ARTICLE

 

The Role of Social Network Brand Personality in a Consumer-Brand Relational Model

 

 

Munyaradzi Mutsikiwa^I; Tania Maree^II

^IGreat Zimbabwe University. mmutsikiwa@gzu.ac.zw. https://orcid.org/0000-0002-9167-3619
^IIUniversity of Pretoria. tania.maree@up.ac.za. https://orcid.org/0000-0002-3158-2803

 

 

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ABSTRACT

PURPOSE: This research employs Aaker's brand personality framework to explore the interrelationships between social network platform brand personality and attitude, motivations, behavioural intention, and behaviour.
DESIGN/METHODOLOGY/APPROACH: Quantitative data were collected from three samples of social network (Facebook, LinkedIn, and YouTube) users via online self-administered surveys. Structural equation modelling was used to test the hypotheses.
FINDINGS: The results showed that some personality traits positively relate to attitudes (excitement for Facebook and LinkedIn; sincerity for YouTube). Excitement was positively related to all motivations for Facebook and LinkedIn and one for YouTube.
PRACTICAL IMPLICATIONS: The paper provides insights into how social network users perceive the brand personality of social network platforms.
ORIGINALITY/VALUE: The paper brings new insights into social networks as brands, contributing new knowledge into the role of brand personality in the social media realm. It further demonstrates how brand personality facilitates consumer-brand relationships and user behaviour. A South African view is provided, contributing to the limited work from an African view.

Keywords:Social network; brand personality; attitude; motivations; behavioural intention; behaviour

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Introduction

The paper explores the brand personality of social network brands as a catalyst for forming attitudes and motivations, subsequently influencing behavioural intention and behaviour. Social media studies mostly focus on using these platforms to build brands rather than seeing social media as intrinsic brands (Dwivedi et al. 2018). Calderón-Fajardo et al. (2023) propose a need for new lines of investigation into how brand personality (BP) is communicated in the social media realm. Despite the proliferation of academic research on social media consumers, there remains a gap in understanding the BPs of social media as a brand (Langstedt and Hunt 2017; Roux and Maree 2022). This study examines Facebook, LinkedIn, and YouTube as social network brands rather than brands featured on social networks, bringing different insights to the brand personality conversation. Moreover, Alvarez et al. (2023) highlight the importance of studying consumer-brand relationships as an enduring research theme. This paper examines how brand personality interrelates with other brand-related constructs in a consumer behaviour relational model.

Considering the diverse types and aims of social media, the study explores three networks with distinct purposes to test the model, namely, Facebook as the leading social network (Statista 2023), LinkedIn as the largest professional social network (LinkedIn 2023), and YouTube as a content-sharing network (YouTube 2023).

Prior BP research has targeted various brand environments: commercial brands (apparel, banking), tourism (destination brands), entity brands (sports teams), created unknown consumer product brands (Feng, Xu, and Wang 2023), and media brands (television broadcasters) (Braunstein and Ross 2010; Garanti and Kissi 2019; Huang et al. 2017; Lin and Huang 2012; Pong et al. 2021; Sung and Park 2011). Research in the media category is limited despite the crucial role that media vehicles play in promoting other brand categories (Kumar and Kumar 2014). Roux and Maree (2022) indicate that media should be viewed as offering opportunities to provide audiences with an experience, moving beyond merely a communication channel.

A review of BP research highlights the importance of studying BP in cultures beyond dominating Western ones (Calderón-Fajardo et al., 2023). Our paper views BP from a South African perspective, adding to the cultural diversity of the extant research. McManus et al. (2022) report that BP facilitates consumer-brand relationships. Theoretical foundations position attitudes and motivations as antecedents to behavioural intention and behaviour: the theory of planned behaviour (TPB) (Ajzen, 1991) and the uses-and-gratifications theory (UGT) (Katz, Blumler, and Gurevitch, 1973). These theories and anthropomorphism theory, proposing the human personification of brands, guide the study.

Literature shows that BP influences attitudes (Eisend and Stokburger-Sauer 2013; Roux and Maree 2022) and motivations (Yuksel and Bilim 2009). However, the interplay between BP and these constructs has not been examined. This paper aims to fill this gap by exploring how social network brand personality is perceived, how it relates to attitudes and motivations, and the subsequent influence on consumer behavioural outcomes.

The objectives include examining the relationships between the BP of social network brands and attitudes towards and motivations to use the platforms; how the attitude towards social network brands influences behavioural intention and user behaviour; how motivation relates to behavioural intention and behaviour; and how behavioural intention influences behaviour for social network brands. The paper endeavours to bridge the knowledge gap by contributing fresh insights into how BP is communicated in the social network domain (Calderón-Fajardo et al. 2023) as a social network brand image component. It specifically demonstrates how social network BP influences antecedents of behaviour, shedding light on its role in consumer-brand relationships (Alvarez et al. 2023; McManus et al. 2022). This is important given the limited understanding of social networks as brands and the importance of an African perspective in a research landscape mostly focused on Western samples (Calderón-Fajardo et al. 2023).

 

Literature Review

Brand Personality

The most often-cited definition of BP is that of Aaker (1997, 347), who defined it as "the set of human characteristics associated with a brand". Table 1 presents an overview of recent work on BP.

 

 

Most studies focused on commercial product- and service brands and destinations. Entity- (sports teams, political parties) and media brands (mass media) have attracted comparatively little research. This paper contributes to the media space.

Aaker's 1997 model is considered the leading framework for BP research, and most studies use her brand personality scale (BPS), as confirmed by Ajeyalemi and Dixon-Ogbechie's (2020) and Calderón-Fajardo et al.'s (2023) reviews. Aaker's BPS proposes five dimensions, namely excitement, competence, sincerity, sophistication, and ruggedness.

Some studies have examined brands appearing online and on social networks. However, very little attention has been devoted to social network brands. Langstedt and Hunt (2017) explored LinkedIn, Instagram, Snapchat, Pinterest, Facebook, and Twitter and how their BPs predicted time spent on the platforms. They reported that BP structure varied due to low reliabilities - ruggedness (for Facebook and LinkedIn) and sophistication (for LinkedIn) were removed from their further analysis. African authors (Mutsikiwa and Maree 2019) only explored the structure of social network BPs. This paper applies Aaker's BPS to three social network brands and builds on previous research by examining how BP interrelates in a consumer-behavioural model.

Theoretical Framework

Anthropomorphism refers to the tendency to imbue humanlike characteristics, intentions, and behaviour on non-human objects - even to the extent that brands are seen as human (Calderón-Fajardo et al. 2023). Applying anthropomorphism to non-humans has produced positive judgements and behaviour (Aggarwal and McGill 2012). Our study examines the extent to which anthropomorphism in the form of BP influences the attitudes and motivations of social network users.

The UGT has been employed to examine how media gratify users' motivations. Media users choose various types of media based on the needs they want to fulfil (Katz, Blumler, and Gurevitch 1973). UGT has been utilised as an appropriate paradigm to observe the motivations for using online and social networks (Liu et al. 2023; Whiting and Williams 2013). Our paper views motivations for social network platform use through the UGT lens.

The TPB posits three drivers of behavioural intention: attitude, subjective norms, and perceived behavioural control. Behaviour is likely to be predicted by behavioural intention (Ajzen 1991). Our paper is relevant to the relationships between attitude, behavioural intention, and behaviour, as we employ TPB to examine these for social network users.

 

 

Attitudes are favourable or unfavourable predispositions towards an object (Maree 2017). If a person has a favourable attitude towards a product or brand, the person will likely perform the behaviour. We focus on users' attitudes towards social network brands. Eisend and Stokburger-Sauer's (2013) meta-analytic study of BP drivers and outcomes report that brand attitudes are particularly influenced by sincerity and competence. Luffarelli et al. (2023) confirm that BP facets influence consumers' feelings towards brands. Kim (2000), who examined the relationship between BP and attitude within the apparel industry, reported that four BP traits (excitement, sincerity, competence, and sophistication) were positively correlated to attitude but not ruggedness, which had mixed results. Möller and Herm (2013) confirmed a positive association between BP and attitude in the retail sector, as did Klabi and Debabi (2011) for mobile operators. Lee and Eastin (2020) found that highly sincere social media influencers (human brand) elicited favourable brand attitudes.

H₁. Perceived BP of social network brands has a significant relationship with attitude towards the platforms.

In the social media realm, motivations can be regarded as the reasons that support users' selection of social media. Across several studies, social media users' motivations overlap: social connection, information-seeking, passing time, entertainment, leisure, communication, expressing of opinion, surveillance, knowledge-seeking, convenience (Whiting and Williams 2013); initiating or terminating romantic relationships, organising events (Tosun 2012); disclosure, status (Xu et al. 2012); information-sharing, self-expression, self-documentation, medium appeal, socialisation, entertainment, escapism (Alhabash and McAlister 2015).

There is a lack of research examining the association between BP and motivations. Murphy et al. (2007) assert that the personality of a tourist destination should relate to the needs of the target consumer. They explored how tourist groups clustered on motivations perceive the BP of a destination and found evidence of congruity between gratifications sought and perceived destination BP. Similarly, Yuksel and Bilim (2009) supported an association between motivation and destination personality.

H₂. Perceived BP of social network brands is significantly related to motivation to use the platforms.

Behavioural intention indicates the probability of an individual exerting effort to do something, and theoretically, attitudes can be strong predictors of behavioural intentions (Ajzen 1991). Empirical research in the digital realm confirms attitude as a determinant of behavioural intention: Bashir and Madhavaiah (2015), online banking adoption; Khoi et al. (2018), mobile commerce; Tariq et al. (2017), Facebook; Sanne and Wiese (2018), Facebook advertising; and Liu et al. (2023), TikTok use.

H₃. Attitude towards social network brands has a significant positive influence on behavioural intention.

The multi-attribute attitude model from Fishbein and Rosenberg explains that individuals make rational decisions before they engage in behaviour and that one's attitude towards an object, such as a brand, is a consequence of the beliefs that one has regarding the brand attributes. Empirical research has confirmed the attitude-behaviour relationship: Ketelaar and van Balen (2018) for attitudes towards phone embedded tracking and users' behaviour; Law (2020) for attitudes towards Facebook and usage behaviour.

H₄. Attitude towards social network brands has a significant positive influence on user behaviour.

Research has confirmed that motivation predicts behavioural intention in various media contexts. Nam (2014) reported positive relationships between motivations and the intention to use web portals; Lee and Ma (2012) that motivation positively influences the intention to share news via social networks; Alhabash and McAlister (2015) that social interaction motivations favourably influenced viral behavioural intentions regarding pro-social messages on Facebook.

H₅. Users' motivation has a significant positive influence on behavioural intention.

The UGT's premise of the audience as active and goal-directed concerning media use supports the ability of motivations to predict behaviour. Studies conceptualise motivations in varied ways, and many show mixed results for how particular motivations influence behaviour. Luo and Remus (2014) found that entertainment motivations are significant predictors of behaviour for web-based information services. Basilisco and Cha (2015) reported that motives (seeking friends, entertainment, information, and convenience) affect Facebook usage.

H₆. Users' motivation has a significant influence on behaviour.

The TPB prescribes that behavioural intentions are driving factors influencing behaviour. This implies that when an individual has a strong intention to perform a behaviour, they are likely to do it (Ajzen 1991). Empirical studies have supported this premise: Luo and Remus (2014) for web-based information services; Sanne and Wiese 2018 for Facebook engagement behaviour.

H₇. Behavioural intention towards social network use has a significant influence on behaviour.

 

Research Methodology

The study used a descriptive, cross-sectional design targeting adult South Africans who qualified if they have used either Facebook, LinkedIn, or YouTube for at least three months. Three unique non-probability convenience samples were drawn to collect data using an online questionnaire, which was appropriate as the focus of the study was online social networks, and the target population was active on social networks. Data collection was facilitated via Qualtrics as a customisable tool, and data was captured automatically (Cushman et al. 2021). A hyperlink was sent to Qualtrics panel members fitting the criteria, and data collection commenced after receiving Ethical Approval from the researchers' home faculty- the questionnaire measured social network members' usage patterns, constructs, and demographics. The operationalisation of the constructs was based on existing scales adapted for social network platform brands (Table 2).

 

 

Except for attitude, which was measured using a semantic differential scale, all the constructs were measured using five-point Likert-style scales (1 = strongly disagree; 5 = strongly agree). The motivations measure was adopted from sources considered suitable to the social network context. The behaviour measure was based on usage patterns, which were derived by combining daily, weekly, or monthly use with usage per session (minutes) and calculating average monthly use from those.

 

Data Analysis and Results

The realised samples were 355 (Facebook), 375 (LinkedIn), and 338 (YouTube). An initial confirmatory factor analysis (CFA) using Amos indicated high multicollinearity for the five-dimensional brand personality model; thus, exploratory factor analyses (SPSS) utilising Principal Axis Factoring (PAF) and Promax rotation were used. Suitability was assessed using Bartlett's test of sphericity (significant) and Kaiser-Meyer-Olkin's measure of sampling adequacy (exceeding 0.6) (Pallant 2016). Reliability and validity were evaluated using Cronbach's alpha (internal consistency) and composite reliability (CR), exceeding 0.70, average variance extracted (AVE) exceeding 0.5 (Hair et al. 2019), and the Fornell and Larcker (1981) criterion and HTMT (below 0.85) to assess discriminant validity (Henseler et al. 2015).

Sample Profile and Usage Patterns

Table 3 shows that the respondents were, on average, in their mid-thirties and well-educated.

 

 

Facebook and YouTube respondents were regular (daily, 69%, 53.3%), prolific (2 hours 28 minutes; 2 hours 4 minutes daily), and long-term (more than seven years, 49.6%; 36.4%) users. LinkedIn respondents reported moderate use: monthly (49.6%), 1-3 years (33.9%), and 18 minutes daily.

Exploratory Factor Analyses (EFA)

For all three platforms, two-factor solutions resulted, which were labelled as follows: Facebook and YouTube excitement and sincerity and LinkedIn competence and excitement. Other research also found varying BP dimensions (Guiry and Vequist 2015). Motivations for Facebook and LinkedIn presented three factors: information-seeking, entertainment, and status-seeking, while YouTube featured two: status-seeking and infotainment-seeking. The latter included items representing both information-seeking and entertainment. Attitude and behavioural intention presented unidimensional results.

Reliability and validity were achieved (Table 4). Four constructs had AVEs slightly below 0.5; however, as the CRs were over 0.7, these were considered permissible (Fornell and Larcker 1981). Discriminant validity was acceptable considering Fornell and Larcker's (1981) criterion and HTMT analyses (Henseler et al. 2015) for cases that did not meet the former criterion (Facebook and YouTube two instances each; LinkedIn one).

The BPs of both Facebook and YouTube were viewed as highly exciting and moderately sincere, and LinkedIn as very competent and exciting to a lesser extent. Facebook users were primarily motivated to use it for entertainment and informational purposes while using it for status was not a strong motivation. Contrary to Facebook, LinkedIn users primarily use it to seek information, then for status, and lastly, as an entertainment platform. YouTube serves its users for infotainment purposes and, to a lesser extent, for seeking status. All three platforms' users reported positive attitudes and continuance intention.

Structural Equation Modelling (SEM)

Incremental and absolute indices were used in aggregate to assess model fit (Hair et al. 2019). The proposed models fit the data satisfactorily (Table 5).

 

 

The results of hypotheses testing revealed several significant relationships (Table 6).

 

 

H₁was supported for both Facebook (excitement p < 0.001, ß = ²1.38; sincerity p < 0.001, ß = -0.73) and LinkedIn (excitement p < 0.001, ß = 1.06; competence p = .0032; ß = -0.33), showing significant relationships between BP and attitude. It was partially supported for YouTube as only sincerity had a significant relationship (p < .001; ß = 0.48).

Support for H₂was found across all three platforms. Excitement had a positive relationship with all three motivations for Facebook (status-seeking p < 0.001; ß = 1.17; entertainment p < 0.001; ß = 2.31; information-seeking p < 0.001; ß = 2.33) and LinkedIn (status-seeking p < 0.001; ß = 1.13; entertainment (p < 0.001; ß = 1.65); and information-seeking (p < 0.001; ß = 1.40). For Facebook, there were negative relationships between sincerity and motivations (status-seeking p = 0.006, ß = -0.65; entertainment p < 0.001; ß = -1.81; information-seeking p < 0.001, ß = -1.62) and for LinkedIn, between competence and motivations (status-seeking p < 0.001, ß = -0.54; entertainment p < .001, ß = -1.23; information-seeking p < .001, ß = -0.73). For YouTube, sincerity was positively related to status-seeking (p < 0.001, ß = 0.64) and infotainment-seeking (p =0.024: ß = 0.23), whereas excitement was positively related to infotainment-seeking (p = 0.001, ß = 0.43), but negatively to status-seeking (p = 0.003; ß = -0.35).

Attitude had a significant relationship with the behavioural intention for Facebook (p < 0.001, ß = 0.16) and LinkedIn (p < 0.001, ß = 0.33), supporting H₃, but not for YouTube. Contrary to the literature (Ketelaar and van Balen 2018; Law 2020), there was no significant association between attitude and behaviour for any platforms (no support for H₄).

H₅hypothesised positive relationships between motivations and behavioural intention. This was partially supported. For Facebook, the relationship was positive for entertainment (p = 0.013, ß = 0.14) and information-seeking (p < 0.001, ß = 0.72), but status-seeking was not significantly related. For LinkedIn, status-seeking (p < 0.001, ß = 0.175) and information-seeking (p < 0.001, ß = 0.66) were positively associated, but entertainment was negatively associated (p < 0.001, ß = -0.21). For YouTube, infotainment-seeking had a positive relationship (p < 0.001, ß = 0.94), but status-seeking was negatively related (p = 0.001, ß = -0.13).

As for the relationships between motivations and behaviour (He), these were only proven for information-seeking for Facebook, which showed a significant positive relationship (p = 0.031, ß = 0.49), as was also the case for Basilisco and Cha (2015). Finally, contrary to the TPB, behavioural intention had no significant relationship with behaviour for any platforms (H₇not supported).

 

Discussion

Our paper explored the interrelationships between social network platforms' perceived BP and attitudes, motivations, behavioural intention, and user behaviour. Some results concur with the theoretical frameworks and literature, while results that differ may be explained by considering other theoretical frameworks.

The respondents view Facebook and YouTube as thrilling and stimulating. LinkedIn is seen as reliable and effective in agreement with its purpose. Three motivations were found for Facebook and LinkedIn: entertainment, information-seeking, and statusseeking, and YouTube, infotainment- and status-seeking.

The motivations are consistent with the premise of the UGT that media use is goal-oriented (Katz, Blumler, and Gurevitch 1973). Entertainment and information-seeking motives were stronger for Facebook than for status. Facebook aims to bring people together, and with diverse functionalities being added constantly, it allows various content to be viewed and shared. This makes it well-suited to use for entertainment and information purposes. It is a friendship rather than a professional network, so its comparatively low use for status-seeking makes sense. LinkedIn users reported using it more for information and status than entertainment. This is expected as LinkedIn is a professional network, and using it to (for example) job-search and display professional acumen (i.e. status) concurs with its purpose. For YouTube users, infotainment (a combination of information-seeking and entertainment) was more prominent than status-seeking. As YouTube is a content-sharing network, these motivations align with its functionality and seem to serve these purposes well.

Consistent with the respondents as frequent and regular users of Facebook and YouTube, their attitudes towards the platform brands were very positive, and they showed high use continuance intention. LinkedIn's attitudes and behavioural intention were also positive, albeit less so, consistent with its lower use frequency.

The findings indicate that one BP dimension (excitement for Facebook and LinkedIn, and sincerity for YouTube), was positively related to attitude, concurring with previous studies (Huaman-Ramirez et al. 2023; Klabi and Debabi 2011; Kim 2000; Möller and Herm 2013). The negative relationships between sincerity (Facebook) and, competence (LinkedIn) and attitude are in contrast with existing work (e.g. Lee and Eastin 2020). This may be due to other theoretical factors that influence attitude (e.g. behavioural control beliefs (TPB) or perceived usefulness (Technology Acceptance Model (TAM)). From a social network brand perspective, this implies that the focus should rather be on building on the "favourable" dimensions of the brand image to affect brand attitudes positively. For example, focusing on the exciting aspects of Facebook BP (spiritedness and imaginativeness) and YouTube's sincerity (honesty and originality) enhances attitudes. McManus et al. (2022) support this and recommend enhancing BP traits, like excitement, by creating marketing messages that relate the brand to spiritedness or vitality.

Excitement was positively related to all motivations for Facebook and LinkedIn, but only for infotainment-seeking for YouTube. Sincerity (Facebook) and competence (LinkedIn) were negatively associated with motivations. Content-sharing platform YouTube's results revealed sincerity to be favourably associated with both infotainment- and status-seeking, whereas excitement had a negative association with status-seeking. Excitement's results mostly concur with views from existing research (Murphy et al. 2007; Yuksel and Bilim 2009). However, the exciting nature of YouTube does not support status-seeking. Our results further suggest that being sincere (Facebook) or competent (LinkedIn) does not support using these platforms for entertainment, information-, or status-seeking purposes. These characteristics may favourably influence motivations not tested in our study (e.g. privacy needs).

Consistent with TPB and research (Ajzen 1991; Bashir and Madhavaiah 2015; Khoi et al. 2018), attitude positively influenced behavioural intention for Facebook and LinkedIn. From a social network brand perspective, this is favourable as it suggests that these brands are well regarded, and this, in turn, supports the continued use intention of the platforms despite a highly competitive environment. In contrast, the YouTube results showed no significant association, suggesting that for this type of platform (content-sharing), even a very favourable attitude may not translate into continued use intention - or that other factors may be more influential (e.g. perceived ease of use as per the Technology Acceptance Model (Liu et al. 2023)).

Contrary to the multi-attribute model and existing research (Huaman-Ramirez 2023; Law 2020), attitude and behaviour had no significant relationship. This may be due to the behaviour measure used in our study or because other factors could be stronger drivers of behaviour, for example, social influences (Nikou and Economides 2017).

The associations between motivations and behavioural intention were favourable for Facebook (entertainment and information-seeking), LinkedIn (status-seeking and information-seeking), and infotainment-seeking for YouTube, concurring with the literature (Alhabash and McAlister 2015; Lee and Ma 2012). This suggests that these are primary motivational drivers for users' intended use of the platforms, respectively. Contrarily, entertainment (LinkedIn) and status-seeking (YouTube) had negative associations. For LinkedIn, the negative association suggests that entertainment will not drive continued platform use; indeed, it may negate future use. This makes sense as LinkedIn has a professional aim rather than being a channel for entertainment. Similarly, status-seeking's negative association with the video-sharing platform YouTube implies that this motivation will likely result in lower future use of the social network.

The only motivation that favourably influenced actual behaviour was information-seeking (Facebook). This suggests that the motivations in our study are not conclusive drivers of behaviour for these platforms. As the behavioural measure in this research was based on usage patterns, our results suggest that information search using Facebook may drive usage.

In contrast with the TPB and literature (Luo and Remus 2014; Sanne and Wiese 2018), no significant relationship existed between behavioural intention and behaviour. Other variables excluded in our study may be more likely to influence usage behaviour. Theoretically, factors such as perceived usefulness - as one example - may influence online platform usage, as posited by the TAM. Individual factors may also play a role. Age and experience, for example, are posited as moderators in the relationship between intention and behaviour for technological resources, as shown by the UTAUT (Luo and Remus 2014).

 

Limitations and Future Research

Opportunities for further research may be gleaned from the limitations of this research. While our study employed Aaker's brand personality model, future investigations should test other paradigms (Calderón-Fajardo et al. 2023) and examine concepts like brand authenticity and coolness (Loureiro 2023) alongside BP for enhanced understanding of consumer behaviour, particularly in the virtual environment. Replicating the study in other contexts and for other platforms could validate our findings. Future work could incorporate other brand concepts, such as brand passion, which Gilal (2023) proposed as a mediator between marketing elements (e.g., BP) and consumer behaviour. The sampling method and specific platforms limit generalisability. Future work could examine newer social media platforms (e.g. TikTok) or the rebranded X (formerly Twitter) and replicate the model in other non-Western contexts.

 

Implications and Recommendations

Though research has investigated the effect of BP on several outcomes, our study brings new insights into applying the model to social network brands, and it is the first to examine the interrelationships between the constructs across three platforms. More importantly, the conceptual framework forms a basis for scholars interested in studying the BP of social networks, and it can be broadened to other social media brands and types. Additionally, the findings contribute insights into the theoretical frameworks of TPB (partially) and UGT from the perspective of social network brands.

We concur with Huaman-Ramirez et al. (2023) that marketers need to understand how specific BP traits influence attitudes to leverage the possible impact thereof. Our findings offer implications for social network brand managers. Considering the findings specific to the excitement trait, which was common across all three platforms, it is recommended that social network brand managers capitalise on excitement to enhance attitudes and support the platform used for the diverse purposes found in our study.

Our paper provides insights into the primary motivational drivers for using (and intention to continue using) the platforms. The Facebook and YouTube findings may provide the impetus for developing improved entertainment properties and search functionalities to promote use intention. Building on the exciting aspects of the brand may be utilised to extend platform use to affiliated brands (e.g. Instagram for Facebook) through engaging, entertaining, and informational content. LinkedIn's primary motivations were seeking information and status, which favourably influenced behavioural intention. This suggests that enhancing continued use could be stimulated by strong search functionalities and a focus on status-building, such as networking suggestions with higher-status individuals or functionalities to show status-related activities or achievements prominently.

 

Contributions and Concluding Remarks

Our paper contributes a new understanding of the role of BP as communicated in the social media space (Calderón-Fajardo et al. 2023) and how it facilitates consumer-brand relationships (Alvarez et al. 2023; McManus et al. 2022). It offers fresh insights into social network BP as a brand image component and how that influences important antecedents of user behaviour. Moreover, it provides a South African perspective, which is important as most research focuses on Western views (Calderón-Fajardo et al. 2023).

 

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1 Due to a transcription error on one item of Ruggedness, it was omitted.
2 According to Deegan (1978), standard regression coefficients are not bound by +/- 1, as would be the case for correlation coefficients, and thus the standard regression coefficients above 1 are acceptable.

 

 

Appendix A: scale items

Brand personality

• The platform is down-to-earth

• The platform is honest

• The platform is original

• The platform is cheerful

• The platform is daring

• The platform is spirited

• The platform is imaginative

• The platform is up-to-date

• The platform is reliable

• The platform is intelligent

• The platform is successful

• The platform is upper-class

• The platform is charming

Motivations

• I use the platform to relax

• I use the platform to do research

• I use the platform to learn new things

• The platform lets me acquire cheap information

• Using the platform helps me pass time

• I use the platform to interact with people

• Using the platform lets me combat boredom

• I share news and ideas using the platform

• I enjoy the cool character of the platform

• The platform lets me connect to the virtual community

• The platform allows me to gain status

• I use the platform for seeking relationships

• Using the platform helps me to appear modern

• The platform helps me feel important

• I use the platform to help me establish my identity

Attitude

• Unappealing - Appealing

• Bad - Good

• Unpleasant - Pleasant

• Unfavourable - Favourable

• Unlikable - Likable

Behavioural intention

• I plan to use the platform in future

• I intend to recommend my friends to use the platform in the future

• I am not likely to use the platform in future*

• I expect to continue using the platform in future

* item reverse scored