How social media influencer collaborations are perceived by consumers

Abstract

Within the social media community, influencers engage in a variety of collaborative practices such as tagging, reposting content from, or forming partnerships with other influencers and brands. While such collaborative efforts are a known practice, less is understood about how influencer collaborations affect consumers' perceptions of the partnering influencers, specifically when a status differential exists within the collaboration. We suggest that such collaborative practices, specifically those where the focal influencer has a higher status than the collaborating partner, may help to weaken consumers' perceptions that the influencer's actions are purely self‐focused. A pilot study, analyzing both influencer–influencer collaborations and influencer–brand collaborations, provides evidence that influencers engage in collaborations with other influencers and brands of different status levels. Two studies then support our theorizing that influencers who collaborate with lower‐status influencers are perceived as less self‐serving and more altruistic, while influencers who collaborate with lower‐status brands are only perceived as less self‐serving. This suggests that, for influencers who desire to enhance how consumers perceive them, an effective strategy is to engage in collaborations with either a lower‐status influencer or brand.

Full text

Received: 29 March 2023
|
Accepted: 24 September 2023
DOI: 10.1002/mar.21918
RESEARCH ARTICLE
How social media influencer collaborations are perceived by
consumers
Veronica L. Thomas
1
|Kendra Fowler
2
|Faegheh Taheran
1
1
Department of Marketing, Strome College of
Business, Old Dominion University, Norfolk,
Virginia, USA
2
Department of Management & Marketing,
Williamson College of Business
Administration, Youngstown State University,
Youngstown, Ohio, USA
Correspondence
Veronica L. Thomas
Email: vlthomas@odu.edu
Abstract
Within the social media community, influencers engage in a variety of collaborative
practices such as tagging, reposting content from, or forming partnerships with other
influencers and brands. While such collaborative efforts are a known practice, less is
understood about how influencer collaborations affect consumers' perceptions of
the partnering influencers, specifically when a status differential exists within the
collaboration. We suggest that such collaborative practices, specifically those where the
focal influencer has a higher status than the collaborating partner, may help to weaken
consumers' perceptions that the influencer's actions are purely self‐focused. A pilot
study, analyzing both influencer–influencer collaborations and influencer–brand
collaborations, provides evidence that influencers engage in collaborations with other
influencers and brands of different status levels. Two studies then support our
theorizing that influencers who collaborate with lower‐status influencers are perceived
as less self‐serving and more altruistic, while influencers who collaborate with lower‐
status brands are only perceived as less self‐serving. This suggests that, for influencers
who desire to enhance how consumers perceive them, an effective strategy is to engage
in collaborations with either a lower‐status influencer or brand.
KEYWORDS
altruistic, attribution theory, collaborations, influencer, partnerships, self‐serving,
signaling theory
1|INTRODUCTION
Social media influencers are individuals who use social media to foster
online connections to gain social capital, often with the intent to parlay
that capital into compensation from others who desire to gain an
advantage from the influencer's ability to persuade their followers
(Fowler & Thomas, 2023). A significant amount of literature examines
influencers from a brand strategy perspective, exploring how social
media influencers can best be utilized to promote a brand's message (for
a review see Hudders et al., 2021). However, influencers are also brands
(Brooks et al., 2021;Thomson,2006) and, as such, must engage in
strategies to promote their personal brand to gain followers and obtain
endorsement deals. Research has recently started to focus on the
personal branding strategies of social media influencers (e.g., Lo &
Peng, 2022), often exploring the more positive perceptions consumers
hold about social media influencers (Kim, Duffy, et al., 2021;Kim,Song,
et al., 2021;Schoutenetal.,2020). However, there is evidence that
influencers may not always be perceived positively (Abidin, 2016;Erz
et al., 2018; Valsesia & Diehl, 2022), resulting in the need for influencers
to engage in strategies to attenuate negative perceptions.
Psychol Mark. 2024;41:168–183.168
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© 2023 The Authors. Psychology & Marketing published by Wiley Periodicals LLC.

We focus on exploring strategies that influencers can employ to
mitigate negative perceptions, specifically examining how an influencer's
collaboration with other influencers or brands affects consumers'
perceptions of the influencer. Collaborations are common and influencers
often engage in these partnerships with both other influencer and brand
collaborators of different statuses. For example, the #ShareTheMicNow
campaign is an example of an influencer–influencer collaboration where
influencers with millions of followers collaborated with influencers with
far few followers to expand the reach of Black women's voices. Similarly,
influencer–brand collaborations exist with varying status differentials
such as influencer Ella Mills (Deliciously Ella, 2.1 M Instagram followers)
who has collaborated with well‐established, larger revenue brands like
Neal's Yard Remedies (established in 1981; 137 K Instagram followers)
and newer, smaller revenue brands like Self Care Co. (established in 2018;
39.9 K Instagram followers). We specifically explore status differentials in
collaborations, proposing that such collaborations (influencer–influencer
and influencer–brand) affect consumers' perceptions of the focal
influencer, an issue the extant research has yet to examine.
Drawing on the brand alliance literature (Rao et al., 1999)and
signaling theory (Spence, 1973), we suggest that when influencers
collaborate (with either another influencer or brand) consumers use cues
to ascertain the status of each of the collaborators. When status
differentials exist in a collaboration, we suggest, in line with attribution
theory (Folkes, 1984), that consumers will attempt to determine the
influencer's motivations for entering the collaboration. Thus, the
collaboration has the potential to influence the extent to which
consumers perceive an influencer as self‐serving or altruistic, an effect
that is dependent upon the status differential of the collaborators.
To support our theorizing, we conducted three studies (a pilot
study, Study 1, and Study 2). The pilot study demonstrates the
prevalence of both influencer–influencer and influencer–brand
collaborations, supporting the relevance and need for this research.
Study 1 demonstrates that when an influencer collaborates with
another influencer who has lower status, the focal influencer is
perceived as less self‐serving and more altruistic. However, the Study
2 results differ slightly, finding that an influencer collaborating with a
brand that has lower status will be perceived as less self‐serving;
however, there is no impact on perceptions of altruism.
Theoretically, our findings contribute to research that explores
collaborations that occur between human brands as well as human
and traditional brands (Miguel et al., 2022; Schouten et al., 2020;
Torres et al., 2019), extending the brand alliance literature into the
context of social media influencers and their collaborating partners.
Our results also integrate signaling theory and attribution theory to
demonstrate that consumers employ status cues when evaluating an
influencer's collaboration with either another influencer or a brand.
Managerially, our results provide important insights for influencers
who wish to engage in collaborations with other influencers or brands
as a means to manage their personal brand perceptions. If an
influencer wishes to be viewed as less self‐serving, they should
collaborate with another influencer or brand who has lower status. If
an influencer wishes to be perceived as more altruistic, they should
collaborate with an influencer who has lower status. Importantly,
collaborating with an influencer or brand with equivalent or higher
status will not negatively affect the influencer, but will fail to reduce
self‐serving perceptions and bolster altruistic perceptions.
2|LITERATURE REVIEW
2.1 |Social media influencers as brands
Extant literature recognizes that people can be brands (Thomson, 2006)
and while social media influencers often promote more traditional
brands (i.e., influencer marketing), social media influencers are also their
own brands (Brooks et al., 2021). The academic literature has started to
recognize influencers as human brands and explore how influencer
actions affect outcome variables germane to the influencer (e.g.,
attitudes toward, perceptions of, and engagement with the influencer).
Indeed, research examines how influencers can manage consumers'
perceptions by engaging withtheirfollowers(Lo&Peng,2022)or
participating in prosocial behaviors (Thomas & Fowler, 2023).
Existing literature often highlights the perceived desirability of
influencers, especially in comparison to celebrity endorsers (Kim, Song,
et al., 2021;Schoutenetal.,2020). Research, though, fails to consider that
consumers may not always perceive influencers positively. Indeed,
influencers, as compared to everyday social media users, are more likely
to be narcissistic and have status‐seeking tendencies (Erz et al., 2018),
and these aspects of influencers are perceived by some consumers as
indicators of influencers' vanity (Abidin, 2016). Further, many of the
activities in which influencers typically engage (e.g., posting about
products) can elicit negative impressions of the poster (Valsesia &
Diehl, 2022). Thus, influencers' efforts to gain social capital, influence
followers, and earn compensation may elicit negative consumer percep-
tions. To more concretely support this assertion, we conducted a small
study
1
which shows consumers perceive influencers as manipulative,
untrustworthy, and narcissistic. Thus, as brands themselves, such negative
perceptions should be cause for concern for social media influencers.
2.2 |Brand alliances
We propose that, by collaborating with another influencer or a brand,
influencers may be able to mitigate negative perceptions and
enhance positive perceptions. Such collaborations represent a brand
alliance that occurs when “two or more brand names are presented
jointly to the consumer”(Rao et al., 1999, p. 259). Just as traditional
brands can form alliances with each other, research demonstrates
that human brands also form alliances for promotional purposes
(Fowler & Thomas, 2019; Kupfer et al., 2018; Nascimento et al., 2020).
1
Three one‐sample ttests, conducted using data collected from the Connect CloudResearch
platform (n= 60; M
age
= 44.50, SD
age
= 13.14, 48% male), demonstrate that consumers'
perceptions of influencers as manipulative (Bock & Thomas, 2023;α= 0.89; M= 4.91,
SD = 1.31; t(59) = 5.36, p< 0.001), untrustworthy (Ohanian, 1990;α= 0.97; M= 4.90,
SD = 1.35; t(59) = 5.15, p< 0.001), and narcissistic (M= 5.32, SD = 1.61; t(59) = 6.33,
p< 0.001) were significantly above the midpoint (4.0) of the scale.
THOMAS ET AL.
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When social media influencers tag another brand or influencer,
repost content from a brand or influencer, or form creative
partnerships, these represent a form of brand alliance where “firm
(s) coordinate marketing activities to communicate value for two
separate brand resources”(Newmeyer et al., 2018, p. 280). Brand
alliances can vary in form, with some alliances representing close
integrations and others looser associations (Fowler & Thomas, 2019;
Newmeyer et al., 2018; Rao & Ruekert, 1994).
For both influencer–influencer and influencer–brand collaborations,
some are longer, more formalized partnerships whereas others are more
informal such as a casual mention or tag in a social media post. For
example, Khaby Lame, a Senegalese‐born Italian social media influencer
and long‐time Hugo Boss brand ambassador, recently announced a
capsule collection with the fashion house that features apparel with a
logo of Khaby's likeness (Hugo, 2023). This would represent a longer,
more formalized collaboration between an influencer and brand.
Conversely, the #ShareTheMicNow campaign, an Instagram initiative
where Black female influencers “took over”the Instagram account of
White female influencers for a single day represents a more abbreviated
example of an influencer–influencer collaboration.
While brand alliances can occur between two brands of similar
levels of equity, brand alliances often form between two brands with
equity differentials. Such partnerships have beneficial effects on the
lower‐equity brand as perceptions of the lesser‐known brand shift to
more closely align with those of the well‐known brand (Gammoh
et al., 2006; Levin & Levin, 2000; Mohan et al., 2018). Rao and
Ruekert (1994) warn that such alliances should be entered into
thoughtfully, however, as a partnering brand may choose to act
opportunistically rather than for the good of the alliance.
2.3 |Status signals
In the context of social media influencers, the categorization of a
high‐equity or low‐equity partner is likely determined by perceptions
of the influencers' level of influence or status (the common currency
of social media influencers) and is conveyed to consumers via various
social media metrics such as number of followers or engagement
rates (De Veirman et al., 2017). Signaling theory provides a
theoretical explanation of how the process works. Originally
developed to understand the dynamics between individuals who
engage in an exchange with asymmetrical information (Spence, 1973),
signaling theory suggests that extrinsic cues can be used to
communicate information to reduce perceived uncertainty (Wells
et al., 2011). Signals can be sent to convey information that is not
readily observable such as the qualities and effectiveness of social
media influencers in general (Hugh et al., 2022). Consumers can use
the numbers displayed for a specific post (e.g., likes, comments) or in
an influencer's bio (e.g., number of followers, number of people the
influencer is following, number of posts) to ascertain an influencer's
status. Similarly, brands can also signal status via social media cues
(Lee, 2021; Li & Shin, 2023) as well as other metrics such as their size
or revenues (Shepherd et al., 2015).
2.4 |Attribution theory
We suggest that when an influencer engages in a collaboration with
another influencer or brand, consumers' perceptions of the focal
influencer will vary based on whether the collaborating partner
(either another influencer or brand) has higher or lower status.
Attribution theory suggests that consumers make inferences about
the world around them to explain or make sense of events
(Folkes, 1984). Such attributions often take the form of inferences,
whereby consumers attempt to determine the motives for another's
actions; this, in turn, affects their perceptions of that individual. As
influencers are motivated to enhance their sphere of status, we
examine how collaborations affect consumers' attributions that the
influencer is self‐serving and altruistic. Although they are related,
these attributions have been shown to operate independently (e.g.,
Reinhard et al., 2006; Siem & Stürmer, 2019; Wei et al., 2020). Self‐
serving attributions are perceptions that an individual is motivated by
a desire to obtain a reward, while altruistic attributions are
perceptions that an individual is motivated by a desire to benefit
another (Ellen et al., 2000). The two may occur in tandem, whereby
an increase in one suggests a decrease in the other. For example, an
action might be perceived to be motivated by a desire to obtain a
reward at the expense of another (leading to perceptions that the
individual is self‐serving and not altruistic), or an action might be
perceived to be an act of kindness, motivated solely by a desire to
help another at the potential the expense of their own self‐interest
(leading to perceptions of altruism, but not self‐serving). Self‐serving
and altruistic attributions may also be independent appraisals. For
example, an individual might be engaged in an action that could be
perceived as self‐serving, but not be concerned with the impact on
another; or the individual's action might be perceived as a willingness
to help another without considering the impact on themselves. In the
context of our research, we suggest the two appraisals will work in
tandem in influencer–influencer collaborations, and independently in
influencer–brand collaborations.
3|HYPOTHESIS DEVELOPMENT
3.1 |Influencer–influencer collaborations
As supported by attribution theory (Folkes, 1984), when an
influencer engages in a collaboration with another influencer,
consumers are likely to make inferences about this decision.
Specifically, consumers are likely to assess whether the influencer's
actions for entering the collaboration are self‐serving (i.e., the
influencer wants to benefit the self) or altruistic (i.e., the influencer
wants to help their collaborator). We suggest that perceptions of the
focal influencer as self‐serving and altruistic will be dependent upon
whether they have higher or lower status than the influencer with
whom they are collaborating. If an influencer collaborates with
another influencer who has lower status, the focal influencer may be
able to reduce self‐serving perceptions and enhance altruistic
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perceptions. This theorizing is supported by the brand alliance
literature which demonstrates that a lesser‐known brand is most
likely to reap benefits from a partnership (Gammoh et al., 2006; Levin
& Levin, 2000; Mohan et al., 2018). This suggests a higher‐status
influencer collaborating with a lower‐status influencer is unlikely to
benefit while the lower‐status influencer is likely to benefit. Previous
research also demonstrates that entities are less likely to be
perceived as self‐serving when they engage in actions where they
do not stand to greatly benefit (Szykman et al., 2004) as is the case
when an influencer partners with a lower‐status influencer. Finally,
research shows that when one's actions benefit others or require
more effort, then they are perceived as more altruistic (Langan &
Kumar, 2019; Miotto & Youn, 2020; Rifon et al., 2004). Thus, by
collaborating with a lower‐status influencer, the focal influencer is
less likely to obtain a reward, thereby reducing self‐serving
perceptions, and more likely to benefit their collaborator, enhancing
altruistic perceptions. Formally:
H1a. An influencer who collaborates with a lower‐status
influencer will be perceived as less self‐serving.
H1b. An influencer who collaborates with a lower‐status
influencer will be perceived as more altruistic.
3.2 |Influencer–brand collaborations
Similar to influencer–influencer collaborations, when an influencer
partners with a brand, consumers will make inferences about the
influencer's motivations (Folkes, 1984), affecting the extent to which
consumers perceive the influencer as altruistic and self‐serving.
Consumers are usually aware that brands typically incentivize such
collaborations. As such, the collaborations are likely viewed as
business transactions, not altruistically motivated acts. Therefore, we
anticipate a null effect on perceptions of altruism. However, when an
influencer collaborates with a lower‐status brand, perceptions that
the influencer is self‐serving are likely to be reduced. This is based on
the brand alliance literature which finds that a well‐known partner
reaps fewer rewards than a lesser‐known partner (Gammoh
et al., 2006; Levin & Levin, 2000; Mohan et al., 2018). Thus, when
a higher‐status influencer collaborates with a lower‐status brand,
consumers will perceive that the influencer is not likely to advance
their career (e.g., enhance their status) through such a collaboration,
while the brand is likely to benefit via their affiliation with the higher‐
status influencer. Therefore, by entering such collaboration, a higher‐
status influencer is likely to be perceived as less self‐serving (see
Figure 1for predicted effects). Formally:
H2. An influencer who collaborates with a lower‐status
brand will be perceived as less self‐serving.
4|PILOT STUDY
The proposed hypotheses are predicated upon the assertion that
influencers collaborate with other influencers and brands and that
such collaborations are not always equivalent in terms of the
collaborating partners' level of status. To determine if such variations
exist in influencer–influencer and influencer–brand collaborations,
we conducted a pilot study examining 622 influencer–influencer
FIGURE 1 Overview of studies.
THOMAS ET AL.
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collaborations and 1347 influencer–brand collaborations on Insta-
gram. See Figure 1for an overview (purpose, design, and results) of
each study.
4.1 |Sample
The social media context employed is Instagram as it is popular
among users, brands, and influencers. Indeed, Instagram has over 2
billion active users (Newberry, 2023) and over 200 million businesses
on its platform (Meta, 2023), and is recognized as an important
platform for social media influencers (Geyser, 2023).
To determine the sample of influencers, we reviewed the existing
literature and, based on precedent (Boerman & Müller, 2022), set the
criteria of collecting data for 50 social media influencers and their
corresponding influencer and brand collaborations over a 6‐month
period (October 19, 2021, to April 19, 2022). We started with a list of
50 social media accounts that was previously employed by Boerman
and Müller (2022). Upon examination of the list, 13 accounts were
removed as they were noninfluencer (i.e., traditional brand) accounts
(n= 4), non‐English speaking accounts (n= 5), private accounts (n= 2),
and accounts without posts during the specified timeframe (n= 2). To
obtain the predetermined number of 50 influencers, we used a
snowball selection process with an emphasis on diversifying our list
of influencers in terms of people of color, men, and influencers who
had a smaller number of followers (less than 1 million). Thus, we
started with Alicia Tenise (33,000 followers) and looked at whom she
followed, selecting only accounts of individuals engaging in influencer
activity (self/brand promotion) with a preference toward those with
smaller follower counts and diversifying the list (see Table 1for the
final list of 50 influencers).
4.2 |Procedure
Data collection was a four‐step process. First, using data extraction
tools from Phantombuster, we scraped the Instagram posts made
during the designated 6‐month period for each of the 50 influencers.
This resulted in a total of 10,638 posts, of which 6,814 tagged at least
one other social media account. For the purposes of this research, a
post was deemed as depicting a collaboration if it tagged another
social media account.
The second step was to categorize the tagged accounts as either
another influencer or a brand. After making this determination, we
were left with 878 unique influencer–influencer collaborations (note
that some influencers tagged the same influencer across multiple
posts and are, therefore, not duplicated in the resulting data set) and
1,868 unique influencer–brand collaborations (note that some
influencers tagged the same brand across multiple posts and are,
therefore, not duplicated in the resulting data set). Table 1includes
the number of unique influencer–influencer collaborations and
unique influencer–brand collaborations for each of the 50 focal
influencers.
The third step was to indicate the status of the focal influencer
and their collaborators. Status was operationalized using the number
of followers as research suggests that as the number of followers
increases, cultural capital and the perceived value of the influencer
increases (Campbell & Farrell, 2020). Therefore, we collected the
number of followers for each of the 50 focal influencers and
the number of followers for each of the 878 influencers and each of
the 1,868 brands tagged by one of the focal influencers.
The final step was to provide an additional means for
categorizing number of followers. Thus, for the influencers (both
partnering and focal), we used Campbell and Farrell's (2020)
taxonomy to categorize each influencer based on number of
followers: nanoinfluencers (<10,000 followers), microinfluencers
(10,000–100,000 followers), macroinfluencers (100,001–1 million
followers), and mega‐influencers (>1 million followers). While this
taxonomy was developed for influencers, for comparability, we
similarly categorized brands as having a small (<10,000 followers),
medium (10,000–100,000 followers), large (100,001–1 million
followers), or extra large (>1 million followers) following. We then
compared the categorization of the focal influencer to the
partnering influencer or brand and cataloged the percentage of
collaborations where the focal influencer partnered with a lower‐
status collaborator (see columns 4 and 6 in Table 1, respectively).
4.3 |Results
For the analysis, influencers who had an exceptionally high number of
collaborations were removed so as not to unduly skew the results.
Specifically, for the influencer–influencer collaboration data, the
average number of influencer–brand collaborations was 17.56
(SD = 27.38). Therefore, we removed two influencers whose number
of brand collaborations were two standard deviations above the
mean. These influencers had 91 and 165 collaborations with other
influencers accounting for 10.36% and 18.79%, respectively, of the
total number of influencer–influencer collaborations. For the
influencer–brand collaboration data, the average number of
influencer–brand collaborations was 37.36 (SD = 56.12). Thus, two
influencers were again removed from the analysis as one had 233
brand collaborations and the other had 288 brand collaborations.
Collectively, the number of brand collaborations these influencers
accounted for was 27.89%, supporting our conjecture that they
would have disproportionately affected the analysis. Removal of the
outliers resulted in a final sample of 622 influencer–influencer
collaborations and 1347 influencer–brand collaborations.
4.3.1 |Influencer–influencer collaborations
As previously noted, two influencers were not included in this
analysis as they were outliers, and five influencers did not have any
influencer–influencer collaborations during the period of analysis. Of
the influencers who qualified for analysis (n= 43), the majority of the
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TABLE 1 Pilot study: Sample description for influencer collaborations.
Account
Number of
followers
# of Influencer
collaborations
% of collaborations FI
followers > PI followers
# of brand
collaborations
% of collaborations FI
followers > Brand followers
deboracornetta 1049 1 0 0 n/a
lrsbrwr 1183 0 n/a 1 0
wh1telightning
a
1461 4 50 11 9.1
Misskaayle 2029 0 n/a 0 n/a
Arjunvsampath
a
2347 17 11.8 17 17.6
priscillajerina 3114 0 n/a 0 n/a
alexisbakerrr 4819 5 60 26 7.7
myrhalyn 9119 3 66.7 7 71.4
mayamchenry
a
11,800 15 33.3 15 13.3
aboxofsweets 22,200 2 100 14 21.4
glennymah 24,200 2 100 7 71.4
balancedles
a
30,700 6 50 31 38.7
aliciatenise
a
33,300 4 25 87 23
rienwelsink 35,500 1 0 21 33.3
summerhopechamblin
a
37,700 11 90.9 21 9.5
lisannede_bruijn 42,200 17 88.2 46 41.3
tristanwalker
a
43,000 8 62.5 8 62.5
hithapalepu
a
57,500 29 55.2 84 35.7
jonaskautenburger 69,500 3 100 1 100
berosa_gogreen 81,800 9 88.9 62 45.2
mr. sangiev
a
92,300 13 69.2 29 58.6
leanneliveshealthy 109,000 0 n/a 27 96.3
serdi_kay 122,000 15 100 18 66.7
iqbalgran 177,000 1 0 66 27.3
kinyaclaiborne
a
221,000 49 57.1 288 Outlier
theserenagoh
a
255,000 35 74.3 117 52.1
maryljean 300,000 1 100 62 45.2
elaisaya 315,000 2 50 42 31
giarogiarratana 411,000 4 50 7 57.1
timorworld 471,000 20 80 12 83.3
vivianhoorn 572,000 39 82.1 142 74.6
breadbyelise 751,000 0 n/a 0 n/a
annanooshin 963,000 19 100 35 60
alexlange 1,800,000 28 78.6 13 61.5
morganharpernichols
a
1,900,000 14 100 12 83.3
lethalshooter
a
2,000,000 165 Outlier 233 Outlier
kaihavertz29 4,500,000 13 53.8 2 0
ijessewilliams 7,600,000 36 97.2 20 90
(Continues)
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collaborations skewed toward the focal influencer having more
collaborations with a lower‐status influencer (i.e., an influencer with
fewer followers). Indeed, 76.7% (n= 33) of the focal influencers
engaged predominantly in collaborations with lower‐status
influencers—meaning that over 50% of the time, the focal influencer
had a higher number of followers (i.e., higher status) than the
collaborator, see the fourth column in Table 1.
Examining the categorical data (nano, micro, macro, and mega
categorizations), a crosstab analysis was conducted, see Table 2. One
hundred sixty‐nine (27.17%) of the collaborations occurred between
influencers with the same status levels. The remaining collaborations
(n= 453; 72.83%) represented partnerships between influencers with
different levels of status. Specifically, there were 92 (14.79%) mega‐
macrocollaborations, 85 (13.67%) mega‐micro collaborations, 76
(12.22%) mega‐nano collaborations, 72 (11.58%) macro–micro
collaborations, 66 (10.61%) macro‐nano collaborations, 62 (10.0%)
micro‐nano collaborations.
4.3.2 |Influencer–brand collaborations
For the influencer–brand analysis, two influencers were excluded as they
constituted outliers and four influencers did not have any brand
collaborations during the period of analysis, resulting in 44 influencers
who qualified for inclusion. The majority of the collaborations skewed
toward the focal influencer having more partnerships with a lower‐status
brand (i.e., a brand with fewer followers). Specifically, 61.3% (n= 27) of
the influencers engaged in brand collaborations where, over 50% of the
time, the influencer had a higher number of followers than the
collaborating brand, see the last column in Table 1.
TABLE 1 (Continued)
Account
Number of
followers
# of Influencer
collaborations
% of collaborations FI
followers > PI followers
# of brand
collaborations
% of collaborations FI
followers > Brand followers
lizgillz 13,800,000 17 94.1 7 71.4
samsmith 14,600,000 4 100 2 100
chiaraferragni 26,800,000 91 Outlier 86 94.2
nickjonas 32,300,000 24 95.8 18 94.4
chrissyteigen 37,500,000 30 100 36 97.2
vanessahudgens 45,000,000 54 98.1 67 98.5
milliebobbybrown 48,300,000 11 100 16 100
zacefron 52,400,000 5 100 5 100
justintimberlake 64,400,000 3 100 1 100
shawnmendes 67,800,000 16 100 7 85.7
badgalriri 127,000,000 5 100 8 100
kendalljenner 232,000,000 27 92.6 31 100
Abbreviations: FI, focal influencer; PI, partnering influencer.
a
Not in Boerman and Muller's original list.
TABLE 2 Pilot study crosstabulation: FI's status and PI's status.
FI
PI Nano Micro Macro Mega Total
Nano
Count 12 56 56 74 198
% within PI 6.1 28.3 28.3 37.4 100%
% within FI 40.0 46.7 30.3 25.8 31.8%
Micro
Count 6 38 51 80 175
% within PI 3.4 21.7 29.1 45.7 100%
% within FI 20.0 31.7 27.6 27.9 28.1%
Macro
Count 10 21 55 69 155
% within PI 6.5 13.5 35.5 44.5 100%
% within FI 33.3 17.5 29.7 24.0 24.9%
Mega
Count 2 5 23 64 94
% within PI 2.1 5.3 24.5 68.1 100%
% within FI 6.7 4.2 12.4 22.3 15.1%
Total
Count 30 120 185 287 622
% within PI 4.8% 19.3% 29.7% 46.1% 100%
% within FI 100% 100% 100% 100% 100%
Abbreviations: FI, focal influencer; PI, partnering influencer.
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A crosstab analysis was also conducted to examine the
categorical variables for influencer (nano, micro, macro, and mega)
and brand (small, medium, large, and extra‐large) status. The results
show that 444 (32.96%) of the influencer–brand collaborations were
between influencers and brands with the same status levels. The
remaining collaborations (n= 903; 67.04%) represented partnerships
differing in status. Specifically, there were 254 (18.86%) mega‐large/
macro‐extra‐large collaborations, 159 (11.80%) mega‐medium/extra‐
large‐micro collaborations, 42 (3.12%) mega‐small/extra‐large‐nano
collaborations, 297 (22.05%) macro‐medium/micro‐large collabora-
tions, 79 (5.86%) macro‐small/nano‐large collaborations, 72 (5.35%)
micro‐small/nano‐medium collaborations (see Table 3).
4.4 |Discussion
The goal of the pilot study was to demonstrate that influencers
engage in collaborations with other influencers and brands who have
different status levels. The results of the pilot study indicate that
influencer collaborations are comprised of varying status structures,
regardless of whether their collaborating partner is another
influencer or a brand. In addition to supporting the contention that
status differentials exist in collaborations, our initial step in the
procedure for the pilot study (determining the total number of posts
and the number of posts where at least one other social media
account was tagged), suggests that collaborative practices are
relatively commonplace. Of the 10,638 posts that were collected,
64.05% (n= 6,814) tagged another social media account, lending
further credence to the need for this research.
5|STUDY 1
Study 1 tests the conjecture that when an influencer (focal
influencer) collaborates with a lower‐status influencer (partnering
influencer), consumers will perceive the focal influencer as less self‐
serving (H1a) and more altruistic (H1b). As with the pilot study, status
is operationalized using number of followers. Study 1 employs a 2
(Focal Influencer Status: lower, higher) × 2 (Partnering Influencer
Status: lower, higher) between‐subjects design with self‐serving and
altruistic perceptions as the dependent variables.
5.1 |Procedure
Using Amazon's Connect CloudResearch platform, 200 individuals
(M
age
= 42.14, SD
age
= 12.15; 49% male) were recruited and compen-
sated. After electing to participate, they opened a link to an online
survey that was administered through Qualtrics. The survey was
open for 3 days, but once participants started the survey it had to be
completed in one sitting.
After opening the survey and providing consent, participants
viewed a fictitious news article. The article was used to manipulate
both the focal and partnering influencers' status and, as such,
announced an upcoming collaboration between two fictitious
influencers and provided a description of each influencer. The use
of fictitious influencers is consistent with previous research and
reduces issues associated with pre‐existing attitudes and familiarity
(Kim, Duffy, et al., 2021; Park et al., 2021). Participants were
randomly assigned to both a focal influencer condition (lower‐status,
higher‐status) and a partnering influencer condition (lower‐status,
higher‐status). For both the focal influencer and partnering influen-
cer, status was manipulated via the number of followers (Focal
influencer: lower‐status condition: 2,700 followers, higher‐status
condition: 86,000 followers; partnering influencer: lower‐status
condition: 2,600 followers, higher‐status condition: 87,000
followers).
After viewing the stimuli, participants were asked to focus only
on the focal influencer and rate their perceptions of the influencer as
self‐serving and altruistic. Both self‐serving and altruistic perceptions
were measured using three items for each construct (Siem &
Stürmer, 2019) and were rated on a one (strongly disagree) to seven
(strongly agree) scale. Specifically, self‐serving perceptions (α= 0.86)
were measured using the items: “The influencer wants to use this
TABLE 3 Pilot study crosstabulation: FI's status and partnering
brand's status.
FI
Partnering brand Nano Micro Macro Mega Total
Small
Count 19 61 71 18 169
% within brand 11.2 36.1 42.0 10.7 100%
% within FI 30.6 15.4 12.7 5.4 12.5%
Medium
Count 11 122 156 86 375
% within brand 2.9 32.5 41.6 22.9 100%
% within FI 17.7 30.7 28.0 26.0 27.8%
Large
Count 8 141 180 104 433
% within brand 1.8 32.6 41.6 24.0 100%
% within FI 12.9 35.5 32.3 31.4 32.1%
Extra‐large
Count 24 73 150 123 370
% within brand 6.5 19.7 40.5 33.2 100%
% within FI 38.7 18.4 26.9 37.2 27.5%
Total
Count 62 397 557 331 1347
% within brand 4.6% 29.5% 41.4% 24.6% 100%
% within FI 100% 100% 100% 100% 100%
Abbreviation: FI, focal influencer.
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collaboration for her own publicity,”“The influencer expects benefits
for her own career from this collaboration,”and “The influencer
wants this collaboration to impress people.”Altruistic perceptions
(α= 0.89) were measured using the items: “The influencer is trying to
give something back to the partnering influencer,”“The influencer
considers it important to help the partnering influencer,”and “The
influencer wants to help the partnering influencer gain followers.”
Demographic information was collected.
5.2 |Results
5.2.1 |Self‐serving perceptions
A two‐way analysis of variance (ANOVA) with focal influencer status
and partnering influencer status as the independent variables and
self‐serving perceptions as the dependent variable was conducted.
The results show a significant interaction (F(1, 196) = 6.70, p= 0.010)
(Figure 2a). To examine the combination of focal influencer and
partnering influencer status conditions that significantly affect self‐
serving perceptions, we ran a Tukey multiple comparison of means
analysis. The results show that when a collaboration occurs between
a higher‐status focal influencer and a lower‐status partnering
influencer, the focal influencer is perceived as significantly less self‐
serving (M= 5.05, SD = 1.35) than when the collaboration occurs
between a higher‐status focal influencer and higher‐status partnering
influencer (M= 5.94, SD = 1.00; p< 0.001), or a lower‐status focal
influencer and lower‐status partnering influencer (M= 5.72, SD =
0.90; p< 0.01), or a lower‐status focal influencer and higher‐status
partnering influencer (M= 5.84, SD = 0.87; p< 0.01). There were no
significant differences (all p> 0.70) in self‐serving perceptions
between the latter three combinations (i.e., higher‐status focal
influencer and higher‐status partnering influencer, lower‐status focal
influencer and lower‐status partnering influencer, and lower‐status
focal influencer and higher‐status partnering influencer), see Table 4.
Collectively, these results support H1a which states that when an
influencer (i.e., the focal influencer) collaborates with a lower‐status
influencer (i.e., the partnering influencer), the focal influencer will be
perceived as less self‐serving. Indeed, when the higher‐status
influencer partnered with an influencer who had lower status, self‐
serving perceptions were significantly reduced (M= 5.05, SD = 1.35).
In addition to the significant interaction, the two‐way ANOVA
revealed both a significant effect of focal influencer status
(F(1, 196) = 3.79, p= 0.053) and partnering influencer status
(F(1, 196) = 11.75, p< 0.001) on self‐serving perceptions. Specifically,
self‐serving perceptions were higher in the lower‐status focal
influencer condition (M= 5.79, SD = 0.89) as compared to the
higher‐status focal influencer condition (M= 5.48, SD = 1.27).
The focal influencer's self‐serving perceptions were also higher in
the higher‐status partnering influencer condition (M= 5.89, SD =
0.93) as compared to the lower‐status partnering influencer condition
(M= 5.38, SD = 1.19).
5.2.2 |Altruistic perceptions
Atwo‐way ANOVA with the focal influencer and partnering
influencer as the independent variables and altruistic perceptions
as the dependent variable was conducted. The results show a
significant interaction (F(1, 196) = 3.64, p= 0.058) (Figure 2b). To
examine the interaction, we ran a Tukey multiple comparison of
means analysis. The results show that when the focal influencer has
high status and the partnering influencer has low status (M=5.09,
SD = 1.24), the focal influencer is perceived as significantly more
altruistic than when the focal influencer has high status and the
partnering influencer has high status (M=4.13,SD=1.31;p< 0.01),
(a) (b)
FIGURE 2 The interactive effect of focal influencer status and partnering influencer status on (a) self‐serving and (b) altruistic perceptions.
FI, focal influencer; PI, partnering influencer.
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the focal influencer has low status and the partnering influencer has low
status (M= 4.41, SD = 1.07; p< 0.05), and the focal influencer has low
status and the partnering influencer has high status (M=4.12,
SD = 1.40; p< 0.001). There were no significant differences (all
p> 0.60) in altruistic perceptions between the latter three combinations
(i.e., high‐status focal influencer and high‐status partnering influencer,
low‐status focal influencer and low‐status partnering influencer, and
low‐status focal influencer and high‐status partnering influencer), see
Table 4. These results support H1b as the higher‐status focal influencer
was perceived as more altruistic when collaborating with the lower‐
status partnering influencer.
In addition to the significant interaction, the two‐way ANOVA
showed a significant effect of both focal influencer status
(F(1, 196) = 3.79, p= 0.053) and partnering influencer status
(F(1, 196) = 12.22, p< 0.001) on altruistic perceptions. Specifically,
altruistic perceptions were higher when the focal influencer had high
status (M= 4.62, SD = 1.36) as compared to low status (M= 4.27,
SD = 1.24). Perceptions of the focal influencer as altruistic were also
higher when the partnering influencer had low status (M= 4.75,
SD = 1.20) as compared to high status (M= 4.13, SD = 1.35).
5.3 |Discussion
The results demonstrate that when an influencer (higher‐status focal
influencer condition) partners with a lower‐status influencer (lower‐
status partnering influencer condition) consumers are less likely to
perceive the influencer as self‐serving and more likely to perceive the
influencer as altruistic. These results also suggest that consumers
tend to perceive influencers as relatively self‐serving and not overly
altruistic. A follow‐up paired samples ttest shows that, on average,
participants perceive influencers as more self‐serving (M= 5.63,
SD = 1.10) than altruistic (M= 4.44, SD = 1.31; t(199) = 9.05,
p< 0.001). This also suggests that there is little to lose for lower‐
status influencers entering a collaboration as consumers tend to
perceive influencers, regardless of status, as being more self‐serving
as compared to altruistic. Indeed, self‐serving perceptions were lower
and perceptions of altruism were higher (compared to the other
conditions) only when the focal influencer had higher status than the
partnering influencer. This suggests that for a lower‐status influencer
who wants to partner with a higher‐status influencer, perceptions of
the lower‐status influencer will not suffer. However, to improve
perceptions (reducing self‐serving perceptions and increasing altruis-
tic perceptions), our results suggest that influencers should collabo-
rate with an influencer who has lower status.
6|STUDY 2
The goal of Study 2 is to examine influencer–brand collaborations as
opposed to influencer–influencer collaborations, exploring the extent
to which influencers are perceived as self‐serving when they partner
with a brand with a higher or lower status (H2). While we only
TABLE 4 Study 1: Mean cell values of dependent variables.
Experimental conditions Differences of mean values between each group
Dependent
variables
Focal influencer
status
Higher–lower
(1)
Higher–higher
(2)
Lower–lower
(3)
Lower–higher
(4)
Difference
of 2 from 1
Difference
of 3 from 1
Difference
of 4 from 1
Difference
of 3 from 2
Difference
of 4 from 2
Difference of
4 from 3
Partnering influencer
status
Self‐serving
perceptions
Mean 5.05 5.94 5.72 5.84 p= 0.00 p= 0.00 p= 0.00 p= 0.72 p= 0.97 p= 0.93
Standard deviation 1.35 1.00 0.90 0.87
Altruistic
perceptions
Mean 5.09 4.13 4.41 5.09 p= 0.00 p= 0.03 p= 0.00 p= 0.69 p= 0.99 p= 0.67
Standard deviation 1.24 1.31 1.07 1.24
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anticipate an effect for the dependent variable, self‐serving percep-
tions, for completeness, we also measure altruistic perceptions. To
increase generalizability, we operationalize status using a fictitious
status score as explained in the procedures below. Study 2 employs a
2 (influencer status: lower, higher) × 2 (brand status: lower, higher)
between‐subjects design with self‐serving perceptions and altruistic
perceptions as the dependent variables.
6.1 |Procedure
Recruitment procedures were the same as those employed in Study 1
with 200 individuals (M
age
= 42.41, SD
age
= 11.16; 49% male) electing
to participate in the study. Similar to Study 1, participants were
provided with a fictitious news article that manipulated both the
influencer and brand's status. Participants were randomly assigned to
both an influencer status (lower‐status, higher‐status) and brand
status (lower‐status, higher‐status) condition. Both influencer and
brand status were manipulated using a fictitious POP score which
was described in the article as a score “assigned to brands and
influencers by the company POP Influential. POP scores range from 0
to 100 and higher scores mean that the brand or influencer is more
influential.”Participants in the higher‐status influencer condition read
that the influencer received a score of 68, while those in the lower‐
status influencer condition read that the influencer received a score
of 32. Participants in the higher‐status brand condition read that the
brand received a score of 67, while those in the lower‐status brand
condition read that the brand received a score of 33.
A pretest conducted on the Prolific platform (n= 120: M
age
=
39.08, SD
age
= 13.17; 55% male) confirmed that the status manipula-
tions were successful. Participants were randomly assigned to
lower‐/higher‐status conditions for both the influencer and brand.
After reading the fictitious news article, participants indicated the
extent to which they perceived that the influencer had higher or
lower status as compared to the brand on a 1 (influencer has lower
status) to 7 (influencer has higher status) scale. As desired, a one‐
sample ttest demonstrates that participants who viewed the article
where the influencer had higher status and the brand had lower
status rated the influencer's status (M= 6.10; SD = 1.18) as signifi-
cantly above the midpoint (Midpoint = 4.0; t= 9.64, p< 0.001),
indicating the influencer had higher status as compared to the brand.
Further, a one‐sample ttest demonstrates that participants who
viewed the article where the brand had higher status and the
influencer had lower status rated the influencer's status (M= 2.03;
SD = 1.10) as significantly below the midpoint (t=−9.81, p< 0.001),
indicating the brand had higher status as compared to the influencer.
Finally, when participants read the article where the influencer and
brands had approximately equivalent status levels (M= 4.08; SD =
0.86), there was no significant difference from the midpoint (t= 0.74,
p= 0.46), indicating that participants viewed the status of the
influencer and brand as equivalent.
After viewing the stimuli, participants then completed the survey.
Participants rated their perceptions that the influencer was self‐
serving and altruistic using the same items employed in Study 1 (Siem
& Stürmer, 2019) except modified slightly for the context of
exploring collaborations in the context of influencer–brand relation-
ships. Specifically, self‐serving perceptions (α= 0.76) were measured
using the items: “The influencer wants to use this collaboration for
her own publicity,”“The influencer expects benefits for her own
career from this collaboration,”and “The influencer wants this
collaboration to impress people.”Altruistic perceptions (α= 0.82)
were measured using the items: “The influencer is trying to give
something back to the brand,”“The influencer considers it important
to help the brand,”and “The influencer wants to help the brand gain
customers.”Demographic information was then collected.
6.2 |Results
6.2.1 |Self‐serving perceptions
A two‐way ANOVA with influencer status and brand status as the
independent variables and self‐serving perceptions as the dependent
variable was conducted and showed a significant interaction
(F(1, 196) = 6.61, p= 0.011), see Figure 3. To examine the interaction,
we ran a Tukey multiple comparison of means analysis. The results
show that in the higher‐status influencer condition and the lower‐
status brand condition (M= 5.51, SD = 0.95), the influencer is
perceived as significantly less self‐serving than when both the
influencer and the brand have a higher status (M= 6.10, SD = 0.85;
p< 0.01), or the influencer and brand both have lower status
(M= 6.11, SD = 0.93; p< 0.01), or the influencer has lower status
and the brand has higher status (M= 6.03, SD = 0.94; p< 0.05). There
were no significant differences (all p> 0.90) in self‐serving percep-
tions between the latter three combinations (i.e., higher‐status
influencer and higher‐status brand, lower‐status influencer and
lower‐status brand, and lower‐status influencer and higher‐status
brand), see Table 5. These results support H2, as a higher‐status
influencer partnering with lower‐status brand was perceived as
significantly less self‐serving.
The results show both a significant effect of influencer status
(F(1, 196) = 4.29, p= 0.040) and brand status (F(1, 196) = 3.95,
p= 0.048) on self‐serving perceptions. Specifically, perceptions that
the influencer was self‐serving were higher when the influencer had
lower status (M= 6.07, SD = 0.93) as compared to higher status
(M= 5.81, SD = 0.94). Perceptions that the influencer was self‐serving
were also higher when the brand had higher status (M= 6.07,
SD = 0.89) as compared to lower status (M= 5.80, SD = 0.98).
6.2.2 |Altruistic perceptions
A two‐way ANOVA with influencer status and brand status as the
independent variables and altruistic perceptions as the dependent
variable was conducted. The results show no significant interaction
(F(1, 196) = 0.031, p= 0.86), see Table 5, or significant main effects
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for influencer status (F(1, 196) = 0.125, p= 0.72) and brand status
(F(1, 196) = 0.273, p= 0.60).
6.3 |Discussion
The results for self‐serving perceptions echo the findings from Study 1.
When an influencer (higher‐status influencer condition) partners with a
lower‐status brand, consumers are less likely to perceive the influencer as
self‐serving. As anticipated, the effect of influencer–brand status
differentials had a null effect on altruistic perceptions, supporting our
conjecture that the nature of an influencer–brand collaboration is
different from an influencer–influencer collaboration. As such, when
collaborating with a lower‐status brand, an influencer may be viewed as
less self‐serving as the influencer is less likely to advance their career
through such a collaboration. However, perceptions of altruism are not
likely to increase as the collaboration is most likely to be viewed as a
business transaction, not an altruistically motivated act. The Study 2
results also continue to support the contention that influencers are
perceived as self‐serving as self‐serving perceptions were only signifi-
cantly lower when the influencer partnered with a lower‐status brand.
7|GENERAL DISCUSSION
7.1 |Theoretical implications
In the context of influencer marketing, research has primarily taken
the endorsed brand's perspective, focusing on tactics for using social
media influencers as part of the brand's strategy. Thus, extant
research makes recommendations, often based on the match‐up
hypothesis (Kahle & Homer, 1985) or the source‐credibility model
(Ohanian, 1990), regarding fit between the influencer and brand
(Breves et al., 2019), brand mention strategies (Hu et al., 2020),
content style (Ki & Kim, 2019; Pozharliev et al., 2022), and influencer
attributes such as attractiveness (Torres et al., 2019), number of
followers (Pozharliev et al., 2022), and the number of accounts the
influencer follows (Valsesia et al., 2020). In making such recommen-
dations, the research provides a relatively positive account of the
impact of social media influencers on brand outcomes.
Less research focuses on the self‐branding strategies of
influencers and even fewer articles discuss the notion that
influencers are not always perceived positively—a worrisome finding
as influencers are brands who also need to engage in self‐promotion
and management of consumers' perceptions. Thus, our findings
provide additional support for research that has highlighted the less
positive aspects of social media influencers and the reactions they
incite (e.g., Mardon et al., 2023; Valsesia & Diehl, 2022). Further, our
findings contribute to the study of human brands (Thomson, 2006)
and, even more germane, our findings contribute to the small, but
growing body of literature that investigates influencers as brands,
exploring factors that affect an influencer's brand management
strategy. Specifically, by drawing on signaling theory (Spence, 1973),
we demonstrate that an influencer's engagement with others who are
not followers (i.e., other influencers and traditional brands) is an
additional tactic that influencers can employ to influence consumer
perceptions. Further, our findings highlight an important difference
between influencer–influencer and influencer–brand collaborations,
contributing to work that highlights both similarities and differences
between traditional brands and human brands (Fournier &
Eckhardt, 2018) in the context of brand relationships theory
(Fournier, 1998).
Our findings also contribute to work that explores brand
alliances. To date, research has examined a variety of configurations
that constitute brand alliances relying predominantly on power
theory (French & Raven, 1959) to explain the dynamics of such
alliances. Our work contributes to this literature and is especially
germane to work examining social media influencers' use of alliances
(Kupfer et al., 2018; Nascimento et al., 2020) as we find that
consumers make inferences about influencers based on their
partnership activities. Importantly, research acknowledges that
influencers engage in both influencer–influencer collaborations
(Miguel et al., 2022) and influencer–brand collaborations (Schouten
et al., 2020; Torres et al., 2019), but research has not examined if
FIGURE 3 The interactive effect of focal
influencer status and partnering brand status on
self‐serving perceptions. FI, focal influencer.
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179

influencer collaborations are a successful promotional tactic for the
partnering influencers themselves. We demonstrate the potential for
success with collaborations but highlight the applicability of signaling
(Spence, 1973) and attribution theory (Folkes, 1984) to explain the
key role of status differentials.
7.2 |Managerial implications
According to Influencer Marketing Hub's 2023 State of Influencer
Marketing Report, 83% of brand managers believe influencer market-
ing is effective and 67% of those who use influencer marketing
intend to increase their budget (Geyser, 2023). Further, the
influencer marketing industry is predicted to grow by an estimated
$21.1 billion (USD) in 2023 (Geyser, 2023). As such, social media
influencers need to engage in strategies that manage how consumers
perceive their brand. Given our finding that status differentials
between collaboration partners serve as a distinguishing characteris-
tic influencing consumer perceptions, influencers interested in
portraying a more benevolent persona would be better served to
seek out collaborations with smaller, less well‐known influencers and
brands. Further, knowing that influencers benefit from partnering
with brands that have lower status, lower‐status brands may use this
to pitch a partnership to a higher‐status influencer. Thus, even if a
brand is unable to pay an influencer a large amount of money, they
can offer the less tangible benefit of a reduction in self‐serving
perceptions.
7.3 |Limitations and future research
The current research is not without its limitations. First, the studies
were conducted within the context of Instagram. Although this
platform is the most often used platform for influencer–brand
collaborations (Geyser, 2023), it may not be the most often used
platform for influencer–influencer collaborations. Further,
Voorveld et al. (2018) suggest that consumer engagement and
response may vary based on the platform. For instance, a classic
double jeopardy pattern observed on TikTok implies that more
followers are associated with greater engagement while this
relationship does not hold true on Instagram (Pourazad et al., 2023).
Thus, it is not known whether our results are applicable across
different social media platforms such as TikTok or YouTube.
Further, recent research also suggests that generational differences
may affect consumers' perceptions of influencers (Pradhan
et al., 2023). According to Haenlein et al. (2020), 60% of Instagram
users in the United States are younger than 34, whereas
approximately 40% of TikTok users are teenagers between 10
and 19 years old, indicating a significant generation gap between
platforms. Finally, there is not always a clear‐cut distinction
between a social media influencer (as a person) and any branded
products that might bear their name. These issues should be
considered in future research.
TABLE 5 Study 2: Mean cell values of dependent variables.
Experimental conditions Differences of mean values between each group
Dependent
variables
Focal influencer
status
Higher–lower
(1)
Higher–higher
(2)
Lower–lower
(3)
Lower–higher
(4)
Difference
of 2 from 1
Difference
of 3 from 1
Difference
of 4 from 1
Difference
of 3 from 2
Difference
of 4 from 2
Difference of
4 from 3
Partnering brand
status
Self‐serving
perceptions
Mean 5.51 6.10 6.11 6.03 p= 0.00 p= 0.00 p= 0.02 p= 0.99 p= 0.98 p= 0.98
Standard deviation 0.95 0.85 0.93 0.94
Altruistic
perceptions
Mean 4.35 4.29 4.32 4.19 p= 0.99 p= 0.99 p= 0.92 p= 0.99 p= 0.98 p= 0.96
Standard deviation 1.17 1.34 1.42 1.44
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The current research used the number of followers to manipulate the
status of both the focal influencer and partnering influencer (Study 1) and
a fictitious status score to manipulate the status of both the focal
influencer and partnering brand (Study 2). While manipulating status
using two different methods enhances generalizability, it is still a limitation
as there may be other ways in which consumers judge the relative status
of collaborators (e.g., number of posts, number of brand collaborations,
value/net worth of brand). Further, the signaling mechanisms used to
judge the status of a brand partner might be different from those used to
judge an influencer as few brands procure the same number of followers
as the top influencers. Thus, future research should investigate other
indicators that consumers might use to assess brand status and how such
indicators compare to status indicators for influencers. For example,
existing research suggests that social media cues (Lee, 2021;Li&
Shin, 2023) as well as firm size and revenues (Shepherd et al., 2015)can
act as brand status signals. Further, both brand and influencer rankings
exist. Do consumers perceive brands and influencers who rank similarly
on these lists as having comparable status levels? In sum, future research
should both identify additional cues that signal status and examine the
comparability of such cues across influencers and brands.
Additional outcome variables are also worth investigating.
Positive perceptions that align or may even correlate with altruistic
perceptions should also be explored. For example, generosity,
kindness, and likability may all potentially be increased when an
influencer collaborates with another influencer or brand who has a
lower status level. However, such positive perceptions may not just
be limited to the collaborator with higher status. While our research
shows that lower‐status influencers did not experience an increase in
positive perceptions (i.e., altruistic perceptions), lower‐status influ-
encers may experience enhanced levels of likability as consumers
come to associate the positive attributes of the higher‐status
influencer with the lower‐status influencer. The potential for this
relationship is supported by the associative network model of
memory (Anderson, 1983) and the brand alliance literature (Gammoh
et al., 2006; Levin & Levin, 2000; Mohan et al., 2018). Further,
consumers may infer that the higher‐status influencer may have
knowledge about the lower‐status influencer or brand which is
affecting their desire to collaborate with the lower‐status influencer
or brand. For example, consumers may perceive that the lower‐status
influencer is especially talented or holds a certain level of expertise if
they have managed to attract the attention of the higher‐status
influencer. In the context of a brand collaboration, similarly,
consumers may infer that the lower‐status brand must be exception-
ally effective or of high quality to attract the attention of the higher‐
status influencer. As such, future research should explore additional
outcome variables (e.g., likability, expertise, quality, etc.).
8|CONCLUSION
In sum, this work explores how consumers perceive social media
influencers who engage in collaborations with other influencers and
brands. In doing so, we provide evidence that influencers frequently
engage in collaborations with status differentials and that when a
social media influencer has a higher status than their collaborating
partner this reduces self‐serving perceptions (in the context of
influencer–influencer and influence–brand collaborations) and en-
hances altruistic perceptions (in the context of influencer–influencer
collaborations). These findings lend support to the conjectures that
influencer collaborations can represent brand alliances, marketing
metrics serve as status signals, and that consumers make inferences
about influencers who engage in collaborations that signal status
differentials.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflict of interest.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the
corresponding author upon reasonable request.
ORCID
Veronica L. Thomas http://orcid.org/0000-0001-8832-703X
Kendra Fowler http://orcid.org/0000-0001-8217-2284
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SUPPORTING INFORMATION
Additional supporting information can be found online in the
Supporting Information section at the end of this article.
How to cite this article: Thomas,V.L.,Fowler,K.,&Taheran,F.
(2024). How social media influencer collaborations are perceived
by consumers. Psychology & Marketing,41,168–183.
https://doi.org/10.1002/mar.21918
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