Does Brand Attitude Complement Influencer Credibility in Shaping Purchase Intention of Indian GenZ Consumers?

1. Introduction

The social media landscape has undergone radical changes over the past few years. It has become an important part of people’s everyday routines and significantly influences cultural aspects of society. It has revolutionized consumer perspectives, purchasing habits, and behaviors (Dwivedi et al., 2021). In today’s technology-driven world, social networking platforms have become an avenue where brands can extend their marketing campaigns to a wider range of consumers. Social media has transformed the way businesses connect with their audience, and India is no exception to this digital revolution social media platforms such as Facebook, YouTube, Instagram, and Twitter have become the grounds for brands to engage with customers, build relationships, and drive sales. India has embraced the Internet, and its digital population has grown rapidly over the past decade, reaching 600 million active Internet users (www.statista.com/, n.d.). Access to social media has also enhanced the time spent by users on social media daily. A report published by The Indian Institute of Management Ahmedabad on “New Age Digital Media Consumption: A survey of Social Media, OTT Content Online Gaming” reported that Indians, on average, spent 194 minutes daily on social media platforms (The Esya Centre and IIM Ahmedabad, 2023) and most of them were in the age group of 18 to 34 years of age (GWI, 2023). This forms a strong foothold for brands to emphasize digital marketing strategies to this specific age group. Amidst this emerging trend is the growth of a concept called marketing influencers. Marketing Influencers are defined as “people who have the power to affect the purchase decisions of others due to their real or perceived authority, knowledge, position, or relationship” (Mavrck, 2014). A further classification of influencers based on the number of followers they have helps different businesses choose which influencers to partner with. While macro-influencers can claim millions of followers, micro-influencers usually have less than 100,000. Micro-influencers are everyday people who post meaningful content with a significant impact on social media sites such as Facebook, Instagram, and YouTube. Social media organizations and celebrities are examples of macro-influencers. In the present digital landscape, consumers seek opinions from their peers (other consumers) and marketing influencers to make informed purchase decisions. Thus, influencers play a major role in shaping consumer purchase decisions and brand choices (Anjali Chopra and Jaju, 2020).

Influencer marketing has been used more recently, but there hasn’t been a single scholarly definition of it—especially when it comes to India (Johansen and Guldvik, n.d.). Based on the number of followers they have, around 4 million influencers in India are divided into four categories: elite, mega, macro, and micro as of June 2023 (Katya Naydu, 2023). About 118 million Indians have purchased goods or services that influencers have promoted, according to Roshan Behera (2023). The authors decided to look into the influencer marketing scene in India, specifically from the perspective of Generation Z (those born between 1997 and 2012), given the growing importance of influencers in the country and the paucity of scholarly research on the subject. Further, on social media, Gen Z users are more likely to be drawn to content about fashion, travel, and movies. According to a demographic comparison, millennials follow 52% of Instagram influencers, whereas Gen Z members follow about 97.9% of them (Bandwagon Online, 2023). This highlights the importance of influencer marketing, especially when aimed at the Gen Z demographic in India. Although the influencers themselves have a charm factor, an important question is what makes their content truly appealing. The answer to this question is perhaps the relationship between the influencer’s credibility, the audience’s views towards the brand, and their attitude toward the content. This study aims to understand the connection between these factors and how the audiences’ attitudes mediate the influencers’ credibility and purchase intention. The objective is to analyze the influencer marketing sector in India and find insights into the characteristics of influencers that contribute to their credibility. Furthermore, study the mediating effect of the audiences’ attitude toward the brand on the relationship between influencer credibility and purchase intention. The proposed conceptual framework is presented in Figure 1.

The subsequent sections of the manuscript are structured as follows: the hypothesis development section presents literature related to the context of the present research endeavour and aids in conceptualizing the proposed conceptual model. The methodology section highlights the study setting, sampling procedure, and the research instrument development process. The results section presents the data analysis, followed by the discussion section and theoretical and managerial implications. The last section of the manuscript presents directions for future research and the limitations of the study.

2. Literature review & hypotheses development

2.7 Influencer credibility

Influencers on social media are essential for improving marketing campaigns in the digital era. Choosing influencers wisely about the target market can have a big impact on audience purchase intentions and increase brand recognition. Purchase intention, according to J. P. Trivedi (2018) and Shah and Pillai (2012), arises from consumers’ comprehension of the thinking behind the choices they make regarding brands (Ki et al., 2023). Claim that it illustrates a scenario in which consumers are likely to purchase a product in a given setting. By using influencers in their marketing campaigns, marketers can positively affect the brand by strengthening the image the influencers have established and enhancing product recognition. Customers are more likely to purchase the promoted products when influencers with a strong connection to the target market are used (Lim et al., 2017). This finding aligns with a study by Singh and Banerjee (2018). Which emphasizes the ability of influencers to attract clients and stimulate purchase intentions through effective communication with their audience. Hence, this research endeavor intends to explore the effect of influencer credibility on the purchase intention of the followers.

H8:

Influencer Credibility has a significant positive influence on the purchase intention of followers.

Figure 1. Proposed conceptual framework.

Source: Author’s own.

3. Methods

4. Results

To investigate the proposed correlations, we used maximum-likelihood estimation in structural equation modeling (SEM). According to Hair (2009), SEM was selected because of its capacity to evaluate the relationships between latent and observable variables directly.

The construct’s reliability and validity were established by assessing Cronbach’s alpha, rhoa, and composite reliability, as outlined in Table 1. The computed rhoa value surpassing the 0.7 cut-offs indicates (Hair et al., 2010) robust reliability. Composite reliability is adopted to examine the internal consistency of the constructs and all values are above the threshold limit (Werts et al., 1974). Cronbach alpha estimates reveal reliability of the all the indicators as all figures were above the threshold value of 0.7 (Ken Kwong-Kay Wong, 2013). Convergent validity was established using Average Variance Extracted (AVE). All constructs have an AVE above the threshold of 0.5 (Richard P. Bagozzi and Youjae Yi, 1988). Collinearity among the indicators was examined in the VIF estimates of the constructs. All the VIF values were less than 0.5 (Sarstedt et al., 2017) no collinearity among the constructs of the study. Similarly, the absence of collinearity among the constructs of the study was established where the VIF values of the inner model of all the exogenous constructs were less than 3.3 (Joseph F. Hair et al., 2017). This also ensures the absence of common method bias impacting the data (Kock, 2015). Evaluation of the Structure Model is presented in Figure 2. Indicating Discriminant validity was confirmed using the Fornell and Larcker methodology, as depicted in Table 2.

Figure 2. Structural Model.

Subsequently, the structural model was assessed by the bootstrapping technique and the hypothesis was tested. The structural wall was further evaluated with the help of the path coefficients ( Table 3). R² and Q² were obtained from the structural model. R² indicates that a model’s prediction ability should be more than 0.1 (Falk and Miller, 1992). Trust, Expertise, Attractiveness, and similarity explained 48.7 percent of the variance for Influencer credibility. The credibility of the influencer explained a 20.9 percent variance of Attitude towards Brand and both these constructs explained a 36.6 percent variance of the outcome construct Purchase Intention. Furthermore, Q², which assesses the model’s predictive usefulness, ought to be greater than 0. The efficiency of the model was confirmed in the current investigation when both R² and Q² values were above the designated thresholds, thus the model’s predictive relevance was justified.

The results revealed that two exogenous constructs, Expertise (β = 0.342, t = 7.007 p = 0.000) & Trust (β = 0.353, t = 6.549, p = 0.000) had a significant positive impact on the credibility of the influencer. However, Similarity (β = 0.123, t = 2.095, p = 0.036) partially influenced the influencer credibility. Hypothesis 5 (Attitude towards Brand on Purchase Intention) and Credibility of Influencer on Attitude towards Brand were supported revealing two dimensions. Firstly, Attitude towards the Video (β = 0.167, t = 2.771, p = 0.006) has a significant positive association with to Purchase Intention of the followers, and secondly, Credibility of the Influencer (β = 0.458, t = 9.063, p = 0.000) had a significant positive influence on the Followers Attitude towards the Brand. Attitude towards the Brand (β = 0.208, t = 3.697, p = 0.000) and Credibility of the Influencer (β = 0.370, t = 6.134, p = 0.000) had a significant positive impact on the Purchase intention of the follower. Thus, H7 and H8 were also supported.

4.2 Importance Performance Matrix Analysis (IPMA)

IPMA’s result is presented as bootstrapping with 5,000 subsamples, demonstrating that all requirements for applying the IPMA approach are met and that some path coefficients are statistically significant. IPMA clarifies the comparative importance and effectiveness of exogenous (Trust, Expertise, Similarity, Attractiveness, Attitude towards Brand, Attitude towards the video, Influencers Credibility) on the endogenous construct (Purchase Intention). Their significance and efficacy are shown by their aggregate impacts and index values. The impact on the endogenous variables is significant. The intrinsic potential of the latent variable scores is demonstrated through effectiveness ( Table 5, Figure 3).

Table 5. Important-Performance Matrix Analysis of Behavior Intention.

Latent construct	Importance (Total effect)	Performance (Index value)
Att towards Brand	0.208	57.862
Attractiveness	0.029	62.887
Attitude towards Video	0.167	62.067
Credibility	0.466	52.412
Experience	0.159	61.272
Similarity	0.057	53.226
Trust	0.164	49.631

Figure 3. Importance performance matrix.

5. Discussion

Influencer marketing has become a potent catalyst propelling brands’ social media investment in the ever-changing world of digital marketing. Influencers provide organizations with a means of accessing pre-existing communities and fostering genuine interactions with their target audiences. Influencers are frequently people with sizable and devoted online followings. Upholding the model proposed by Hovland et al. (1953) on Communication and persuasion, trust in the influencer significantly influences the credibility of the influencer. Similarity with the influencer and Expertise of the influencer is explored to have a significant role in determining the influencer’s Credibility. These findings are in line with the previously published literature on the construct of trust in the marketing influencer (Johnsson, 2023; Saima & Khan, 2020; Trivedi & Sama, 2020; Patmawati & Miswanto, 2022). Digital media platforms provide internet users with substantial control over the information they share, which fosters a climate even conducive to the spread of misleading information, such as fake news. Internet users now place more emphasis on original information and reliable sources, highlighting the significance of real and honest information sources in the digital sphere.

Further Naderer et al., (2021) documented that similarity with the influencer had a direct positive effect on the purchase intention of the promoted brand. Additionally, a qualitative study undertaken by Johnsson (2023). Among GenZ of Bangladesh, it was documented that most of the followers compared themselves with celebrity influencers and tried to imitate them. This is not justified in our research context as attractiveness did not significantly influence the credibility of the influencer. Another study undertaken by Trivedi (2018) revealed a higher efficacy of attractiveness the social media influencers. Although the findings contradict the research findings of Johnsson (2023) and Trivedi (2018), it is noteworthy to observe that these studies are undertaken in different contexts. Trivedi (2018) documented research in the context of fashion influencers. However, it is also documented by Masuda et al. (2022) that the strength of this association can vary depending on the age group of the followers and the product category under consideration. Younger consumers or those who highly value physical appearance might be more susceptible to attractiveness pull. Similarly, luxury or aspirational products can have a stronger effect.

Attitude towards the Video content is documented to have a significant direct positive influence on purchase intention by the followers, leading to acceptance of H5. This finding is also affirmed by Trivedi (2018) that attitude towards the brand endorsed plays a significant role in determining the consumers’ purchase intention. This finding was significantly endorsed in the fashion marketing landscape. This strongly affirms the Theory of Reasoned Action (Icek Ajzen, 1980).

Attitude towards the brand significantly influenced Purchase Intention and it partially mediated the association between influencer credibility and purchase intention leading to acceptance of H7 and H9. The result is consistent with previous research, supporting the important role that attitudes are shaped by perceived information credibility, as has been shown in studies by Masuda et al. (2022); Naderer et al. (2021) and Wang et al. (2008). This finding also raises questions about the possible value of using YouTube videos’ perceived legitimacy to forecast viewers’ purchase intentions for the products they showcase. The substantial correlation between attitudes and behavioral intentions is a link that Ajzen and Fishbein (1977). Thoroughly examined gives rise to this assumption.

6. Theoretical and managerial implications

This study is meaningful in its input to the theoretical understanding of using the Theory of Reasoned Action and the Tri Component Attitude Model in explaining the impact of relevant cues on influencer credibility and purchase intention. This research attempts to deepen knowledge of how GenZ influencer marketing in the context of the Indian market. This study closes a gap in the literature by examining the influence of social media influencers on purchase intentions in India, a topic that has not been well studied. By providing a thorough framework that clarifies the role of influencer qualities in influencing customer purchase intentions through the mediation of credibility, it advances our understanding of the subject. The importance of antecedents of the credibility of the influencer, namely expertise, trust, and similarity, has emerged in this research endeavor. The impact of influencer credibility on purchase intention is well documented and resonates outcomes of previous researchers. This study establishes the significance of the truthfulness and resemblance of the influencer to be effective with his or her followers. It is observed that the target segment (GenZ) gives less importance to the Attractiveness of the influencer and it was insignificant in influencing the credibility. In the backdrop of the Tri Component Attitude Model (Rosenberg et al., 1960), this finding emphasizes the cognitive component of attitude formation. The Tripartite model, also recognized as the three components of attitude, encompasses affective, behavioural, and cognitive elements. Collectively, these elements create attitudes, with one element usually predominating over the others at any one time. The findings revealed that Attitude towards the brand has a significant positive influence on Purchase intention. The IPMA results also indicate that Attitude towards the brand is the second most important factor determining the purchase intention of followers. Similar previous studies (J. P. Trivedi, 2018; J. Trivedi & Sama, 2020) have also highlighted the importance of attitude towards the brand in followers’ purchase intention. This strengthens our understanding of the need to build brands and consider influencers as mere enablers of decision-making. This is further validated by the mediation analysis performed in this study. A partial mediation is proved ( Table 4) which indicates that both the antecedents (attitude towards brand and influencer Credibility) have an important role to play in shaping followers’ purchase intention. The significant and positive impact of trustworthiness, similarity, and expertise on influencer credibility should inform advertisers or marketers to use trustworthiness as a criterion to evaluate the power of a social media influencer as a potential advertising partner. This project is also among one of the few studies to analyze the follower’s attitude towards video content on purchase intention. It indicates marketers to take special cognizance of this fact and encourages them to create defined standard operating procedures to be necessarily followed by the influencers. If social media influencer intends to continue their collaborations with advertisers, or wish to expand their followers they must connect with the followers.

7. Future directions and limitations

There are certain drawbacks to this study. It doesn’t distinguish between different kinds of videos or brands/products; instead, it concentrates on social media influencers and brands/products in a general way. Subsequent investigations ought to improve the accuracy of influencer marketing theories by examining particular video categories (e.g., office supplies, alcoholic beverages, gaming videos), alternative content formats (e.g., blog posts, audio podcasts, Instagram/Facebook photos), or product genres (e.g., product reviews, how-to tutorials, gaming videos). Further research could also be extended to influencer marketing across specific product categories. Furthermore, examining particular groups of micro or macro influencers may reveal differences in the ways that trustworthiness is influenced. Additionally, this study uses a single survey instrument and depends on a single source of consumers, which could introduce a single-source bias. To get over this restriction, future research should think about selecting participants from a variety of sources and using a range of techniques to look more deeply into the dynamics of social media influencer marketing and how consumers perceive the reliability of information.

Author contributions