Congruence effects in social media influencer marketing: the moderating role of wishful identification in online impulse buying intentions

Abstract

Purpose

Grounded in self-congruency theory, this study aims to investigate the impact of different types of congruence in social media influencer marketing on consumers’ online impulse buying intentions under the moderating influence of wishful identification.

Design/methodology/approach

This study collects survey responses from an online sample of 232 social media users and analyses them using partial least squares structural equation modelling.

Findings

This study delineates two distinct pathways influencing online impulse buying intentions within influencer marketing: direct consumer–product congruence and the conditional role of consumer–influencer congruence. Particularly, the alignment between a consumer’s self-image and the product’s attributes independently drives online impulse buying intentions. Conversely, consumer–influencer congruence, despite high alignment, fails to spur online impulse buying intentions unless amplified by wishful identification – the consumer’s aspirational desire to emulate the influencer. This finding underscores the complexity of impulsive consumer behaviours in the digital marketplace, highlighting the pivotal role of product appeal and the conditional influence of influencer relationships on spontaneous purchasing decisions.

Originality/value

This study pioneers by elucidating the congruence interplay between consumers, influencers and products in online impulse buying, emphasising wishful identification as a critical moderating factor. Theoretically, it expands self-congruency theory by detailing the distinct roles of congruence types on impulsive behaviours, notably underlining the essential role of wishful identification for the effect of consumer–influencer congruence. Practically, the insights equip brands with a deeper understanding of the key drivers behind impulsive purchases in an influencer-centric digital marketplace, offering strategic guidance for optimising influencer collaborations and product presentations to enhance consumer engagement and sales.

Citation

Koay, K.Y. and Lim, W.M. (2024), "Congruence effects in social media influencer marketing: the moderating role of wishful identification in online impulse buying intentions", Journal of Product & Brand Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JPBM-09-2023-4709

1. Introduction

In the rapidly evolving digital ecosystem, characterised by the pervasive influence of social media, influencer marketing has risen to prominence as a powerful avenue for captivating target audiences (Bastrygina et al., 2024; Cheah et al., 2024; Joshi et al., 2024). Central to this evolution is a dynamic collaboration between brands and social media influencers (Koay et al., 2021, 2022, 2023, 2024). With a knack for crafting bespoke content, social media influencers not only advocate for brands but also extend their reach significantly to a vast array of followers (Agnihotri et al., 2023; Bastrygina and Lim, 2023; Bastrygina et al., 2024; Gamage and Ashill, 2023). Noteworthily, influencer marketing is witnessing an exponential increase in adoption, reflecting its escalating importance as an integral component of contemporary branding and marketing strategies (Bastrygina et al., 2024; Joshi et al., 2024). To illustrate, back in 2016, the influencer marketing sector held a value of $1.7bn, as reported by Influencer Marketing Hub, and by 2022, this figure had surged to $16.4bn; furthermore, it is estimated that brands have the potential to generate approximately $5.78 in return for each dollar invested in influencer marketing (Celestino, 2023).

Social media influencers are individuals on socially oriented digital platforms who have organically nurtured engaged communities by curating and sharing original content within their areas of expertise and interest, including beauty, fashion, lifestyle, sports and more (Bastrygina and Lim, 2023; Koay et al., 2021; Joshi et al., 2024). Social media influencers interact with their followers by offering engaging content such as live interactions, stories and video logs (vlogs) (Bastrygina and Lim, 2023; Kim and Yoon, 2024). These activities allow social media influencers to grow and establish strong bonds with followers, influencing consumption decisions besides spurring a rise to fame (Kim and Kim, 2022). Social media influencers, by virtue of their curated content across various platforms, cultivate a sense of relatability and trust that often surpasses that of traditional celebrities (Joshi et al., 2024; Liu and Lee, 2024). This authenticity fosters stronger connections with their audience, making endorsements by social media influencers particularly influential (Bastrygina et al., 2024). Brands endorsed by these social media personalities, therefore, are often met with more favourable consumer reception compared to those promoted by celebrities (Schouten et al., 2021). This dynamic underscores the potent influence of social media influencers on consumer behaviour, a subject of increasing scholarly interest aimed at unravelling the ways these organic celebrities sway consumer decision-making (Cheung et al., 2022a, 2022b; Pradhan et al., 2023).

Anchoring the exploration in the self-congruence theory, this study recognises that individuals harbour an innate desire to align their actions with their self-concept, values and identity (Johar and Sirgy, 1991). Through this prism, social media influencers attain prominence, serving as pivotal reference groups that inform how consumers assess, aspire and act (Osgood and Tannenbaum, 1955; Shan et al., 2020). This draws consumers to social media influencers whose personas mirror their own beliefs or cultural norms. Existing literature corroborates the influence of consumer-influencer congruence on myriad consumer behaviours, ranging from brand engagement (Tafheem et al., 2022) to parasocial identification (Shan et al., 2020). Yet, a conspicuous void persists. Much of extant research is confined to consumer–influencer congruence, with scant attention to other facets of congruence outlined by Belanche et al. (2021) and Koay et al. (2023) – namely, consumer–product and influencer–product congruences. Furthermore, there is a discernible dearth of scholarship probing the ramifications of these congruences on online impulse buying intentions, as the focus has been largely restricted to planned purchases (Liang et al., 2022; Masuda et al., 2022; Shan et al., 2020).

With regards to limited exploration of multifaceted congruence, the overemphasis on consumer–influencer congruence in the extant literature (Shan et al., 2020; Tafheem et al., 2022) reveals a myopic understanding of the broader spectrum of congruence that potentially drives consumer behaviour. When the investigation is limited to this singular dimension, the academic community risks missing out on capturing a holistic understanding of the peculiarities of congruence in influencer marketing. Examining other facets, like consumer–product and influencer–product congruences (Belanche et al., 2021; Koay et al., 2023), can unearth a more comprehensive and granular understanding of how congruence operates across various dimensions and its impacts on consumer behaviour. From a managerial standpoint, this insight equips brands with a more detailed and informed understanding, allowing them to optimise the alignment between influencers, consumers and products. Recognising and leveraging the right kind of congruence should therefore lead to better influencer partnerships and enhanced consumer brand engagement.

With regards to the overlooking of online impulse buying intentions, the predominant focus on planned purchases (Aw and Chuah, 2021; Gani et al., 2023; Hsieh et al., 2023; Masuda et al., 2022) indicates an incomplete understanding of the consumer’s shopping journey. This gap is significant as it fails to account for the spontaneous and often unplanned nature of online impulse purchases, a phenomenon that is becoming increasingly prevalent in the digital age (Shamim et al., 2024). The importance of addressing this gap lies in its potential to expand understanding of consumer behaviour beyond the confines of planned purchasing processes, shedding light on the immediate, emotive responses that drive consumers to make impulsive purchases in response to influencer marketing. From a practical standpoint, deciphering the triggers of online impulse buying intentions is crucial. In the dynamic environment of e-commerce, where transactions are executed instantaneously (Kumar et al., 2021), tapping into the mechanisms of online impulse buying intentions can significantly alter the conversion trajectory from mere browsing to actual purchasing. Understanding how different types of congruence between influencers, consumers and products affect online impulse buying intentions should therefore assist brands and social media influencers to craft more compelling calls-to-action, and ultimately, scale their mutual returns in influencer marketing.

Navigating deeper into the complex domain of influencer marketing, this study introduces and foregrounds the role of wishful identification as an instrumental moderator shaping the nexus between congruence and online impulse buying intentions. Theoretically, the concept of wishful identification enriches understanding by presenting a more granular lens through which to scrutinise consumer behaviour. Beyond mere alignment or resonance between a consumer and an influencer, wishful identification encapsulates a deeper, more refined psychological dimension – the aspirational impetus propelling a consumer to emulate a preferred social media influencer. Centering on this dynamic, this study captures a richer understanding of the affective forces underpinning online impulse buying intentions, thereby offering a more holistic conceptual model. Practically, this insight is invaluable as it implies that brands and social media influencers cannot simply rely on the apparent synergies in congruence – be it consumer–influencer, consumer–product or influencer–product congruence. Instead, they must account for the profound motivational undertow of wishful identification. Recognising the potency of this yearning to emulate can empower brands and social media influencers to tailor their collaborations more astutely, ensuring not just congruence, but also an aspirational resonance with their target audiences. Put succinctly, while pronounced congruencies across various axes might set the stage, it is the magnitude of wishful identification that ultimately catalyses the act of online impulse buying intentions. Thus, this study does not merely contend but also illuminates by refining the contours of both theoretical discourse and practical strategy in influencer marketing.

This study offers salient contributions. At its core, this study amplifies the theoretical dimensions of congruence in influencer marketing by introducing a multidimensional model, addressing not just the prevalent consumer–influencer congruence but also spotlighting the dynamics of consumer–product and influencer–product congruences, which elevates the discourse to a holistic understanding, heeding the clarion call for a deeper dive into congruence in social media influencer marketing research (Koay et al., 2023, 2024; Tanwar et al., 2022). Simultaneously, this study transitions from the widely accepted emphasis on planned purchases to a focus on online impulse buying intentions, offering a more comprehensive view of the consumer decision-making process in the digital era (Shamim et al., 2024). Central to this study’s contributions is the interposition of wishful identification – a deep-seated aspirational construct – as a moderator, reshaping the theoretical underpinnings by introducing emotive currents propelling consumers towards impulsive actions. From a pragmatic standpoint, brands and social media influencers are armed with insights that promise enhanced resonance with target audiences, guiding them towards refined partnerships, tailored content strategies and amplified returns. More importantly, this study serves as a linchpin, laying the foundation for ensuing scholarly endeavours, inviting deeper dives into the complexities this study has unearthed and prompting exploration, particularly around the novel concept of wishful identification as well as the intersection of congruence, influencer marketing and impulse buying.

2. Literature review

2.1 Conceptual foundation: influencer marketing and the transition from planned to impulse buying

Extensive research on influencer marketing has explored the factors that shape consumers’ motivations to embrace brands endorsed by social media influencers (Joshi et al., 2024), including influencers’ attributes (Dhun and Dangi, 2023), personal disclosure (Koay et al., 2023), parasocial dynamics (Nadroo et al., 2024) and transparency about sponsorships (Xie and Feng, 2023). Yet, the extant body of work has predominantly focused on delineating the contours of consumers’ planned purchases (Aw and Chuah, 2021; Gani et al., 2023; Hsieh et al., 2023; Masuda et al., 2022), overlooking a critical aspect of consumer behaviour: the fact that a considerable segment of customers makes purchase decisions based on spontaneous emotional responses, without any prior planning or intent (Koay et al., 2021; Szymkowiak et al., 2021).

The distinction between planned purchases and impulse buying is crucial: while planned purchases are rooted in a thoughtful, premeditated process, impulse buying is characterised by its spontaneous nature, driven by immediate emotional responses and unanticipated desires (Aragoncillo and Orus, 2018; Iyer et al., 2020). This oversight presents a significant gap, particularly in understanding how influencer marketing might impact the less-explored impulsive dimension of online buying behaviour. Addressing this gap not only answers the call by recent scholars to advance the current discourse on influencer marketing (Koay et al., 2023) and to enrich theoretical understanding of online consumer behaviour (Lim et al., 2023) but also offers practical insights for crafting more effective engagement strategies (Lim et al., 2022) via social media influencers (Joshi et al., 2024), thereby expanding the scope of the product and brand management literature (Donthu et al., 2022).

2.2 Theoretical foundation: self-congruence theory and the transition to multiple congruences

The self-congruency theory suggests that consumers tend to be drawn to and buy products from brands that mirror their self-concept (Sirgy, 1982, 1985), indicating that a brand’s resonance with their self-perception makes it more appealing. Building on this premise, consumers have a natural inclination to favour products that they see as reflecting their own identities (Escalas and Bettman, 2005). Self-congruence encompasses two dimensions, namely, actual and ideal (Zogaj et al., 2021). When an individual compares someone else’s self-concept with their current personality (i.e. their actual self-concept), the outcome is termed actual self-congruence. Conversely, if the comparison involves someone else’s self-concept and the individual’s desired self-image (i.e. their ideal self-concept), the result is referred to as ideal self-congruence (Zogaj et al., 2021).

The influence of self-congruence on behaviour can be explained through two primary motives. Firstly, the need for self-consistency drives consumers to buy products aligning with their actual self-concept (Liberman et al., 1999). This motivation stems from the desire for self-verification to affirm personal values and mitigate the perceived risk associated with changes. Secondly, the need for self-enhancement propels consumers to consume products that resonate with their ideal self-concept (Zogaj et al., 2021). Empirical research provides evidence for the idea that consumers tend to develop favourable opinions of brands, products, or services that align with their self-concept (e.g. Chauhan et al., 2021; Lee et al., 2020; Wallace et al., 2020). This self-congruence triggers a cognitive alignment with one’s identity, thereby enhancing the attractiveness of engaging shopping experiences and fostering a propensity for making online impulse purchases.

The emergence of social media influencers has sparked the utilisation of the self-congruency theory in influencer marketing research, drawing the attention of numerous scholars (Shan et al., 2020; Tseng and Wang, 2023). Social media influencers are strategically shaping their public image to align with their followers’ values, aiming to establish trust – a pivotal asset that significantly aids influencers in persuading their audience to engage with endorsed products (Bastrygina et al., 2024). Consumers adopt the values embodied by social media influencers and extend these principles from brands and products to build, sustain and elevate their self-concept. Moreover, consumers tend to follow social media influencers who display comparable personality traits, a lifestyle congruent with their own, or shared preferences. These influencers are perceived by their audience as reference groups, holding significant cultural importance and recognised for their ability to influence consumer values and behaviours (Iqani, 2019). Existing studies have found that consumer–influencer congruence significantly affects consumer attitudes (Shan et al., 2020), brand and content engagement (Tafheem et al., 2022; Shan et al., 2020), desire to mimic (Xiao et al., 2021), parasocial identification (Shan et al., 2020) and purchase intentions (Shan et al., 2020). However, a critical gap persists in these studies: their focus narrows on consumer–influencer congruence, sidelining other congruence dimensions that might significantly impact consumer decisions.

Recognising the gap, Belanche et al. (2021) broaden the perspective by delineating three critical congruence dimensions: consumer–influencer, consumer–product and influencer–product congruences. Yet, despite the developmental work of Koay et al. (2023), research remains sparse on how these congruence dimensions collectively influence consumer behaviours, particularly in terms of online impulse buying intentions – a domain where existing literature predominantly orbits around planned purchasing behaviours (Liang et al., 2022; Masuda et al., 2022; Shan et al., 2020). The present study bridges the latest gap by examining the interplay of all three congruence dimensions within influencer marketing and introduces wishful identification as a moderating force in this dynamic. Rooted in social cognitive theory (Bandura, 1986), wishful identification reflects the consumer’s aspiration to mirror the admired traits of their favoured social media influencer. This study posits that while significant congruences may set the stage, it is the intensity of wishful identification that catalyses the leap from admiration to action – transforming high congruence into impulsive purchases.

Our investigation therefore offers substantial contributions to the influencer marketing discourse. It not only explores the effects of multiple congruences on online impulse buying intentions but also responds to recent calls for a deeper understanding of congruence’s role in influencer marketing (Koay et al., 2023; Tanwar et al., 2022). The insights gleaned provide practical guidance for brand managers in selecting social media influencers who not only align with their brand’s identity but also resonate on a deeper, aspirational level with their target audience. More importantly, by strategically and rigorously examining wishful identification as a moderating factor, this study equips brands and social media influencers with strategic insights for crafting compelling collaborations, enhancing content engagement and ultimately, driving higher returns on investment.

2.3 Hypotheses development: congruence, wishful identification and online impulse buying intentions

2.3.1 Congruence between influencers, consumers and products

Consumer–influencer congruence pertains to the extent to which the persona of the social media influencer aligns with that of the consumer (Belanche et al., 2021). Consumers are more likely to perceive a social media influencer as persuasive and impactful when they sense a similarity between themselves and the influencer. In line with the findings of Aw and Chuah (2021), it was reported that individuals who experience significant self-discrepancy show a higher tendency to form one-sided relationships with appealing and esteemed influencers. This inclination arises from a motivation to bridge the gap in self-image. Consumers are more prone to embracing a social media influencer's endorsements and imitating them when they perceive a notable degree of resemblance with said influencer (Xiao et al., 2021). Hence, it is argued that high levels of consumer–influencer congruence lead to online impulse buying intentions:

H1.

Consumer–influencer congruence has a significant positive influence on online impulse buying intentions.

Consumer–product congruence denotes the extent to which the image of the consumer aligns with the image of the product (Belanche et al., 2021). Consumers might develop a liking for a social media influencer because they share similar characteristics, but this does not necessarily translate into purchasing the influencer-endorsed products (Koay et al., 2023). In the modern landscape, many social media influencers inundate their followers with excessive sponsored content primarily for monetary gain (Cheah et al., 2024). Consequently, consumers will only opt to acquire products recommended by the social media influencer if the product’s image resonates with their own preferences (Bastrygina et al., 2024). Belanche et al. (2021) demonstrated that high levels of consumer–product congruence as a key factor in cultivating favourable opinions regarding the product, along with heightened intentions to buy and endorse it. Hence, it is postulated that high levels of consumer–product congruence lead to online impulse buying intentions:

H2.

Consumer–product congruence has a significant positive influence on online impulse buying intentions.

Influencer–product congruence signifies the extent to which the persona of the social media influencer aligns with the image of the endorsed product (Belanche et al., 2021). As previously noted, numerous social media influencers are primarily motivated by financial incentives (Cheah et al., 2024), causing them to endorse brands or products that might not match their personal self-image. This can negatively impact the genuineness of the promoted content, ultimately failing to capture consumers’ attention (Leung et al., 2022). The alignment between a celebrity and a brand influences both attitudes towards the celebrity and the endorsed product, consequently influencing purchasing intentions (Min et al., 2019). Accordingly, it is posited that high levels of influencer–product congruence can result in online impulse buying intentions:

H3.

Influencer–product congruence has a significant positive influence on online impulse buying intentions.

2.3.2 Wishful identification as a moderator

Congruence between influencers, consumers and products is indeed important when it comes to predicting consumers’ online impulse buying intentions. This study further proposes wishful identification as a moderator in the relationships between consumer–influencer congruence, consumer–product congruence and influencer–product congruence with online impulse buying intentions. In brief, wishful identification indicates the extent to which a consumer desires to be like the social media influencer. According to social cognitive theory (Bandura, 1986), people often adjust their behaviours to imitate someone else, a phenomenon known as psychological matching. When an individual is seen as a role model, there is a tendency to engage in wishful identification with that person, as emulating such a role model could result in recognition and approval within one’s social circle (Tian et al., 2023). Consumers’ desire to mimic also plays a significant role in their purchase decisions (Ki and Kim, 2019). Based on this logic, it is proposed that congruence between influencers, consumers and products may be important to predict consumers’ online impulse buying intentions. However, it may not be sufficient in the absence of wishful identification. That is, only when consumers are motivated to be like the social media influencer, they will make an online impulse purchase for products recommended by the social media influencer. In other words, the influence of congruence between influencers, consumers and products on online impulse buying intentions will be stronger when wishful identification is high. Accordingly, the following hypotheses are proposed:

H4.

Wishful identification strengthens the positive relationship between consumer–influencer congruence and online impulse buying intentions.

H5.

Wishful identification strengthens the positive relationship between consumer–product congruence and online impulse buying intentions.

H6.

Wishful identification strengthens the positive relationship between influencer–product congruence and online impulse buying intentions.

The conceptual model illustrating these hypotheses can be found in Figure 1.

3. Methodology

3.1 Instrumentation

This study used an online survey to gather data, using Google Forms to create a structured questionnaire. The construction of this questionnaire was guided by the principle of empirical rigour, drawing upon established scales from the scholarly literature to ensure the reliability and validity of the measurements.

The assessment of consumer–influencer congruence was based on a three-item scale, whereas consumer–product and influencer–product congruences were each evaluated using four-item scales, all of which were derived from the work of Belanche et al. (2021). The dimension of wishful identification was measured through a four-item scale developed by Hu et al. (2020), a tool that has gained empirical validation through its application and subsequent confirmation of reliability and validity by Cheung et al. (2022a). The phenomenon of online impulse buying intentions was quantified using a three-item scale sourced from Koay et al. (2021). Each item within the questionnaire was anchored to a seven-point Likert scale, ranging from “1 = strongly disagree” to “7 = strongly agree”.

3.2 Sampling

The survey was disseminated through various social media channels, notably Facebook and Instagram, leveraging feeds and shares in social groups in Malaysia. This approach aligns with methodologies adopted in prior studies (e.g. Cheung et al., 2022a, 2022b), ensuring a wide reach and diverse participant engagement.

Given that probability sampling is not possible for the study’s target respondents (e.g. absence of a population list), the purposive sampling method is used to select respondents who best fit the target population. More specifically, participant eligibility was determined based on several key purposive criteria to ensure the relevance and accuracy of the responses. Eligible participants were required to have an active Instagram account, given the platform’s prominence in influencer marketing strategies (Barnhart, 2023; Bastrygina et al., 2024). In addition, they needed to follow at least one social media influencer on Instagram, with the term “social media influencer” clearly defined to standardise understanding among respondents. Participants were asked to name an influencer they follow, using this information to contextualise subsequent survey questions. Responses lacking a valid influencer name – verified through Instagram – or listing multiple names were excluded to maintain data integrity and focus.

To ensure the study’s statistical robustness, a power analysis was conducted using G Power software, setting parameters to an effect size of 0.15, an alpha level of 0.05, seven predictors (i.e. three direct predictors, three interaction terms and one moderator) and a desired power of 80%. This analysis determined that a minimum sample size of 107 participants was required. This rigorous selection process and methodological approach were designed to capture informed and relevant insights from a well-defined respondent group, thereby enhancing the reliability and applicability of the research findings.

The survey garnered 232 valid responses, which were analysed to understand the profile of the participants. The gender distribution showed a higher participation rate among females, with 141 respondents (60.8%), compared to 91 male respondents (39.2%). In terms of ethnicity, the sample was predominantly Malay, accounting for 121 participants (52.2%), followed by Chinese with 62 participants (26.7%), Indians with 19 participants (8.2%) and individuals from other ethnic backgrounds comprising 30 respondents (12.9%). The educational attainment of the participants revealed a significant leaning towards higher education, with the majority holding bachelor’s degrees (77.2%). This was complemented by a smaller segment of the sample with postgraduate qualifications, including master’s or doctoral degrees (9.9%) and others with diplomas (7.8%). Participants with pre-university level education constituted 3.0% of the sample, whereas those with high school qualifications represented a minimal 2.2%. In addition, the study also examined the preferred devices for internet access among participants. The findings indicate a predominant use of smartphones, with 84.1% of respondents identifying this as their primary device for accessing the internet. This is followed by a smaller proportion using laptop computers (11.6%), desktop computers (3.4%) and tablets (0.9%). This data underscores the central role of mobile technology in the digital habits of the survey participants, reflecting broader trends in internet usage. The detailed breakdown of internet access devices used by the participants enriches the contextual understanding of their online engagement patterns, which is crucial for interpreting their interactions with social media influencers. This information is integrated into the comprehensive analysis of respondent characteristics, alongside demographic and educational information, as presented in Table 1.

4. Results

4.1 Common method bias

Given the potential vulnerabilities inherent in a cross-sectional research design to common method bias, this study executed both procedural and statistical countermeasures to attenuate its impact (Kock et al., 2021).

Procedurally, a cover page was attached to the initial questionnaire page, addressing important details. First, respondents were assured that all information provided would remain confidential and anonymous. Second, it was emphasised that there were no right or wrong answers, encouraging genuine responses. Third, an estimated completion time was provided, ensuring participants had ample time to complete the survey.

Statistically, a Harman’s single-factor test was conducted. The results indicated that the first factor accounted for 47.924% of the total variance, which was below the recommended threshold of 50% (Harman, 1960). This outcome suggested that common method bias was unlikely to be a dominant concern in this present study. In addition, this study performed the full collinearity test, and all variance inflation factor values were below 3.3 (Kock, 2015). This finding provided further confirmation that common method bias was not a significant threat in the present investigation.

4.2 Measurement model

As per the guidelines by Hair et al. (2019), the measurement model was evaluated based on three key criteria: reliability, convergent validity and discriminant validity. Reliability examines the internal consistency of the measures and can be assessed through Cronbach’s alpha and composite reliability. Table 2 demonstrates that all Cronbach’s alpha and composite reliability values exceeded 0.7, indicating a satisfactory level of reliability. To establish convergent validity, it is essential that the items within a specific construct converge to accurately represent the underlying concept. Table 2 reveals that all the factor loadings were greater than the recommended threshold of 0.7, supporting the construct’s convergent validity. In addition, all average variance extracted values (AVEs) were found to be higher than 0.5, providing further evidence that convergent validity was adequately demonstrated and did not pose a concern. Next, to ensure that all the constructs under investigation were conceptually and empirically distinct from each other, the heterotrait–monotrait (HTMT) ratio of correlations criterion was used. Table 3 reveals that all the HTMT values were below 0.85 (Henseler et al., 2015), indicating the absence of any discriminant validity concerns.

4.3 Structural model

The structural model results can be seen in Table 4. It was found that consumer–influencer congruence and influencer–product congruence do not affect online impulse buying intentions; thus, H1 and H3 were not supported. However, it was reported that consumer–product congruence positively and significantly affects online impulse buying intentions, supporting H2. We next assess the moderating effects by computing the interaction terms. It was found that wishful identification does not moderate the relationships between consumer–product congruence and online impulse buying intentions and influencer–product congruence and online impulse buying intentions. However, it was reported that wishful identification moderates the relationship between consumer–influencer congruence and online impulse buying intentions, as seen in Figure 2. As a result, only H4 found support, whereas H5 and H6 did not receive support.

Proceeding beyond testing the significance of path coefficients, this study also determined the performance of the model in predicting out-of-sample data. For this, it used the PLSpredict algorithm (Shmueli et al., 2019), the details of which are captured in Table 5. The Q² value in PLSpredict, a yardstick to juxtapose the prediction errors of the partial least square (PLS)-path model against simple mean predictions, exhibited a commendable score. Specifically, the Q² predict value for online impulse buying intentions was 0.282. This value, greater than the zero threshold, is an indication of the model’s significant predictive relevance. Furthermore, a side-by-side comparison of root mean squared error (RMSE) and mean absolute error (MAE) values for all the indicators between the PLS-path model and its linear regression counterpart revealed the former’s superiority. The PLS-path model consistently registered smaller values for the majority of indicators, underlining its moderate levels of predictive relevance.

5. Discussion

5.1 Theoretical implications

The study found that consumer-influencer congruence does not influence consumers’ online impulse buying intentions, implying that despite high levels of consumer–influencer congruence, the urge to buy products recommended by social media influencers remains subdued. This insignificance could be attributed to the inherent nature of impulse purchases and the peripheral role of influencer alignment in such spontaneous transactions. Impulse buying, driven by immediate emotional responses and the intrinsic appeal of a product (Liao et al., 2009), relies little on the cultivated relationship or values shared between the consumer and the influencer. This rapid, instinctual decision-making process prioritises the emotional and visual allure of the product itself (Liao et al., 2016), sidelining the deeper, reflective considerations associated with influencer congruence. Given the swift nature of impulse buying, there is a scant opportunity for consumers to meaningfully connect the influencer’s endorsement with their personal decision to purchase on the spur of the moment. This dynamic underscores a fundamental aspect of consumer psychology: in the fleeting moments of impulse buying, the direct, tangible appeal of the product could overshadow the more abstract and extended influence of consumer-influencer congruence.

Next, it was found that consumer–product congruence positively and significantly affects consumers’ online impulse buying intentions, suggesting that consumers are more likely to impulsively purchase products endorsed by influencers if the image of the products matches the image of the consumers. This finding could also potentially explain the insignificant influence of consumer–influencer congruence on online impulse buying intentions. In the contemporary era, consumers are increasingly discerning in their reception of content from social media influencers (Bastrygina et al., 2024; Rao Hill and Qesja, 2023). Consumers now tend to display a greater inclination towards impulsive buying only when the products endorsed by social media influencers resonate closely with their own self-image. The key priority lies in consumers purchasing a product capable of minimising the gap between their present self-image and their desired ideal self-image. In today’s digital age, where personal branding and self-presentation on social platforms play a pivotal role, products that echo a consumer’s self-image not only fulfil a functional or emotional need but also aid in crafting and projecting their desired online persona (Lim, 2016; Joshi et al., 2024).

Notably, high levels of influencer-product congruence do not seem to play a significant role in influencing consumers to make impulsive purchases online. The lack of significant influence from influencer–product congruence on online impulsive buying contrasts with the notable impact of consumer–product congruence witnessed in this study. This discrepancy indicates that the impetus for impulse buying is more closely tied to the consumer’s personal resonance with the product rather than the alignment between the influencer and the product. This insight is critical for three major reasons.

First, it suggests that impulsive purchasing decisions are primarily consumer-centric, driven by immediate personal identification with the product, rather than influencer-centric. This consumer-driven nature of impulse buying emphasises the intrinsic appeal or value of the product itself as the primary motivator, overshadowing the influencer’s endorsement.

Second, it shows that impulse purchases contrast against planned purchases, where consumers have the luxury of time to engage with and absorb content from influencers, potentially developing parasocial relationships that can influence purchasing decisions over time (Koay et al., 2023). This engagement allows consumers to immerse themselves in the influencer’s narrative and vicariously experience the products or services being endorsed (Nadroo et al., 2024), which might not be as prevalent in the quick, spontaneous context of online impulse buying. The immediacy of impulse purchases may not afford consumers the opportunity to deeply process influencer–product alignments, rendering these congruences less pivotal in the decision-making process.

Third, it speaks to the prevailing inundation of sponsored content targeting social media influencers, resulting in a situation where numerous endorsed products may not align with consumers’ actual needs (Bastrygina et al., 2024). The omnipresence of influencer endorsements can raise consumer scepticism, diluting the impact of any single influencer–product match on impulsive buying decisions. This scepticism could stem from perceived inauthenticity or over-commercialisation, where consumers become wary of the genuineness of the endorsements.

Finally, building on the understanding of consumer–influencer congruence’s limited role in online impulse buying intentions, this study further illuminates the critical function of wishful identification as a boundary condition that interplays with consumer–influencer congruence in this context. While consumer–product and influencer–product congruences do not significantly interact with online impulse buying intentions, wishful identification emerges as a pivotal factor that can amplify the effect of consumer–influencer congruence on such purchases. This suggests that mere alignment with an influencer’s persona or values is insufficient to trigger impulsive buying behaviours. Instead, it is the consumer’s deep-seated desire to emulate the influencer, a longing that transcends mere congruence, that can potentiate the likelihood of an impulse purchase. This distinction underscores the complexity of the consumer-influencer relationship, highlighting that the most powerful impetus for impulse buying arises not from a general alignment with the influencer’s image but from an intense, aspirational connection that stirs the consumer’s immediate buying impulses. This insight delineates a more granular understanding of influencer marketing, where the emotional and aspirational dimensions of consumer engagement hold the keys to unlocking impulsive buying behaviours.

To this end, this study marks a pivotal theoretical advancement in influencer marketing by shifting the academic lens from the well-trodden path of planned purchasing behaviours to the less-explored terrain of online impulse buying intentions. In doing so, it challenges the conventional focus on consumer-influencer congruence as a primary driver of purchasing decisions, revealing that congruence between the two plays a minimal role in spontaneous buying actions; rather, it is the consumer–product congruence that plays a critical role in stimulating impulse purchases. This revelation underscores the importance of immediate product appeal and emotional resonance in impulse buying, diverging from the assumption that influencer endorsements are universally influential across different buying contexts.

Nevertheless, by integrating wishful identification into the model as a significant boundary condition, this study enriches the theoretical understanding of the conditions under which consumer–influencer congruence might influence impulse buying. It elucidates that the impact of congruence between consumers and influencers is not straightforward but is contingent upon the depth of the consumer’s aspirational connection with the influencer. This insight contributes to a better understanding of consumer behaviour, suggesting that the psychological processes driving impulse purchases are distinct from those influencing planned purchases. The exploration of these dynamics not only broadens the theoretical scope of influencer marketing studies but also invites future research to dive deeper into the psychological and emotional underpinnings of impulse buying in the digital age. Therefore, this study, by highlighting the critical role of product-centric factors and aspirational consumer–influencer relationships in impulse buying scenarios, sets a new agenda for scholarly inquiry, urging a re-evaluation of existing paradigms and the development of theories that capture the complexity of consumer decision-making in influencer marketing.

5.2 Managerial implications

To optimise the impact of influencer marketing on online impulse buying intentions, brands and social media influencers can pursue two strategic pathways: leveraging consumer–product congruence and harnessing the power of wishful identification through consumer–influencer congruence. Understanding these distinct yet complementary routes can guide brands and social media influencers in crafting more effective influencer marketing strategies.

To maximise the effectiveness of influencer marketing in stimulating online impulse buying intentions, it is imperative for both brands and social media influencers to prioritise and cultivate consumer–product congruence. This strategic alignment hinges on selecting influencers whose followers’ preferences, lifestyles and values mirror those of the brand’s target audience, ensuring that the endorsed products resonate deeply and authentically with potential consumers (Bastrygina et al., 2024). For brands, this entails a thorough vetting process, moving beyond superficial metrics like follower counts to analyse the content’s relevance, the consistency of product alignment in influencers’ past posts and the genuine engagement of their audience. Influencers, on their part, must maintain authenticity and select partnerships that align with their own brand and audience’s expectations, preserving the trust and connection that are crucial for influence. This symbiotic relationship between brands and influencers enhances the perceived relevance and appeal of the products to the audience, significantly increasing the likelihood of impulse purchases. Fostering a genuine connection that reflects shared values and aesthetic preferences, both parties can create a more compelling and persuasive narrative that naturally encourages consumers to make spontaneous purchasing decisions, leveraging the instantaneous and emotionally charged nature of impulse buying, which is especially pronounced in digital marketplaces (Shamim et al., 2024).

Harnessing the power of wishful identification to enhance consumer–influencer congruence is another strategic imperative that necessitates a collaborative effort between brands and social media influencers. This approach focuses on forging a deeper, more aspirational connection between consumers and influencers, where the latter embodies the lifestyle, values or image that consumers aspire to achieve. Brands must carefully select influencers who not only resonate with their product ethos but also possess the aspirational qualities that appeal to the brand’s target demographic. This selection process involves understanding the influencer’s content, the authenticity of their engagement with their audience and their ability to inspire and motivate their followers. Influencers, in turn, play a pivotal role by crafting and sharing content that not only showcases the brand’s products but also aligns with the narrative of their personal brand and the aspirational desires of their audience. This content should transcend mere product promotion, weaving stories and experiences that reflect the influencer’s authentic lifestyle and values, thereby fostering a deeper emotional and aspirational connection with the audience. Such storytelling and narrative-building should be strategic (Júnior et al., 2023), with a focus on relatability and the capacity to inspire wishful identification among followers.

For both brands and influencers, the goal is to create a marketing synergy that not only highlights the product but also embeds it within a lifestyle or set of values that the audience aspires to. This strategy leverages the emotional and aspirational dimensions of consumer engagement (Lim et al., 2022), enhancing the influencer’s impact on online impulse buying intentions by making the endorsed products not just desirable but integral to achieving the aspirational lifestyle presented. Through this collaborative and strategic approach, brands and influencers can significantly magnify the influence of consumer–influencer congruence on impulse purchasing decisions, tapping into the potent combination of aspiration, identification and spontaneous consumer action.

In implementing strategies to enhance online impulse buying intentions through influencer marketing, it is paramount for both brands and social media influencers to navigate these practices with a strong ethical compass. While fostering consumer–product congruence and cultivating wishful identification can significantly impact purchasing behaviours, it is crucial to balance these strategies with a commitment to authenticity and transparency while safeguarding consumer well-being. Brands and social media influencers should ensure that their marketing efforts, while persuasive, do not exploit consumer vulnerabilities or encourage excessive spending. Ethical influencer marketing should prioritise clear disclosure of sponsored content, genuine endorsements and respect for the consumer’s autonomy and decision-making process. Adhering to these ethical standards, brands and social media influencers can build trust and maintain long-term relationships with their audience, ensuring that their influence remains positive and sustainable in the evolving landscape of digital, and increasingly real-time (or live), commerce (Luo et al., 2024).

5.3 Limitations and future research

Although this study represents a significant step forward in understanding the impacts of congruence and wishful identification on consumers’ online impulse buying intentions, it is essential to acknowledge several limitations.

Firstly, the data collected in this study were exclusively from one country (Malaysia), which might restrict the generalisability of this study’s findings to a more diverse population.

Secondly, this study predominantly focused on influencers from the Instagram platform. To enhance the robustness of this study’s conclusions, further investigations should replicate this study’s model using a broader and more varied sample of influencers, encompassing platforms like Facebook, OnlyFans, Snapchat or TikTok. This broader scope can offer a holistic understanding of the roles of congruence and wishful identification in influencing consumers’ online impulse buying intentions across various social media platforms.

Thirdly, the collection of cross-sectional data for this study involved distributing the online survey link across social media platforms. This data collection method provides convenience and efficiency, but it does limit the capability to establish causal relationships. As a result, future research endeavours might gain advantages by adopting longitudinal data collection with a controlled and randomised approach. Such an approach would enhance the robustness of the relationships investigated in this study.

Fourthly, participants in this study were asked to furnish the name of a social media influencer (in general) to be used as a point of reference when completing the questionnaire. It is important to note that social media influencers can be categorised into various types, such as megainfluencers, macroinfluencers and microinfluencers. In future research, it is advisable to consider this factor when replicating the same study.

Fifthly, while this study uses multidimensional scales for all constructs, it is acknowledged that some constructs, specifically consumer–influencer congruence and online impulse buying intentions, are measured with a relatively low number of indicators. This limitation might not fully capture the multifaceted nature of these constructs. Recognising this as an opportunity, future research is encouraged to engage in scale development studies aimed at enhancing the comprehensiveness and sensitivity of these measures. In developing and validating more robust scales with a greater number of indicators, subsequent studies could offer deeper insights into the peculiarities of consumer–influencer dynamics and the process of online impulse buying intentions, thereby contributing to a more precise and detailed understanding of these important phenomena in the context of social media and influencer marketing.

Finally, although this study offers a fresh outlook by shifting the focus from planned purchases to impulsive buying, the measures employed remain intention-driven, which might not fully capture the spontaneous nature of impulse purchases. Future research could benefit from incorporating more direct or behavioural measures of impulse buying, such as real-time tracking of purchasing behaviours or experimental designs that simulate online shopping environments. This methodological enhancement would provide a more accurate depiction of impulsive buying behaviours and offer deeper insights into the immediate effects of influencer endorsements and product congruence on consumer actions.

Figures

Figure 1

The congruence-wishful identification model of online impulse buying intentions

Figure 2

Moderating effect of wishful identification on the relationship between consumer–influencer congruence and online impulse buying intentions

Table 1

Respondent profile

Gender
Female	60.8%
Male	39.2%
Ethnicity
Chinese	26.7%
Indian	8.2%
Malay	52.2%
Others	12.9%
Education
High school	2.2%
Pre-university	3.0%
Diploma	7.8%
Bachelor’s degree	77.2%
Master’s or doctoral degree	9.9%
Most-used device for internet access
Desktop computer	3.4%
Laptop computer	11.6%
Smartphone	84.1%
Tablet	0.9%

Source: Authors’ own compilation

Table 2

Measurement model

Construct	Item	Factor loading	Average variance extracted	Cronbach’s alpha	Composite reliability
Consumer–influencer congruence	CCI1. (SMI’s name) is congruent with my values	0.856	0.808	0.881	0.927
	CCI2. (SMI’s name) matches my personality	0.911
	CCI3. I feel identified with (SMI’s name)	0.928
Consumer–product congruence	CCP1. The products that (SMI’s name) always advertises match my style	0.947	0.900	0.963	0.973
	CCP2. The compatibility between the products that (SMI’s name) always advertises and me is high	0.955
	CCP3. The alignment between the products that (SMI’s name) always advertises and me is high	0.948
	CCP4. The products that (SMI’s name) always advertises fit my style	0.946
Influencer–product congruence	CIP1. (SMI’s name) has a good match with the products that he or she always advertises	0.912	0.869	0.950	0.964
	CIP2. The compatibility between (SMI’s name) and the products that he or she always advertises is high	0.945
	CIP3. The alignment between (SMI’s name) and the products that he or she always advertises is high	0.945
	CIP4. (SMI’s name) and the products that he or she always advertises have a high fit	0.928
Online impulse buying intentions	OIBI1. As I read the product recommendations in this (SMI’s name) account, I had the urge to purchase the advertised products or services other than in addition to my specific shopping goal	0.936	0.890	0.938	0.960
	OIBI2. As I read the product recommendations in this (SMI’s name) account, I had a desire to buy the advertised products or services that did not pertain to my specific shopping goal	0.956
	OIBI3. As I read the product recommendations in this (SMI’s name) account, I had the inclination to purchase the advertised products or services outside of my specific shopping goal	0.938
Wishful identification	WI1. (SMI’s name) is the sort of person I want to be like myself	0.876	0.804	0.919	0.942
	WI2. Sometimes I wish I could be more like (SMI’s name)	0.890
	WI3. (SMI’s name) is someone I would like to emulate	0.935
	WI4. I’d like to do the kinds of things (SMI’s name) does	0.883

Source: Authors’ own compilation

Table 3

Heterotrait–monotrait (HTMT) ratio of correlations

Construct	Consumer–influencer congruence	Consumer–product congruence	Influencer–product congruence	Online impulse buying intentions	Wishful identification
Consumer–influencer congruence
Consumer–product congruence	0.522
Influencer–product congruence	0.438	0.597
Online impulse buying intentions	0.430	0.565	0.408
Wishful identification	0.589	0.432	0.392	0.351

Source: Authors’ own compilation

Table 4

Structural model

Hypothesised relationship	Beta	Standard error	t-value	p-value	BCCI 95%		Outcome
Direct effects
H1. Consumer–influencer congruence → Online impulse buying intentions	0.120	0.126	1.515	0.065	−0.016	0.245	Not supported
H2. Consumer–product congruence → Online impulse buying intentions	0.403	0.402	4.932	0.000	0.269	0.536	Supported
H3. Influencer–product congruence → Online impulse buying intentions	0.087	0.085	1.183	0.118	−0.033	0.209	Not supported
Moderating effects
H4. Wishful identification × Consumer–influencer congruence → Online impulse buying intentions	0.110	0.098	1.697	0.045	−0.002	0.202	Supported
H5. Wishful identification × Consumer–product congruence → Online impulse buying intentions	−0.109	−0.098	1.367	0.086	−0.235	0.018	Not supported
H6. Wishful identification × Influencer–product congruence → Online impulse buying intentions	0.029	0.029	0.540	0.295	−0.059	0.115	Not supported

Note:

BCCI = bias-corrected bootstrap confidence interval

Source: Authors’ own compilation

Table 5

PLSpredict indicator prediction summary

Item	Q² predict	PLS		LM		PLS-LM		Decision of
		RMSE	MAE	RMSE	MAE	RMSE	MAE	predictive relevance
OIBI1	0.269	1.388	1.081	1.419	1.115	−0.031	−0.033	Moderate
OIBI2	0.230	1.437	1.154	1.442	1.153	−0.005	0.001
OIBI3	0.250	1.343	1.040	1.348	1.074	−0.005	−0.034

Notes:

OIBI = online impulse buying intentions; Q² = predictive relevance; PLS = partial least squares; LM = linear model; RMSE = root mean squared error; MAE = mean absolute error

Source: Authors’ own compilation