the ability to consider detailed information in a given message, persuasion occurs via the central route (Chang, Yu, and Lu 2015). It requires them to think hard about issue-related arguments in a message and reflect on the relative merits and relevance of those arguments (Cyr et al. 2018). Conversely, the peripheral route involves less cognitive effort, where individuals accept or reject a message without any active thinking about the attributes of the issue of the object of consideration (Liao and Huang 2021). Instead of doing extensive cognitive work, recipients rely on a variety of cues that allow them to make quick decisions (Shi et al. 2018). It is due to the lack of either motivation or the ability to cope with the detailed information in a given message (Pee and Lee 2016). While there were some challenging questions about the effectiveness of ELM in driving individual attitudes & behaviour (Kitchen et al. 2014; Kerr et al. 2015), EML is still a unified model that deals with both low and high cognitive processing aspects, particularly with social media context (Goh and Chi 2017; Shahab, Ghazali, and Mohtar 2021)

Using ELM, we argue the influence of social media marketing activities using UGC and FGC on CBBE via the mediating effects of brand credibility. In the social media context, the central route occurs when users need to review the content, and the strengths of arguments shared by others (UGC) and consider the likelihood of the claims. The reviews were based on the truthfulness of the UGC message, the relevance of the UGC message, the potential risks/benefits of sharing, etc. It required the use of critical thinking and consideration to process information, which needs more cognitive effort and careful observations (Chang et al., 2015). With the comprehensive consideration of relevant arguments, individuals can judge the brand’s credibility and subsequent behaviour toward the brand. On the other hand, FGC is processed by the peripheral route where individuals feel emotionally connected with the brand. If the brand creates a meaningful image through the FGC on social media such as physical facilities, its rankings in the marketplace, activities with stakeholders, and excellent service delivery, it could signal the brand’s ability and expertise in providing superior performances (Wang, Kao, and Ngamsiriudom 2017). In that case, users perceive the sources of the FGC information as credible, non-commercial, unbiased information. As such, individuals use some cues that the brand shared in FCGs to form their attitudes and make the decision toward the brand.

Mediating effect of brand credibility on brand equity

Social media allows users to create and exchange brand-related information on online platforms (Buzeta, De Pelsmacker, and Dens 2020). In this case, the evaluation of the brand occurs not only between customers and firms interactions but also among customers (Müller and Christandl 2019). Individuals believe that the opinions about the brand shared by their peers, family, or other influential people are trustworthy and reliable (Tajvidi et al. 2020). As such, UGC could create a varying effect on users’ perceptions of the brands (Jiao et al. 2018). The brand-related UGC such as reviews of the service/product, comments about the facilities, and people working for the brand may involve lots of ‘Likes’, ‘Comments’, ‘Shares’, and ‘Voting’ would help users to recognize the brand’s expertise and trustworthiness (Quesenberry and Coolsen 2019). The rationale for individuals to trust UGC is its lack of commercial purpose (Oliveira and Casais 2018). As such, if the users are highly engaged with the positive brand-related UGC activities, the effect on the evaluation of the brand is likely to be more positive (Jiao et al. 2018).

Accordingly, the information shared by users relating to HEIs on social media could influence the prospective students’ brand perception. When prospects perceive relevant brand-generated information shared by users that they already know as helpful, valuable, or persuasive, they follow these reviews and recommendations (Mourad, Meshreki, and Sarofim 2020). The higher the believability of the information shared by the existing students, and parents, the higher HEI brand credibility social media users perceive. It can result in a formation of brand value in their mind and, thus, lead to a better evaluation of the equity of the HE brands. We hypothesize that:

H1a:

Brand credibility mediates the effect of user-generated content on CBBE

The information on the brand’s official pages disseminates the signal of brand expertise, influencing the customers’ future brand considerations (Ismail 2017). Prospective customers gain a better understanding of the brand expertise and performance by reviewing the number of followers of firms’ brand pages, and the interactions in the posts (Mourad, Meshreki, and Sarofim 2020). Social media users typically rely on the content published by the brand assuming that the brand knows their brands better than others (Mishra 2019). Meaningful brand image through the published FGC on social media provides some cues for the brand’s ability and expertise in providing superior performance to competitive brands (Wang, Kao, and Ngamsiriudom 2017).

For HEIs, the information shared by the HEIs on their social media pages could help to influence the students’ perceptions (Peruta and Shields 2018). Information such as career advancement, collaborations with top tier industry partners, institutions’ rankings, research and education success stories, university scholarships, job placement opportunities, advanced facilities, student clubs, societies, etc. could provide some cues for students to judge the credibility of the HEIs (Beneke 2011). This would enable prospective students to form the credibility of an HEI’s brand and, thus, develop their strong HEIs brand equity perception. Hence, we hypothesize that:

H1b:

Brand credibility mediates the effect of firm-generated content on CBBE

Cultural differences in the adoption of social media marketing

Cross-cultural psychology theories and empirical research suggest that culture impacts everything from attitudes to motivations to social media needs and responses (Krishen et al. 2018). In this study, Sri Lanka and Vietnam were selected for comparison since both governments’ visions of Sri Lanka and Vietnam for 2025 are to transform the higher education industry for higher quality education service, more competitive, and better global positioning in the marketplace (Department for international trade 2017). The booming economy has triggered the development of HE sectors in Vietnam consisting of 171 public, and 65 private HEIs with a higher level of undergraduate enrolment rate (Tran and Villano 2017). Vietnam finds itself as a successful mover in Asian transnational education (TNE) (Nguyen et al. 2020). Conversely, Sri Lanka is still having a lower developing rate in the HE sectors consisting of 20 public and 17 private HEIs, with the lowest undergraduate enrolment rate which reached close to 20% in 2016, placing it among the lowest rates of all emerging countries (Nedelkoska, O’Brien, and Stock 2018). Moreover, it is projected that outbound mobility from Sri Lanka will exceed 32,000 students by 2027, a roughly 80% increase over the current UNESCO benchmark (British Council 2018). Similarly, over the past six years, the number of Vietnamese students studying abroad has increased by 69%. Accordingly, there are 170,000 students Vietnamese studying abroad in 2019 (Studyportal 2020). As such, Sri Lanka and Vietnam are looking forward to reducing the outbound student mobility to increase their enrolment rate in local HEIs by introducing a variety of marketing strategies (Tran and Villano 2017).

Despite the rapid growth of worldwide social media usage, the adoption and use of social media marketing have been highly variable across countries (Dwyer 2019). Using Hofstede (2001) cultural framework, previous studies suggested a strong association between cultural factors and social media usage together with marketing activities, given the fact that many countries share similar economic, literacy, and technology patterns (Hoehle, Zhang, and Venkatesh 2015; Mulvey, Lever, and Elliot 2020). In particular, the cultural dimensions of Individualism/Collectivism and Uncertainty Avoidance might have strong influences on young people’s social media behavior (Hoehle, Zhang, and Venkatesh 2015; Mulvey, Lever, and Elliot 2020; Hur, Kang, and Kim 2015). In higher individualism culture, individuals focus primarily on their thinking and are less likely to follow advice from others in cyberspace (Hoehle, Zhang, and Venkatesh 2015). Conversely, in lower individualism culture, individuals tend to enhance collaborations among social media users, build social relations among people, follow the online advice of others, and be responsive to the needs of others (Hur, Kang, and Kim 2015). As such, they particularly utilize the interactions for creating and exchanging user-generated content (Mulvey, Lever, and Elliot 2020). Because they tend to enjoy group environments, they more greatly value user-generated content in driving their perception of the brands.

Moreover, scholars found that the intention to adapt to social media sharing is stronger for individuals high on uncertainty avoidance (Goodrich and De Mooij 2014; Hoehle, Zhang, and Venkatesh 2015). Uncertainty Avoidance refers to the extent to which the members of a culture are ready to make decisions in ambiguous or unknown situations (Goodrich and De Mooij 2014). Hoehle, Zhang, and Venkatesh (2015) highlighted that social media users tend to follow well-established standards to reduce the uncertainty when selecting social media applications. In contrast, individuals in low uncertainty avoidance cultures tend to be more open and willing to take risks in unstructured situations (Goodrich and De Mooij 2014). Such individuals are less likely to be influenced by pieces of advice, sharing from others. Using Hofstede’s cultural dimension scores as references (Hofstede 2001; Hofstede Insights 2022), Sri Lanka is more likely to be high individualism culture (score: 35), while Vietnam is more likely to be low individualism culture (score: 20). Moreover, Sri Lanka is more likely to be high uncertainty avoidance (score: 45), while Vietnam is more likely to be low uncertainty avoidance (score: 30). Accordingly, that suggests some differences in the way prospective students adopt the FGC and UGC to form the brand credibility of HEIs.

Moreover, the different social media usage between countries could strengthen/weaken the perceived brand credibility, and perceived importance for HEIs’ brand equity (Garanti and Kissi 2019). While both Vietnam & Sri Lanka experience remarkable growth in the internet and social media with the advancement of new technologies, Vietnamese people are more active on social media than Sri Lankans. There are 64% of the Vietnamese population are active social media users (Hootsuite 2020), and this high number ranks 8th in Asia, 18th worldwide, and 2nd in South East Asia (Khuong and Huong 2016). Conversely, Sri Lanka has only 30% of active social media users (Hootsuite 2020). Since the manner and how undergraduates’ perception of the importance of the content generated by users and HEIs through social media could vary across the countries, and, therefore, their standpoint on HEI branding could also be diverse. George, Giordano, and Tilley (2016) found the brand perceptions of HEIs can be stronger generated if the prospects have higher interactions with other like-minded people on social media. Similarly, George, Giordano, and Tilley (2016) highlighted a positive link between social media engagement and increased brand interests. Higher usages of social media would lead to more searching activities about topics of interest including the higher educations firms. This results in more exposures to UGC and FGC shared by the brands and other social media groups, like-minded prospectives. As such, the following hypothesis is proposed in a higher education context:

H2

(a): The impacts of UGC on HEIs brand credibility will be stronger for Vietnamese students than their Sri Lanka Counterparts

H2

(b): The impacts of FGC on HEIs brand credibility will be stronger for Vietnamese students than their Sri Lanka Counterparts

Research method

Data were collected from a national sample of 1024 undergraduates studying at Sri Lankan, and Vietnamese HEIs. Two criteria were applied to identify the eligibility of each individual for this study: the first was that they must be a current undergraduate of the selected HEI, and the second was they must have at least one social media profile because some questions were based on undergraduates’ experience with social media. The researcher selected four institutions; one from each category based on (a) research-intensive, (b) teaching-intensive, (c) regional-focused, and (d) special interest from Vietnamese, and Sri Lankan HE sectors (Kandiko and Mawer 2013). All students in this study were enrolled in a degree program at accredited Sri Lankan, and Vietnamese HEIs (Table 1). Out of 1024 sent-out questionnaires, 978 were returned and 936 were considered valid for subsequent quantitative analysis as 42 were unusable due to the missing responses.

Table 1. Demographics.

	Sri Lanka		Vietnam
	n=412	%=44.02	n=524	%=55.98
Gender
Female	262	63.59	365	69.66
Male	150	36.41	159	30.34
College Status
1^st Year	159	38.59	218	41.60
2^nd Year	45	10.92	76	14.50
3^rd Year	154	37.38	131	25
4^th Year	54	13.11	99	18.90

The questionnaire was designed using existing scales from Lassar, Mittal, and Sharma (1995), Bougoure et al. (2016), Osei-Frimpong and Mclean (2018), Schivinski and Dabrowski (2016) (see Table 2). All responses were recorded using an ordinal 7-point Likert scale, which ranged from ‘”completely disagree (1)”’ to ‘”completely agree (7)”’. Descriptive statistics and exploratory factor analysis were used to create profile data and to identify the observed variables for these constructs using SPSS 23. Confirmatory Factor Analysis was used to assess the goodness of fit for the framework and structural equation modeling was used to analyze the structural relationships of the framework using AMOS 23. The mediating effect of brand credibility between UGC, FGC, and the dimensions of brand equity was also analyzed using the PROCESS macro developed by Hayes and Scharkow (2013). Further, this study conducted cross-country comparisons through multigroup analysis using AMOS 23.

Table 2. Factor loading and construct reliability.

Factors	Loading	α
Customer-Based Brand Equity (CBBE) - Lassar, Mittal, and Sharma (1995)
I can expect an outstanding teaching quality from this university	0.763	0.948
During the study period, I found that the quality of this university was less prone to errors	0.718
This university seems to be a learning place without quality problems	0.720
I feel proud of the decision to enrol in this university	0.720
This university will be well appreciated by my friends	0.765
Based on information on social networks, this university is suitable for my personality	0.584
This university degree is valuable	0.752
Considering the level of tuition that I pay for this university; I believe I will receive more than that tuition that I spend	0.764
I chose this university degree because of the benefits I received	0.805
If I look at the faculty and facilities of the university, I find this university very reliable	0.776
For students’ interests, the university seems very attentive	0.812
I believe this university does not take advantage of its students	0.756
After experiencing this university, I was very pleased with my growth and knowledge	0.731
I have a positive feeling for this university	0.791
The time at the university helped me feel friendlier towards this university	0.720
Brand Credibility (BC) - Bougoure et al. (2016)
This university does exactly what they promise	0.845	0.886
The quality promoted by this university is trustworthy	0.856
I can count on the brand of this university	0.861
This university reminds me of a graduate who is equipped with enough skills and knowledge and knows what they are doing	0.799
Firm-generated content (FGC) - Osei-Frimpong and Mclean (2018)
I follow the information posted by this university on their official social networking sites to get the updated information about the university	0.811	0.840
I follow up by communicating with the university’s official social networking sites to get more information about the university	0.838
I will follow the information on the university’s official social networking sites if the university-related information is interesting	0.837
User-generated content (UGC) - Schivinski and Dabrowski (2016)
I follow the university’s social networking sites to learn more about the upcoming activities of the university	0.762	0.833
Within these social networking sites, the content shared by other users about my university on meets my expectation	0.819
Within these social networking sites, the content shared by other users about my university is very attractive	0.811
Within these social networking sites, the content shared by other users about my university is better than other universities	0.770

Findings

Construct validity, common method bias testing

To assess the adequacy of the measures, the authors estimated the convergent validity through item reliability (see Table 2). Firstly, item reliability was evaluated based on the factor loadings of the items (i.e., observed variables) on their respective constructs. As all the factor loadings were higher than the threshold value of 0.5, convergent validity was supported (Hair et al. 2014). Secondly, construct reliability was assessed through Cronbach’s alpha (α). As Cronbach’s alpha was higher than the threshold value of 0.7, construct reliability was supported (Hair et al. 2014).

The authors also estimated discriminant validity to further ensure the adequacy of the measures. As all the Average Variance Extracted (AVE) values were higher than the threshold value of 0.5, convergent validity was supported (Hair et al. 2014). Discriminant validity was further evaluated by comparing the square root of the AVE of each construct with the bivariate correlations among constructs (see Table 3). Composite Reliability (CR) values were higher than 0.7, therefore, construct reliability was further supported.

Table 3. Construct reliability, convergent validity, and discriminate validity.

	CR	AVE	FGC	BC	UGC	CBBE
FGC	0.852	0.658	0.811^a
BC	0.874	0.640	0.177^b	0.800^a
UGC	0.803	0.577	0.213	0.318	0.760^a
CBBE	0.972	0.875	0.464	0.302	0.393	0.935^a

a: Square root of AVE in the diagonal.

b: Pearson correlations among constructs.

To estimate the fitness of the model estimates including the χ2 statistic, the goodness of fit index (GFI), root mean square error of approximation (RMSEA), comparative fit index (CFI) and Standardized Root Mean Squared Residual (SRMR) were assessed using AMOS and SPSS. The model yielded acceptable fit indices: χ2/df = 3.808, GFI = 0.941, RMSEA = 0.045, CFI = 0.957, and SRMR = 0. 0394.

Due to our data which is self-reported, a common method bias test was executed (Podsakoff 2003). We used Harman’s single factor analysis (Harman 1976), and the results show that 38.4% (less than 50% threshold) of variance was accounted for by the first factor. Therefore, we can conclude that this study data has no common method bias problems (Podsakoff 2003).

In the current study, all individual measured items were tested for normality using skewness and kurtosis statistics, which reveals that for the 26 items, the skewness was in the range of −0.339 to 0.250, and kurtosis was in the range of −0.701 to 0.201. According to Hair et al. (2014), any skewness and kurtosis values falling outside the range of −1 to + 1 represent a potential normality problem. This indicates no significant deviation from the normal distribution.

To decrease the variability of the data set, the researcher identified univariate and multivariate outliers. Univariate outliers were identified through z-score frequency distributions, and multivariate outliers were detected by calculating the Mahalanobis distance (D²). No standard score less than −3.29 or greater than +3.29 concerning all research variables indicated the absence of univariate outliers. Mahalanobis D² with p˂0.001 indicated the absence of multivariate outliers.

Hypothesis testing

Hypothesis 1 depicts that brand credibility mediates the effect of (a) UGC, (b) FGC on CBBE (Table 4). The indirect effect between UGC and CBBE was significant (indirect effect = 0.18; 95% bootstrap CI from 0.12 to 0.24). In addition, the direct effect of UGC on CBBE was also significant (direct effect = 0.22; 95% bootstrap CI from 0.16 to 0.27). This suggests brand credibility partially mediates the relationship between UGC and CBBE. Further, the indirect effect between FGC and CBBE was significant (indirect effect = 0.19; 95% bootstrap CI from 0.13 to 0.24). The direct effect of FGC on CBBE remained statistically significant over and above the indirect effect, indicating a partial mediation (direct effect = 0.32; 95% bootstrap CI from 0.27 to 0.38).

Table 4. Summary of path coefficients and associated bootstrap confidence intervals.

Path	CBBE
	B	95% CI
Without brand credibility as the mediators
Direct effect of UGC	.35	.29 to .40
Direct effect of FGC	.26	.21 to 32
With brand credibility as the mediators
Direct effect of UGC	.22	.16 to .27
Direct effect of FGC	.32	.27 to .38
Indirect effect of UGC via brand credibility	.18	.12 to .24
Indirect effect of FGC via brand credibility	.19	.13 to .24

Hypothesis 2 depicts that Vietnamese prospects will utilize (a) UGC (b) FGC to evaluate HEIs’ brand credibility higher than their Sri Lankan counterparts. The estimated path coefficients of Sri Lanka and Vietnam are 0.24 and 0.25, respectively. The critical ratio for both countries were 4.26 and 5.87 (>1.96), respectively, which are significant at 0.05 (p = 0.000), supporting H2a. Regression coefficient divided by standard deviation yields the critical ratio with absolute numbers <1.96, equating to non-significance (Gao, Mokhtarian, and Johnston 2008; Mandrell et al. 2018). In comparing both countries, Vietnamese are highly relying on UGC on identifying the credibility of a brand than Sri Lankan counterparts. When it comes to FGC, the estimates between BC in Sri Lanka and Vietnam were 0.11 and 0.21. The critical ratios were significant at the 0.05 level (p = 0.000), supporting H2b.

According to the findings (Table 5), Vietnamese believe that UGC could influence the performance, social image, value, trustworthiness, and attachment of an HEI brand. Vietnamese are possibly fostering a deeper connection with the brand community members while interacting with like-minded people to have the experience in selecting a specific HEI brand than Sri Lankan. In terms of FGC, Sri Lankans are lagging in following the information published by HEIs on the official social media pages than Vietnamese. Vietnamese seems to have relied more on information provided by the HEIs on their official social media pages to HEIs. The findings illustrated that Vietnamese students are concerned more about UGC, and FGC compared to Sri Lankans in identifying HEIs’ brand credibility supporting H2a, and H2b.

Table 5. Moderating effect of location.

Relationship	Sri Lanka (n=413)		Vietnam (n=523)		Differences between parameters	t-value differences between parameters
	B	t-value	B	t-value
UGC ⇨ BC	0.24	4.26***	0.25	5.87***	0.01	1.61**
FGC ⇨ BC	0.11	2.66***	0.21	4.03***	0.10	1.37**
BC ⇨ CBBE	0.06	1.55 (N/S)	0.07	2.11***	0.01	N/S

B = Estimate effect, *** p < 0.01, ** p < 0.05, N/S not significant.

Discussion

Theoretical contribution

This study builds on the process-focused CBBE model in a cross-cultural context with a view to (a) test its robustness in an international environment and assess its usefulness as a diagnostic tool for monitoring and managing brands internationally, and (b) illuminate the underlying mechanism by which the CBBE process results in key consumer outcomes and identify cross-country differences. We tested the proposed CBBE model with data from two national contexts (Sri Lanka, and Vietnam). The results showed that the model remains robust in explaining CBBE across the two countries. The confirmation of the research hypotheses underlying the model’s rationale underscores the structural power and operationalization of each of the three building blocks- social media marketing, and brand credibility throughout the entire CBBE building process concerning different national contexts. The findings of the present study could provide four valuable contributions to the existing knowledge.

Firstly, prior research suggests the effects of SMM on branding but offers limited discussions about the exact activity that might impact brand credibility and brand equity. Our findings highlighted both FGC and UGC exert positive effects on brand credibility and CBBE. On the one hand, prospects on social media spend more time with others, be more attentive to shared content by like-minded users about available programs, the quality of lecturers, and supporting activities. On the other hand, regular interactions on social media enable them to be exposed to content created and shared by the brands such as HEIs rankings, updated activities, and relevant programs to form their understanding of the HEIs. While past research has shown that contents shared by users are important for high involvement services of higher education (Del Rocío Bonilla et al. 2020; Gyamfi et al. 2021), our findings illustrate that content shared by the HEIs also impact fairly to people’s perception of CBBE. These results contribute to the debates among scholars about the influences of firm-created and user-generated social media communication on consumer perceptions of brands and consumer behaviour (Estrella-Ramon et al. 2019; Huerta-Álvarez, Cambra-Fierro, and Fuentes-Blasco 2020; Sagynbekova et al. 2021). Schivinski and Dabrowski (2016) noted that firm-created social media communication does not affect the consumers’ perceptions of brand value. However, the present study confirms FGC has an impact on brand credibility perception and brand equity in the higher education sector. However, the findings show that UGC exerts slightly stronger direct effects on CBBE than FGC does. This finding support Kim and Song (2018) who reported the importance of brand-related UGC in increasing customers’ brand purchase intention.

Secondly, our findings identify the important mediating roles of brand credibility. Previous studies also seem to agree on the mediating effect of brand-relationship construct in linking user-generated content to customer-based brand equity, such as brand commitment (Barreda et al. 2020), brand trust (Ebrahim 2020), or brand identification (Augusto and Torres 2018). However, the role of brand credibility as the mediating effect has not been investigated. Our results showed that the effect of UGC and FGC on CBBE is partially mediated by brand credibility. UGC and FGC do not build brand equity directly. Instead, parts of UGC and FGC’s total influences on CBE are transmitted through brand credibility. Shared content by users would allow prospects to gain knowledge about how HEIs have the ability to deliver their brand promise. Similarly, the updated contents by the brand through FB Advs, posts, comments, reply to individual comments on the brand pages help prospects recognize whether the brand is credible or not. As a result, it sharps their strong perception of the HEIs’ brand equity. By confirming the mediating role of brand credibility, this study extends the arguments of Dwivedi, Nayeem, and Murshed (2018) who report that building credibility of the brand is an effective way to attract customers, which in turn also makes it easier for consumers to justify paying a higher price for the brand value.

Thirdly, cultural differences influence social media practices among the Vietnamese, and Sri Lankan students in engaging with the branding activities. Previous research had identified the cultural factors to be of high importance to student choice (Briggs 2006; Rutter, Lettice, and Nadeau 2017). Vietnamese students are engaging with UGC and FGC more than their Sri Lankan counterparts indicating their higher level of engagement with social media and its marketing activities. Besides, Vietnamese exert a higher level of dependent on the brand’s credibility in evaluating HEIs’ brand equity than Sri Lankans showing their believability towards the brand’s ability and willingness in providing the promised service in making selection intentions. These differences are likely to reflect the different nature of the country’s cultural backgrounds of two of Hofstede’s cultural dimensions: Individualism and Uncertainty avoidance (Lin, Swarna, and Bruning 2017). In lower individualism culture, people seek group activities, trust their group members, enhance their group affiliation, and participate in collective decision making (Alsaleh et al. 2019). Conversely, people in higher individualism cultures tend to not follow the collective actions and norms for their attitudes and purchase decisions (Mourad, Meshreki, and Sarofim 2020). According to Hofstede’s cultural dimension (Dissanayake et al. 2015), Sri Lanka has a higher individualism score which accounts for 35 whereas the Vietnamese score is only 20. It can be explained by the results that Vietnamese seems to rely on the information shared on social media to shape their perception toward the brands more than the Sri Lankans. Sri Lankan is less be impacted by the group recommendations, advises to form brand credibility. Further, Hofstede’s cultural dimension of Uncertainty Avoidance score also can be used to explain the findings. It refers to the extent to which the members of a culture are ready to make decisions in ambiguous or unknown situations. The relatively intermediate score of 45 indicates that Sri Lanka does not indicate a strong preference for changes in their attitude and behaviours (Dissanayake et al. 2015). Conversely, Vietnam scored 30 for uncertainty avoidance which is lower than Sri Lanka indicating peoples’ openness to change and generally inclusive. Vietnamese prospects have a higher willingness to adopt social media sharing by users and firms in the evaluation of brand credibility and brand equity.

Finally, given the emergent nature of this research area, this work is one of the few studies to empirically examine students’ participation in SMM activities in creating brand credibility, and CBBE from the ELM perspective. Past study on ELM focuses on changing attitudes and intentions towards information and products (Chang, Yu, and Lu 2015), but seldom on the intentions to promote social media marketing (Zhang et al. 2021). Therefore, we make a detailed exposition of the ELM, extended the usefulness of this theory to social media marketing, and illustrate its application to the context of the higher education sector. Traditional ELM research described elaboration likelihood as the factor to facilitates or inhibits the motivation and ability to engage in issue-relevant thinking (Liao and Huang 2021). In this research, we argue that the perception of the content on social media, and BC can also reflect elaboration likelihood. This research provides a deeper understanding of how to change and improve students’ perception of brand equity about HEIs by developing a theoretical model based on ELM.

We refer to the ELM to explain the effects of CBBE through UGC, FGC, and BC through different routes as elaboration likelihood. Whereas fragmented studies identified UGC, FCG, and BC as important drivers of CBBE (Chang, Yu, and Lu 2015; Tajvidi et al. 2020; Nanne et al. 2021), our findings on elaboration indicate that social media marketing influences the audience in two major ways. On one hand, it affects elaboration and decision making through the peripheral route of persuasion by offering evidence-based HEIs information from the official social media pages such as outstanding facilities for study, its good rankings among other HEIs, extensive activities for students which clearly highlight brand’s expertise and excellent services sold by the firm (Liao and Huang 2021). On the other hand, information from third-party, such as users, which are not directly related to the content of the product but represent the popularity of the brand, can invoke heuristic rules of users and require them to use more cognitive effort to process information (Anglada-Tort et al. 2022). This is the central route of persuasion. Through showing the statistical significance of these relationships, this study is the first to demonstrate how ELM can play an important role in marketing for higher education institutes. The application of the ELM in the context of higher education has improved its ability to explain in multiple fields, which not only enriches the core content of the theory itself but also expands the theoretical basis of higher education research.

Managerial implications

This study offers a practical framework for HEIs to design long-term SMM strategies to enhance the global awareness of the HEIs. Evidence indicates that the overall use of social media has expanded significantly in recent years due to the pandemic (Tam and Kim 2019). Therefore, it is intuitive to assume that the use of social media for brand-related behaviours has likely increased by the emergence of the pandemic as consumers’ fears of physical contact with others have increased (Knowles et al. 2020). Furthermore, in the Higher Education field, 81% of prospective students use social media daily to search for relevant information about their target HEIs (Smith and Anderson 2018). As such, how to engage with a prospective student in cyberspace is critical for any HEIs. The study provides an opportunity for marketers to identify the most influential content generated on social media and implement branding strategies to attract their prospective students. By supporting the idea of brand equity under the prism of global common patterns, the findings help managers in mapping and designing new landscapes for HEIs, including specificities of the national context (Khoshtaria, Datuashvili, and Matin 2020).

Understanding what motivates prospective students to connect with institution brands is critical for marketing managers to build a healthy relationship with students (Manca 2020). This study provides valuable insight for how to conduct marketing activities on social media by balancing hybrid contents created by the HEIs marketing team and the other stakeholders in order to enhance their relationships with prospective students.

Firstly, marketing managers should strengthen their social media communication to offer a uniques value to HEIs to influence prospective students’ perception of the HEI’s brand equity. The marketing communication campaigns designed to attract prospective students should include a clear and appealing description of the services provided by the HEIs, together with academic and scientific data about the institution (Del Rocío Bonilla et al. 2020). An example would be publishing on social media such as physical facilities for study and life balance, institutions’ rankings, social club activities, job placement opportunities, research and education success stories of Lecturing team, students, alumni, and University scholarships. This credible, non-commercial, unbiased information could demonstrate excellent education service deliveries provided by HEIs. This variety of cues allows students to make a quick evaluation of the HE brand’s expertise in education. In turn, this could make prospective students become ‘followers’ of their social media pages in order to build their ties with the institution.

Secondly, prospective students can also explore HEIs that they plan to study by interacting with HEIs stakeholders on social media. They start searching posts from like-minded students, seeking for advices from alumni and educational experts, joining discussions about HEIs in 3^rd party social media groups. As such, UGC about the HEIs is important to allow prospective students to process cognitively the brand information and develop their critical thinking about the brand performance that is beneficial for the HEI brand image in the minds of prospective students. It is suggested that student ambassadors are perceived trustworthiness and empathetic which can engender favorable impressions about HEIs (Shu and Scott 2014). Accordingly, HEIs need to encourage the current students, and alumni to create more content about their student life and daily activities with HEIs on social media. More UGC will result in increased satisfaction, which will boost students’ positive opinions of HEI brands.

Thirdly, since our framework implies that brand credibility is critical for CBBE, marketing managers should ensure the clarity of the brand message in order to attract prospective students’ attention to what the HEI stands for. Therefore, there should be consistency in the marketing mix decisions, including communication with the students using both FGC and UGC in order to depict the credibility of the education services the HEI provide. HEIs should invest more to create and maintain the determinants of brand equity rather than simply expanding their promotional campaigns (Mourad, Meshreki, and Sarofim 2020). As a result, focusing on developing and maintaining the determinants of brand equity will help HEIs in positioning their service in the market and hence influencing the students’ enrollment intention (Kaushal and Ali 2020).

Finally, although both Vietnam and Sri Lanka are located in Asia, the social media marketing activities using both FGC and UGC seems working better in Vietnam. Marketing managers targeting Vietnam market should focus more on developing credible content in highlighting their ability to offer the promised service as Vietnamese are highly dependent on the trustworthiness and expertise of their services than their Sri Lankan counterparts. Similarly, HEIs who want to target Vietnamese market need to encourage the stakeholders (e.g., students, alumni, community, etc.) to create more positive content about HEIs to increase their credibility among the competitors. It highlights that there is no ‘one side fit all’ in the higher education market (Pinar, Girard, and Basfirinci 2020). The important message is that HEIs should develop their different branding strategies based on an in-depth analysis of the social media activities of prospective students in each country.

Limitations and future research

Notwithstanding its theoretical contributions and managerial implications, this research also has some limitations. Firstly, this research used private HEIs, so that the data about SMM, brand credibility, and CBBE was only available for private HEIs. This study focuses only on private HEIs in emerging countries. In Vietnam and Sri Lanka, public HEIs aim to maximize public surplus (Muller 2017), and their costs are covered by general taxation, and access to higher education is usually determined through selective exams (Frisancho and Krishna 2016). Therefore, a rigorous competition to attract the students and the requirement to differentiate from the other HEIs do not occur among the public HEIs. However, the government starts to reform public HEIs for a better competitive education market (Võ and Laking 2020). Thus, future researchers could be extended to public HEIs and identify how Public HEIs develop branding strategies by using social media. Secondly, this study is limited to the HE sectors, and therefore the external validity of the findings is an issue (Price and Kirkwood 2014). Future researchers could widen the diversity of service settings in the sample and replicate this investigation to discover if the results are consistent across the whole services sector. Thirdly, as data were only collected through questionnaires, mono-method bias is a concern (Abid and Butt 2017). Future research could triangulate surveys with qualitative data sources, such as direct observations or in-depth interviews. This would be useful to get more substantive insights about the branding activities in social media and their translation into brand credibility. Finally, future research could extend the model of this article by examining other brand-related SMM factors to identify the antecedences and consequences of brand credibility.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Charitha Harshani Perera

Dr. Charitha Harshani Perera is a lecturer at the Department of Marketing, Operations, and Systems, School of Business and Law, Northumbria University, UK. She holds a Ph.D. in Marketing Communication (RMIT University). Her research interest includes digital marketing, branding, and consumer behavior. Over the years, she has built a broad area of expertise across the marketing discipline as she spent several years in the industry prior to joining academia. She has attended several international conferences and published in several reputed international journals.

Rajkishore Nayak

Prof. Rajkishore Nayak is currently a senior lecturer at the Centre of Communication and Design, RMIT University, Vietnam. He completed his Ph.D. from the School of Fashion and Textiles, RMIT University, Australia. He has around 15 years of experience in teaching and research related to Fashion and Textiles. He published about 90 peer-reviewed papers in national and international journals. Recently, Rajkishore was awarded the ”RMIT University Research Excellence Award-2015”. He also received the ”RMIT University Teaching and Research Excellence Award-2012” and ”RMIT University International Scholarship-2008”. He worked with the School of Fashion and Textiles, RMIT University, Australia from 2012 to 2016 in teaching and research.

Long Thang Van Nguyen

Dr. Long Nguyen is a senior lecturer at the Professional Communication Department, School of Communication and Design of RMIT University in Vietnam. He holds a Ph.D. Degree in Marketing (The University of Adelaide, Australia). His research interests include customer engagement with social media, and dynamic pricing in the hospitality industry. Prior to joining academia, Long spent 10 years in sales and marketing and held a range of senior management roles in several global hospitality organizations including The Ascott Limited, and Saigon tourist.