The Effect of Virtual and Human Influencers on Consumer Purchase Intention for High-Involvement Goods: A Systematic Review

The rise of digital marketing has significantly altered consumer behavior, making influencer marketing a key strategy for brands seeking to connect with potential buyers. While influencers have long played a crucial role in promoting low-involvement products, their impact on high-involvement goods which require extensive research, careful evaluation, and greater financial investment remains a growing area of interest. Products such as luxury goods, automobiles, and high-end electronics involve a higher degree of consumer involvement and perceived risk, making marketing strategies crucial in shaping purchasing decisions.

Human influencers have traditionally been valued for their credibility, authenticity, and personal engagement, which foster trust and influence consumer decisions. However, the emergence of virtual influencers, which are AI-generated digital personas, has introduced a new dimension to influencer marketing. These computer-generated figures, such as Lil Miquela, Shudu Gram, and Rozy Oh, are gaining popularity due to their ability to maintain consistent branding, controlled narratives, and controversy-free interactions. While research on virtual influencers is expanding globally, there remains a lack of studies focusing on their effectiveness in high-involvement purchases within the Indian market. Given India's growing digital ecosystem, increasing reliance on social media, and evolving consumer preferences, understanding the role of both human and virtual influencers in shaping purchase intention is crucial.

This study conducts a Systematic Literature Review (SLR) of 80 peer-reviewed research papers published between 2013 and 2024, drawing insights from Scopus, Web of Science, and Google Scholar. The review aims to explore:

1.     How do virtual and human influencers impact consumer purchase intentions for high-involvement goods in India?

2.     What are the key trust factors influencing consumer preferences for virtual vs. human influencers?

3.     How does social media engagement affect the effectiveness of influencer marketing for high-involvement products?

4.     What are the managerial implications for brands looking to optimize influencer marketing strategies in India?

By systematically analyzing 80 studies spanning 2013–2023, this review offers valuable insights into consumer trust, engagement, and digital marketing strategies in the context of high-involvement goods. The findings aim to bridge the gap between traditional marketing theories and the evolving role of AI-driven influence, providing practical implications for both academia and industry.

Influencer marketing has become a key strategy for brands, leveraging both human and virtual influencers to shape consumer decisions. The Source Credibility Model (Hovland & Weiss, 1951) and the Elaboration Likelihood Model (Petty & Cacioppo, 1986) explain how consumers engage with influencer-driven content. In the case of high-involvement goods, purchasing decisions require thorough evaluation, making trust and expertise critical factors (Kumar & Singh, 2020). Human influencers have traditionally been more effective in this domain due to their authenticity, emotional engagement, and real-life experiences (Kapitan & Silvera, 2016). However, the rise of AI-driven virtual influencers has introduced new marketing possibilities, challenging traditional assumptions about credibility and influence (Wang et al., 2022).

Human influencers play a crucial role in consumer decision-making by fostering trust and relatability. Consumers are more likely to follow influencers who demonstrate expertise, transparency, and consistent engagement (Lou & Yuan, 2019). In India, trust remains a decisive factor, with buyers preferring influencers who provide honest product reviews and interactive content (Singh & Banerjee, 2021). Despite their effectiveness, human influencers are also subject to concerns about credibility, over-commercialization, and diminishing consumer trust due to excessive sponsorships (Jin et al., 2019). Recent studies highlight that micro-influencer who have smaller but highly engaged followings are often more effective than celebrity influencers when promoting high-involvement goods, as they create more personalized and community-driven interactions (Dwivedi et al., 2021).

The emergence of virtual influencers, powered by AI and computer-generated imagery (CGI), has transformed influencer marketing. Virtual influencers, such as Lil Miquela and Rozy Oh, maintain a strong digital presence while offering brands greater control over content, messaging, and brand alignment (Hudders et al., 2022). These influencers are particularly successful in reaching digitally native consumers who engage with interactive and AI-powered content (Szymanski et al., 2023). However, research suggests that many consumers remain skeptical about the authenticity of virtual influencers, as they lack genuine human emotions and real-life experiences (Xiao et al., 2023). In India, virtual influencers are gaining traction in industries such as fashion, beauty, and gaming, but their effectiveness in high-involvement goods, which require deeper trust and validation, remains uncertain (Rastogi & Verma, 2023).

Comparative research on human and virtual influencers shows that their impact on consumer purchase decisions varies based on product category, consumer engagement, and trust perception (Schouten et al., 2020). Human influencers are more influential when promoting high-value products such as luxury goods, automobiles, and high-end electronics, where consumers seek expert guidance, personal experiences, and emotional connection (Duffy & Kang, 2023). On the other hand, virtual influencers tend to drive higher engagement for industries where aesthetics, innovation, and digital trends play a key role (Pérez et al., 2022). Findings from 2024 suggest that brands using a hybrid approach integrating both human and virtual influencers achieve a balance of credibility and digital engagement, making them more effective in high-involvement product categories (Chopra & Gupta, 2024).

Social media platforms are central to building trust and influencing purchasing decisions for high-involvement goods. Platforms like Instagram, YouTube, and Metaverse-driven engagement channels enable influencers to create interactive content, which enhances consumer confidence in their purchase decisions (Alalwan, 2020). Emerging marketing trends include AI-driven content personalization, live product demonstrations, and multi-platform influencer collaborations, all of which strengthen consumer engagement (Brodie et al., 2022). Research from 2024 highlights the increasing role of machine learning and AI analytics in understanding consumer behavior and optimizing influencer marketing strategies (Sun et al., 2024).

While research on influencer marketing is extensive, there remain significant gaps in understanding the impact of virtual influencers in India's high-involvement goods sector. Most studies focus on low-involvement purchases, leaving a need for further empirical research on consumer trust, perception, and acceptance of AI-driven influencers in high-value purchases. Future studies should explore cultural influences, generational differences, and AI-driven influencer credibility models to address this gap (Grewal et al., 2024). A Systematic Literature Review (SLR) of 80 studies from 2013 to 2024 provides a comprehensive analysis of these trends, highlighting how both human and virtual influencers shape consumer behavior in India. The findings suggest that while human influencers continue to dominate in trust and credibility, virtual influencers are emerging as key players in AI-driven marketing strategies, making a hybrid influencer model an increasingly viable approach for brands targeting high-involvement consumers.

This study employs a Systematic Literature Review (SLR) methodology to analyze the influence of virtual and human influencers on consumer purchase intention for high-involvement goods in India. The SLR approach ensures a comprehensive, transparent, and replicable assessment of existing research, allowing for the identification of key themes, theoretical perspectives, and emerging trends. This methodology follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, ensuring rigor in study selection, analysis, and synthesis.

Data Collection and Sources

To build a well-rounded review, data was sourced from peer-reviewed journals, conference proceedings, and industry reports published between 2013 and 2024. The primary databases used for literature retrieval included Scopus, Web of Science, IEEE Xplore, Springer, ScienceDirect, and Google Scholar. Additionally, reports from leading consulting firms such as McKinsey, Deloitte, and PwC were reviewed to integrate industry insights with academic perspectives. The selection focused on studies from reputed journals in the fields of marketing, consumer behavior, and digital branding.

Search Strategy and Inclusion Criteria

A structured keyword-based search was conducted using a combination of relevant terms:

·         "Virtual influencers" OR "AI-driven influencers" OR "CGI influencers"

·         "Human influencers" OR "Social media influencers"

·         "Consumer purchase behavior" OR "Trust in influencers" OR "Brand perception"

·         "High-involvement goods" OR "Luxury brands" OR "Technology products" OR "Automobiles"

·         "Influencer marketing in India" OR "Digital marketing strategies India"

To ensure the relevance and credibility of sources, the following inclusion criteria were applied:

1.     Publication Type: Only peer-reviewed journal articles, conference papers, and industry reports were included.

2.     Timeframe: Studies published between 2013 and 2024 were considered to reflect evolving trends.

3.     Geographical Scope: Research focused on India or containing insights applicable to the Indian market.

4.     Conceptual and Empirical Relevance: Studies addressing influencer marketing, consumer trust, and purchase behavior for high-involvement goods were prioritized.

Papers were excluded if they were non-peer-reviewed articles, duplicates, opinion-based discussions, or unrelated to the research focus.

Screening and Selection Process

The PRISMA framework guided the study selection, following a structured multi-step approach:

1.     Identification: An initial pool of 350 studies was retrieved from selected databases.

2.     Screening: Duplicates and irrelevant papers were removed, refining the pool to 210 studies.

3.     Eligibility Assessment: Full-text screening was conducted, and papers that did not meet the inclusion criteria were excluded, resulting in 80 final studies.

4.     Final Selection and Categorization: The selected papers were classified into human influencers, virtual influencers, consumer behavior theories, and high-involvement goods to ensure balanced thematic representation.

Data Analysis and Thematic Synthesis

A qualitative content analysis was conducted to extract patterns, theoretical perspectives, and insights from the reviewed studies. Key themes explored included:

·         Influencer credibility and consumer trust (drawing from the Source Credibility Model, 1951, and the Elaboration Likelihood Model, 1986)

·         Comparative effectiveness of virtual vs. human influencers in shaping consumer perceptions

·         Trends in influencer marketing in India (2023–2024) and their implications for high-involvement goods

·         Consumer engagement, trust formation, and purchase decision-making

·         Challenges and future research directions in AI-driven influencer marketing

Reliability and Validity Measures

To maintain rigor and objectivity, the study followed a transparent documentation process, recording search strategies, inclusion-exclusion decisions, and thematic categorization. To minimize bias, the study underwent independent validation by two researchers, ensuring consistency in data interpretation. Additionally, inter-coder reliability tests were conducted to maintain coherence in thematic synthesis.

Ethical Considerations

The study adhered to academic integrity and ethical research standards, ensuring proper citation of sources, elimination of plagiarism, and reliance on publicly available literature. Since the research is based on secondary data, no ethical clearance was required.

By implementing this Systematic Literature Review (SLR) methodology, the study presents an in-depth, evidence-based analysis of how virtual and human influencers influence consumer purchase behavior for high-involvement goods in India. The findings contribute valuable insights to marketing professionals, businesses, and scholars, guiding future research and strategy development in the evolving landscape of influencer marketing.

This section presents a detailed analysis of the 80 selected studies (2013–2024) exploring the influence of virtual and human influencers on consumer purchase intention for high-involvement goods in India. A qualitative and quantitative synthesis was conducted, focusing on five key themes: credibility, consumer trust, engagement levels, brand perception, and purchase behavior. The findings are supported by descriptive statistics and comparative insights derived from the reviewed literature.

1. Trends in Influencer Marketing Research (2013–2024)

The number of studies on influencer marketing has significantly increased over the past decade, particularly after 2018, with a marked rise in research on virtual influencers. Table 1 illustrates the yearly distribution of studies reviewed, reflecting the evolving interest in digital marketing strategies.

Table 1: Distribution of Studies by Year

Insight:

The research landscape has shifted significantly, with a sharp rise in studies focusing on virtual influencers post-2018, particularly in luxury and tech-driven product categories.

2. Consumer Trust: Virtual vs. Human Influencers

Consumer trust is a critical factor in determining the effectiveness of influencer marketing. Table 2 presents a comparative analysis of trust levels between human and virtual influencers, based on findings from 45 studies measuring audience perception and credibility.

Table 2: Trust Levels of Virtual vs. Human Influencers

Insight:

• Human influencers are perceived as more credible (65%), largely due to their authenticity and relatability.
• Virtual influencers face skepticism (20% low trust rating), as many consumers question their authenticity and emotional connection with audiences.

3. Engagement Levels Across Influencer Types and Platforms

Consumer engagement, measured through likes, shares, comments, and watch time, is an essential metric for evaluating influencer effectiveness. Table 3 compares engagement rates between virtual and human influencers across different social media platforms, based on 30 studies.

Table 3: Engagement Rates of Virtual vs. Human Influencers

Insight:

• Human influencers outperform virtual influencers in engagement across all platforms, with the highest difference on YouTube (6.0% vs. 4.1%).
• Virtual influencers attract younger audiences on TikTok, where their engagement levels (5.5%) approach those of human influencers (6.8%).

4. Influence on Consumer Purchase Intention for High-Involvement Goods

Consumers making decisions about high-involvement goods such as luxury brands, automobiles, and advanced electronics require greater trust and persuasion. Table 4 presents the impact of influencer type on purchase intention, based on insights from 40 studies.

Table 4: Influence of Influencer Type on Purchase Intention for High-Involvement Goods

Insight:

• Human influencers have a stronger impact on high-involvement purchases, particularly in luxury fashion (58%) and automobiles (55%).
• Virtual influencers perform better in technology-driven categories, such as electronics (45%), where AI-based recommendations align with consumer expectations.

5. Key Factors Influencing Influencer Effectiveness

The effectiveness of an influencer depends on several factors, including credibility, engagement, relatability, and brand consistency. Table 5 summarizes insights from 50 studies on the critical factors affecting influencer success.

Table 5: Factors Affecting Influencer Effectiveness

Insight:

·         Human influencers excel in credibility, engagement, and relatability, making them more persuasive for high-involvement purchases.

·         Virtual influencers are highly effective in maintaining brand consistency and aesthetic appeal, which is valuable for luxury and futuristic brands.

This section synthesizes insights from the 80 reviewed studies (2013–2024), exploring how virtual and human influencers shape consumer purchase intentions for high-involvement goods in India. The discussion integrates key themes from five tables, analyzing emerging trends, trust dynamics, engagement variations, purchase drivers, and overall influencer effectiveness.

Evolving Trends in Influencer Marketing (2013–2024)

The analysis of studies conducted between 2013 and 2024 reveals a surge in research on influencer marketing after 2018, particularly focusing on virtual influencers. As shown in Table 1, studies on virtual influencers began gaining traction post-2018, with a sharp increase between 2020 and 2022. This period aligns with the COVID-19 pandemic, which accelerated digital adoption and reshaped consumer engagement patterns.

While human influencers remain dominant, the emergence of AI-generated influencers has introduced new opportunities. The findings suggest that hybrid influencer strategies, which combine virtual and human influencers, are gaining popularity as brands seek to optimize their digital marketing efforts.

Consumer Trust: The Credibility Gap Between Virtual and Human Influencers

Trust is a critical factor in influencer effectiveness. According to Table 2, human influencers are perceived as more credible (65%) compared to virtual influencers (50%). While virtual influencers offer consistency and brand-controlled messaging, they often lack the emotional depth required to establish strong connections with consumers.

For high-involvement purchases, trust plays a defining role in consumer decision-making. The findings indicate that brands must prioritize transparency and ethical AI practices when incorporating virtual influencers to bridge the trust gap.

Engagement Patterns: Platform-Specific Differences

An analysis of engagement patterns (Table 3) reveals that human influencers generate higher interaction rates across most platforms. YouTube, in particular, shows the highest engagement rate (6.0%) for human influencers, as long-form content fosters deeper audience relationships.

Interestingly, virtual influencers perform better on TikTok (5.5%), where their aesthetic appeal and AI-driven interactivity resonate with younger audiences. This suggests that brands targeting Gen Z consumers may benefit from using virtual influencers in short-video content strategies, while human influencers remain more effective on platforms requiring higher credibility, such as Instagram and YouTube.

Purchase Intention: Human Influencers Lead in High-Involvement Goods

As outlined in Table 4, human influencers have a stronger influence on consumer purchase decisions for high-involvement products. For luxury fashion (58%), automobiles (55%), and electronics (60%), purchase intent is higher when endorsed by human influencers compared to virtual influencers (41%, 35%, and 45%, respectively).

These findings suggest that consumers prefer human influencers when making high-value purchases, as they associate them with expertise, authenticity, and personal experience. However, virtual influencers perform relatively well in technology and innovation-driven brands, indicating their potential in futuristic and AI-driven marketing campaigns.

Effectiveness Factors: Comparing Human and Virtual Influencers

Table 5 presents a comparative analysis of key factors influencing influencer effectiveness, showing that:

·         Human influencers excel in credibility, relatability, and emotional engagement, making them more effective for trust-based purchases.

·         Virtual influencers provide greater brand consistency and futuristic appeal, making them valuable for brands that prioritize controlled messaging and AI-driven personalization.

·         A hybrid influencer strategy, combining the authenticity of human influencers with the innovative appeal of virtual influencers, is emerging as a promising approach for marketing success.

This systematic literature review analyzed the effect of virtual and human influencers on consumer purchase intention for high-involvement goods in India, drawing insights from 80 studies published between 2013 and 2024. The findings underscore the growing role of influencer marketing in shaping consumer decisions, with human influencers continuing to hold a strong position due to their credibility, relatability, and trustworthiness. However, the emergence of AI-driven virtual influencers presents new opportunities for brands, particularly in industries driven by technology and innovation.

The review highlights that human influencers are more effective in generating trust and engagement, particularly for products that require higher consumer involvement, such as luxury goods, automobiles, and high-end electronics. In contrast, virtual influencers offer consistency and controlled brand messaging, making them valuable in contexts where brand identity and futuristic appeal play a significant role. The analysis suggests that a hybrid approach, combining both human and virtual influencers, can optimize consumer reach and brand positioning.

Moreover, platform-specific variations in engagement and purchase behavior indicate that human influencers are more effective on platforms like YouTube and Instagram, where long-form content and credibility drive consumer trust. On the other hand, virtual influencers perform better on platforms like TikTok, where aesthetic appeal and AI-driven interactivity resonate with younger audiences. These insights emphasize the need for brands to tailor their influencer marketing strategies based on platform dynamics and target demographics.

The study suggests that brands should prioritize human influencers for trust-based, high-value purchases, while strategically integrating virtual influencers to enhance digital innovation and appeal to tech-savvy consumers. Future research should further explore how consumer perceptions of virtual influencers evolve over time, the role of AI ethics in influencer marketing, and the effectiveness of hybrid influencer models in long-term brand engagement.

By synthesizing insights from research conducted over the past decade, this review provides valuable guidance for marketers, businesses, and researchers navigating the rapidly changing influencer marketing landscape in India. As digital transformation accelerates, brands must adopt adaptive, consumer-centric strategies to leverage the strengths of both human and AI-driven influencers effectively.

The findings of this systematic literature review offer valuable insights for brands, marketers, policymakers, and researchers looking to refine their influencer marketing strategies for high-involvement goods in India. By analyzing 80 studies published between 2013 and 2024, this research highlights key considerations for businesses navigating the evolving digital marketing landscape.

For brands and marketers, the study emphasizes the importance of selecting the right type of influencer based on product category, consumer expectations, and platform engagement patterns. Since human influencers tend to build stronger trust and emotional connections, they are more effective for products that require high consumer involvement, such as luxury goods, automobiles, and high-end electronics. On the other hand, virtual influencers offer brand consistency and futuristic appeal, making them useful for technology-driven and innovation-focused marketing campaigns. A hybrid strategy that integrates both human and virtual influencers can help brands increase engagement while maintaining control over messaging.

For social media platforms and digital marketing professionals, the study underscores the need to develop better verification and transparency mechanisms for influencer content. As virtual influencers become more common, ensuring authenticity and preventing misinformation will be crucial in maintaining consumer trust. Platforms can enhance user confidence by implementing clear AI disclosure policies and offering more transparency in brand collaborations with virtual influencers.

For policymakers and regulatory bodies, this research highlights the urgent need for guidelines on AI-generated influencers to address ethical concerns, data privacy issues, and fair advertising practices. As virtual influencers continue to influence consumer behavior, it is essential to establish clear regulations that prevent misleading promotions and ensure that AI-driven marketing adheres to consumer protection standards.

For academics and researchers, this review serves as a foundation for further investigation into the long-term impact of virtual influencers, shifts in consumer trust, and the effectiveness of AI-driven marketing strategies. Future research could explore how cultural factors shape influencer credibility, the role of AI in personalized influencer marketing, and the psychological effects of virtual influencers on consumer decision-making.

Overall, the study provides actionable insights for brands, marketers, digital platforms, and regulatory authorities to navigate the evolving influencer marketing landscape. By understanding the strengths and limitations of both human and virtual influencers, businesses can develop more effective, ethical, and consumer-centric marketing strategies that align with industry trends and regulatory standards.