Literature Review Sample: Influencer Marketing and Consumer Trust

Model Answer

Introduction

Influencer marketing has become one of the most significant developments in digital promotional strategy over the past decade, with brands increasingly directing marketing budgets toward individuals who have built dedicated followings on platforms such as Instagram, YouTube and TikTok. Central to the effectiveness of this practice is consumer trust: the extent to which audiences believe an influencer’s recommendations are honest, competent and reasonably free from undue commercial bias. This review critically synthesises the empirical literature on influencer marketing and consumer trust, organised around four themes.

The review first examines source credibility and parasocial relationships, before turning to authenticity and sponsorship disclosure. It then considers how influencer-brand fit and follower count moderate trust, and finally traces the pathway from trust to purchase intention. The review closes by identifying methodological and geographical gaps that limit the generalisability of current findings, and by outlining directions for future research that would strengthen the UK evidence base in particular.

The review draws primarily on quantitative survey-based studies published between 2016 and 2021, supplemented by qualitative and ethnographic work where it offers explanatory depth that survey designs cannot provide. This mixed base of evidence is deliberate: consumer trust is a psychological construct that quantitative studies can measure at scale, but the meaning consumers attach to disclosure, authenticity and endorsement is better understood through the richer, interpretive accounts that qualitative research affords. Reading these literatures together, rather than treating them as separate bodies of work, is central to the critical synthesis attempted here.

Source Credibility and Parasocial Relationships

Source credibility theory, adapted from traditional celebrity endorsement research, has provided the dominant lens through which scholars have examined influencer trust. De Veirman, Cauberghe and Hudders (2017) found that Instagram influencers with very large follower counts were sometimes perceived as less likeable, a “follower count paradox” that complicates the assumption that reach alone builds trust; likeability, rather than raw popularity, mediated brand attitude in their study. This finding is broadly consistent with Djafarova and Rushworth (2017), who reported that young female consumers regarded Instagram influencers as more credible and relatable than traditional celebrities, precisely because influencers were perceived as “ordinary people” whose lifestyles felt attainable rather than aspirational in an unreachable sense. Both studies converge on the idea that credibility is less a function of status and more a function of perceived similarity and everyday authenticity.

Parasocial interaction theory extends this picture by explaining why followers come to trust influencers as though they were personal acquaintances rather than distant public figures. Reinikainen et al. (2020) demonstrated that parasocial relationships strengthened over repeated exposure to an influencer’s content, and that this closeness heightened perceived credibility even in the presence of clearly sponsored posts; audience comments moderated the effect, with visible peer endorsement in the comments section reinforcing trust further. Munnukka, Uusitalo and Toivonen (2016) similarly found that “peer-like” endorsers, positioned as ordinary consumers rather than experts, generated stronger persuasive effectiveness than expert endorsers for some product categories, although the effect varied with the audience’s level of product involvement. Sokolova and Kefi (2020) add a further nuance, showing that parasocial interaction and credibility operated as parallel but partly distinct predictors of purchase intention, meaning an influencer could be trusted without a strong parasocial bond existing, and vice versa.

A further consideration within this theme is expertise, which functions somewhat differently from likeability and familiarity. Where an endorsement concerns a technical or high-involvement category, such as financial products or skincare with active ingredients, audiences appear to weight perceived expertise more heavily than parasocial closeness alone; several of the studies above note this as a boundary condition rather than testing it as a primary variable, which leaves the relative weighting of expertise versus familiarity across product categories only partially resolved in the current literature.

Taken together, this body of work indicates that trust in influencer marketing is not a single construct but is built from at least two related processes: judgements about the source’s expertise and honesty, and an emotional sense of familiarity that develops through sustained parasocial engagement. What remains underexplored is how these two mechanisms interact over time, since most of the studies reviewed here relied on cross-sectional surveys that captured trust at a single point rather than as it develops across the life of a follower’s relationship with an influencer.

Authenticity, Sponsorship Disclosure and Perceived Manipulative Intent

A second, closely related theme concerns how the disclosure of paid partnerships affects perceived authenticity. Persuasion knowledge theory suggests that once consumers recognise a persuasion attempt, they become more sceptical of the source, and several studies have tested this proposition directly in the influencer context. Evans et al. (2017) found that explicit disclosure language such as “sponsored” reduced advertising-recognition failures compared with ambiguous hashtags like #sp, but this increased recognition also modestly lowered attitudes toward the endorsed brand, illustrating a trade-off between transparency and persuasive effectiveness. Boerman (2020) extended this line of enquiry to micro- and meso-influencers specifically, finding that a standardised disclosure label increased recognition of commercial intent without significantly damaging the influencer’s perceived trustworthiness, a more optimistic result than that reported by Evans et al.

Other researchers have queried whether disclosure alone is sufficient to protect consumer trust. Kim and Kim (2021) proposed a “multiple inference model” in which consumers simultaneously infer both the influencer’s sincerity and the brand’s motives from a disclosed post, concluding that disclosure interacts with influencer-product congruence: a well-matched pairing softened the negative effect of disclosure, while a poor fit amplified scepticism considerably. Chapple and Cownie (2017) took a qualitative approach with YouTube vloggers’ audiences and found that viewers valued disclosure but simultaneously expected influencers to endorse only products they personally used, suggesting that authenticity is judged less by the disclosure itself than by consistency between the influencer’s established persona and the endorsed brand.

Audrezet, de Kerviler and Guidry Moulard (2020) offer a theoretical account that helps reconcile these mixed findings, arguing that influencers manage authenticity through two distinct strategies: “passable authenticity”, where sponsored content is made to resemble organic posts, and “self-disclosure authenticity”, where the influencer openly frames the partnership as a personal choice they have made. Their model implies that the disclosure debate in the quantitative literature may understate the agency influencers exercise in framing commercial content, a nuance that survey-based designs struggle to capture in a single measured item. Stubb, Nyström and Colliander (2019) support this reading, showing that when influencers explicitly justified why they had accepted a sponsorship, disclosed content was rated as more trustworthy than undisclosed content, effectively reversing the typical disclosure penalty found elsewhere.

Considered as a whole, this theme suggests that the effect of disclosure on trust is neither uniformly positive nor uniformly negative, but is instead contingent on framing, fit and the audience’s prior relationship with the influencer. Studies that treat disclosure as a simple binary, present or absent, tend to find a modest trust penalty; studies that examine how disclosure is delivered, whether justified, integrated into an established persona, or paired with a well-matched product, tend to find that the penalty can be minimised or even reversed. This distinction has practical implications for regulators and platforms designing disclosure standards, since a one-size-fits-all disclosure label may not capture the more nuanced dynamics this literature has identified.

Influencer-Brand Fit and the Micro-Influencer Effect

A third theme addresses structural features of the influencer-brand relationship, in particular perceived fit and audience scale. Breves et al. (2019) found that congruence between an influencer’s established content niche and the endorsed brand significantly predicted source credibility and, in turn, purchase intention; a fitness influencer promoting sportswear generated stronger outcomes than the same influencer promoting an unrelated product category. Schouten, Janssen and Verspaget (2020) compared celebrity and influencer endorsers directly and found that influencers generated stronger audience identification, but that product-endorser fit predicted credibility more strongly than the type of endorser itself, suggesting fit may matter more than whether the source is a celebrity or an everyday influencer.

The question of scale, meanwhile, produces a genuinely contested picture. De Veirman et al. (2017), discussed above, found a negative relationship between follower count and likeability at very high follower levels. Hughes, Swaminathan and Brooks (2019) offer a more granular explanation, showing that follower count interacted with parasocial interaction and brand engagement differently depending on whether a campaign’s goal was awareness or purchase: micro-influencers with smaller, more engaged audiences outperformed macro-influencers on purchase-related outcomes, while macro-influencers retained an advantage for broad awareness metrics. Belanche et al. (2021) add that followers’ attitudes toward an influencer were shaped less by follower count directly and more by perceived attractiveness, expertise and trustworthiness, which followers relied on as heuristics whenever the influencer was relatively unfamiliar to them.

These studies collectively challenge the assumption, common in industry commentary, that larger reach straightforwardly produces greater marketing value. Instead, the literature suggests a more nuanced trade-off in which micro-influencers may generate superior trust and conversion for niche or considered purchases, while macro-influencers remain useful chiefly for broad brand awareness. However, the definitions of “micro” and “macro” influencer vary considerably across these studies, ranging from follower thresholds in the low thousands to several hundred thousand, which limits direct comparison and points to a clear need for a more standardised classification in future work.

It is also worth noting that fit and scale interact rather than operating independently. A macro-influencer with a strong niche identity, for example a well-known fitness personality, may achieve fit-driven credibility comparable to a micro-influencer while retaining the reach advantages associated with a larger following; conversely, a micro-influencer who frequently switches between unrelated product categories may struggle to build the perceived expertise that smaller scale is otherwise assumed to confer. Few of the studies reviewed here model this interaction directly, instead treating fit and follower count as separate predictors, which likely understates the complexity of how brands and consumers actually evaluate influencer partnerships in practice.

From Trust to Purchase Intention: Scepticism and Behavioural Outcomes

The final theme concerns the extent to which trust actually translates into behavioural outcomes such as purchase intention, and the scepticism that can interrupt this pathway. Lou and Yuan (2019) found that informative and credible influencer content positively predicted followers’ trust in branded posts, which in turn predicted purchase intention; message value operated as a stronger predictor of trust than the influencer’s perceived attractiveness, challenging assumptions in earlier celebrity endorsement research that appearance is the dominant driver of endorsement effectiveness. Sokolova and Kefi (2020), reviewed above, similarly found that both credibility and parasocial interaction predicted purchase intention, though the strength of this relationship depended on product category, with stronger effects for beauty and lifestyle products than for more functional goods.

Jin and Muqaddam (2019) examined how different post formats, such as a product being used naturally within a lifestyle photo versus a direct product-placement shot, affected brand attitude, finding that subtler placements generated more favourable attitudes overall, consistent with persuasion knowledge theory’s prediction that overt persuasion attempts trigger consumer resistance. Abidin (2016), using an ethnographic approach to fashion “outfit-of-the-day” content, offers a complementary account of the labour influencers invest in appearing authentic, describing “visibility labour” as the ongoing, often invisible work of maintaining a relatable persona that sustains follower trust over an extended period.

Read together, these studies suggest trust functions as a necessary but not sufficient condition for purchase intention: message quality, product category and the subtlety of commercial framing all moderate whether trust converts into behaviour. Notably, almost all of the quantitative studies within this theme measured purchase intention rather than observed purchasing behaviour, a methodological limitation that recurs throughout the wider literature and is addressed further in the section below.

Gaps in the Literature

Several limitations recur across the reviewed literature. First, the overwhelming majority of studies rely on self-reported purchase intention rather than observed purchasing behaviour, leaving open the question of whether the trust-purchase relationship holds under real transactional conditions. Second, samples are drawn disproportionately from US, Western European or East Asian student and young-adult populations; UK-specific data on influencer trust remains comparatively sparse, despite the UK’s distinct regulatory environment for influencer advertising under the Advertising Standards Authority’s disclosure rules. Third, almost all of the studies discussed here are cross-sectional, capturing consumer trust at a single moment rather than tracking how it develops, and potentially erodes, over a sustained parasocial relationship or following repeated disclosure of commercial partnerships.

Fourth, TikTok-based influencer marketing remains markedly under-researched relative to Instagram and YouTube, despite its distinct short-form format and younger user base, which may generate different credibility and disclosure dynamics that the existing literature has not yet captured. Finally, comparatively little attention has been paid to generational differences in influencer trust; existing work rarely distinguishes Generation Z consumers, who have grown up alongside influencer culture as a normal feature of social media, from older cohorts for whom the format remains a comparatively novel and unfamiliar form of marketing communication. Addressing these gaps through longitudinal, UK-focused and platform-diverse research designs would considerably strengthen the evidence base available to both scholars and practitioners.

A further, more subtle gap concerns measurement consistency. Constructs central to this literature, including credibility, authenticity and parasocial interaction, are operationalised differently across studies, with varying numbers of survey items and inconsistent scale anchors. This inconsistency makes it difficult to compare effect sizes directly across studies or to conduct a reliable meta-analysis of the field as a whole, and it represents a methodological gap that a future systematic review, rather than a narrative review of this kind, would be well placed to quantify more precisely.

Conclusion

This review has shown that consumer trust in influencer marketing is shaped by an interdependent set of factors: perceived source credibility and parasocial closeness, the framing and justification of sponsorship disclosure, the fit between influencer and brand, and the scale of the influencer’s following. While trust generally predicts purchase intention, this relationship is moderated by product category, message subtlety and disclosure strategy, and it is rarely tested against actual purchasing behaviour rather than stated intention. The literature also remains geographically and methodologically narrow, with heavy reliance on cross-sectional, self-report designs conducted largely outside the UK.

Future research employing longitudinal designs, UK-based samples and platforms beyond Instagram and YouTube, particularly TikTok, would help clarify whether the mechanisms identified in this review generalise across contexts. Such research would also provide marketers, and the brands that work with them, with a more robust evidence base for building durable, ethically sound consumer trust rather than short-term engagement alone.

References

Abidin, C. (2016) ‘Visibility labour: engaging with influencers’ fashion brands and #OOTD advertorial campaigns on Instagram’, Media International Australia, 161(1), pp. 86–100.

Audrezet, A., de Kerviler, G. and Guidry Moulard, J. (2020) ‘Authenticity under threat: when social media influencers need to go beyond self-presentation’, Journal of Business Research, 117, pp. 557–569.

Belanche, D., Casaló, L.V., Flavián, M. and Ibáñez-Sánchez, S. (2021) ‘Building influencers’ credibility on Instagram: effects on followers’ attitudes and behavioural responses toward the influencer’, Journal of Retailing and Consumer Services, 61, 102585.

Boerman, S.C. (2020) ‘The effects of the standardized Instagram disclosure for micro- and meso-influencers’, Computers in Human Behavior, 103, pp. 199–207.

Breves, P.L., Liebers, N., Abt, M. and Kunze, A. (2019) ‘The perceived fit between Instagram influencers and the endorsed brand: how influencer-brand fit affects source credibility and persuasive effectiveness’, Journal of Advertising Research, 59(4), pp. 440–454.

Chapple, C. and Cownie, F. (2017) ‘An investigation into viewers’ trust in and response towards disclosed paid-for-endorsements by YouTube lifestyle vloggers’, Journal of Promotional Communications, 5(2), pp. 110–136.

De Veirman, M., Cauberghe, V. and Hudders, L. (2017) ‘Marketing through Instagram influencers: the impact of number of followers and product divergence on brand attitude’, International Journal of Advertising, 36(5), pp. 798–828.

Djafarova, E. and Rushworth, C. (2017) ‘Exploring the credibility of online celebrities’ Instagram profiles in influencing the purchase decisions of young female users’, Computers in Human Behavior, 68, pp. 1–7.

Evans, N.J., Phua, J., Lim, J. and Jun, H. (2017) ‘Disclosing Instagram influencer advertising: the effects of disclosure language on advertising recognition, attitudes, and behavioral intent’, Journal of Interactive Advertising, 17(2), pp. 138–149.

Hughes, C., Swaminathan, V. and Brooks, G. (2019) ‘Driving brand engagement through online social influencers: an empirical investigation of sponsored blogging campaigns’, Journal of Marketing, 83(5), pp. 78–96.

Jin, S.V. and Muqaddam, A. (2019) ‘Product placement 2.0: do Instagram influencers’ post types affect brand attitude and purchase intention?’, Journal of Retailing and Consumer Services, 47, pp. 27–47.

Kim, D.Y. and Kim, H.-Y. (2021) ‘Influencer advertising on social media: the multiple inference model on influencer-product congruence and sponsorship disclosure’, Journal of Business Research, 130, pp. 405–415.

Lou, C. and Yuan, S. (2019) ‘Influencer marketing: how message value and credibility affect consumer trust of branded content on social media’, Journal of Interactive Advertising, 19(1), pp. 58–73.

Munnukka, J., Uusitalo, O. and Toivonen, H. (2016) ‘Credibility of a peer endorser and advertising effectiveness’, Journal of Consumer Marketing, 33(3), pp. 182–192.

Reinikainen, H., Munnukka, J., Maity, D. and Luoma-aho, V. (2020) ‘”You really are a great big sister” – parasocial relationships, credibility, and the moderating role of audience comments in influencer marketing’, Journal of Marketing Management, 36(3–4), pp. 279–298.

Schouten, A.P., Janssen, L. and Verspaget, M. (2020) ‘Celebrity vs. influencer endorsements in advertising: the role of identification, credibility, and product-endorser fit’, International Journal of Advertising, 39(2), pp. 258–281.

Sokolova, K. and Kefi, H. (2020) ‘Instagram and YouTube bloggers promote it, why should I buy? How credibility and parasocial interaction influence purchase intentions’, Journal of Retailing and Consumer Services, 53, 101742.

Stubb, C., Nyström, A.-G. and Colliander, J. (2019) ‘Influencer marketing: the impact of disclosing sponsorship compensation justification on sponsored content effectiveness’, Journal of Communication Management, 23(2), pp. 109–122.