Journal of Consumer Behaviour
REVIEW
Engagement in Influencer Marketing: A Systematic Review
of Key Drivers, Behaviors, and Future Research Directions
Tareq Aldlimi1
| Constantinos-Vasilios Priporas1,2,3
| Shing-Wang Chang4
1Department of Marketing, Branding & Tourism, Middlesex University, Business School, London, UK
| 2Middlesex University, London,
| 4Department of Marketing,
3GNOSIS Mediterranean Institute for Management Science, School of Business, University of Nicosia, Nicosia, Cyprus
UK |
Branding & Tourism, Business School, London, UK
Correspondence: Tareq Aldlimi (ta858@live.mdx.ac.uk; tareq.aldlimi@hotmail.com)
Received: 11 August 2024 | Revised: 27 January 2025 | Accepted: 6 March 2025
Keywords: behavioral engagement | engagement | influencer marketing | social media influencers
ABSTRACT
Influencer marketing research is rapidly evolving, with growing interest in the dynamics between social media influencers and
their followers. Engagement, defined as the active interaction between followers and influencers, remains a fragmented area
of study, despite valuable insights from recent research. This systematic literature review synthesizes findings from 43 scholarly articles retrieved from the Web of Science database, focusing explicitly on engagement with SMIs. Using the Antecedents,
Decisions, Outcomes (ADO) framework, the review categorizes factors influencing engagement into source, content, and
audience-­related dimensions and integrates them into a comprehensive framework. This framework clarifies how these factors
drive various engagement behaviors, such as likes, comments, and shares, and explores conceptualizations of engagement across
cognitive, emotional, and behavioral dimensions. By consolidating existing knowledge, identifying gaps, and proposing future
research directions, this review enhances theoretical understanding and offers actionable insights for practitioners aiming to
increase engagement with social media influencers.
1   |   Introduction
Social media platforms have become an integral part of people's
daily lives, with billions of users worldwide (Wong 2023). The
popularity of social media platforms has encouraged social interaction and participation on an unprecedented scale. These
platforms have revolutionized communication, sharing, and interaction, thereby changing the role of individuals in the context
of communication. Specifically, social media platforms function
as bidirectional communication channels, offering users a range
of tools to express their engagement with posted content. Given
the widespread use of social media platforms, it has become necessary for marketers to tap into this vast user base and develop
strategies to enhance content interactions (Hazari et al. 2023).
One effective approach is collaborating with social media influencers (SMIs) strategically leveraging their influence to improve
engagement within the dynamic landscape of social media.
An SMI is a content creator who has expertise in a particular
field and possesses an actively engaged audience (i.e., followers)
on social media platforms (Lou and Yuan 2019). Compared to
traditional celebrities, SMIs are seen as regular individuals who
share similar interests with their followers (Ren et al. 2023), exerting a substantial influence on forming attitudes and behaviors
among their followers (Gamage and Ashill 2023). The growing
popularity of SMIs has spurred the development of influencer
marketing as a key marketing strategy. Specifically, influencer
marketing enables marketers to leverage SMIs' assets, content
creation strategies, and connect with their followers personally
(Leung, Gu, Li, et al. 2022). The surge in influencer marketing research underscores its essential role in contemporary marketing
(Lou et al. 2023; Fowler and Thomas 2023; Vrontis et al. 2021).
While the majority of research on influencer marketing predominantly focuses on followers' purchase intentions, scholars such
© 2025 John Wiley & Sons Ltd.
Journal of Consumer Behaviour, 2025; 24:1541–1566
https://doi.org/10.1002/cb.2485
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Although enhancing engagement remains a critical objective for
marketers (Wies et al. 2023; Leung, Gu, and Palmatier 2022),
identifying suitable SMIs to effectively boost engagement in
campaigns remains a significant challenge (Valsesia et al. 2020;
Chetioui et al. 2023; Ren et al. 2023; Park et al. 2024). This challenge is exacerbated by the ever-­increasing number of SMIs
competing in the digital space (Ren et al. 2023; Park et al. 2024).
Selecting the right SMI is crucial, as a mismatch between the
influencer and the campaign's goals can undermine its success.
To address this, understanding the mechanisms through which
SMIs stimulate follower engagement decisions is paramount.
This knowledge equips marketers with the tools to select SMIs
more strategically, ensuring alignment with their target audience
and campaign objectives (Hughes et al. 2019; Park et al. 2024).
As firms increasingly rely on influencer marketing to drive
engagement activities (Leung, Gu, Li, et al. 2022; Hughes
et al. 2019), there is an urgent need for deeper research into follower engagement with SMIs (Joshi et al. 2023). Understanding
the factors that enhance this engagement is critical for both
scholars and practitioners (Cascio Rizzo et al. 2023; Pradhan
et al. 2023; Zheng et al. 2023). As Gurrieri, Drenten, and
Abidin (2023, 925) aptly noted, “a deep dive into the intricacies
of content creation, audience engagement, and evolving trends
is necessary.” While the broader field of influencer marketing
has seen growing interest (Vrontis et al. 2021), research specifically focused on engagement remains underdeveloped (Pradhan
et al. 2023). Hazari et al. (2023) similarly emphasize the need
for more dedicated studies on engagement dynamics. The fragmented findings in the existing literature and the multitude
of influencing factors highlight the importance of a rigourous
Systematic Literature Review (SLR) to consolidate and advance understanding. Although several SLRs have been published in the influencer marketing field (e.g., Vrontis et al. 2021;
Pradhan et al. 2023; Fowler and Thomas 2023; Pushparaj and
Kushwaha 2024), none have systematically synthesized the
literature with a specific focus on engagement in influencer
marketing.
There is significant ambiguity surrounding the specific engagement behaviors studied in the influencer marketing literature,
such as likes, comments, and shares. Additionally, the fragmented exploration of moderators and mediators influencing engagement with SMIs exacerbates this lack of clarity. Addressing
these gaps is critical to fostering a more comprehensive
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understanding of engagement dynamics. Furthermore, identifying overarching theoretical and methodological trends within
the literature is vital to assess the current state-­of-­the-­art and
guide future research directions. By synthesizing existing findings and pinpointing avenues for further exploration, this review
aims to enhance the understanding of the dynamic interplay between SMIs and their audiences.
The primary objective of this SLR is to consolidate and analyze existing research on engagement with SMIs. By synthesizing findings from various studies, we aim to identify the
antecedents, consequences, mediators, and moderators relevant to engagement within the influencer marketing literature.
Additionally, we explore the different types of engagement
between SMIs and their audiences, while also reviewing the
theoretical and methodological trends in the field. This review
makes several contributions to both theory and practice. First,
it consolidates engagement-­related factors into an integrative
framework, offering a robust theoretical basis to guide future
researchers and assisting practitioners in developing more effective influencer marketing strategies. Second, it advances our
understanding of SMI engagement by moving beyond a general
perspective to explore diverse conceptualizations of engagement—cognitive, emotional, and behavioral. It also examines
engagement at a granular level, capturing dimensions such as
liking, commenting, sharing, viewing, clicking, mentioning,
watching, and reading. Third, by identifying notable research
gaps, this study provides a comprehensive agenda for future research with respect to theory, context, and methodology. Finally,
it equips marketers with state-­of-­the-­art insights to identify and
effectively collaborate with SMIs, fostering consumer engagement and optimizing influencer marketing efforts.
The structure of this paper is organized as follows. First, we provide a brief review of engagement in the context of SMIs, highlighting deficiencies in prior SLRs. Next, we detail our review
methodology, followed by a descriptive overview and systematic
classification of the findings. Subsequently, we integrate these
findings into an overarching framework and discuss the results.
Finally, we propose avenues for future research and conclude
with a discussion of this study's implications for both research
and practice.
2   |   Theoretical Background
2.1   |   Influencer Marketing
Certain individuals are more influential than others. This influence stems from their social status or personal attributes,
potentially impacting the behavior of others (Zhang et al. 2017).
The term “Influencer” originated from the concept of personal
influence coined by Katz and Lazarsfeld (1955). The widespread
adoption of social media in contemporary times has amplified
the impact of ordinary individuals' thoughts, enabling them
to connect with a much larger audience than in the past (Hu
et al. 2020). Consequently, this phenomenon has motivated certain users to commit themselves to expressing their viewpoints
via social media platforms (Audrezet et al. 2018). These users
are known as SMIs.
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as Sokolova and Perez (2021) and Bailey et al. (2023) emphasize
the need to expand beyond these commonly studied outcomes.
Engagement with SMIs, characterized by social interactions
such as likes, comments, and shares, represents a critical yet
underexplored dimension of influencer marketing (Cheung,
Leung, Yang, et al. 2022). This engagement is critical, as social
media algorithms prioritize highly interactive posts, boosting
their visibility and increasing their chances of being labeled
“trending” (Feng and Xie 2023; Karhawi 2022). Furthermore,
marketers frequently utilize engagement metrics to evaluate
the performance of influencer marketing campaigns (Syrdal
et al. 2023), as they reflect followers' active participation, loyalty,
trust, and sustained interest in the content and the influencer
(Chen et al. 2023).
SMIs vary in their focus, social media platform selections, and
number of followers. Moreover, SMIs wear many hats; they are
content creators, opinion leaders, persuasive agents, and entrepreneurs (Childers et al. 2019). SMIs usually share stories
about their personal lives (Martínez-­López et al. 2020), generate high perceived credibility (Djafarova and Rushworth 2017),
perceived authenticity (Lee and Eastin 2021), post creative content (Casaló et al. 2021), amass a large number of followers (De
Veirman et al. 2017), and become a source of advice (Vrontis
et al. 2021). Thus, they can greatly influence their followers' attitudes and behaviors.
SMIs are referred to by various names. For instance, SMIs
(Freberg et al. 2011), digital SMIs (Torres et al. 2019), micro-­
influencers (Khamis et al. 2017), and vloggers (Munnukka
et al. 2019). It is also worth mentioning that SMIs might
be referred to according to the platform used. For example, YouTubers, Facebookers, Instagrammers, Twitterers,
Snapchatters, or TikTokers (Wielki 2020). Together, recent research often uses the overarching term “SMIs” to describe influencers (Lou et al. 2023).
2.2   |   Engagement With SMIs
SMIs have garnered significant attention from marketers due
to their ability to influence large audiences effectively (Hu and
Yao 2021). SMIs play a crucial role in spreading information
and shaping followers' attitudes and behaviors, making them
valuable assets in digital marketing strategies (Gamage and
Ashill 2023). Followers are drawn to engage with SMIs for
various reasons, such as accessing information, staying updated on trends, and seeking entertainment (Cao et al. 2021).
Engagement on social media refers to the use of platform
tools to interact and respond to content shared by other users
(Hazari et al. 2023).
Existing research identifies several engagement activities, including liking, commenting, sharing, clicking, viewing, and
reading (Zhao et al. 2023; Mir and Salo 2024). “Likes” measure
a follower's positive reception of content, “comments” reflect
active discussions around it, and “shares” demonstrate followers endorsing and disseminating the content within their networks (Chen et al. 2023). Additional actions such as clicking,
viewing, and reading content provide more nuanced insights
into followers' engagement behaviors, ranging from passive consumption to active interaction. Content with higher engagement
metrics—often referred to as “social currencies” due to their
importance in social media engagement (Cotter 2019)—is more
likely to be promoted by platform algorithms, increasing its visibility and reach (Syrdal et al. 2023).
Social media algorithms prioritize engaging content (Hazari
et al. 2023; Feng and Xie 2023), promoting SMIs to increase
their visibility on social media platforms by intentionally using
social media algorithms (Cotter 2019). SMIs' effectiveness is
based on the engagement rate generated by their posted content
on social media, as a high engagement rate indicates a broader
audience reach, trust, closeness, and loyalty, reflecting a strong
influencer–follower relationship (Tian et al. 2023). Indeed, one
of the reasons why influencer marketing is so attractive to marketers is that SMIs can promote engagement (Boerman 2020).
As a result, engagement is a desirable criterion for gauging
the effectiveness of SMIs (Gross and Wangenheim 2022; Tian
et al. 2023). Therefore, scholars and marketers increasingly
acknowledge the potential of SMIs in influencing follower engagement (Holiday et al. 2023), as the success of influencer
marketing remains in strong influencer–follower engagement
(Campbell and Farrell 2020).
2.3   |   Limitations of Previous Systematic Literature
Reviews
Numerous reviews on SMIs have emerged, with many being relatively recent. While these reviews offer valuable insights, they
are constrained by certain limitations that drive the need for the
current review. For example, the first literature review was published in 2019 by Sundermann and Raabe (2019). Its primary
objective was to reveal the existing state of research in strategic
SMI communication, emphasizing the strategic side of SMIs.
However, this review did not focus on the specific factors driving engagement, which are critical for understanding influencer
marketing effectiveness. Similarly, Veirman et al. (2019) concentrated on children and SMIs, yet had a restricted scope, covering
only eight articles and focusing on a specific target audience. As
a result, their findings are not fully generalizable to broader influencer marketing contexts, especially regarding engagement
with diverse audiences. The review by Vrontis et al. (2021) included 68 articles and provided valuable insights into the antecedents and consequences of influencer marketing. However,
the review was too broad, covering a wide variety of behaviors,
and fell short in exploring specific engagement-­related factors
with SMIs. Kanaveedu and Kalapurackal (2022) focus narrowly
on the role of SMIs in transforming consumer behavior, but they
overlook critical aspects such as engagement and fail to provide
a broader perspective on influencer marketing beyond consumer
behavior, limiting the overall scope of the review.
Hudders et al. (2021) advanced the field by examining an even
more extensive collection of 154 articles. Nonetheless, their
focus primarily centered on the commercial aspects of SMIs,
offering strategic insights but lacking a deeper examination of
how and why followers engage with SMIs at a more tactical
level. Fowler and Thomas's (2023) review also included 150
articles but focused on the broader area of influencer marketing rather than specifically on the engagement perspective.
This broader scope left a gap in the literature regarding the
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SMIs emerged throughout the 2010s alongside the rise of social
media platforms such as Facebook, YouTube, and Instagram
(Gurrieri et al. 2023). While the term SMI is widely used in
practice, there remains no universally accepted academic definition (Lee et al. 2021; Gamage and Ashill 2023). Nevertheless,
the most frequently referenced definition characterizes SMIs as
“a new type of independent third-­party endorser who shapes
audience attitudes through blogs, tweets, and the use of other
social media” (Freberg et al. 2011, 90). This definition implies
that SMIs need the exposure provided by social media platforms
to gain popularity and notoriety, while these platforms derive
their appeal from the content shared by SMIs (Gamage and
Ashill 2023).
To summarize, while previous reviews provide valuable foundations, they leave certain gaps unaddressed, particularly in terms
of engagement with SMIs. New reviews are warranted when
prior work has limitations (Paul et al. 2021). Given the rapid
emergence of the influencer marketing field, our review specifically addresses these gaps by focusing on engagement-­related
factors, offering a comprehensive and state-­of-­the-­art synthesis of past research findings. Table 1 provides an overview of
previous SLRs, comparing their scope, number of studies reviewed, date range, frameworks used, and engagement focus,
which contextualizes the distinctive focus of our review on engagement factors and outcomes. This targeted review aims to
advance understanding and encourage further research in this
evolving area.
3   |   Methodology
In the first step, we determined the objectives that shaped
our review as follows: (1) to identify the publication, theoretical, and methodological trends; (2) to identify the conceptualization of engagement, including cognitive, emotional, and
behavioral dimensions, and specify the type of engagement
behavior under study, such as likes, comments, and shares;
and (3) to identify the antecedents, consequences, mediators,
and moderators relevant to engagement in the influencer marketing literature.
A review is deemed to be systematic when the review incorporates a key question that the researcher needs to address
on a particular subject matter without predisposition (Harris
et al. 2014) and resolves the answer by following a systematic approach and unambiguous methodology to collect, identify, synthesize and report the findings (Khan et al. 2003). In
this regard, Paul and Criado (2020) classified systematic reviews into three categories—namely, domain-­based, theory-­
based, and method-­
based reviews. Domain-­
based reviews
focus on specific subject areas or fields of study, aiming to
synthesize and analyzes existing literature within those domains. Theory-­based reviews, on the other hand, center on
theoretical frameworks, aiming to examine how various theories contribute to understanding a particular phenomenon
across different studies. Method-­based reviews concentrate
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on research methodologies and techniques, aiming to evaluate the strengths and limitations of different research methods
employed in the literature.
Specifically, domain-­based reviews allow authors to describe
state-­of-­the-­art knowledge in the research domain and identify useful paths for future research. There are several types of
domain-­
based reviews: structured reviews, framework-­
based
reviews, bibliometric reviews, hybrid reviews, and conceptual
reviews. Precisely, framework-­based reviews allow researchers
to analyze and organize emerging themes using existing frameworks (Paul and Criado 2020).
The Antecedents Decisions Outcomes (ADO) framework is
a popular framework often used in marketing and consumer
behavior reviews (Paul and Benito 2018). Specifically, it was
utilized in previous review articles in the field of influencer marketing (Pradhan et al. 2023). The ADO framework aids in organizing and outlining the findings related to engagement with
SMIs, thereby facilitating scholars' understanding of the various
constructs involved. Antecedents refer to the factors influencing
followers'/consumers' engagement with SMIs, decisions refer to
the form of engagement, and outcomes refer to the result of such
engagement.
The Preferred Reporting Items for Systematic Reviews and
Meta-­A nalyses (PRISMA) protocol is a widely recognized and
accepted guideline for conducting SLRs and meta-­analyses in
various fields. It provides a structured framework to ensure
transparency, rigour, and reproducibility in the review process
(Moher et al. 2009; Page et al. 2021). Therefore, this review
adheres to the PRISMA protocol, which involves a structured
approach encompassing four distinct stages for conducting systematic reviews: identification, screening, eligibility, and inclusion (Figure 1).
3.1   |   Identification
The first stage of the PRISMA protocol is identification, which
includes three main considerations: search engines, search
period, and search string (also known as keywords). As for
search engines, Paul et al. (2021) argue that using multiple
search engines is not recommended because it will require
researchers to consolidate duplications that appear, which is
a redundant and unproductive endeavor. In this regard, the
Web of Science is the world's oldest, most widely used, and
authoritative database of research publications and citations
(Birkle et al. 2020). Web of Science is widely recognized as
a comprehensive and authoritative database for academic research, particularly in the scientific and social science disciplines (Paul et al. 2021). Memon et al. (2018) note that Web
of Science extensively covers peer-­reviewed journals, conference proceedings, and other scholarly literature, making it
an invaluable resource for systematic reviews. Additionally,
studies by Kulkarni et al. (2009) and Falagas et al. (2008)
have highlighted the high level of accuracy and reliability
of Web of Science's indexing and citation tracking capabilities, further affirming its suitability for rigourous academic
investigations. In terms of the search period, a bibliometric
analysis conducted by Abhishek and Srivastava (2021) shows
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drivers of engagement, an area that requires more targeted exploration. Laszkiewicz and Kalinska-­Kula (2023) limit their
review by focusing exclusively on virtual SMIs, ignoring the
important role that human SMIs play in social media marketing. Additionally, the review fails to address engagement,
which narrows its overall relevance to the broader influencer
landscape. Moreover, while Pradhan et al. (2023) came closest
to addressing engagement by focusing on social media more
broadly, they did not specifically explore SMIs or the factors
that contribute to engagement in influencer marketing contexts, such as content type, mediators, and moderators influencing engagement. In addition, they did not cover articles
after June 2021. Lastly, Pushparaj and Kushwaha (2024) provide a comprehensive analysis of the impact of SMIs on consumer decisions, focusing primarily on purchase intentions.
However, their review limits its scope to consumer behavior,
without addressing the broader context of engagement.
Comprehensive
influencer marketing
Strategic/commercial
SMI communication
Vrontis et al. (2021)
Hudders et al. (2021)
SMIs and consumer
behavior
Drivers, outcomes, &
conceptualization of
SMI engagement
Pushparaj and Kushwaha (2024)
Current review
Virtual SMIs
Comprehensive
influencer marketing
Fowler and Thomas (2023)
Laszkiewicz and Kalinska-­Kula (2023)
SMIs and consumer
engagement
Pradhan et al. (2023)
SMIs and consumer
behavior transformation
Children up to
12 years old
Veirman et al. (2019)
Kanaveedu and Kalapurackal (2022)
Strategic SMI
communication
Scope
Sundermann and Raabe (2019)
Author (year)
TABLE 1    |    Overview of previous SLRs on SMIs.
43
62
35
150
50
65
154
2011–2024
2012–2023
2012–2023
1999–2020
2012–2021
2016–2021
2011–2020
2007–2020
2018–2019
8
68
2011–2018
Date range
of studies
39
No. of
studies
reviewed
ADO
TCM (Theory, Context,
and Method) + ADO
Unidentified
TCCM (Theory, Context,
Concepts, and Method)
ADO (Antecedents
Decisions Outcomes)
Unidentified
Stern's (1994) revised
model of communication
Unidentified
Unidentified
Lasswell's (1948) model
of communication
Framework used
Yes
No
No
No
Yes, but focuses on general engagement
behaviors without exploring specific factors
contributing to engagement with SMIs
No
No
No
No
No
Engagement focus?
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that the first peer-­reviewed article in the context of influencer
marketing was published in 2011. Hence, we only included
papers published after 2011 until August 2024. Lastly, while
conducting a preliminary search on the term SMIs, we found
that SMIs have various names in the literature. For instance,
digital influencers, micro-­
influencers, virtual-­
influencers
and vloggers. Therefore, to broaden our search results we included the following keywords: “Influencer marketing” OR
“digital influencer” OR “social media influencer” OR “micro-­
influencer” OR “macro-­influencer” OR “pet-­influencer” OR
“virtual-­
influencer” OR “micro-­
celebrity” OR “vloggers”
AND “engagement” OR “interaction” OR “influencer outcome” OR “follower response”. In order to comprehensively
identify relevant research, we focused on articles where the
keywords were present in the article title, subject terms, keywords, or abstract. This approach was guided by the advice
of Paul and Criado (2020), who caution that conducting keyword searches throughout the entire article can lead to a broad
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scope. Applying these three search criteria yielded a total of
(4346) articles.
3.2   |   Screening
The second stage of the PRISMA protocol is screening, which
includes three considerations: document type, subject area, and
quality. In terms of document type, we refined our search to include only English articles that were published in peer-­reviewed
journals to ensure scientific rigour, consistent with other literature reviews in the field (e.g., Fowler and Thomas 2023; Vrontis
et al. 2021). For example, we did not include the following
types: non-­English (249), conference papers (430), review articles (138), editorial material (83), meeting abstracts (48), letters
(29), book reviews (17), corrections (11), and others (8). Hence,
(1013) publications were excluded. In terms of subject area,
(2587) articles were excluded because they were from domains
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FIGURE 1    |    PRISMA protocol.
3.3   |   Eligibility
The third stage of the PRISMA protocol is eligibility. To be considered eligible for inclusion, an article needed to be related to
the subject of influencer marketing and engagement. This involved a thorough title and abstract review to exclude articles
that do not relate to engagement with SMIs. Consequently, 557
journal articles were excluded, resulting in the retention of 91
articles that successfully advanced to the subsequent stage.
3.4   |   Inclusion
The final stage in the PRISMA protocol is the inclusion stage.
During this step, a comprehensive examination of the complete
texts was undertaken to further refine the selection process.
Specifically, the articles that met the eligibility criteria were further assessed for their relevance and alignment with the review's
objectives and to ensure that those articles closely aligned with
the study's focus on influencer marketing and engagement. For
example, we excluded articles focusing on corporate social responsibility (CSR). Moreover, studies that rarely refer to the concept of
engagement were excluded, as engagement did not constitute their
principal area of focus. Therefore, out of the 91 articles identified
as eligible, only 43 have been included in the inclusion stage. The
Appendix S1 summarizes the articles relevant to this review's aim.
The final stage in the PRISMA protocol is the inclusion stage.
During this step, a comprehensive examination of the complete
texts was undertaken to further refine the selection process. To
ensure the selection of relevant articles, we applied strict inclusion criteria that focused on studies explicitly examining engagement with SMIs. Articles were included only if they directly
addressed how engagement was defined, measured, or impacted
by factors affecting the interaction between SMIs and their audiences. Additionally, theoretical papers that discussed influencer
marketing strategies without providing empirical insights into
engagement behaviors were also excluded.
4   |   Results
The following section presents the outcomes of the SLR, highlighting key aspects of the existing body of literature on SMI
engagement. We present numerical results related to publication trends, the choice of social media platforms, industries
studied, theoretical perspectives, conceptualizations of engagement, key constructs investigated, and prevalent methodological trends.
4.1   |   Distribution by Year of Publications
We have observed a noteworthy surge in research interest in
recent years, reflecting the growing significance and relevance
of SMIs in fostering engagement as a field of study. For example, the distribution of publications by year vividly portrays this
trend, with (n = 3) articles published in 2019, (n = 2) in 2020,
(n = 7) in 2021, (n = 7) in 2022, (n = 16) in 2023, and (n = 8) in
2024 (Figure 2).
4.2   |   Distribution by Journal
As seen in Figure 3, the Journal of Business Research is the
journal that contains the highest number of articles relevant
to our topic (n = 6), followed by the Journal of Retailing and
Consumer Services (n = 4), Journal of Marketing (n = 3), Journal
of Interactive Marketing (n = 2), Journal of Travel Research
(n = 2), and Young Consumers (n = 2).
The remaining journals that appear in the review published no
more than one (n = 1) article, including The Journal of Interactive
Advertising, Journal of Interactive Marketing, Journal of Consumer
Behaviour, Journal of Consumer Research, Journal of Marketing
Research, Journal of Product and Brand Management, Journal
of Research in Interactive Marketing, Journal of the Academy of
Marketing Science, Journal of Travel Research, Asia Pacific Journal
of Marketing and Logistics, Computers in Human Behavior,
International Journal of Advertising, International Journal of
Information Management, International Journal of Internet
Marketing and Advertising, Journal of Strategic Marketing, PLOS
ONE, Journal of Research in Interactive Marketing, Review of
International Business and Strategy, Journal of Communication
Management, Humanities and Social Sciences Communications,
Tourism Management, Journal of Hospitality & Tourism Research,
Internet Research, and Current Issues in Tourism. This distribution highlights the notable presence of certain journals in this
research field, particularly the Journal of Business Research,
which stands out as a key source of relevant articles.
4.3   |   Distribution by Country
Figure 4 indicates that China dominates the scene with (n = 10)
of the total studies in the sample. The United States of America
(USA) followed with (n = 5) articles, while Malaysia, Ireland,
and India had (n = 2) articles, and the remaining countries had
only (n = 1) article each, including Spain, Australia, Pakistan,
Jordan, Hungary, Portugal, and South Africa. It is worth noting that in (n = 14) articles, the study did not specify a particular country where the research was conducted. Therefore, it
is evident that the majority of studies have been conducted
in Western and East Asian countries (see the extensive list in
Appendix S1).
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outside business, communication, and management (e.g., medicine, environmental studies, education, engineering, ethnic
studies, geography, nursing, mathematics, religion, linguistics,
arts, criminology, history, and international relations). We included studies from disciplines such as psychology, hospitality, computer science, and multidisciplinary science, as these
areas could potentially intersect with the domain of influencer
marketing. As for quality, journal articles successfully indexed
in Web of Science have passed stringent quality check criteria
(Paul et al. 2021). Specifically, Paul and Criado (2020) suggest
that an article must have an impact factor score above 1.0 in
the Journal Citation Reports published by Clarivate Analytics.
Therefore, (98) articles were excluded. Overall, (3698) articles
were excluded and (648) articles were included based on these
three screening criteria.
FIGURE 3    |    Top journals by frequency of articles.
4.4   |   Distribution by Social Media Platforms
and Industry
In terms of social media platforms studied, Instagram appears to be the most frequently studied platform among the
articles reviewed (n = 21). This suggests a significant focus
on Instagram as a channel for engagement with SMIs in
1548
the context of the research topic. Additionally, some studies considered two or more platforms, combining various
social media platforms (n = 10), while the Chinese blogging
platform, Sina Weibo, was studied (n = 3) times. Other platforms, such as Bilibili, TikTok, Facebook, Wenjuanxing,
Xiaohongshu, and X (previously known as Twitter), have been
examined in a smaller number of studies (n = 1) individually.
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FIGURE 2    |    Number of articles published by year.
Additionally, n = 3 studies did not specify a particular platform (see the extensive list in Appendix S1). Consequently, although Instagram dominates as the platform most frequently
used by SMIs, previous reviews suggest that influencer marketing research should expand to other platforms (Fowler and
Thomas 2023; Pradhan et al. 2023).
4.5   |   Distribution of Articles by Industry
The selected articles cover a diverse array of sectors and industries. Upon analysis, it was observed that the majority of the
articles revolved around sectors such as travel (n = 7) and fashion (n = 6). Moreover, (n = 2) studies focused on mommy SMIs
and lifestyle SMIs, with a smaller number of studies centered
on esthetic dermatology clinics (n = 1), hospitality (n = 1), food
(n = 1), and athletes (n = 1). Additionally, the review revealed
that (n = 15) studies did not specify any particular industry,
while (n = 6) studies covered multiple sectors simultaneously.
The comprehensive list is available in Appendix S1.
4.6   |   Theoretical Perspectives
Various theoretical perspectives have been used to study the
phenomenon of engagement in the context of influencer marketing. Among the articles included in this review, theories related to communication were among the most frequently used
to explain engagement with SMIs. For example, Social influence Theory (Kelman 1958) (n = 4), Elaboration Likelihood
Model (Petty and Cacioppo 1986) (n = 4), Social Exchange
Theory (Homans 1961) (n = 3), Media Dependency Theory
(Ball-­Rokeach 1985) (n = 2), Lasswell's Communication Model
(Lasswell 1948) (n = 2), and the Communication-­Persuasion
Matrix (McGuire 1989) (n = 1). Other studies focused on
the SMI personal qualities, for example, Source Credibility
Theory (Ohanian 1990) (n = 4) and Source Attractiveness theory (McGuire 1985) (n = 1). Additionally, there were investigations into the one-­sided relationship between SMIs and their
followers, known as the Parasocial Relationship Theory. This
theory, proposed by Horton and Richard Wohl (1956), garnered attention in (n = 2) studies.
Some other studies applied the Stimulus-­Organism-­Response
Theory (Mehrabian and Russell 1974) (n = 2), which assumes
that the stimulus refers to factors that impact followers' internal state and arouse interest; the organism refers to the
follower's evaluation; and the response represents the outcome of the follower's reaction. Only (n = 1) study employed
the Persuasion Knowledge Theory (Friestad and Wright 1994)
(n = 1), referring to followers' knowledge that the endorsement
is paid, and the Uses and Gratifications Theory (Blumler and
Katz 1974) (n = 1), to understand the needs, motives, and gratifications of followers. In addition, one (n = 1) study utilized
the Spillover Theory (Staines 1980), suggesting that behaviors
in one context can spill over into another, and another study
(n = 1) utilized the Self-­perception Theory (Bem 1967), which
suggests that individuals develop attitudes by observing their
own behavior and attributing it to internal or external factors. The Multi-­Attribute Attitude Model (Fishbein 1967) was
applied to one (n = 1) study. This model posits that attitudes
are formed based on the evaluation of multiple attributes of
a product or person. Social Learning Theory (Bandura and
Walters 1977) suggests that people learn behaviors by observing and imitating others, which was examined in one (n = 1)
study within this review.
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FIGURE 4    |    Top countries by frequency.
To summarize, out of the 43 journal articles in the review,
(n = 22) articles have used one theory, (n = 13) have utilized two
or more theories, and (n = 8) articles did not rely on any theory
(see the extensive list in Appendix S1).
4.7   |   Conceptualization of Engagement
Most scholars in consumer behavior studies conceptualize engagement into three distinctive aspects: cognitive, emotional,
and behavioral aspects (e.g., Dessart et al. 2015; Hollebeek
et al. 2014). Cognitive engagement refers to the degree to which
followers engage in intense thinking, focusing on intense
attention and absorption. Emotional engagement revolves
around emotional reactions, such as enthusiasm, enjoyment,
and cultivating a positive emotional bond. Behavioral engagement is the active manifestation of the engagement concept,
relating to the extent of followers' dedication, energy, and
time they invest in their interactions, which include activities
such as viewing, following, liking, commenting, and sharing
(Hollebeek et al. 2014).
Although it is acknowledged that the cognitive, affective, and
behavioral components are important aspects of online engagement, we found that most studies in our review adopted a behavioral perspective. Specifically, the majority of studies under
consideration focused on the behavioral aspect of engagement
(n = 18). This behavioral perspective is thought to be in line with
the SMI context, more practical, and offer more actionable insights (Buvár et al. 2022).
In terms of other conceptualizations of engagement, we found
that (n = 7) studies considered the cognitive, emotional, and
behavioral aspects; (n = 1) study focused on the cognitive and
emotional aspects, while (n = 1) considered the emotional and
behavioral aspects of engagement. Lastly, (n = 16) studies did not
specify the type of engagement they were investigating. Detailed
information on these studies and their categorizations can be
found in Appendix S1.
4.8   |   Virtual Influencers (VIs) and Engagement
Strategies
VIs have emerged as a compelling area of focus within the broader
field of SMI engagement, with 7 out of 43 studies in our review
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specifically addressing this phenomenon. VIs are computer-­
generated characters operated by businesses or creators to interact with audiences on social media platforms (Xie-­Carson,
Benckendorff, et al. 2023). Unlike human SMIs, VIs allow for
complete control over their personas and messaging, presenting
businesses with opportunities for consistent, highly curated engagement strategies (Agnihotri et al. 2024). Specifically, VIs are
immune to scandals, do not age, gain weight, or face scheduling
conflicts, offering brands consistent, reliable representation and
making them a compelling choice for long-­term marketing strategies (Ameen et al. 2024).
The studies reviewed highlight that VIs offer unique engagement advantages by leveraging their novel, tech-­d riven appeal to captivate audiences. Notably, their ability to simulate
human-­l ike interactions—such as using conversational tones,
autonomy, and responsiveness—strengthens perceptions of
social presence and enhances the overall engagement experience (Lin et al. 2024). Furthermore, findings by Xie-­C arson,
Magor, et al. (2023) indicate that humanlike VIs are particularly effective when paired with rational messaging and
visually compelling imagery, suggesting an alignment between technology-­d riven personas and audience preferences.
Meanwhile, Xie-­
C arson, Benckendorff, et al. (2023) highlighted followers' mixed feelings toward VIs, noting higher
receptivity when ethical concerns are addressed. Collectively,
these studies underscore the diverse mechanisms through
which VIs influence engagement, emphasizing their growing
significance in the context of influencer marketing.
4.9   |   Factors Investigated
As outlined in Section 3, our review employed the ADO framework to structure and categorize the identified factors that impact followers' engagement with SMIs, as illustrated in Figure 5.
In this framework, we considered not only antecedents but also
moderators and mediators that influence engagement decisions.
Specifically, this framework delineates that certain factors serve
as antecedents, influencing followers' engagement with SMIs,
which in turn shape their decisions regarding various forms of
engagement. Subsequently, these decisions contribute to various
attitudinal and behavioral transformations, ultimately leading
to distinct outcomes. We explain each stage of this framework
in greater detail.
4.9.1   |   Antecedents
Antecedents capture the reasons for engaging or not engaging
in the behavior and produce a direct influence on decisions,
in this case, followers' engagement (Paul and Benito 2018).
Following previous reviews in the field (e.g., Hudders
et al. 2021), the antecedents used by the studies under consideration are classified into three broad categories, namely,
source, content, and audience-­related factors. These three factors are central to campaign designs, which generally involve
selecting effective SMIs, creative content, and follower groups
to target (Leung, Gu, Li, et al. 2022). However, before attempting to classify those factors, each article has undergone careful
systematic steps. Initially, we identified the primary objective
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Other studies borrowed theories from the information systems contexts to explain the phenomena of engagement.
For example, Computers as Social Actors Theory (Nass and
Moon 2000) posits that humans interact with computers as if
they are social beings, a concept used in (n = 2) studies to explain follower engagement with AI-­generated, virtual SMIs.
The Modality–Agency–Interactivity–Navigability Model
(Sundar 2008), (n = 1), posits that media attention, interactivity, and navigability are crucial factors influencing user perceptions and responses in interactive media environments.
Some other studies applied theories originating from the
field of consumer behavior and marketing, such as Sussman
and Siegal's Information Adoption Model (Sussman and
Siegal 2003) (n = 1).
of each paper to gain insight into the overarching theme of
the research. Subsequently, we carefully extracted and scrutinized any available conceptual/theoretical models. Finally,
we thoroughly examined the measurement items associated
with each construct, where applicable, to gain a comprehensive understanding of their respective perspectives. These
steps enabled us to identify and classify the source, content,
and audience factors that influence engagement with SMIs.
Source factors are the SMI's personal characteristics which
can increase the level of acceptance in the process of persuasion and impact followers' perceptions, behaviors, and engagement (Vrontis et al. 2021). These include factors such as
perceived authenticity, credibility, and number of followers
(i.e., popularity). Next in line are content factors, which include the various techniques, tactics, attributes, and qualities
of the content that an SMI uses in persuasive communication
to influence the audience. Factors within this category include
quality, type of post, creativity, and informative or entertaining content. Lastly, audience factors are followers' personal
characteristics that influence how they cope with persuasive
communication, including factors such as attitudes, involvement, and wishful identification.
We identified (n = 34) source factors, (n = 41) content factors, and
(n = 14) audience factors. Source factors are featured in the majority of studies (n = 12), indicating that source-­related factors are
frequently discussed in the literature. Content factors appeared
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FIGURE 5    |    ADO framework.
FIGURE 6    |    Venn Diagram of studied source, content, and audience
factors.
independently (n = 8) times, audience factors appeared alone in
(n = 5) studies, while (n = 1) study did not mention any antecedents.
Some studies attempted to mix factors. For example, source and
content factors (n = 10), source and audience factors (n = 5), and
content and audience factors (n = 2). Notably, no study was found
to incorporate all three factors simultaneously. Figure 6 presents a
visual summary of the patterns identified in our analysis, illustrating that none of the included studies attempted to integrate source,
content, and audience factors into one holistic model.
4.9.2   |   Decisions
The articles in this review showed two distinct decisions of engagement: followers' engagement with SMIs and followers' engagement with brands. Specifically, our findings reveal that
engagement can take diverse forms concerning SMIs. For example, engagement with their posts (Wies et al. 2023), with the platform they use (Hughes et al. 2019), and engagement with the SMIs
themselves (Tafesse and Wood 2021). On the other hand, when it
comes to brands, studies take a consumer/customer perspective
(Syrdal et al. 2023), demonstrating that they engage with branded
content (Chen et al. 2021) and actively contribute to the creation
of branded content (Cheung, Leung, Aw, et al. 2022). Overall, out
of the 43 studies identified in this review, engagement with SMIs
has been studied (n = 24) times, while engagement with brands has
been the focus of (n = 19) studies.
Given the growing scholarly interest in behavioral engagement,
our review aimed to explore various indicators of engagement,
considering the diverse configurations of online platforms.
Specifically, the review indicates that followers' or consumers'
engagement behavior manifests in eight distinct ways: liking,
commenting, sharing, viewing, mentioning, clicking, watching,
and reading. In particular, likes serve as indicators of a follower's
1552
Notably, likes and comments have received the most research
attention (n = 12), and (n = 10) studies have investigated likes,
comments, and shares. Additionally, (n = 2) studies focused on
likes, comments, and views; (n = 2) considered likes and shares;
and (n = 2) studies exclusively focused on likes. In addition,
(n = 1) studied likes, clicks, and shares; only (n = 1) study examined likes, comments, mentions, and clicks; while (n = 1) study
focused on likes, comments, sharing, watching, and reading behaviors. There is only (n = 1) study that specifically concentrated
on sharing. Lastly, in (n = 11) studies, no specific engagement
behaviors or activities were explicitly mentioned or detailed.
Table 2 presents a detailed breakdown of the types of engagement
behaviors studied.
4.9.3   |   Outcomes
Outcomes are the results of decisions (Paul and Benito 2018).
In the context of this review, they signify the consequences of
engagement with SMIs. Out of the 43 articles we reviewed, it
is worth noting that a substantial majority centered their research on engagement as an outcome (see the extensive list in
Appendix S1). However, it is interesting to observe that (n = 17)
of these articles explored outcomes beyond the realm of engagement with SMIs. The review suggests that followers' engagement
will influence their purchase intentions, attitudes, affective
commitment, brand equity, brand expected value, brand online
sales, brand attitude, and trust in branded content. The most frequent outcome was purchasing intention (n = 3).
4.9.4   |   Mediating and Moderating Variables
We also explored the presence of mediating and moderating
variables—factors that enhance our understanding of the relationships between antecedents, decisions, and outcomes. These
mediating and moderating variables add additional layers of
depth to our analysis, shedding light on the nuanced mechanisms and conditions influencing engagement dynamics. The
most common mediating variable was customer brand engagement (n = 4), followed by Parasocial Relationships (n = 2) and
engagement with SMIs (n = 2). Perceptions of SMIs' characteristics were also used as mediating variables, including perceived
authenticity and credibility. Moreover, content characteristics
such as creativity and text length were also included as mediators. (n = 20) articles did not incorporate mediation variables in
their analysis. As for moderators, the most common moderator
variable was the number of followers (n = 3) and brand fit (n = 2).
Content characteristics such as post positivity, length, and content customization were also included as moderating variables,
while followers' demographics such as gender appeared in one
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favorable reception toward content; comments reflect engaged
discussions and conversations prompted by the content; shares
indicate followers actively endorsing and distributing the content across their social networks; viewing represents a passive
engagement with the content; mentioning signifies direct references to the content by followers; clicking demonstrates followers' active interaction with links or prompts within the content;
watching reflects sustained attention given to the content; and
reading denotes a thorough consumption of written material.
Authors (year)
Likes
Comments
✓
✓
Lou et al. (2019)
✓
✓
Argyris et al. (2020)
✓
✓
Valsesia et al. (2020)
✓
Hughes et al. (2019)
Views
Mentions
Click
Shares
Watch
Reads
✓
✓
Jiménez-­Castillo and
Sánchez-­Fernández (2019)
✓
AlFarraj et al. (2021)
Jang et al. (2021)
Chen et al. (2021)
✓
✓
✓
Hudders and De Jans (2021)
✓
✓
✓
Tafesse and Wood (2021)
✓
✓
Shen (2021)
✓
✓
Buvár et al. (2022)
✓
✓
Cheung, Leung, Yang, et al. (2022)
✓
✓
✓
Cheung, Leung, Aw, et al. (2022)
✓
✓
✓
Onofrei et al. (2022)
✓
✓
✓
Duh and Thabethe (2021)
Casaló et al. (2021)
✓
✓
Leung, Gu, Li, et al. (2022)
Wang and Huang (2023)
✓
Tafesse and Wood (2023)
✓
Zhao et al. (2023)
✓
Beheshti et al. (2023)
✓
✓
Cascio Rizzo et al. (2023)
✓
✓
Fan et al. (2023)
✓
✓
Shuqair et al. (2023)
✓
✓
Holiday et al. (2023)
✓
✓
Syrdal et al. (2023)
✓
✓
Wies et al. (2023)
✓
✓
Ren et al. (2023)
✓
✓
Chen et al. (2023)
✓
✓
Abell and Biswas (2023)
✓
Xie-­Carson, Magor, et al. (2023)
✓
Xie-­Carson, Benckendorff, et al. (2023)
✓
✓
Mir and Salo (2024)
✓
✓
✓
✓
✓
✓
✓
Borges-­Tiago et al. (2023)
Gupta et al. (2023)
✓
✓
✓
✓
✓
✓
✓
Roy and Attri (2024)
(Continues)
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TABLE 2    |    Types of engagement behaviors studied.
Authors (year)
Likes
Comments
Yu et al. (2024)
✓
✓
Melnychuk et al. (2024)
✓
✓
✓
✓
Views
Mentions
Click
Shares
Watch
Reads
Lin et al. (2024)
Akhtar et al. (2024)
Agnihotri et al. (2024)
Gu and Duan (2024)
study. It is worth noting that (n = 24) articles did not incorporate
moderation variables in their analysis.
4.9.5   |   Overlaps Across the ADO Framework
Several overlaps are evident across the five sections of the ADO
framework in Figure 5. For instance, credibility is mentioned
under source factors, mediators, and moderators, reflecting its
role as both an inherent attribute of SMIs and a dynamic element of engagement outcomes. Similarly, informational social
influence and normative social influence appear under both audience factors and mediators, underscoring their dual function
in shaping engagement behaviors and mediating their impact
on outcomes. Additionally, parasocial relationships are included
in audience factors, mediators, and moderators, highlighting
their pivotal role in fostering one-­sided emotional connections,
mediating engagement mechanisms, and shaping the context
under which engagement occurs. Moreover, identification and
wishful identification feature in audience factors and mediators, emphasizing their dual role as audience traits that drive
engagement and as mediators that explain how other factors
influence outcomes. These overlaps underline the multifaceted
nature of these constructs but also point to potential redundancies. Clearer distinctions between their roles within each section
would enhance conceptual clarity and minimize repetition, ultimately aiding in a more streamlined understanding of engagement dynamics with SMIs.
4.10   |   Methodological Approaches
Of the 43 articles reviewed, engagement research in the SMI
context has been largely quantitative. Survey-­based approaches
emerged as the most commonly utilized method among the reviewed studies (n = 16). Surveys offer advantages in terms of direct and controlled data gathering. Specifically, they enable the
customization of questions based on research objectives, ensuring a thorough exploration of relevant factors. Additionally, the
inclusion of validated scales and measures enhances the reliability and validity of the collected data (Hair et al. 2019).
Next in line is web-­scraped data (n = 13), which involves collecting secondary data from online sources using automated tools.
Despite this, it is important to address the limitations of relying
on web-­scraped data to evaluate engagement behaviors. While
readily accessible, these metrics primarily reflect the extent of
engagement rather than uncovering the underlying factors that
1554
✓
motivate followers to engage with SMI content. Without exploring these drivers, web-­scraped data may limit the scope of understanding engagement decisions. Moreover, the reliance on
platform-­generated metrics introduces risks, such as the potential for SMIs to fabricate engagement metrics to create a false impression of performance (Leung, Gu, Li, et al. 2022). Thus, while
web-­scraped data provide valuable insights, we believe that it
should not be the sole basis for assessing engagement.
Experiments were used in (n = 4) studies, while mixed methods combining web-­scraped data with experiments appeared in
(n = 6) studies. Additionally, (n = 3) studies used a combination
of focus groups, interviews, and surveys, and (n = 1) study integrated experiments, field tests, and eye-­tracking tests. Notably,
none of the studies relied solely on qualitative methods, such
as in-­depth interviews, to explore engagement determinants
with SMIs.
The data analysis techniques employed across the 43 articles in the SLR exhibit a diverse range of statistical methods.
Specifically, Covariance-­Based Structural Equation Modelling
(CB-­SEM) emerged as the most frequently utilized technique,
appearing in (n = 11) articles. Partial Least Squares Structural
Equation Modelling (PLS-­SEM) is found in (n = 6) articles, offering an alternative Structural Equation Modelling approach
suitable for smaller sample sizes with non-­normal data and formative constructs. Content analysis follows closely, featured in
(n = 5) articles, providing a qualitative means to systematically
analyze textual, visual, or audio content, which is mostly used in
studies adopting web-­scraped data. Moreover, linear regression,
Ordinary Least Squares (OLS) regression, multivariate regression, and Poisson regression each appeared in (n = 2) articles.
Additional techniques, such as Analysis of Variance (ANOVA),
computational linguistic analysis, facial expression analysis,
Analysis of Covariance (ANCOVA), and negative binomial regression, were each featured in (n = 1) articles.
5   |   Discussion
5.1   |   Publication Trends
The notable surge in academic research on engagement with
SMIs began in 2021, as the unprecedented circumstances
brought about by the COVID-­19 pandemic fueled a substantial
increase in engagement with SMIs (Al Khasawneh et al. 2021;
Taylor 2020). This surge also aligns with the significant investments made in influencer marketing, with the market
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TABLE 2    |    (Continued)
In terms of geographic distribution, China leads with the highest
number of studies (n = 10), followed by the United States (n = 5).
This concentration of research in Western and East Asian contexts highlights a significant geographic bias in influencer marketing literature, limiting the generalizability of findings to
other regions. While this focus can be attributed to the advanced
digital ecosystems in these regions, it underscores the need for
broader exploration. Given that cultural differences influence
engagement behaviors, expanding research to underrepresented
regions is essential for uncovering culturally specific engagement strategies (Vrontis et al. 2021; Fowler and Thomas 2023).
For example, Silva, Farias, and Silva et al. (2023) found that individualistic cultures emphasize the independence and success
of SMIs, while collectivist cultures highlight interdependence,
family integrity, and group well-­being. In collectivist contexts,
SMIs who represent cultural values and traditions tend to foster
stronger emotional connections with their followers, promoting
a sense of shared identity and belonging. These cultural differences may influence engagement behaviors, where individualistic cultures often encourage more expressive interactions, such
as commenting, while collectivist cultures might favor less expressive forms, such as liking. Understanding these distinctions
is crucial for tailoring influencer marketing strategies to diverse
cultural contexts and ensuring that engagement efforts resonate
with different audiences.
While previous SLRs suggest that Instagram is the most
widely used platform by SMIs for promoting their content (e.g.,
Kanaveedu and Kalapurackal 2022; Pradhan et al. 2023), our review indicates that Instagram dominates as the most frequently
studied platform (n = 21). This focus may limit the broader understanding of engagement across other platforms. The limited
attention given to platforms such as TikTok, YouTube, and
Snapchat, as well as emerging networks like Xiaohongshu, suggests that much of the existing literature may not fully capture
the diversity of engagement behaviors across different digital
ecosystems. Since platform-­specific features—such as TikTok's
algorithm-­driven discovery or Snapchat's ephemeral content—
can influence how followers interact with SMIs, it is crucial
to explore engagement dynamics across multiple platforms
to understand variations in engagement depth and frequency
(Hazari et al. 2023). Scholars have recommended expanding
research to cover these alternative platforms, as engagement
dynamics could differ significantly based on platform format,
user base, and content-­sharing mechanisms (e.g., Fowler and
Thomas 2023; Pradhan et al. 2023; Agnihotri et al. 2024).
Broadening this scope will contribute to a more comprehensive
understanding of platform-­specific engagement strategies and
their effectiveness in diverse digital contexts.
The review shows a strong focus on travel (n = 7) and fashion
(n = 6) sectors, which are among the most popular industries
for SMIs due to their high visibility and consumer appeal (Zhao
et al. 2023; Roy and Attri 2024). These industries, known for
their visually driven content, are particularly suited to platforms
like Instagram and TikTok, where engaging visuals play a critical role in driving follower interaction. However, this focus
leaves a noticeable gap in research across other industries, such
as technology and healthcare, where engagement strategies
may rely more on informational or educational content rather
than esthetics. Additionally, the review identified a significant
number of studies (n = 15) that did not specify a particular industry, along with several (n = 6) that covered multiple sectors simultaneously. This suggests that influencer marketing
is being applied in a diverse range of domains, many of which
remain underexplored in academic research. For instance, lifestyle SMIs and mommy SMIs (n = 2) often span multiple sectors—such as parenting, wellness, and fashion—requiring more
complex engagement strategies that balance the expectations of
varied audiences (Holiday et al. 2023).
Lastly, the rise of VIs adds a new dimension to the social media
landscape by blending technology with consumer engagement
strategies (Yu et al. 2024). The inclusion of VIs in seven studies highlights their growing importance in the influencer marketing landscape and their potential to reshape how brands
interact with audiences. This trend marks a significant shift
in engagement strategies, blending artificial intelligence with
traditional influencer marketing approaches. While the studies
provide valuable insights into the innovative ways VIs engage
audiences (e.g., Xie-­Carson, Benckendorff, et al. 2023), they also
underscore the need for further research to evaluate their long-­
term effectiveness compared to human SMIs. The prominence
of VIs in these studies reflects their rising relevance in understanding engagement dynamics within the SMI domain, with
their ability to deliver consistent, creative, and scalable engagement solutions making them a noteworthy development in this
evolving field.
5.2   |   Theoretical Insights
The reviewed studies reveal a diverse use of theoretical perspectives, emphasizing the complexity of SMI engagement and
suggesting that engagement behaviors cannot be explained
through a single theoretical lens. Communication theories like
Social Influence Theory (e.g., Akhtar et al. 2024; Tafesse and
Wood 2023) and the Elaboration Likelihood Model (e.g., Syrdal
et al. 2023; Zhao et al. 2023) were common, underscoring the persuasive aspects of SMI engagement and followers' information-­
processing routes. These theories, along with Social Exchange
Theory (e.g., Holiday et al. 2023) and Source Credibility Theory
(e.g., Agnihotri et al. 2024), demonstrate a strong emphasis on
SMIs' attributes (e.g., credibility, attractiveness) as key engagement drivers.
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growing from $9.7 billion in 2020 to $13.8 billion in 2021 and
$16.4 billion in 2022. By the conclusion of 2023, the market
had exceeded expectations, reaching an impressive valuation
of $21.1 billion (Geyser 2023). These statistics underscore
the dynamic and rapidly evolving nature of influencer marketing, making it a key area of interest for both researchers
and businesses. However, in 2024, there has been a noticeable
decline in the number of academic papers focused on engagement with SMIs, which may indicate saturation in certain research areas. Despite this decline, one significant trend has
emerged—the growing attention on VIs (e.g., Lin et al. 2024;
Yu et al. 2024), with an increasing number of studies (n = 7)
focusing on their role and impact. This shift suggests that VIs
may represent the future of influencer marketing, offering
new opportunities for both theoretical exploration and practical application in the evolving digital landscape.
This varied use of theories, as indicated by 13 studies applying
multiple theories, signals an evolving understanding that SMI
engagement is multifaceted, involving elements of communication, credibility, social relationships, and digital interaction.
Expanding theoretical approaches in future research could provide a more comprehensive understanding of the complex drivers behind SMI engagement. In particular, integrating multiple
theoretical perspectives could help bridge gaps in understanding
cognitive, emotional, and behavioral engagement processes, offering a more holistic framework for future studies.
5.3   |   Insights on Engagement Dimensions
While recognizing the significance of cognitive, affective, and
behavioral components in understanding online engagement
(Dessart et al. 2015; Hollebeek et al. 2014), our observation
shows a strong focus on the behavioral aspect in the majority
of included studies (n = 18). Given its importance, research has
begun to examine different drivers of behavioral engagement.
For example, disclosing a post as advertising increases engagement (Shuqair et al. 2023). SMIs with a high number of followers are linked to lower engagement (Wies et al. 2023; Tafesse
and Wood 2021) while following fewer people is linked to higher
engagement (Valsesia et al. 2020). Moreover, SMIs' attributes,
such as credibility (Buvár et al. 2022) and authenticity (Cascio
Rizzo et al. 2023), were also positive drivers of engagement.
Other scholars identified attributes related to the content of
SMIs' such as post length (Fan et al. 2023) and post creativity
(Casaló et al. 2021). Research has also underscored the significance of follower-­related attributes in enhancing behavioral
engagement, including involvement (Borges-­Tiago et al. 2023)
and wishful identification (Cheung, Leung, Aw, et al. 2022; Roy
and Attri 2024). It should be noted that behavioral engagement
has been studied in relation to the platform (Hughes et al. 2019),
SMIs (Tafesse and Wood 2021), and consumers (Holiday
et al. 2023).
In addition to studies focusing on human SMIs, behavioral
engagement has also been explored in the context of VIs. For
example, Mir and Salo (2024) highlighted that visually appealing and credible VI-­generated content drives ad-­click behavior,
while Lin et al. (2024) examined how factors like conversational
1556
tone, autonomy, and responsiveness of VIs impact engagement
through perceived social presence and telepresence. Akhtar
et al. (2024) further demonstrated that both informational and
normative social influences positively affect behavioral engagement with VIs. These findings suggest that while VIs share some
common engagement drivers with human SMIs, their unique,
AI-­driven nature requires further investigation into how these
drivers operate differently.
Some scholars, such as Gu and Duan (2024) Cheung, Leung, Aw,
et al. (2022) and Cheung, Leung, Yang, et al. (2022), conceptualize behavioral engagement as a multidimensional model with
three levels: consuming, contributing, and creating. Consuming
represents the lowest level, where followers engage passively by
viewing, following, or liking an SMI's content. Contributing involves a more active form of engagement, such as commenting
on content, while creating is the highest level, where followers
actively share the SMI's content with their contacts. This tiered
framework provides a structured understanding of engagement
behaviors and could be applied in future research to investigate
engagement patterns across various follower demographics and
platforms. Such a framework could be valuable for future studies aiming to capture the full spectrum of follower interactions
with SMIs.
The findings reveal that while engagement behaviors such as
liking, commenting, sharing, viewing, mentioning, clicking,
watching, and reading have been studied, there is a clear overemphasis on likes and comments (n = 12), which represent low-­
effort interactions. This focus on easily quantifiable metrics
reflects a tendency in the literature to prioritize visible behaviors
over those that may offer deeper insights into audience engagement. Research highlights that each of these behaviors serves
distinct purposes and represents different levels of engagement,
from passive actions like liking to more active behaviors such as
sharing (Li and Xie 2020). For instance, higher-­effort behaviors
like sharing, which indicate active endorsement and a stronger
connection to the content, have only been studied by Leung, Gu,
Li, et al. (2022). Similarly, less-­explored actions like clicking,
mentioning, and reading, which could illuminate more cognitive dimensions of engagement, remain significantly underrepresented. Moreover, the lack of specificity in 11 studies, where
engagement behaviors were not clearly detailed, limits the ability to fully capture and analyze the diverse ways followers interact with SMIs. This fragmented focus on certain behaviors
undermines a more comprehensive understanding of engagement, as it fails to capture the full range of actions followers undertake when interacting with SMIs.
5.4   |   Engagement Factors in Context
The findings demonstrate that while diverse factors have been
examined to understand engagement with SMIs (i.e., source,
content, and audience factors), significant gaps remain in integrating these factors into a comprehensive model. Most reviewed
studies concentrate on one or two of these factors; however, none
fully integrate all three, limiting the ability to capture the holistic
dynamics of SMI engagement. To address this, future research
could explore integrative models that examine the interplay of
source, content, and audience factors simultaneously, thereby
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However, the review highlights gaps where some theories
address only certain engagement elements. For instance,
Parasocial Relationship Theory explores follower–SMI relationships, yet does not encompass the broader contextual factors influencing engagement. Less-­
used theories like Social
Learning Theory and Stimulus–Organism–Response Theory
offer potential for exploring the learning and emotional aspects
of engagement, areas that deserve further research attention.
Notably, Computers as Social Actors Theory and the Uncanny
Valley Theory were employed in virtual SMI studies (e.g., Lin
et al. 2024; Xie-­Carson, Magor, et al. 2023), illustrating how
human-­like interactions with AI SMIs create engagement dynamics similar to those with human SMIs. The limited application of consumer behavior models (e.g., Information Adoption
Model, Multi-­Attribute Attitude Model) also highlights a gap,
suggesting room to further explore how followers' decision-­
making processes impact engagement with SMIs.
Our review also underscores another crucial gap—a limited
exploration of mediators and moderators in the engagement
process. Research in this field need not be confined to a straightforward antecedent–consequence relationship. Instead, it can
benefit from examining the mediating and moderating effects
of various factors. Delving into these mediating and moderating variables holds three advantages. First, it enables a deeper
comprehension of the complex mechanisms underpinning engagement dynamics. Secondly, it provides a more nuanced understanding of the “how” and “why” behind follower–influencer
interactions. Third, it allows for the development of targeted
strategies to enhance engagement with SMIs. Despite the benefits they offer, half of the studies in our analysis did not include
any mediators or moderators. This highlights the need for future
research to delve deeper into the role of these variables in influencing engagement with SMIs.
The analysis of engagement decisions revealed a distinct split between engagement with SMIs versus engagement with brands.
Notably, followers tend to engage more with SMI-­driven organic
content than with branded content, which aligns with research
indicating a preference for content that feels less commercialized. The reason behind the prevalence of studies focusing on
engagement with SMIs rather than brands is that followers usually follow SMIs for entertaining and informing content rather
than watching advertisements (Buvár et al. 2022). Branded
content posted by SMIs is less likely to engage followers (Fan
et al. 2023; Shuqair et al. 2023; Holiday et al. 2023), while organic
posts are generally more memorable and trustworthy (Tafesse
and Wien 2018). In the present-­day context, the prevailing trend
is that the majority of content shared by SMIs is organic and
non-­commercial (Audrezet et al. 2018; Filieri et al. 2023; Tafesse
and Wood 2021). It should be noted that follower–influencer
relationships behave much like consumer–brand relationships
built through engagement (Holiday et al. 2023). Consequently,
understanding the drive that motivates followers to engage with
SMIs consistently is as important as comprehending the engagement between brands and followers. Additionally, while several
behavioral engagement indicators (e.g., likes, comments, shares)
have been explored, certain behaviors such as mentioning, clicking, and reading remain under-­investigated, pointing to a need
for more diverse metrics in future studies to better capture the
complexities of engagement behaviors.
6   |   Theoretical and Practical Implications
This review carries important implications for researchers in
the growing field of influencer marketing, advancing the understanding of engagement mechanisms and enhancing marketing
strategies involving SMIs.
6.1   |   Theoretical Implications
First, through a comprehensive synthesis of existing literature,
this review develops an integrated framework that organizes
engagement-­
related factors, including antecedents, decisions,
outcomes, mediators, and moderators, into a cohesive structure.
By addressing the limitations of prior research, which often focused on source, content, and audience factors independently,
this framework advances a more holistic understanding of engagement. It not only deepens theoretical insights but also provides a structured guide for future research, directing scholars to
new and promising areas within influencer marketing. Second,
the review presents fresh insights into engagement behaviors,
distinguishing between studies that focus on single engagement
types versus those that explore multiple behaviors. Many studies
have concentrated primarily on behavioral engagement, while
cognitive and emotional aspects have received less attention.
Our review encourages a more comprehensive view of engagement types, which can serve as a foundation for future research
to deepen understanding of how various engagement forms
interact and evolve. Third, the insights gained from exploring
the theories, contexts, and research methods in this review can
provide valuable support to future scholars in defining and advancing new research endeavors in the field. Fourth, we have
identified several notable research gaps that offer promising avenues for future researchers. Specifically, we have highlighted
areas with potential for exploration, including antecedents of
engagement, various engagement behaviors, and opportunities for integrated theoretical and methodological approaches.
These identified gaps could serve as valuable starting points for
future studies, contributing to the enrichment and expansion of
the field.
6.2   |   Practical Implications
The projected substantial expansion of influencer marketing,
estimated to reach $69.92 billion by 2029 (Yahoo Finance 2023),
underscores the significance of the practical implications outlined in this study. First, by integrating diverse factors influencing engagement with SMIs, this review offers marketers valuable
insights for crafting more tailored strategies. This integrative
framework enables practitioners to develop campaigns that
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providing a more comprehensive understanding of the engagement mechanism. Previous research emphasizes that these factors collectively carry a significant influence on the effectiveness
of SMI campaigns (Lou et al. 2023; Hudders et al. 2021). Viewing
them in isolation may mistakenly convey a sense of separateness
and mutual exclusivity, potentially misguiding our understanding of the engagement mechanism. For instance, consider a scenario where a follower exhibits an inclination to share creative
and high-­quality content. If we solely attribute this heightened
engagement to content-­related factors, we risk overlooking the
critical influence of other variables, such as the SMI-­specific
characteristics or follower-­specific characteristics, which may
be the actual drivers behind increased engagement behavior.
Without a comprehensive grasp of these factors, we encounter
challenges in pinpointing the specific elements that contribute to the maximization of engagement with SMIs. Although
we acknowledge a single instance where a study explored the
moderating roles of source, content, and audience factors in a
theoretical model (e.g., Leung, Gu, Li, et al. 2022), this primarily focused on moderation rather than considering them as antecedents to followers' engagement with SMIs. Therefore, while
prior studies have contributed valuable insights, there remains
an opportunity for future research to provide a more comprehensive understanding of the key source, content, and audience
factors that stimulate high levels of engagement.
7   |   Future Research Agenda
In response to the gaps identified, we have developed a set of
research questions to guide future exploration in SMI engagement. These questions are organized into key areas, including
context, social platforms, industry, theory, VIs, engagement
behavior, antecedents, mediators, moderators, outcomes, and
methodology. These questions are summarized in Table 3.
7.1   |   Context, Social Media Platforms,
and Industry
The review highlights that the majority of previous studies on
social SMI engagement have been conducted in Western and
East Asian contexts, reflecting an overreliance on these perspectives in influencer marketing research. Expanding this research to include underexplored geographic regions is essential
for developing a more thorough understanding of how cultural
contexts influence engagement behaviors. Such studies would
provide more detailed and reliable insights by capturing the
cross-­cultural differences in how followers respond to and interact with SMIs. For example, followers in individualistic cultures
might be more inclined to express themselves through comments, while those in collectivist cultures might prefer less expressive engagement forms, such as likes. To address these gaps,
future research should explore: How does cultural context differentially influence distinct engagement activities, such as liking,
commenting, and sharing, with SMIs across geographic regions?
While Instagram remains the most studied platform for engagement with SMIs, there is a growing need to examine engagement
behaviors across other social media networks, such as Snapchat
and TikTok. Each platform offers unique features and user dynamics that could influence how followers interact with SMIs.
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For instance, TikTok's short-­form video content and algorithm-­
driven discovery might encourage behaviors like sharing and
commenting, whereas Snapchat's ephemeral nature may foster
more direct interactions or passive viewing. Comparative studies can provide valuable insights into whether engagement behaviors such as liking, commenting, sharing, and viewing differ
across platforms or remain consistent. These studies could also
explore how platform-­specific features shape the evolution of
engagement behaviors over time. Future research should address the question: Do engagement behaviors with SMIs vary
across platforms such as Snapchat, TikTok, and Instagram, and
how do these behaviors evolve with platform-­specific features?
Expanding research into niche industries offers significant potential for understanding the effectiveness of influencer marketing and how engagement behaviors vary across sectors. While
broader industries like travel and fashion have received substantial attention, niche industries may exhibit unique engagement
patterns influenced by their specific audience characteristics
and content requirements. Examining niche industries could
reveal tailored engagement strategies and behaviors, such as
the types of content or interactions most effective for building
connections with highly specialized audiences. To advance this
area, future research should explore: What insights can be gained
from investigating engagement behaviors within niche industries?
7.2   |   Theory
Our review found that eight of the reviewed articles did not explicitly apply or reference established theoretical frameworks
to examine engagement with SMIs. This highlights a gap where
research on SMI engagement often lacks a robust theoretical
foundation. Future studies should consider leveraging established theories to provide deeper insights into the dynamics of
engagement. For example, the Uses and Gratifications Theory
could elucidate why followers engage with SMIs and what
needs they aim to fulfill through such interactions. Similarly,
Social Exchange Theory offers a perspective on how engagement is influenced by the perceived exchange of value or benefits between the influencer and their followers. Moreover,
Cognitive Dissonance Theory could be applied to explore how
followers navigate conflicting information or perceptions associated with SMIs, particularly in cases where their actions
or endorsements contradict follower expectations. To address
these gaps, future research should ask: How can established
theories be applied to enhance our understanding of engagement
with SMIs?
Our review revealed a notable absence of studies dedicated to
developing new theoretical frameworks tailored to comprehensively understand engagement with SMIs. This gap highlights
the need for innovative models that capture the unique dynamics of leveraging SMIs for social media promotion. Existing
frameworks often lack the specificity required to address the
complex interplay of cognitive, emotional, and behavioral factors driving engagement. Future research should prioritize the
development of such models to advance theoretical understanding in this field. Furthermore, integrating multiple theoretical
perspectives within a single investigation offers a promising avenue for enhancing our understanding of engagement dynamics.
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consider source, content, and audience characteristics in a cohesive manner, improving the relevance and effectiveness of influencer collaborations. Second, while engagement enhancement
remains a core objective, marketers continue to face challenges
in identifying suitable SMIs for brand partnerships (Chetioui
et al. 2023; Ren et al. 2023). The insights from this review provide
a structured roadmap for SMI selection, helping practitioners
align SMIs with campaign objectives and target demographics
to increase the likelihood of successful collaborations. Third,
as Instagram remains the most frequently studied platform for
SMI engagement, there is potential value in expanding engagement efforts to other platforms, such as TikTok, where younger
and diverse audiences might engage differently with SMIs. This
approach could enhance marketers' ability to reach target audiences and develop platform-­specific engagement strategies.
Finally, the review underscores the varied purposes of engagement behaviors (e.g., likes, comments, shares), highlighting the
unique value each behavior can bring to campaign objectives.
Understanding these differences allows marketers to optimize
content for desired outcomes, effectively leveraging passive and
active engagement behaviors to maximize campaign impact.
Further, with the rise of VIs, brands have an opportunity to
explore AI-­driven SMI strategies that cater to tech-­savvy audiences, opening new pathways for engagement.
Areas of research
Context, social media platforms, and industry
Theory
Future research agenda
• How does cultural context differentially influence distinct engagement
activities, such as liking, commenting, and sharing, with SMIs across
geographic regions?
• Do engagement behaviors with SMIs vary across platforms such as Snapchat,
TikTok, and Instagram, and how do these behaviors evolve with platform-­
specific features?
• What insights can be gained from investigating engagement behaviors within
niche industries?
• How can established theories be applied to enhance our understanding of
engagement with SMIs?
• What new theoretical frameworks can be developed to understand
engagement with SMIs, and how does the integration of multiple theoretical
perspectives enrich our understanding of these engagement dynamics?
The rise of virtual SMIs
• How do the design and content strategies of VIs influence specific engagement
behaviors, such as liking, commenting, and sharing?
• How do audience demographics and cultural contexts impact engagement
behaviors with VIs, and what factors drive active versus passive engagement
behaviors in different settings?
• What factors, including ethical considerations and source credibility
influence the effectiveness of VIs in fostering long-­term audience engagement?
Understanding engagement behaviors
• How do different engagement behaviors, such as liking, commenting, sharing,
and clicking, uniquely influence the success of influencer marketing campaigns,
and what factors drive these specific behaviors?
Antecedents of engagement
• How do source, content, and audience factors collectively influence
engagement with SMIs, and which factors are most significant in driving high
levels of engagement?
• What role do audience characteristics, such as demographics, self-­efficacy,
and cultural orientation, play in shaping engagement behaviors with SMI
content?
• What negative factors, such as follower fatigue, content saturation, and
verification behavior, hinder engagement with SMIs, and how can they be
mitigated?
• How do different types of SMIs (micro, macro, and mega-­influencers)
influence engagement dynamics, and what strategies are most effective for each
category in driving active engagement?
Mediators and moderators
• How do parasocial relationships and other psychological constructs mediate
the impact of source, content, and audience factors on follower engagement
outcomes?
• What role does gender play in moderating the relationship between
engagement antecedents and engagement outcomes with SMIs?
Outcomes of engagement
• How does engagement with SMIs contribute to outcomes beyond purchase
intentions?
Methodology
• What insights can qualitative methods, such as in-­depth interviews, reveal
about follower motivations and perceptions in SMI engagement, and how do
these insights enhance our understanding of the engagement process?
• What insights can longitudinal studies provide into the evolution of
engagement behaviors towards SMIs, and how do these behaviors change across
life stages, technological shifts, and cultural contexts?
By combining insights from different frameworks, researchers
can explore how various psychological, social, and contextual
factors interact to influence follower engagement. Such integration enables a more holistic approach, uncovering connections
and mechanisms that may remain hidden when theories are applied in isolation. To address these gaps, future research should
ask: What new theoretical frameworks can be developed to understand engagement with SMIs, and how does the integration
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TABLE 3    |    Future research agenda.
7.3   |   The Rise of VIs
VIs differ significantly from human SMIs due to their controlled
and curated nature, offering unique opportunities to optimize
engagement strategies. Unlike human SMIs, VIs are entirely customizable, allowing precise control over their appearance, personality, and content style. These attributes enable businesses to
craft campaigns that leverage specific design elements, such as
realism, interactivity, or creativity, and content strategies, such
as humor, storytelling, or informational posts, to encourage distinct engagement behaviors. For instance, design choices may
influence whether followers are more likely to like, comment, or
share VI content. To better understand these dynamics, we ask:
How do the design and content strategies of VIs influence specific
engagement behaviors, such as liking, commenting, and sharing?
Engagement with VIs also varies across audience demographics
and cultural contexts, with factors such as age, gender, and cultural background shaping how followers interact with these digital personas. For example, younger, tech-­savvy audiences may
be more inclined to actively comment or share VI posts, while
cultural preferences may dictate differing levels of engagement
intensity, such as passive behaviors like liking versus active behaviors like sharing. To explore these variations, future research
should address the question: How do audience demographics
and cultural contexts impact engagement behaviors with VIs, and
what factors drive active versus passive engagement behaviors in
different settings?
Despite their advantages, the role of VIs in influencer marketing raises critical questions that warrant further exploration.
For instance, Agnihotri et al. (2024) found mixed results regarding trustworthiness as a dimension of source credibility. While
trustworthiness was not a consistent driver of engagement, virtual engagement positively mediated behavioral outcomes, suggesting that other factors might compensate for this limitation.
Additionally, ethical concerns surrounding VIs remain a pressing issue. Xie-­Carson, Benckendorff, et al. (2023) emphasized
that user receptivity to VIs improves significantly when transparency is prioritized, particularly in addressing ethical considerations such as the authenticity of interactions and disclosure
of their artificial nature. These findings suggest that, while VIs
offer unique opportunities for engagement through their curated and controlled nature, they may face challenges in achieving long-­
term relational effectiveness comparable to human
SMIs. To address these challenges, future research should explore: What factors, including ethical considerations and source
credibility, influence the effectiveness of VIs in fostering long-­term
audience engagement?
7.4   |   Understanding Engagement Behaviors
There exists a notable gap in existing research, as many studies
fail to distinguish between different types of engagement behaviors on social media platforms, such as likes, comments, shares,
views, and clicks. Treating engagement as a single construct may
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oversimplify its complexity and overlook the fact that different
behaviors serve unique purposes (Li and Xie 2020). For example,
followers may like a post without necessarily commenting on or
sharing it, and each action represents a distinct level of engagement. Prior research highlights these distinctions, with sharing
identified as the most impactful form of engagement due to its
combination of affective approval and cognitive action, followed
by commenting and then liking, which is considered the least
intensive form (Kim and Yang 2017). By understanding the factors that drive each type of engagement behavior, marketers can
better control influencer marketing campaigns, reduce costs,
and enhance campaign effectiveness through targeted strategies (Ren et al. 2023). Given these gaps, future research should
explore: How do different engagement behaviors, such as liking,
commenting, sharing, and clicking, uniquely influence the success
of influencer marketing campaigns, and what factors drive these
specific behaviors?
7.5   |   Antecedents of Engagement
In our review, a prevalent pattern emerged where the antecedents of engagement—namely, source, content, and audience
factors—have frequently been examined in isolation. Rarely
did studies attempt to mix two factors, and none attempted to
encompass all three simultaneously. The integration of source,
content, and audience factors allows us to potentially uncover
situations where certain factors might hold more significance
than others. For example, integrating insights about the attributes of SMIs (source) with content strategies and audience
preferences may provide a more comprehensive understanding
of what drives specific engagement behaviors. Therefore, future
research should explore: How do source, content, and audience
factors collectively influence engagement with SMIs, and which
factors are most significant in driving high levels of engagement?
Whereas source and content factors have garnered some attention in previous research, the role of audience-­
specific
factors remains relatively understudied. Content posted by
SMIs should resonate well with their followers' characteristics (Syrdal et al. 2023; Ren et al. 2023). Understanding these
characteristics that drive followers' engagement is crucial
for unraveling the complex dynamics of engagement. As the
audience of an SMI is an integral part of influencer marketing (Leung, Gu, Li, et al. 2022), more research is needed to
understand the role that audiences play in the persuasion
process. In this context, we advocate for future research to
incorporate culture as a pivotal audience variable, examining variations in individualistic and collectivist cultural orientations (Hofstede 1984) and their impact on engagement in
influencer marketing. Furthermore, a notable void exists in
exploring the link between followers' self-­efficacy and their
engagement decisions. Exploring followers' self-­efficacy, representing their proficiency in utilizing social media platforms
(Hocevar et al. 2014), is important for comprehending its influence on engagement decisions. Additionally, investigating
demographic characteristics such as age, gender, income,
and educational levels provides insights into how different
segments engage with SMI content. Further, followers' interests, hobbies, and motivations for engagement offer nuanced
perspectives on the drivers behind their interaction with SMI
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of multiple theoretical perspectives enrich our understanding of
these engagement dynamics?
Despite significant research on positive engagement drivers,
there is a notable gap in understanding negative factors that may
hinder engagement. Potential obstacles include follower fatigue,
where excessive content from SMIs leads to disengagement,
and content saturation, where similar content across different
SMIs reduces its impact. Additionally, followers' verification
behavior, the tendency to seek validation or confirmation of an
SMI's information, may negatively influence engagement by fostering skepticism. Another underexplored area is the potential
adverse effects of idealized content, such as promoting glamorous lifestyles, which may harm followers' physical health and
psychological well-­being. Future research could explore these
challenges by addressing the question:
What negative factors, such as follower fatigue, content saturation, and verification behavior, hinder engagement with SMIs,
and how can they be mitigated?
Another promising avenue involves understanding engagement
dynamics across different types of SMIs, such as micro, macro,
and mega-­influencers. The literature presents contrasting views
on which category generates higher engagement (Conde and
Casais 2023). Some scholars argue that micro-­influencers, due
to their ability to build close personal relationships with followers, achieve higher engagement (Tafesse and Wood 2021).
Others suggest that macro-­and mega-­influencers, by virtue of
their larger follower bases, yield greater engagement due to their
broader reach and influence (Leung, Gu, Li, et al. 2022). Each
type may employ distinct persuasive strategies, and exploring
their differential impact on follower engagement could provide
valuable insights for refining influencer marketing strategies.
Therefore, future research should consider: How do different
types of SMIs (micro, macro, and mega-­influencers) influence
engagement dynamics, and what strategies are most effective for
each category in driving active engagement?
7.6   |   Mediators and Moderators
Parasocial relationships, defined as one-­sided emotional connections that followers develop with SMIs, represent a key mediator
in the engagement process (Horton and Richard Wohl 1956).
Examining how these relationships mediate the influence of
source, content, and audience factors on engagement outcomes
can provide valuable insights into the psychological mechanisms underlying follower–SMI interactions. Additionally, psychological constructs such as trust and perceived authenticity
play a significant role in shaping these relationships and may
serve as mediators that explain how engagement behaviors are
triggered. Moreover, variables related to follower involvement
and identification with an influencer's content warrant further
exploration, as they could illuminate the pathways through
which engagement is enhanced. To address these points, future
research could explore: How do parasocial relationships and
other psychological constructs mediate the impact of source, content, and audience factors on follower engagement outcomes?
Moderating variables, on the other hand, serve as contextual
factors that influence the strength or direction of relationships
between engagement antecedents and outcomes. Demographic
factors such as gender present an intriguing avenue for research,
as gender-­specific differences in engagement preferences and
behaviors are likely to exist (Chetioui et al. 2023). For example,
gender may moderate the extent to which followers respond to
various content types or influencer characteristics, leading to
differing levels of engagement. Therefore, future studies should
investigate: What role does gender play in moderating the relationship between engagement antecedents and engagement outcomes with SMIs?
7.7   |   Outcomes of Engagement
The outcomes of engagement explored in the reviewed studies
predominantly revolve around purchase intentions, with fewer
studies addressing broader impacts, such as attitudinal shifts or
brand equity. This outcome-­centric approach to purchase behaviors highlights a gap in understanding engagement's indirect
impacts, such as long-­term brand loyalty or community building, both of which are crucial for influencer-­driven marketing
strategies. To address this, future research could benefit from
examining not just direct purchasing decisions but also how engagement with SMIs fosters sustained connections and attitudinal loyalty toward brands. Therefore, future research should
explore: How does engagement with SMIs contribute to outcomes
beyond purchase intentions?
7.8   |   Methodology
It was observed that none of the included studies employed qualitative methods, such as in-­depth interviews, to explore the factors influencing followers' engagement with SMIs. Qualitative
research can provide a deeper understanding of the subjective
experiences, motivations, and perceptions that drive engagement, offering insights that quantitative approaches may overlook (Saunders et al. 2019). By capturing rich, detailed narratives,
in-­depth interviews could help uncover previously unexamined
factors, such as emotional drivers, personal relevance, and
audience-­specific preferences, thereby extending prior research
by incorporating audience-­centric perspectives. This method
could be particularly useful for understanding how followers'
motivations differ across demographics, engagement types (e.g.,
commenting vs. sharing), and cultural contexts. To address this
gap, future research could explore: What insights can qualitative
methods, such as in-­depth interviews, reveal about follower motivations and perceptions in SMI engagement, and how do these
insights enhance our understanding of the engagement process?
Another notable gap is the absence of longitudinal studies
tracking how engagement behaviors with SMIs evolve over
time. Longitudinal research has the unique potential to capture
changes in engagement patterns across different stages of life,
technological advancements, and cultural shifts. For example,
followers' engagement behaviors might differ as they age, or
as new social media features emerge. Tracking these changes
over time would provide valuable insights into the dynamics
of engagement and help marketers understand how to sustain
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content. To address these gaps, we ask: What role do audience
characteristics, such as demographics, self-­efficacy, and cultural orientation, play in shaping engagement behaviors with
SMI content?
8   |   Conclusion
Driven by limitations in previous reviews, this study conducted
a framework-­based systematic review to provide a comprehensive analysis of engagement with SMIs. Our review was guided
by three primary objectives, each aimed at addressing key gaps
in the current literature.
First, we identified publication, theoretical, and methodological
trends, offering insights into how engagement with SMIs has
evolved over time and revealing prevalent theories and methodologies. This foundational overview provides a roadmap for
researchers aiming to address theoretical and methodological
gaps in the field. Secondly, we examined the conceptualization
of engagement within influencer marketing, categorizing it into
cognitive, emotional, and behavioral dimensions. By specifying
the engagement behaviors under study, such as likes, comments,
and shares, our review provides a detailed understanding of engagement types, which can help future research and strategy development. Lastly, we identified key antecedents, consequences,
mediators, and moderators that influence engagement with
SMIs. This integrated framework provides a holistic perspective
that advances the understanding of how various factors work
together to drive engagement.
These findings carry valuable implications for stakeholders in
the influencer marketing industry. Marketers and brand strategists can use the insights into engagement behaviors and influencing factors to design more targeted influencer campaigns.
The framework can guide practitioners in selecting SMIs whose
content, audience, and attributes align closely with campaign
objectives, maximizing engagement and return on investment.
Additionally, understanding distinct engagement behaviors enables brands to fine-­tune their strategies based on desired outcomes—whether that is broadening visibility through shares or
fostering a deeper connection through comments. In conclusion,
this study not only fills critical gaps in the literature but also offers a comprehensive framework that serves as a valuable tool
for both researchers and practitioners in influencer marketing.
By bridging theoretical insights with practical applications, it
provides a foundation for more informed, effective engagement
strategies that resonate with diverse audiences.
9   |   Limitations
We acknowledge several limitations in our methodology that
warrant consideration and provide directions for future research. First, our search was limited to the Web of Science database, which may have restricted the comprehensiveness of our
findings. Additionally, as new studies on engagement with SMIs
may have been published since the completion of this SLR, recent insights and developments might not be represented in our
analysis. Our review also focused solely on studies published
1562
in English, potentially overlooking valuable contributions from
non-­English sources. Furthermore, we concentrated on the domains of business and marketing, excluding studies from fields
such as medicine, education, and ethnic studies, which may offer
unique perspectives on engagement. Geographically, the majority of included studies focused on Western and Asian contexts,
which raise concerns regarding the generalizability of findings
to other regions, such as the Arab world. Finally, we recognize
that our chosen search terms and filtering process might not
have captured all relevant publications on the topic. Addressing
these limitations in future research can help enrich our understanding of engagement with SMIs, broadening its implications
across diverse domains, languages, and cultural contexts.
Data Availability Statement
The data that supports the findings of this study are available in the
Supporting Information material of this article.
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