
- ABSTRACT:
- 1. INTRODUCTION
- 2. LITERATURE REVIEW
- 3. METHODOLOGY
- 4. RESULTS
- CONCLUSION
- LIMITATIONS
- POLICY AND IMPLICATIONS
- LIST OF ABBREVIATIONS
- AUTHOR'S CONTRIBUTION
- ETHICAL APPROVAL & INFORMED CONSENT
- AVAILABILITY OF DATA AND MATERIALS
- FUNDING
- CONFLICT OF INTEREST
- ACKNOWLEDGEMENTS
- DECLARATION OF AI
- APPENDIX A
- REFERENCES
Article ID: PD2601203004
Views: 423The Impact of Socially Conscious Marketing on Gen-Z’s Brand Preferences: Exploring the Role of Social Media Influence as a Mediator
⬇ Downloads: 16
1Imam AbdulRahman Bin Faisal University, Dammam, Saudi Arabia
Received: 17 February, 2026
Accepted: 25 June, 2026
Revised: 20 June, 2026
Published: 24 July, 2026
ABSTRACT:
Introduction: This study examined the impact of socially conscious marketing on brand preference among United Kingdom (UK) Gen Z consumers, with the mediating effect of social media influence, using Signalling Theory.
Methodology: A structured, self-administered, online questionnaire was used to collect primary data using a quantitative research design. A total of 450 respondents from the UK Gen-Z participated in the study. Structural equation modelling (SEM) was used to analyse the data, which involved a measurement model to determine measurement validity and reliability, and path analysis to test the hypothesised relationships.
Results: The results indicate that socially conscious marketing has a direct, positive, and significant influence on brand preference. Furthermore, through social media influence, socially conscious marketing has an indirect and positive impact on brand preferences, showing a partial mediating effect of social media.
Conclusion: The research concluded that socially conscious marketing signals value and ethics that are effective in creating UK Gen-Z brand preference, especially when enhanced by social media. The results have practical implications for marketers and policymakers since the researchers highlight the critical role of strategic incorporation of socially-conscious messages in digital marketing to enhance long-term brand loyalty among the UK Gen-Z consumers
Keywords: Socially conscious marketing, brand preference, social media influence, UK gen z, United Kingdom, SEM.
1. INTRODUCTION
The concept of marketing has changed significantly in recent years, going beyond conventional promotional strategies and incorporating a more profound devotion to ethical, social, and environmental principles. Today’s customers, especially Generation Z (Gen-Z), are becoming increasingly critical of not just what is advertised by brands, but the values of these brands (Panton, 2025). This change has pushed socially conscious marketing, which is a strategic brand communication focused on purpose-driven initiatives, sustainability, ethical actions, and societal impact, beyond niche positioning to mainstream consumer expectations (Eastman, 2020). Socially conscious marketing is not a luxury to Gen-Z, a generation of consumers born around 1997-2012; rather, it is a defining aspect of their perception, engagement, and ultimate selection of brands.
Data support this shift toward value-led consumption. According to a Forbes report, 62% of Gen Z shoppers like purchasing sustainable brands, which is also supported by another report from Thomson Reuters, which further adds that 73% of Gen Zs are ready to pay more to purchase sustainable products, which points to the strong global preference for ethical consumption (Petro, 2020; Panton, 2025). Nearly every Gen-Z user uses social media daily, and channels such as TikTok, Instagram, and Snapchat influence how they learn about, judge, and relate to brands (El-Shihy & Awaad, 2025; Zhong et al., 2025). This overlap of values and digital lifestyle indicates the pivotal role of social media in mediating the effect of socially conscious marketing on Gen Z’s brand preference. As digital natives, Gen Zs are continually exposed to brand stories in the form of peer communications, influencer posts, user-created content, and algorithm feeds. Studies indicate that Gen Z consumers become more attentive to a brand when they listen to their social media influencers, and that 43% of Gen Zs use TikTok to research products (Bratina & Faganel, 2024; Melgarejo-Espinoza et al., 2025). These observations highlight the importance of social media in spreading marketing messages and influencing perceptions, social proof, and community norms that guide individual brand decisions.
Theoretically, these insights support the narrative of signalling theory. According to this theory, conveying meaningful, observable cues for otherwise unobservable attributes (ethical commitment) reduces information asymmetry and builds trust with consumers (Connelly et al., 2025). However, these signals are only effective when they are perceived as authentic and consistent, as actions that are genuine and effort-focused are preferred and trusted by Gen-Z consumers. These signals can be boosted by social media, considering the digital landscape, as it provides visibility, validation from peers, and endorsement by influencers, which collectively shape Gen-Z’s interpretations and responses to brands’ value-based communication.
In an empirical context, a recent quantitative study on the impact of social media marketing on the purchase intentions of Gen-Z found that the use of digital marketing strategies, such as engagement and trendiness, has a significant impact on consumer behaviour on online platforms, supporting the relevance of social media as a mediator (Deepika & Massand, 2024). Furthermore, another study examining social media behaviour and brand equity among Gen Z shows that influencer partnerships, user-created content, and direct communication on social media platforms such as Instagram and TikTok build brand reputation, perceived quality, and brand loyalty among Gen Z consumers (Agrawal, 2025). Additionally, a study reported that the viral content of social media has a strong impact on purchasing intention among Gen Z, both directly and indirectly, depending on the mediating variables of engagement and trust, which confirms that online social signals play a significant role in influencing consumer preference (Lesmana, 2025).
Although this body of research is increasing, some gaps remain. First, most literature available on socially conscious marketing and Gen-Z deals with the general market rather than the UK context (John & Kalyanrao, 2026; Mohamed et al., 2025). Despite the growing research on socially conscious marketing, social media, and Gen Z consumer behaviour, there are three key gaps. Second, previous research has mostly considered outcomes such as purchase intention, engagement, and brand awareness instead of brand preference as a specific attitudinal outcome. Third, there has been a lack of research that has concurrently explored the mediating value of social media influence in clarifying how socially conscious marketing translates to brand preference. Thus, this research fills these gaps by empirically researching the direct impact of socially conscious marketing on brand preference and the mediating influence of social media on UK Gen-Z consumers using Signalling Theory. In practice, this study provides marketers with evidence-based information on how to create and communicate socially conscious campaigns that appeal to the expectations and digital behaviours of Gen Z. This study aims to inform brands that are interested not only in appealing to Gen Z but also in making a meaningful connection in the age of socially conscious consumption.
2. LITERATURE REVIEW
2.1. Theoretical Framework
A theoretical framework offers a conceptual basis for research by providing a theory or theories that describe the association between major variables. In this study, Signalling Theory was chosen as the theoretical approach to explain how brands can send meaningful signals that decrease information asymmetry and foster trust in consumers (Connelly et al., 2025). Signalling Theory states that marketers use observable signals, including ethical promises, sustainability credentials, Corporate Social Responsibility (CSR) communications, and influencer endorsements, to convey brand values and credibility to consumers, who then respond to the signals to make informed decisions in a state of uncertainty (Shahid et al., 2024). Within the framework of socially conscious marketing, ethical communication and open social responsibility campaigns are high-quality signals that lower uncertainty about the intentions of the brand and brand authenticity and shape brand preferences in Gen-Z. Signalling Theory explains how social media is not only a channel but also a mechanism for distributing, amplifying, and interpreting these signals so that Gen Z can measure brand legitimacy based on visible indicators such as peer commenting, influencer credibility, and engagement metrics.
New empirical evidence justifies the use of signals in digital consumer behaviour. (Cambier & Poncin, 2020) demonstrate that ethically transparent marketing serves as a credibility signal that positively affects consumers’ brand choice by decreasing information asymmetry. In the same vein, (Saraç, 2025) confirms that social media marketing practices can be seen as signalling mechanisms that mediate brand assessments by increasing perceived credibility and indirectly influencing positive brand choices using digital interactions and endorsement signals.
Additionally, the researcher considered Social Identity Theory, which describes how consumers identify with brands that affirm their self-concept (Guan & So, 2023). However, this was dropped, as this theory would be relevant if the current research focus was on how Gen Z aligns with brands to reflect their self-concept and not on the formation and validation of this alignment. In contrast, Signalling Theory provided a more process-oriented explanation as it inherently focused on the ability of observable cues to communicate credibility under uncertainty. Rather than rejecting Social Identity Theory, its scope is narrowed in this study by acknowledging that alignment with identity may influence brand evaluations by Gen Z, but the emphasis remains on signalling mechanisms (externally observable) instead of self-concept congruence processes.
In the context of the digital landscape, this is of particular importance, considering that consumers rely on signals which are visible and verifiable instead of evaluating brands based on identity fit.
Furthermore, the suitability of Signalling Theory is that it enables the explanation of not just the transmission of signals but also the interpretation of these socially conscious cues within mediated environments. For example, in this study, Socially Conscious Marketing is used as a quality signal, signifying ethical and socially responsible intentions to consumers. Social media serves as a signal amplifier, disseminating and reinforcing these messages with the help of peer communications and influencer endorsements. Lastly, Brand Preference, which is a signal interpretation, involves Gen Z using these signals to develop a positive attitude and effective brand choices.
Therefore, signalling theory was found to be appropriate for examining the effect of these signals on consumer attitudes and online behaviour, making it a strong tool in the mediation model of socially conscious marketing → social media influence → brand preference.
Nevertheless, there are certain limitations to consider when employing this theory. This theory often assumes that signals are evaluated rationally; however, consumers interpret (particularly within the current digital setting) based on bounded rationality, emotions, and social biases, which can potentially lead to distorted judgments (Steigenberger, 2025). Additionally, there is a likelihood of signals that are deceptive or low-cost (such as greenwashing or symbolic CSR claims), which challenges the reliability of signals and undermines their claim for effective reduction of information asymmetry (Tham, 2023).
2.2. Key Constructs
Socially conscious marketing can be defined as a strategic marketing concept wherein organisations intentionally incorporate ethical, social, and environmental values within their marketing communications and practices to make a positive impact on society in addition to business success. Socially conscious marketing prioritises purpose-driven messages over traditional marketing, where the main goal is to sell and convince customers instead of matching brand values with their expectations. The literature frames socially conscious marketing as the expansion of CSR, with more emphasis on how ethical commitments are expressed and integrated into brand stories to establish trust and long-term relationships with consumers (Trkulja et al., 2024). Empirical studies indicate that socially responsible and value-based marketing campaigns positively impact consumer attitudes, brand credibility, perceived authenticity, and brand reviews, especially among younger generations, who are more socially conscious and value-oriented (Tarapata & Kostecki, 2025; Tewari et al., 2025). In the context of the current research, socially conscious marketing is conceptualised as the perception of consumers regarding brands signals that are ethical and sustainability-focused, with a particular focus on Gen-Z consumers who are value-driven. In recent literature, this concept has been measured based on dimensions such as perceived social sustainability, ethical credibility, and CSR communication, often using Likert-based multi-item measures to assess consumers’ evaluations of brands (Nagendra et al., 2024). Thus, in this study, the researcher adapted reflective measurement items to encapsulate credibility, trustworthiness, long-term commitment in long run, and perceived value congruence of the signals (Appendix A).
In contrast, brand preference can be defined as a bias or predisposition of consumers to choose one brand over another based on cognitive and affective considerations, which entails deeper evaluative consideration by consumers instead of temporary intent or behaviour (Ngan et al., 2019). It is also conceptualised as an attitudinal state that informs choice in situations where there is an alternative and is different from purchase intention (probability of buying), loyalty (commitment and repeat behaviour), and engagement (interaction or involvement). Traditional definitions of brand preference state that it is the degree to which a consumer prefers a brand compared to others in a competitive category, and it is based on brand perception and brand meaning memories (Ngan et al., 2019). In this study, brand preference is investigated as an outcome which is attitudinal and carved from ethical evaluation instead of entirely functional-based considerations, which reflects decision-making based on values by Gen Z. (Karantonis et al., 2025) measured this construct through a survey-based multi-item or by asking people to rank their likes and dislikes, choice tendencies, and consumer-based brand equity outcomes. In the current study, these measures were adapted, and key determinants of brand preference focused on ethical alignment, social responsibility preference, and affective attachment (Appendix A).
2.3. Hypotheses Development
Recent empirical studies have highlighted the fact that value-based or socially aware marketing shapes behavioural reactions among younger customers. For example, (El-Shihy & Awaad, 2025) examined the influence of brand- and user-created content on TikTok and Instagram on the purchase intentions of Gen Z towards sustainable fashion. It was concluded that both content types had a significant effect on purchasing intentions, but social media activity mediated them. Although this was not a study in a UK setting, the survey of 643 Gen-Z members in the study illustrates how visible marketing content associated with sustainability can play a role in informing consumer choice processes. Nonetheless, it did not measure the direct impact on brand preference as a construct, which is a conceptual limitation. On the same note, (Theocharis & Tsekouropoulos, 2025) investigated Gen-Z sustainable consumption and branding. The study concluded that marketing approaches that promote online brand experience and explicate sustainability values favourably influence sustainable consumption behaviour. Although this research elucidates the importance of sustainability in the context of overall consumer behaviour, it has not addressed the holistic preference of the brand, but rather products and new technology adoption, hence demonstrating a limitation in the determination of preference as a direct result.
Moreover, a study on Social Media Marketing Activities (SMMA) determined that digital activities had a notable impact on purchase intentions based on perceived quality, perceived value, and electronic word-of-mouth among Gen Z consumers in Vietnam. The results indicate that social media marketing has the potential to influence brand-related behavioural intentions when it is associated with values such as sustainability. Nevertheless, the cultural and market settings are not comparable to the UK, and the emphasis was not placed directly on social values or ethical content, which indicates a certain limitation of generalisability. Additionally, a study showed that the ethical relevance of influencers positively influences brand recognition and consumer purchasing choices among Gen Z and Millennial customers (Rajkumar, 2025). This study supports the idea that socially compatible content improves brand-related performance. Nonetheless, this research employed a very small sample (n = 50), and the combination of Gen-Z and Millennials weakens the findings unique to Gen-Z.
These empirical studies imply that sustainability-related and ethics-based marketing and influencer communication provide signals that inform Gen’s attitudes and intentions toward brands. However, current research typically focuses on purchase intention, engagement, or awareness as the outcome, but not brand preference, and most studies are not UK-based. Therefore, Hypothesis 1 is proposed as follows:
H1: Socially conscious marketing positively and significantly impacts the brand preferences of UK Gen-Z.
(Eandhizhai et al., 2025) examined the effects of social media green marketing on brand perception and green purchase intention among Gen Zs, concluding that social media marketing significantly affects brand perception, subsequently increasing sustainable consumer behaviours. However, it was not UK-specific, which restricts its generalisability to the current population of interest. Furthermore, (El-Shihy & Awaad, 2025) analysed the mediating role of social media while comparing the impact of brand and user-generated content on Gen Z purchase intentions in sustainable fashion. The study concluded that social media engagement partially mediated the impact of digital content on behaviour. This research proves that social media engagement plays a critical role in the present study, but it does not target brand perception, but purchase intentions, and the context is in Egypt and not in the UK.
(Deepika & Massand, 2025) elaborated on the role of SMMAs using a Vietnamese sample and stated that SMMAs (e-WOM, interaction, and trendiness) had a greater impact on purchase intention among Gen Z by modulating their response to marketing signals. This means that social media not only acts as a channel but also as an intermediary in defining the route between marketing efforts and consumer decisions. Nevertheless, this study was not conducted in the UK or a Western setting. Likewise, (Kusuma et al., 2024) examined the effects of social media on brand engagement, awareness, and image of Gen Zs and discovered that marketing components of social media entertainment and trendiness nurtured consumer-brand engagement significantly. In this case, interaction improved brand image and awareness, implying that the influence of digital content on brand performance is mediated by engagement. However, this study did not consider downstream preferences, and its fairly small sample (n = 138), based in Bali, restricts the extrapolation of its findings to the UK Gen Z.
A more general study, but with a larger focus, indicated that consumer brand preference may serve as a partial mediator between brand loyalty and SMMA in the Middle East in a Gen Z coffee shop setting (Abdou, 2025). Brand preference is an internal attitudinal outcome that associates digital marketing stimuli with loyal behaviour. This is important because it indicates preference, which is more proximate to this study’s dependent variable, but not socially conscious marketing material per se, and the sample was not UK-based. In addition, the presence of broader consumer and branding research confirms that social media use leads to brand trust and brand loyalty, which go hand in hand with preference, therefore justifying the mediation models (Ahsan & Kusuma, 2025). Although the outcome variables in these studies vary, they agree on the importance of social media-mediated processes in influencing consumer reactions to marketing stimuli among Gen Z. Thus, Hypothesis 2 is as follows:
H2: Social media positively and significantly mediates the relationship between socially conscious marketing and brand preferences among the UK Gen-Z.
2.4. Conceptual Framework
The hypothesised associations are presented as a conceptual framework in (Fig. 1). Socially conscious marketing is an independent variable showing a direct association with the dependent variable, UK Gen-Z’s brand preferences (H1), and an indirect association through the mediator, social media influence (H2).
Fig. (1). Conceptual framework.
3. METHODOLOGY
3.1. Research Design
The research design of this study adopted a quantitative research design based on a structured online survey to empirically investigate the influence of socially conscious marketing on the brand preference of the UK Gen-Z and the mediating effect of social media influence in the UK.
3.2. Data Collection Tool
A Google form was used to gather data, and all the questions were on a five-point Likert scale, where 1 = strongly disagree (1) and 5 = strongly agree (5). The questionnaire contained questions assessing three key constructs: socially conscious marketing, social media influence, and brand preference. Each measurement item was tailored to an already validated scale in the literature on marketing and consumer behaviour and adjusted to the UK setting and the UK Gen-Z consumer traits (Appendix A). Socially conscious marketing encompasses perceptions of ethical behaviour, sustainability programs of brands, and social responsibility communications. The measure of social media influence determined the degree to which social media, influencers, and peer relationships affected respondents’ brand judgment and perceptions. Brand preference evaluated the favourability, preference, and likelihood of respondents’ selecting brands that were in line with their values. The questionnaire was pre-tested to remove ambiguity, irrelevance, and content invalidity.
3.3. Sampling Technique and Sample Size
The sample consisted of Gen-Z consumers aged (18-26), who were UK-based, active on social media, and had recently encountered or purchased a consumer brand. A non-probabilistic purposive sampling technique was adopted to ensure that only those who met specific criteria were included. The sample comprised university students, newly graduated professionals, and early career workers in various industries. The rationale for this sample is that they are digitally native consumers whose decisions to buy certain brands are highly affected by social values and online interactions. Invitations to the survey were shared on LinkedIn, university student communities, an online Gen-Z community, and social media, which increased the coverage of the target population.
The sample is relatively representative of UK Gen-Z consumers since it includes people in the main age bracket of this generation who are active social media users and interact with brands frequently online. The sample included a high percentage of students, but there were also graduates and early career professionals with various educational and employment experiences. Since Gen-Z consumers are digital natives and among the most active users of social media platforms in the UK, this sample is suitable for representing the segment that is most prone to socially conscious marketing and digital brand communications.
Since the research was explanatory in nature and did not attempt to statistically generalise results to the entire UK population, probability-based sample size estimation techniques, such as the z-formula, could not be used and were thus not used. Rather, sample adequacy was evaluated using PLS-SEM-specific guidelines. According to the commonly used 10 -times rule, any sample size must be at least ten times the maximum number of structural paths to any endogenous construct (Demir & Uskak, 2025). Brand Preference in the proposed model is predicted by two constructs which means a minimum level of 20 observations, which far exceeds the final sample of 450 respondents. To ensure the robustness of the analysis, a statistical power analysis was conducted using G*Power, which proved that a sample size of 450 would produce sufficient power (more than 0.80) to identify medium effect sizes with a 5% significance level, as stated by (Memon et al., 2020).
Approximately 900 questionnaires were distributed to compensate for incomplete responses and possible non-responses. A response rate of approximately 56% was achieved, with 500 responses obtained. After screening the data, 90% of usable responses were retained, giving 450 respondents as the final usable sample, which is above the minimum that can be considered a robust multivariate analysis sample.
3.4. Assessing CMB and Non-Response Bias
Moreover, to assess the potential impact of Common Method Bias (CMB), Harman’s single-factor test was used. It is a diagnostic technique suitable for cross-sectional, self-reported survey data, where predictor and criterion variables are collected from the same respondents (Polas, 2025). In particular, an unrotated exploratory factor analysis applying principal component analysis was conducted on all the measurement items simultaneously. It examined whether a single latent factor accounts for the majority of the covariance among the constructs. This analysis found that none of the factors explained more than 50% of the variance, implying that the problem of common method bias was not significant (Katsekpor et al., 2025). Additionally, the issue of non-response bias was investigated by comparing early and late respondents on the key constructs using independent t-tests, and no statistically significant differences were found.
3.5. Data Analysis
Data analysis involved a Partial Least Squares Structural Equation Modelling (PLS-SEM) model, which is most appropriate in predictive and explanatory research with mediation analysis and latent constructs (Haji-Othman et al., 2024). The selection of PLS-SEM was based on the predictive orientation of the study, the mediation model used, and complex latent constructs instead of theory confirmation per se. In addition, PLS-SEM can be used to estimate models with non-normal data distributions, which are typical in behavioural and social media surveys with Gen-Z participants (Roy et al., 2025). Each construct in the model, such as socially conscious marketing, social media influence, and brand preference, was represented as a reflective construct, where the indicators were believed to be manifestations of the underlying latent variables and were likely to covary.
The analysis was conducted in two stages. First, the measurement model was tested to evaluate the measurement model to measure both the reliability and validity based on the factor loading, Cronbach’s alpha, composite reliability, convergent and discriminant validities (AVE), and the discriminant validities. The Heterotrait-Monotrait (HTMT) ratio was used to evaluate discriminant validity because it is more precise and reliable than traditional measures such as the Fornell-Larcker criterion in identifying construct overlap in PLS-SEM models, as stated by (Rasoolimanesh, 2022). Second, path analysis was used to evaluate the hypothesised relationships in the structural model, one of which was the mediating role of social media influence. Although the use of PLS-SEM allows flexibility in moderate sample sizes and non-normal data, special precautions were taken to provide proper model specification and prevent over-interpretation of causal relationships.
3.6. Ethical Considerations
Ethical considerations were strictly followed during the study. The respondents participated in the research on a voluntary basis, and the aim of the research was explained to them prior to the initiation of the survey. Electronic informed consent was obtained, and anonymity and confidentiality were guaranteed. No personally identifiable information was gathered, and data were kept safely and used only for academic interests, which are under the UK data protection regulations.
4. RESULTS
4.1. Demographic Analysis
The demographic profiles of the 450 respondents are presented in Table 1. The gender structure was even, with 50% of the respondents being female and (46.7%) being male, with only a small percentage (3.3) being non-binary or preferring not to respond. The age distribution is well distributed among the Gen-Z respondents, with most of them being 21-23 years old (40%), followed by the 18-20 and 24-26 age groups (30% each). Undergraduate students represented the highest population (43.3%), with (36.7%) having a degree. The employment status indicates that is (46.7%) of the population are full-time students, which indicates that many students are actively involved in education and digital settings that are of interest in this research.
Table 1. Descriptive analysis results.
| Variable | Category | Frequency (n) | Percentage (%) |
| Gender | Male | 210 | 46.7 |
| Female | 225 | 50.0 | |
| Non-binary / Prefer not to say | 15 | 3.3 | |
| Age Group | 18–20 years | 135 | 30.0 |
| 21–23 years | 180 | 40.0 | |
| 24–26 years | 135 | 30.0 | |
| Education Level | Undergraduate student | 195 | 43.3 |
| Postgraduate student | 90 | 20.0 | |
| Completed degree | 165 | 36.7 | |
| Employment Status | Student (full-time) | 210 | 46.7 |
| Employed (part/full-time) | 180 | 40.0 | |
| Unemployed | 60 | 13.3 |
4.2. Measurement Model Evaluation in PLS-SEM
To achieve measurement validity, a factor loading of more than 0.70 represented high item reliability, a Cronbach’s alpha and composite reliability of more than 0.70 indicated high internal consistency, and an AVE of more than 0.50 indicated convergent validity. Table 2 Brand Preferences reveals high factor loading (0.809-0.913), high reliability (α = 0.832), and high AVE (0.748), which is a strong construct measurement. Socially Conscious Marketing also has high loadings (0.842–0.899) and reliability (0.840), which attests to its consistency. Social media influence had the greatest reliability (α = 0.890) and AVE (0.819). Overall, these findings prove good measurement principles, which means that the constructs are reliable in reflecting the perceptions of the UK Gen-Z in this research.
Table 2. Measurement model.
| Latent Construct | Indicators | Factors Loading | Cronbach’s Alpha | Composite Reliability | Average Variance Extracted (AVE) |
| Brand Preferences | BP1 | 0.809*** | 0.832 | 0.850 | 0.748 |
| BP2 | 0.913*** | ||||
| BP3 | 0.870*** | ||||
| Socially Conscious Marketing | SCM1 | 0.871*** | 0.840 | 0.842 | 0.758 |
| SCM2 | 0.899*** | ||||
| SCM3 | 0.842*** | ||||
| Social Media Influence | SMI1 | 0.897*** | 0.890 | 0.891 | 0.819 |
| SMI2 | 0.929*** | ||||
| SMI3 | 0.888*** |
Note: ***p < 0.01
4.3. Discriminant Validity
Table 3 presents the discriminant validity, measured using the HTMT criterion, where values lower than the conservative threshold of 0.85 indicate that the constructs are empirically different. The HTMT value between brand preference and Social Media Influence was 0.521, and Socially Conscious Marketing had 0.602 with brand preference and 0.713 with social media influence. All the values were lower than 0.85, which shows sufficient discriminant validity between the constructs. These statistics confirm that the latent variables measure distinct conceptual domains that are not too overlapping. This means that the relationships examined in the structural model are not inflated by construct redundancy, which enhances the validity of the theoretical framework of the study.
Table 3. Discriminant validity (HTMT).
| – | Brand Preferences | Social Media Influence |
| Social Media Influence | 0.521 | – |
| Socially Conscious Marketing | 0.602 | 0.713 |
4.4. Model Explanatory Power
Table 4 shows the R-squared values, which indicate the percentage of variability in the predictor constructs. The R-Square of Social Media Influence is 0.382 and indicates that Socially Conscious Marketing accounts for 38.2% of its variation, which is weak to moderate explanatory power. The R-squared value of brand preference is 0.289, which means that both Socially Conscious Marketing and Social Media Influence explain the variance at 28.9. The adjusted R-squared values are closely matched, proving that the models are stable.
Table 4. R-square.
| – | R-square | R-square adjusted | Q-square |
| Brand Preferences | 0.289 | 0.285 | 0.251 |
| Social Media Influence | 0.382 | 0.381 | 0.375 |
The predictive relevance of the model was confirmed by the Q² values. Brand preference demonstrated moderate predictive relevance (Q² = 0.251), and Social Media Influence showed substantial predictive relevance (Q² = 0.375). As both values are greater than zero, the out-of-sample predictive capability is adequate for this model, which supports that endogenous constructs can be explained meaningfully and predicted by the predictor constructs.
4.5. Path Coefficient
The structural path results are shown in Table 5, where p-values less than 0.001 signify significant relationships.
Table 5. Path coefficient.
| – | Path Co-efficient | T-statistics | P-values | f-square |
| Direct Effects | ||||
| Social Media Influence -> Brand Preferences | 0.225*** | 3.343 | 0.001 | 0.044 |
| Socially Conscious Marketing -> Brand Preferences | 0.369*** | 5.920 | 0.001 | 0.118 |
| Socially Conscious Marketing -> Social Media Influence | 0.618*** | 16.553 | 0.001 | 0.619 |
| Indirect Effects | ||||
| Socially Conscious Marketing -> Social Media Influence -> Brand Preferences | 0.139** | 3.221 | 0.001 | |
Note: * indicates significance at p < 0.05; ** indicates significance at p < 0.01; *** indicates significance at p < 0.001.
H1: is supported, which states that socially conscious marketing positively and significantly impacts the UK Gen-Z’s brand preferences, as Socially Conscious Marketing positively influences Brand Preferences (β = 0.369, t = 5.920). However, the effect size is small to medium (0.118), which is expected as brand preference is a complex construct that depends on multiple factors other than socially conscious marketing, including price, product quality, brand recognition, and word of mouth. However, the statistically significant relationship indicates that socially conscious marketing still holds a significant place in brand preference among UK Gen Z consumers, especially in the context of value-driven purchasing choices. This implies that Gen-Z does not base their judgments solely on the functional benefits of brands but also on their perceived social and ethical compatibility. These findings contribute to the notion that socially responsible marketing promotes positive brand perceptions, which lie at the centre of preference development. This first-hand connection proves that brand messages laden with value possess an inherent persuasive force, even before the amplifying influences of social media are factored into the equation. This connection explains why authenticity and ethical positioning are vital elements of modern brand strategy. In addition, although not hypothesised, Social Media Influence is also associated with Brand Preferences (β = 0.225, t = 3.343). However, its effect size was small (f² = 0.044), indicating limited practical value. On the other hand, Socially Conscious Marketing is a strong predictor of Social Media Influence (β = 0.618, t = 16.553), with strong effect size (0.619).
Theoretically, this result validates the applicability of signalling theory in explaining the development of brand preference. For example, ethical and value-based marketing cues function as credible signals that reduce information asymmetry and shape favourable brand evaluations. By communicating socially responsible actions, brands signal trustworthiness, quality, and moral alignment, which Gen Z consumers interpret as indicators of socially acceptable and desirable brands. Nevertheless, the framework is still constrained, as it does not embrace identity-based motivations that can also be used to explain why Gen Z supports ethical brands. These findings can be associated with and add to the existing literature. Previous research, including (El-Shihy & Awaad .2025; and Theocharis & Tsekouropoulos, 2025), proved that sustainability-oriented marketing affects Gen-Z purchase intentions and consumption behaviour. Similarly, (Rajkumar, 2025) established that the relevance of ethics in influencer content enhances brand recognition and buying decisions. Nevertheless, these studies were constrained by their purchase intention and not brand preference, small generational samples, and non-UK settings. Having empirically tested brand preference as a unique attitudinal response in a UK Gen Z sample, this study fills these gaps in the literature by demonstrating that socially conscious marketing provides deeper and more long-lasting brand relationships.
H2: is also supported, which states that social media positively and significantly mediates the relationship between socially conscious marketing and brand preferences among UK Gen Z. The results in Table 5 also show the indirect influence of socially conscious marketing on brand preferences through social media influence (β =0.139, t=3.221), indicating partial mediation. Social media, instead of being a passive medium, has become a vital platform on which Gen Z consumers process ethical messages as a result of peer communication, the influence of influencers, and interaction.
More to the point, this work builds upon Signalling Theory, showing that signals are not merely passed on between brands and consumers but are also socialised using digital means. Social media is a signal-enhancing factor that deepens the visibility, credibility, and interpretation of ethical brand messages through peer-to-peer interactions and influencer recommendations. Thus, this study takes Signalling Theory a step beyond the conventional one-way communication model and into the dynamic digital signalling process, where consumers become active validators and reinforcers of brand signals prior to the process of developing brand preferences.
Moreover, this mediated relationship is in line with previous empirical evidence, as it addresses these gaps. (Deepika & Massand, 2024; Lesmana, 2025; and Agrawal, 2025) reported that engagement, trust, and influencer-generated content mediate the effects of digital marketing on purchase intention and brand equity. Similarly, (Deepika & Massand, 2025; and Kusuma et al., 2024) established the mediating role of SMMA in developing engagement and awareness. Incorporating social media mediation, socially conscious marketing, and brand preference in a UK Gen-Z context, this study builds on signalling theory and adds to the existing literature. Overall, this study highlights that brands should consider and signal value-based marketing and social media dynamics to develop long-term brand affinity, as opposed to short-term behavioural reactions through both direct and mediated influences on brand preference.
CONCLUSION
This study examined the impact of socially conscious marketing on brand preference among UK Gen Z consumers and social media influence as a partial mediator variable under Signalling Theory. The results validate that the direct influence of socially conscious marketing on brand preference is significant, which means that ethical and value-based brand communication (as signals) is associated with the UK Gen Z attitudes. The results also show that social media is a critical mediating factor in boosting and decoding socially aware signals into positive brand perceptions. Collectively, these results provide evidence for the application of signalling theory to brand preference in a UK-based digital environment.
LIMITATIONS
This study has several limitations despite its contributions. First, the cross-sectional design limits time-based causation. Second, the self-reported survey data could have perceptual bias, despite the methodological control. Future studies may adopt a longitudinal or experimental design to capture changing brand preferences. Moreover, the data were gathered using non-probability sampling, and most of the sample were students which further limits generalisability. Thus, future researchers can add to the current findings by expanding the sample to include more working Gen Z respondents.
POLICY AND IMPLICATIONS
On a policy and practical level, the results indicate that brands aiming to reach UK Gen-Z must incorporate socially responsible principles into their main marketing strategies. In practice, when marketing to UK Gen-Z, marketers must go beyond generic sustainability statements and convey quantifiable social benefits. To begin with, brands must post evidence-based content, including carbon reduction, ethical sourcing, or community activities in the form of short-form TikTok and Instagram videos. Second, marketers must consider working with influencers whose personal values truly match brand values and not just followings. Third, to promote peer validation, brands must stimulate user engagement with sustainability challenges, interactive polls, and cause-related hashtag campaigns. Fourth, marketers need to constantly evaluate the quality of engagement with measures of sentiment analysis, authenticity of comments, and share rates, instead of only using likes and impressions. Such measures can enhance brand credibility, consumer confidence, and long-term brand preference among UK Gen-Z consumers.
In terms of policy, regulators in government and industry should develop single standards for sustainability reporting and ethical marketing practices (e.g. reporting standards or badges) to reduce the occurrence of greenwashing and enhance the consistency of social signals. Similarly, tax exemption or prizes and awards can be included in brands that can demonstrate social responsibility to create confidence and long-term sustainable marketing.
LIST OF ABBREVIATIONS
AVE | = | Average Variance Extracted |
CMB | = | Common Method Bias |
CSR | = | Corporate Social Responsibility |
Gen-Z | = | Generation Z |
HTMT | = | Heterotrait-Monotrait |
PLS-SEM | = | Partial Least Squares Structural Equation Modelling |
SMMA | = | Social Media Marketing Activities |
AUTHOR’S CONTRIBUTION
T.S. has designed and developed the study, formulated the model, conducted the mathematical analyses, interpreted the findings, supervised all aspects of the research, refined the presentation of the results, and approved the final manuscript.
ETHICAL APPROVAL & INFORMED CONSENT
Ethical considerations were strictly followed during the study. The respondents participated in the research on a voluntary basis, and the aim of the research was explained to them prior to the initiation of the survey. Electronic informed consent was obtained, and anonymity and confidentiality were guaranteed. No personally identifiable information was gathered, and data were kept safely and used only for academic interests, which are under the UK data protection regulations.
AVAILABILITY OF DATA AND MATERIALS
Available upon request.
FUNDING
None.
CONFLICT OF INTEREST
The author declares that there are no competing interests or conflicts of interest relevant to the content of this work.
ACKNOWLEDGEMENTS
None.
DECLARATION OF AI
During the preparation of this manuscript, the author used ChatGPT for language editing and manuscript refinement. The author reviewed and verified all AI-assisted content and accepted full responsibility for the final manuscript.
APPENDIX A
Demographic
Demographic Variable | Category | Response (tick) |
Age | 18–20 years | ☐ |
21–23 years | ☐ | |
24–26 years | ☐ | |
Gender | Male | ☐ |
Female | ☐ | |
Non-binary / Prefer not to say | – | |
Education Level | Undergraduate student | ☐ |
Postgraduate student | ☐ | |
Completed degree | ☐ | |
Student (full-time) | ☐ | |
Employment Status | Employed (part/full-time) | ☐ |
Unemployed | ☐ |
Section A: Socially Conscious Marketing (SCM)
Code | Statement | 1 | 2 | 3 | 4 | 5 |
SCM1 | A brand’s social and environmental initiatives signal its genuine values and long-term commitment. | ☐ | ☐ | ☐ | ☐ | ☐ |
SCM2 | Ethical and socially responsible marketing helps me judge a brand’s trustworthiness and credibility. | ☐ | ☐ | ☐ | ☐ | ☐ |
SCM3 | Brands that address social issues signal alignment with my personal values. | ☐ | ☐ | ☐ | ☐ | ☐ |
Section B: Social Media Influence (SMI)
Code | Statement | 1 | 2 | 3 | 4 | 5 |
SMI1 | Social media content, influencers, and user reviews influence how I evaluate brands. | ☐ | ☐ | ☐ | ☐ | ☐ |
SMI2 | Social media helps me understand a brand’s ethical values. | ☐ | ☐ | ☐ | ☐ | ☐ |
SMI3 | Interacting with brands on social media strengthens my connection with them. | ☐ | ☐ | ☐ | ☐ | ☐ |
Section C: Brand Preferences (BP)
Code | Statement | 1 | 2 | 3 | 4 | 5 |
BP1 | I prefer and choose brands that align with my social and ethical values. | ☐ | ☐ | ☐ | ☐ | ☐ |
BP2 | I feel a stronger attachment to brands that demonstrate social responsibility and ethical behaviour. | ☐ | ☐ | ☐ | ☐ | ☐ |
BP3 | A brand’s social responsibility increases my likelihood of choosing and remaining loyal to it. | ☐ | ☐ | ☐ | ☐ | ☐ |
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