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Communitas

On-line version ISSN 2415-0525
Print version ISSN 1023-0556

Communitas (Bloemfontein. Online) vol.26  Bloemfontein  2021

http://dx.doi.org/10.18820/24150525/comm.v26.3 

ARTICLES

 

The development of a brand perception instrument for South African youth

 

 

Caroline Muyaluka AzionyaI; Nina Overton de KlerkII

IDepartment of Strategic Communication, University of Johannesburg, Johannesburg, South Africa. Email: carolinea@uj.ac.za; ORCID: https://orcid.org/0000-0003-1051-274X
IIDepartment of Strategic Communication, University of Johannesburg, Johannesburg, South Africa. Email: ndeklerk@uj.ac.za; ORCID: https://orcid.org/0000-0001-7466-8837

 

 


ABSTRACT

South African youth are a diverse, multicultural heterogeneous cohort differentiated racially, spatially, digitally and socio-economically. This study aimed to develop a quantitative instrument to measure the brand perceptions of 18 to 24-year-old South African consumers communicated on Facebook. Young adults base their perceptions of brands on their touchpoints and other consumer experiences. Therefore, brands need to have a reliable means of measuring the brand perceptions of young adult consumers to avoid negative earned media and reputational damage. Ten factors that explained 62.812% of total variance were extracted after exploratory factor analysis. These factors are brand fan behaviour, shared brand-related content, value brand influencers, corporate social responsiveness, user-generated content, brand-related content, familial influencers, premium brand influencers, communication expectations and recommending behaviour. Key findings indicate that measuring brand fan behaviour or interactions with brand advocates is critical to building positive perceptions and relationships with 18 to 24-year-old consumers on Facebook. Second, the shared brand-related content factor highlights the critical role brand experiences and customer opinion play on Facebook when shaping the perceptions about brands for young adults via positive and negative earned media.

Keywords: earned media; shared media; consumer brand perceptions; digital participation; UGC; brand advocates; Facebook; youth influencers


 

 

INTRODUCTION

The current South African business context for brands can be characterised as complex with fluid micro and macro trends. Furthermore, brand communication stewards (client and agency) face various challenges such as a fragmented media landscape, advertising fraud, keeping abreast of automation, diverse channel options with various content needs, budget pressures and a distracted and demanding consumer toggling between multiple screens and channels.

Consequently, mobile, digital, social and marketing technologies have largely relegated traditional advertising to an expensive practice - difficult to measure, increasingly avoided, and blocked by consumers (Macnamara et al. 2016; Shiao 2019).

The demand for more accountability on brand communication budget spend and the provision of high impact measurable results on profits and reputation from South Africa's burgeoning digital industry grows daily (Pienaar 2020). Consequently, marketers are using consumer-centric content strategies to try to capture and engage the attention of key stakeholders, boost sales and solve business problems via digital (Pienaar 2020). Digital spend in South Africa amounted to $1.37 billion in 2019 (DataReportal 2020).

The literature review outlines the key traits and characteristics of 18 to 24-year-old young adults, followed by an exposition of Facebook as a brand communication channel. A comprehensive discussion on media precedes a discussion on how consumer brand perception is influenced by social media.

 

LITERATURE REVIEW

South African youth

South African youth are part of a diverse multicultural heterogeneous cohort differentiated by 11 official languages, race, spatial (rural, peri-urban and urban), and polarised socio-economic circumstances. The heterogeneity expresses itself as unique consumer sub-segments even within the same age group and region. "The majority of SA's youth often falls within one of three categories: uneducated, unemployed, and unemployable" (Statistics South Africa 2019).

South African youth spend

Despite not having the buying power of their parents, these 18 to 24-year-olds are still a significant consumer group. In 2017, they represented R33 billion in spend (Student Brands 2017). By 2019, the figure had grown to R44.6 billion (Media Update 2019). As key decision-makers, South African youth influence the majority of household buying decisions, identifying trends and endorsing brands (Media Update 2019). Currently the youth market is worth R131.2 billion annually in direct and indirect youth expenditure (Media Update 2019). Therefore, building sustainable relationships via expressive social media channels of which they are frequent users (Deloitte Global 2019) could foster brand affinity, loyalty, current profitability, and lucrative lifetime value.

Key characteristics and traits of 18 to 24-year-old South Africans

These young adults are increasingly sceptical towards traditional push advertising and content from brands (Jordaan et al. 2011: 2-3; Rhodes 2020). Therefore, it is difficult for brands to capture and sustain their attention (Lazarevic 2012). Brand content needs tailoring according to gender, status elements of products, self-congruity, product category, language, and geographical and ethnic requirements to capture their attention (Dalziel & De Klerk 2018: 267).

In the digital sphere, brand messages compete with friends and followers, consumer readers and blogs (Phillips & Young 2009: 113-114). Young adults prefer crowdsourcing opinions and ratings about brand performance from sources outside a brand's influence, including family, friends and influencers. For credibility, influencers must demonstrate real humanity, achievement, and create emotional connections that foster closeness and friendship (Van den Bergh et al. 2011). Subsequently, young adults' value and trust directly contact more (Mucundorfeanu 2014: 43).

These considerations necessitate a channel agnostic approach that avoids the inclusion of digital channels that do not serve a strategic purpose and/or resonate with end-users. Prime examples include social media channels created for brands, which have a digital presence that is not updated regularly. In concurrence, Nhedzi (2018: 34-35) cautions against discarding traditional print media and television media advertising in favour of digital media. His study advocates a complementary usage reflective of the economic realities of South Africa, where access to digital platforms is limited by data affordability. In addition, the internet penetration rate is 62% (n = 32.54 million; DataReportal 2020) and the social media penetration rate 37% (n = 22 million; DataReportal 2020).

Radio reaches 37 million out of the 40 million South Africans 15 years and older (The Broadcasting Research Council Of South Africa 2019a) and South Africa's free-to-air linear top-rated television show reaches 10 072 999 viewers (The Broadcasting Research Council Of South Africa 2019b). These are still significant platforms to reach youth with brand messages. However, print media in South Africa is experiencing a sharp decline due to pressure on consumer spending and free content online. Advertisers are debating the relevance of this platform in light of these declines.

Although poorer young adults display elevated levels of narcissism, technology addiction and materialism (Guse & Jesse 2014), there is generally a culture of instant gratification and hyper-consumerism amongst 18 to 24-year-olds (Finweek 2013). These youth use a collection of carefully selected value and premium brands, sometimes from the same product category, for these purposes. Individual realities and life stage influence these choices. Therefore, brands are used to construct, represent and amplify their fluid, multiplicious, inter-connected and individual-centred self-identity; using transference to reflect associated brand meanings and values (Robards & Bennett 2011: 312-313). They participate in digital culture and manage their digital identities through discourse that signifies their aspired and existing selves via identity-resonant content (Berger 2014: 591) and their interests and opinions. Young adults tend to be team-oriented, collaborative and prone to activism over issues they care about, such as free higher education. Young adults are socially influential, and significantly influence the purchase decisions of their acquaintances and close relatives.

Digital participation in South Africa is complex. Sharp differences exist between the haves and the have-nots in terms of access to the internet, and more so in rural areas that are under-resourced in comparison to urban areas (Bornman 2015). High data costs and a lack of equipment (a smartphone with adequate or expandable memory or computer) exacerbate this inequality. This digital divide in South Africa is not only about meaningful access to hardware and the internet; the lack of ICT skills, income and education compounds the issue (Bornman 2015: 6). Therefore, the notion that every young adult is a digital native or has a higher digital competence than older generations is problematic. As is the notion that they engage in educational, business and social activities in a cyber-smart and secure way that does not compromise them to the same extent as their counterparts in the developed world (Takavarasha et al. 2018).

The digitally connected young adult has the necessary resources for a brand's survival (education, skills, infrastructure and meaningful access, influence, social capital and network of friends and family). The less digitally connected consumer uses the internet primarily for socialising and entertainment (Bornman 2015: 6). In addition to socialising and entertainment, the digitally connected make full use of its capabilities through gathering and disseminating information (Jordaan et al. 2011: 3) linked to organisational and personal tasks (Bornman 2015: 6). South Africa's most popular social networking platform, Facebook, has an estimated 21.1 million users (NapoleonCat 2020) who are increasingly using the platform to engage with its news and entertainment features, as well as its video feeds (Nhlapo 2018).

Facebook and Facebook Lite

While internet access and literacy remains a barrier in South Africa's lower income groups, Facebook Lite has sparked a rapid uptake within this group via its Facebook Lite app (Nhlapo 2018). Due to its massive appeal and adoption in South Africa and globally it has "become the ideal platform for companies to advertise and approach their consumers". Facebook offers brands user-friendly, cost effective campaign setup and management tools with numerous resources and support. Brands can optimise their successes by changing their campaign budgets daily or in real-time in response to visualisations and reports. Facebook uses artificial intelligence and machine learning to allow brands to profile and target consumers and prospects and personalise content according to various behavioural (Rhodes 2020), demographic, location and interest Alters. Brands can use various advertisement formats to create awareness, brand discovery, generate sales leads, and boost their presence, or encourage loyalty and measure the success of their campaigns. Critical success factors for young adults' attitudes towards Facebook advertising include perceived interactivity, advertising avoidance, credibility, and privacy.

Social media

Social media or "social forms of media" are web-based applications enabling multidirectional delayed time/asynchronous and synchronous/real-time computer mediated interactions between individuals or brand communities (Romiszowski & Mason 2004: 398). They introduced novel interaction paradigms that produce crowdsourced digitised content created and enriched by users and first-person engagement (Rossoa et al. 2016: 1).

Social media are also categorised as shared media (Xie et al. 2018: 164). When categorised as shared media, these digital platforms include LinkedIn, Instagram and Twitter, as well as messenger applications such as WhatsApp (Waddington 2018). Using online profiles, users make friends, create and share text, photographs, video content (Boyd & Ellison 2007), audio recordings, or links to other online content. Within a brand context, shared content is brand-related consumer generated conversations, content and actions that are exchanged, distributed and received by other consumers (Burcher 2012: 8; Lieb et al. 2012: 5). This electronic word of mouth (eWOM) is a form of user-generated content (UGC). Examples include likes, retweets and shares, or comments using smart devices and user-friendly applications. Consumers, as evidenced by their preference for less commercial and photoshopped content from brands, generally prefer UGC (Rhodes 2020). Social media's multi-directionality affords brands the possibility of interactive stakeholder dialogue and engagement, which theoretically should yield better results than the interruptive monologues of old.

Although the focus of this article is the social media channel with specific reference to Facebook, social media use must be informed by its role and ability to deliver on key strategic business and brand outcomes, as outlined in a content strategy versus a stand-alone or bolted-on element. Content strategies detail the creation, distribution and governance of content for the delivery of "relevant, personalised experiences for an audience of one in their micro-moment of need" along the digital consumer journey (Lieb 2016: 8). Social media content or assets can either be paid, owned or earned.

Paid social media

Paid/bought social media is a paid placement of brand-related content on a channel owned by a third party to leverage brand-related content and positively influence various stakeholders. The emphasis is on the distribution of such content for maximum reach and impact. Sponsored posts, native advertising, all Facebook ads and online branded entertainment are examples of paid social media.

Paid media is generally the least trusted media by young consumers (Rhodes 2020). Therefore, the presentation and promotion of paid content forms, such as native advertising "where the ad matches the form, feel, function, and quality of the content of the media on which it appears" (Shiao 2019), raises ethical dilemmas; specifically, the lack of transparency and disclosure about the authorship of content for sponsored and native adverts (Macnamara et al. 2016).

Despite the ethical concerns, paid media has a enhancing-enjoyment effect, can be used to spark conversation before and after a campaign, remind consumers, build awareness or interest, and present a call to action or influence perceptions (Lovette & Staelin 2016: 156; Mattke et al. 2019: 802). Native advertising on social media platforms specifically can convert sales leads into brand advocates, build a brand's online community, and heighten the customer experience in non-intrusive ways (Lieb et al. 2013: 9; Shiao 2019). Using social analytics based on real-time data and other customer data (mobile, store, website, purchase behaviour and preferences), the brand can create and share relevant content in posts and other online interactions. The paid social channel gives direct access to the consumer and enables content co-creation with young consumers. Lovette and Staelin (2016: 156) emphasise that "engagement strategies can be an effective complement to paid media strategies that keep the brand in memory and consideration". With reference to Facebook: it enables brands to incorporate content from a user's newsfeed into campaign messages to tap into the influence a referral from their social network has over them, thereby theoretically increasing message reception. Successful and credible social influencer marketing requires transparency about the contracted influencer remuneration and/or rewards for ethical, legal and reputational reasons. By using paid influencer content, brands can tap into the social media influencer's following to get their brand message across. However, the trade-off for potential reach is that they seldom have control over the brand message and run the risk of negative posts and comments.

Owned social media

Owned social media is any digital content or communication channel a brand owns and stewards on a social platform. These include Facebook pages, brand communities, podcasts, branded apps, and branded microsites/websites with social plugins or branded channels, for example Red Bull Media. Owned social media are the primary source of brand-generated content (informational, educational and culturally relevant) for all stakeholders. In other words, engaging stories about the brand are usually found on a brand's owned media (Shiao 2019). This relationship-building channel (Thompson et al. 2018) potentially facilitates increased interaction and the reinforcement of positive brand association and identification with consumers.

Brand-related content fulfils a brand positioning function by highlighting its operations, management or employees, and its influential relationships or links to its advertisements and advertorials. To appeal to young adults' need for co-creation, owned and paid channels must incorporate elements of shareability to spark conversations about the brand versus leading them. When owned social media channel strategies are implemented correctly, brand advocates or fans positively influence their social network and those of other consumers. Brand advocates defend and recommend the brand online, and tend to give positive ratings and reviews online (Awad & Abdel Fatah 2015: 38).

Earned social media

In a social marketing context, earned social media is publicity or third party validations of brand related content that is "repurposed" by the third party for its network or "audience" (Waddington 2018). The planned expressions of "editorial publicity" are sparked using blogger, influencer and "media relations" (Xie et al. 2018: 164). Earned social media are not always positive, as is evident in brands going viral on parody accounts and memes. For earned media to have a positive effect on consumers' brand perceptions, they need to "have a high product involvement, need to perceive the earned media as non-entertaining and non-irritating, but as informative and credible" (Mattke et al. 2019: 808). Consumers, therefore, evaluate these different forms of media using the following attributes: irritation, informativeness, entertainment, credibility, product involvement (Mattke et al. 2019: 802), the strength of social ties, and source credibility.

Ideally, a brand's paid and/or owned social media need to spark talk-ability by creating "contagious" content (Penn 2010) that consumers will share. Research by Stephen and Galak (2012) compared how earned traditional media and earned social media affect sales. Results found both have an effect on sales. Furthermore, earned social media drives earned traditional media (publicity and media mentions) and play a predictive versus causal role in intention to purchase (Stephen & Galak 2012).

The measurement of earned media has become a contentious issue. The practice of measuring earned media using the advertising value equivalents (AVE) metric has largely been denounced as a vanity metric by the global communication measurement industry (McCarthy 2019) and communication trade associations (AMEC 2017). Consequently, they drew up seven principles for best practices in the measurement and evaluation of communication. Principle five from the Barcelona Principles 2.0 states,

AVEs are not the value of communication. Do not use advertising value equivalents (AVEs). Do not use multipliers for pass-along values for earned versus paid media (unless proven to exist). If you must make a comparison between the cost of space or time from earned versus paid media, use negotiated advertising rates relevant to the client, (the) quality of the coverage (see Principle 4) including negative results; and physical space or time of the coverage related to the portion of the coverage that is relevant (AMEC 2015).

The main argument against earned AVEs is these are not suited to social media or digital media and their measurement is not standardised. AMEC (2015) argues that no peer-reviewed academic research has established the legitimacy of the metric. AMEC (2015) emphasises the differences in how online advertising works in print and online. Online advertising is centred on "paid for exposures instead of guaranteed runs in publications" (AMEC 2015). Therefore, attributing AVE to online content is flawed and impossible (AMEC 2015).

An emerging barrier to the clear measurement and evaluation of social media interactions is the emergence of dark social (media) or dark traffic. Dark social is the use of less public and more private interactions by consumers, typically via dark social platforms like direct messaging (DMs), emails, and links from chat apps (Rhodes 2020; Swart et al. 2018). In South Africa, 89% of internet users report using WhatsApp and 61% use Facebook Messenger chat apps (DataReportal 2020). Conventional web analytics programmes find it difficult to pick up and track activity through such channels due to a lack of referral data when users click on links (Swart et al. 2018).

Consumer brand perceptions

Consumer brand perceptions are shaped over time into an overall evaluation based on trust, respect, admiration and a good feeling about a brand and its activities online and offline (Foroudi 2018). Social media content that is relevant, builds the brand image, attracts consumers and creates an engaged brand community that gives the brand presence and global reach and promotes the brand (Helal et al. 2018: 985). Young adults base their perceptions on first-hand experiences of a brand's touchpoints, or crowdsourced peer vetting of their perceptions via online consumer intelligence models such as reviews, ratings and recommendations using Web 2.0 technologies. In concurrence, Kumar et al. (2018) assert, "Crowdsourcing as a concept per se creates favourable consumer brand perceptions and behavioural intentions, provided crowdsourcing involves social initiative". Therefore, social media allow them to search for, create, and consume UGC opinions based on brand independent first and/or second-hand brand experiences. Benchmarking of brands occurs according to perceived accountability, sustainability, authenticity, transparency, trustworthiness and dialogic communicative practices (Kumar et al. 2018). Considering all this, it is important to have a reliable means of measuring the brand perceptions of young adult consumers to avoid negative earned media and reputational damage.

 

RESEARCH OBJECTIVES

The objectives of the research were:

To develop a valid and reliable measure of 18 to 24-year-old South Africans' communication of brand perceptions on Facebook

To determine which variables are related to the construct of brand perceptions communicated on Facebook amongst 18 to 24-year-old South Africans.

 

METHODOLOGY

The primary purpose of the research was not the generalisation of results per se but rather the development of a valid and reliable measuring instrument. Recent research suggests the biggest driver of income inequality in South Africa since 2012 has been attainment of a tertiary education (Leibbrandt et al. 2018: 12). Therefore, the study focused on students pursuing a tertiary qualification, regardless of specialisation, with the assumption they will become the future middle and upper class in South Africa. Secondly, Facebook was selected due to its widespread adoption and use in South Africa. According to NapoleonCat Stats (2020), the largest user group are people aged 25 to 34 (35.1%) followed by 18 to 24-year-olds (24.6%). The largest proportion of students at institutions of higher learning is 18 to 24-year-old undergraduate students and, to a lesser extent, honours students; hence, their selection for this study.

A list of all young adults on Facebook at institutions of higher learning in South Africa was not available. Non-probability purposive sampling was used to address this. Five hundred undergraduate and honours 18 to 24-year-old students at an institution of higher learning in Johannesburg, who are active on Facebook, participated in the study. According to Du Plooy (2009: 112-113), adequate sample sizes are a minimum requirement to ensure research stays within 5% error tolerance and a 95% confidence level. Conway and Huffcutt (2003: 8) propose a minimum sample of 400 to produce undistorted results for a factor analysis. Therefore, the realised sample (n = 468) met both requirements. Data was collected using a standardised self-administered questionnaire. The final instrument had 49 items, excluding the biographical data.

Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy

To ensure that the instrument measures what it intends to measure, the data was subjected to various statistical tests. Firstly, Kaiser-Meyer-Olkin (KMO), which measures sampling adequacy, was used to verify if the sample was big enough for factor analysis, and Bartlett's test of sphericity was used to determine the data set's appropriateness for structure detection (Chan & Idris 2017). The KMO has a range of 0 to 1. It is an index, which compares the values of correlations between partial correlations and variables (Williams et al. 2010). The KMO index for these variables was meritorious (.879) and above the minimum .50 requirement (Chan & Idris 2017). The approximate Chi-Square and Df values were 8438.153 and 1176 respectively. The data had a Sig. Value (0.00), which was within the (p<.05) range, and thus suitable for factor analysis because correlations were present (Williams et al. 2010).

Validity test using exploratory factor analysis (EFA)

Factor analysis was used "to determine the extent to which shared variance (the inter-correlation between measures) exists between variables or items within the item pool for a developing measure" (Gerber & Price 2018). Factor analysis was used to provide evidence of a relationship between the contents of the instrument and the constructs it was intended to measure and to show that there was internal consistency in terms of the structure.

Similarly, factor analysis is used to identify the dimensionality of the constructs by looking at how the items and factors are related. To maintain the methodological rigour used for this research, exploratory factor analysis was conducted, using SPSS, to validate the instrument. All data associated to cases whose values were missing were deleted from the data set. Listwise deletion is useful when the proportion of missing data is small or when the sample is large enough to counter the effect of any missing data. In other words, the statistics are based on cases with no missing values in any variable used in the analysis.

Content and construct validity

To achieve content validity for the instrument, a brand communication subject expert and an expert in questionnaire design were consulted twice and a pilot study using 30 young adults vetted the questionnaire. An exploratory factor analysis was run to measure construct validity and to ensure that the instrument measures what it intends to measure.

Reliability score

The reliability coefficient of the 49 items is a 0.929. From these items, ten factors were identified for the scale. They cumulatively explain 62.812% of total variance. Therefore, a high degree of internal consistency was observed for the total scale.

 

RESULTS

Descriptive statistics

The results of the descriptive statistics, the factors, their values, and the variances explained are depicted in Table 1. Altogether ten factors were extracted with each loading on a minimum of three items, with the result of their means, and standard deviations alongside. Each factor represented an underlying dimension of the latent variable or construct, cementing the relationship between the items and the factor. Mean scores are representative of a set of scores in a latent factor, with the standard deviation indicating the spread of values in relation to the mean. Both serve as indicators of how well an item correlates with the rest of the items in a latent factor.

 

 

Factor extraction method

Factors were extracted according to the Maximum Likelihood method. It allows for inferential procedures for assessing model data fit and identifies standard errors (Ferrando & Lorenzo-Seva 2013: 16). It is ideal/efficient statistically when inferential interpretation is founded on the normality assumption; specifically, when the degree of model misspecification is small; otherwise, it becomes an unstable procedure (ibid.). The factor retention method used was a combination of Eigen Values greater than one (>1) rule and a Scree Test. Promax with a Kaiser Normalisation was used as a rotation method. This Oblique class of rotation was used, as it tends to generate simple, decipherable and correlated factors. Ten factors were identified with a minimum of three degrees of freedom (see Table 1).

The communalities of the ten factors, another way of showing internal consistency, are reported in Table 2. Communality is the amount of common variance shared by the items, which indicate the extent of the relationship among the items in the constructs measured. A cursory look at the table of the communality shows that the result of the scale is reliable, consistent and dependable. Since the communalities are generally high, it indicates that the extracted factors account for most of the variances. In other words, it shows that the ratio of couplings and dependencies between the variables and the extracted factors are quite high. Overall, more factors were retained to give a better account of the variances.

 

 

DISCUSSION AND CONCLUSION

The exploratory factor analysis and reliability tests have established that a valid and reliable measure of young adult brand perceptions on Facebook was developed, explaining 62.812% of the total variance and representing the key underlying conceptual dimensions; thereby, fulfilling the first objective of this research. The second objective was to establish which variables relate to the construct of brand perceptions communicated amongst 18 to 24-year-olds on Facebook.

The exploratory factor analysis illustrated that all ten factors extracted with their underlying dimensions can be regarded as valid and reliable underlying dimensions or constructs in the measurement of young adult brand perceptions. Brand fan behaviour (BFB) constitutes nearly 40% of the total variances explained, accounting for 24.891%. This indicates that the measurement of brand fan behaviour is critical in perceptions and relationships of 18 to 24-year-old consumers with brands. It is through interacting with brands, via creating and consuming content on a brand's official Facebook page, that loyalty and engagement with them are potentially created. These findings are consistent with Dawson (2018) and Mattke et al. (2019).

The second most important latent variable or factor unveiled by the instrument is the Shared Brand-related Content (SBC), accounting for 7.440% of the variances explained. The factor highlights the important role brand experiences and customer opinion (Fombrun et al. 2015: 4) on Facebook play in shaping perceptions of brands for young adults via positive or negative earned media.

Value Brand Influencers (VBI) explained 6.603% of variance and highlighted the important role of crowdsourcing opinions via reviews and ratings from various nonbrand related sources during the information seeking stages for value brand purchases. These findings are consistent with Jordaan et al. (2011: 2-3), Lazarevic (2012), and Dalziel and De Klerk (2018: 267). Young adults rely less on brand-generated content (traditional push advertising content) and more on customer and expert opinions for purchases, as validated by the study of Kumar et al. (2018).

Corporate Social Responsiveness (CSR) explained 4.479% of all variance. This is an important issue for young adults as their expectations are that brands should operate ethically, according to good governance and fair trade practices (Fombrun et al. 2015).

The remaining six factors, namely User-generated Content (UGC), Brand-related Content (BRC), Familial Influencers (FI), Premium Brand Influencers (PBI), Communication Expectations (CE) and Recommending Behaviour (RB), had variance

values ranging between 4.161% for user-generated content (UGC) to familial influencers (FI), explaining 2.422% of variance.

Recommendations for future research

The study was limited to young adults aged 18 to 24 and geographically confined to an institution of higher learning in Johannesburg, South Africa. The aim of the research was not to achieve external validity but to develop a valid and reliable measuring instrument for the measurement of young adult brand perceptions on Facebook. The measuring instrument can be applied to a broader sample beyond young adults and in different emerging markets in Africa to allow for comparisons and establish the diversity of South African adults. While this study represents an important first building block, further triangulation can add to much needed insights with respect to young adults, their brand perceptions, and social media behaviour in emerging markets.

 

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Date submitted: 14 October 2020
Date accepted: 03 November 2021
Date published: 31 December 2021

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