ArticlePDF Available

One size doesn’t fit all: a uses and gratifications analysis of social media platforms



Purpose This research study aims to investigate consumer usage motivations for three of the top social media platforms today: Facebook, Twitter and Instagram. Additionally, through understanding various platform distinctions, firms can understand which social media platforms consumers prefer to use to co-create with brands online. Design/methodology/approach An exploratory qualitative study is first conducted to understand consumer motivations for using different social media platforms. The main study tests five hypotheses related to consumer usage intentions and social media co-creation behavior across three social media platforms. A survey is conducted with 1,050 social media users with a comparison of mean responses using multivariate analysis of covariance. Findings Results support significant differences between platforms in terms of use and co-creation behaviors. For informational purposes, consumers gravitate toward Twitter. For social purposes, Twitter and Instagram are preferred. Instagram is the primary platform for entertainment motivation as well as co-creating with brands via social media. Surprisingly, Facebook shows the lowest usage intentions and co-creation despite being the largest platform and network most widely used by marketers. Originality/value To the best of the authors’ knowledge, this is one of the first studies to take a multi-platform approach to understanding consumer social media use and co-creation with brands. The results highlight that marketing academics and practitioners must segment the various social media platforms as each offers unique value propositions to consumers.
One size doesntt all: a uses and
gratications analysis of social
media platforms
Mark J. Pelletier
Department of Marketing, University of North Carolina at Wilmington,
Wilmington, North Carolina, USA
Alexandra Krallman
Department of Marketing, Industrial Distribution, and Economics, University of
Alabama at Birmingham, Birmingham, Alabama, USA
Frank G. Adams
Department of Marketing, Quantitative Analysis, and Business Law, Mississippi
State University, Mississippi State, Mississippi, USA, and
Tyler Hancock
Department of Marketing and International Business, The University of Toledo,
Toledo, Ohio, USA
Purpose This research study aims to investigate consumer usage motivations for three of the top social
media platforms today: Facebook, Twitter and Instagram. Additionally, through understanding various
platform distinctions, rms can understand which social media platforms consumers prefer to use to co-create
with brands online.
Design/methodology/approach An exploratory qualitative study is rst conducted to understand
consumer motivations for using different social media platforms. The main study tests ve hypotheses
related to consumer usage intentions and social media co-creation behavior across three social media
platforms. A survey is conducted with 1,050 social media users with a comparison of mean responses using
multivariate analysis of covariance.
Findings Results support signicant differences between platforms in terms of use and co-creation
behaviors. For informational purposes,consumersgravitate toward Twitter. For social purposes, Twitter and
Instagram are preferred. Instagram is the primary platform for entertainment motivation as well as co-
creating with brands via social media. Surprisingly, Facebook shows the lowest usage intentions and co-
creation despite beingthe largest platform and network most widely used by marketers.
Originality/value To the best of the authorsknowledge, this is one of the rst studies to take a multi-
platform approach to understanding consumer social media use and co-creation with brands. The results
highlight that marketing academics and practitioners must segment the various social media platforms as
each offers unique value propositions to consumers.
Keywords Social media marketing, Facebook, Twitter, Social networking sites
Paper type Research paper
Social media is about the people! Not about your business. Provide for the people and the people
will provide for you Matt Goulart.
With nearly 3.5 billion social media users worldwide, or roughly 45% of the global
population, social media has proven its ability to reach individuals in almost every
Analysis of
social media
Received 1 October2019
Revised 25 March 2020
Accepted 2 April2020
Journal of Research in Interactive
Vol. 14 No. 2, 2020
pp. 269-284
© Emerald Publishing Limited
DOI 10.1108/JRIM-10-2019-0159
The current issue and full text archive of this journal is available on Emerald Insight at:
marketing segment imaginable (Kemp, 2019;Hanna et al.,2011). Naturally, the growth of
social media has drawn the attention of marketing practitioners, who seek to promote and
enhance their brands via social medias power to aim specic brand content at precise
consumer targets (Economist, 2015). According to Pew Research (2018), nearly 70% of US
adults use at least one social media platform, and over 50% of users visit social media sites
daily (Smith and Anderson, 2018). Spending on social media and online advertising is
expected to grow by 18.7% through 2022, compared to a mere 1.3% growth for television
and, relatively at projections for radio advertising and an almost 27% drop in print
advertising (Pricewaterhouse Coopers, 2018).
However, even with the manifest growth of social media advertising, only 49% of
surveyed Facebook advertisers believe that their efforts are effective (Stelzner, 2018). Some
may be tempted to simply dismiss social media advertising as ineffective, particularly in
light of Gallop Poll ndings (Elder, 2014) describing social media as overhyped. The
problem may actually stem from a lack of a clear understanding of what social media are,
the various forms of social media and how value is best created on social media networks
(Kaplan and Haenlein, 2010). Internet-based technologies, such as social media Platforms,
naturally lend themselves to enhanced opportunities for value co-creation and enhanced
engagement opportunities to take place by allowing customers and rms to interact with
one another in a real-time setting (Dessart, 2017;Yang et al.,2016;Balaji and Roy, 2017).
Although social media in general offers a channel to facilitate co-creative experiences,
current research lacks an understanding of how co-creation may differ on each distinct
Platform and which Platforms consumers gravitate toward when looking to interact with a
Furthermore, the current social media landscape is full of rich and diverse Platforms that
differ in not only size, but also functionality (Kietzmann et al.,2011). In practice, however,
social media marketing is often viewed as a one size ts allapproach that includes sharing
the same social media post across all social media Platforms, also referred to as cross-
posting. This practice is discouraged by most social media practitioners (Cyca, 2018);
however, current research lacks a clear understanding of what consumers truly desire from
each Platform and how marketers can optimize content for each specic Platform to deliver
customer value.
To succeed in the social media environment, additional research is needed to understand
how brands can develop strategies that are congruent not only the Platform being used
(Kietzmann et al., 2011), but also with the needs and motivations of the users on those
Platforms (Zhu and Chen, 2015). Supporting this academic need for social media research, a
2018 survey of social media advertisers indicated that most respondents desired answers to
two primary questions: what social media tactics are the most effective, and what are the
best ways to engage with customers (Stelzner, 2018).
In response to these calls from marketing academics and practitioners alike, this research
seeks to explore the various consumer motivations for using the most popular social media
Platforms and understand which Platforms lead to more co-creation between marketers and
customers. Using this information brands can create a more effective social media content
strategy that resonates with their customers on each specic Platform. Through an
exploratory qualitative study, the three Platforms investigated include Facebook, Twitter
and Instagram, which are not only the most popular Platforms in terms of consumer usage,
but also the largest for social media marketing expenditures (Stelzner, 2018). Coupling the
results from this initial study with the foundations of Uses and Gratications Theory, ve
hypotheses detail how the consumer usage intentions and co-creation with brands differ
across three different social media Platforms. Results of a survey data collection will then be
discussed along with implications for marketing theory and practice, and related future
research directions.
Exploratory study
In an effort to understand what drives consumers to use the various social media Platforms, the
research team recruited 363 US-based social media users from the Amazon Mechanical Turk
online panel and compensated each for participation. The qualitative instrument asked
respondents which social media Platforms they use, how long they had been a user of the
platform and the frequency in which they use the Platform. Within this sample, 337
respondents were Facebook users, 255 respondents used Twitter and only 226 used Instagram.
In terms of multi-Platform usage, 62% of the sample used all three Platforms, 8% used two
Platforms, 23% used only one Platform and 7% reported to only use othertypes of social
media. Next, participants were asked how frequently they logged into each Platform. Facebook
users logged in most frequently with 56% of users signing in multiple times per day, 23%
daily, 11% weekly, 3% monthly and 7% rarely. For Twitter users, 18% logged in multiple
times per day, 20% daily, 18% weekly, 14% monthly and 30% rarely using the Platform.
Finally, Instagram users reported 17% multiple daily uses, 19% daily, 19% weekly, 8%
monthly and 37% rarely. Based on which Platforms each participant reported using (users
reported monthly use or greater), they were then asked open-ended questions regarding why
they use that particular Platform. Demographic information was then collected, with the nal
sample consisting of 52% female and an average age of 39 years.
Two coders with doctoral-level training in marketing research coded the qualitative
responses to understand why consumers use Facebook, Twitter and Instagram.
Independently, each judge identied the discrete emerging themes from each response, with
themes then compared to one another to develop a master list of categories. The coders then
went back through the data to discuss any discrepancies. Overall, the percentage agreement
among coders indicated an acceptable level of agreement (per cent agreement = 0.96)
(Gremler, 2004). In the coding of responses, multiple categories were often conveyed in one
individuals comments.
Overall, four themes consistently emerged from the customer responses: social purposes,
informational purposes, entertainment purposes and, to a lesser degree, convenience
purposes. Responses within the Socialtheme reiterated the desire for consumers to
interact with other social media users (including people they know and people they do not
know) and share their personal content with others. This theme comprised the largest
category within the Facebook usersresponses, although it was also heavily mentioned
across Instagram and even Twitter to a lesser extent. The Informationaltheme was
heavily dominant on the Twitter Platform, and included users seeking out information,
news and events, as well as for professional business purposes. The third theme
Entertainmentincluded consumers using the Platform to have fun or follow their favorite
celebrities/pop-culture events. Instagram was the Platform most frequently used for
entertainment, which is logical given the visual focus of the Platform. Finally, the
Conveniencetheme reected respondents using the various Platforms just to browse or
observe when they were bored. This theme was predominately mentioned by Instagram
users only. Table 1 provides sample quotes and frequencies to illustrate each of these
themes within the data.
Uses and gratications theory
Building on the results of the initial exploratory study, an examination of the literature
related to why customers used specic types of media leads to the foundations of Uses and
Analysis of
social media
Gratications Theory (U&G). In general, U&G suggests that the benets extracted from a
given media source may vary based on the different purposes for which specic individuals
choose to consume media (Severin and Tankard, 1997). U&G focuses on consumer use and
choice by stating that different individuals may use the same mass media sources for
various purposes (Katz, 1959). By understanding the intrinsic needs that draw consumers
toward specic media, U&G further helps recognize consumersmotives for usage
behaviors to receive gratication.
U&G has been used in various forms of digital marketing, including e-mail (Dimmick
et al.,2004) and websites (Korgaonkar and Wolin, 1999); however, it is especially well suited
to examine social media because of the high levels of involvement (Ruggiero, 2000), bonding
social capital (Phua et al.,2017), interactivity of participants (Korgaonkar and Wolin, 1999)
and positive vs negative brand communication (Dolan et al., 2016). Through the social media
context, brands can provide value or gratication for consumers by optimizing the content
they put forth (Malthouse et al.,2013). The ndings from the exploratory study align with
the tenets of U&G theory, with the main drivers of social media usage identied as social,
informational, entertainment and convenience/distraction purposes (Ashley and Tuten,
2015;Jahn and Kunz, 2012). The primary limitation of these prior social media-based studies
is that all research has relied on examining social media as a whole (i.e. all Platforms treated
as one) or only specically examining one Platform (i.e. Facebook). No research to date has
considered how consumers may have differing usage intentions across the various
Platforms, and what these differences may mean to marketers in terms of engagement and
content creation.
Social motivations
Value from social motivations stems from a participant communicating and interacting with
others, keeping up with their personal contacts, and meeting people with similar interests
(Korgaonkar and Wolin, 1999). In a manner similar to approval utility in Electronic word-of-
Table 1.
Exploratory themes,
frequencies and
sample quotes
Platform frequencies Sample quotes
Use for social purposes
Facebook = 92.7%
Twitter = 38.7%
Instagram = 62.4%
For connecting with family that lives far away and friends that I dont see
regularly.Keeping connected and up to date with friends and family and
offering/receiving advice from the many groups that I am part of
Use for informational purposes
Facebook = 28.5%
Twitter = 68.7%
Instagram = 12.2%
To keep up with political news and opinions and see what other people in the
world are talking about or what is trending.Breaking news, or details about
live events, or current reactions to recent events.
Use for entertainment purposes
Facebook = 12.7%
Twitter = 37.5%
Instagram = 49.7%
I mainly use it to follow sports and entertainment celebrities to look at
videos and photos they post.
For playing games online and sharing funny memes.
Use for convenience purposes
Facebook = 1.5%
Twitter = 2%
Instagram = 25.7%
I use it to just watch random stuff on my Explore page.For when Im bored
for viewing photos and reading comments
Notes: *Percentages are based on the total number of times code was present/total respondents reporting
per platform
mouth, receiving acceptance from other members of their virtual community may elevate a
social media participants overall perceived social status (Hennig-Thurau et al., 2004). Not
only does this social interaction lead to enhanced social status, but it also has weight on the
overall value of the rms offerings (Hewett et al., 2016).
From a social media perspective, Platforms provide means for users to interact with their
personal network of family and friends, while expanding their networks to connect with new
users (Korgaonkar and Wolin, 1999). In a similar sense, Facebook users visit the site for
socializing purposes to make connections with others users (Zhu and Chen, 2015) by joining
various Facebook groups, fan pages and gaining a sense of community in a virtual setting
(Dineva et al., 2017). The results of the exploratory study further support Facebook as the
dominant Platform for social interaction purposes. Of the three Platforms examined in this
research, Facebook has the largest base of users, and the broadest, most exible array of
means to facilitate communication between its parties. Facebook is also the Platform best
suited to maintaining small member groups, enabling users to control the breadth of the
connections they have with various contacts, and thus manage the identity, relationships,
reputation, group and presence functional building blocks of social media described by
Kietzmann and his colleagues (2011). In contrast, Twitter limits the number of characters
within a post, which may deter longer and more in-depth social connections to be formed,
while Instagram also minimizes the textual-based content on the Platform by requiring
visual media to create a post. As a result, for social usage intentions, the authors hypothesize
the following:
H1. Users with social purpose usage intentions will be attracted more to Platforms with
a broad array of communications mechanisms.
Informational motivations
Use for informational purposes refers to using social media to seek information that is both
helpful and educational. Individuals motivated by information purposes seek means of
internalizing data from external sources, and the more information individuals receive from
a given media source, the more positive attitude they tend to hold toward that media source
(Luo, 2002). In the online environment, individuals will often use various links to obtain
additional information, and informational content of a new site tends to correlate with
positive attitudes toward the website (Chen and Wells, 1999) and toward advertisements
featured on the website (Ducoffe, 1996).
In terms of social media Platforms, Twitter serves as a microblogging network of real-
time posts from individuals, interest organizations of every type and even traditional media
news outlets (Kaplan and Haenlein, 2010). With 500 million tweets sent each day, or 5,787
tweets per second, No other platform rivals Twitter for bleeding-edge news and up-to-the
second happenings (Cooper, 2019).In fact, 71% of Twitter users are reading news on the
Platform (Matsa and Shearer, 2018), which also happens to be the number one Platform for
government leaders as well (Lufkens, 2018). The Twitter Platform allows marketers to begin
brand-specic conversations with consumers because of this emphasis on information
sharing and discussion (Soboleva et al., 2017). Overwhelmingly, Twitter was the Platform
most respondents in the exploratory study turned to when seeking information. This
suggests the following hypothesis:
H2. Users with informational purpose usage intentions will be attracted more to
Platforms with an emphasis on real-time information.
Analysis of
social media
Entertainment motivations
Value from entertainment refers to the extent to which the media source is used for hedonic
benets (Eighmey, 1997). Users seeking entertainment benets use media formats for
hedonic purposes of escapism and enjoyable experiences (Korgaonkar and Wolin, 1999).
From a digital marketing perspective, interactive content and banner ads that consumers
nd entertaining lead to greater positive attitudes toward the site (Chen and Wells, 1999).
The visual and hedonic attributes of social media provide numerous benets to rms in
terms of getting consumers more engaged on the Platform and more willing to interact with
content (Carlson et al., 2018;Mawhinney, 2018;Triantallidou and Siomkos, 2018).
Although all social media Platforms attempt to provide entertainment for users, the visual
nature of the Instagram Platform most readily lends itself to this goal. Instagram is a content-
basedPlatform that seeks to provide its users with a shared experiencethrough pictures and
video content posted on a particular prole (Frier, 2018;Zhu and Chen, 2015). With more than 100
million photos and videos shared on the Platform each day (Kolowich, 2019), brands, digital
inuencers/celebrities and everyday consumers use the Platform to tell their personal stories and
experiences. These statistics were further supported in the results of the exploratory study with
Instagram showing the highest usage intentions for hedonic types of entertainment. Thus:
H3. Users with entertainment purpose usage intentions will be attracted more to
Platforms with an emphasis on hedonic experiences.
Convenience motivations
This particular usage category is dened by consumersneed to use the media as a source of
convenience or distraction. Although initially introduced to describe television viewing behaviors,
more recent research has shown that various forms of digital media are often used by consumers
to simply pass time(Papacharissi and Rubin, 2000;Ko et al., 2005). With the growth of
smartphone adoption, consumers are now able to easily access social media Platforms numerous
times per day, with the majority of social media usage now facilitated through mobile devices
(Sterling, 2017). Surprisingly, it is estimated that the average person spends nearly 2 h a day
browsing, watching or posting on social media Platforms (Asano, 2017).
Although Facebook may be the Platform that has existed the longest and has the largest
number of users, results of the exploratory study indicate that Instagram is the Platform
consumers turn to for easy browsing or for scrolling through content. This result may be
because of the fact that Instagrams focus on visual content and minimizing text allows users to
put forth less effort when taking a passive observer role. This aligns with individuals
motivated by convenience purposes who are interestedincommunicationsolutions that require
less resources to meet their individual needs (Ko et al., 2005). Furthermore, smartphone usage
may further contribute to this fact as Instagram is the only solely mobile device Platform
included in this study. Thus, this research hypothesizes the following:
H4. Users with convenience purpose usage intentions will be attracted more to
Platforms with an emphasis on visual content and minimal text.
Social media co-creation
Recent research has shifted to try to understand the interactive consumer/brand relationship
that occurs within this virtual setting (Hollebeek et al., 2014;Kao et al.,2016). As social
media enables consumers to become active instead of passive participants, enhanced
opportunities for co-creation exist. Social media users co-create brands through storytelling
and sharing personal experiences (Singh and Sonnenburg, 2012). Storytelling and narrative
transportation fosters engagement with customers by stimulating dialogue and access,
leading to increased attitudinal evaluations (Huang et al.,2018;Hatch and Schultz, 2010). As
seen in Hewett et al. (2016), this dialogue between brands and social media users can
eventually create, or in some cases even destroy, value for the brand.
As previously discussed, the sheer volume of activity on Facebook (Perrin, 2015),
alongwiththeheavypresenceofbrands(Stelzner, 2018), would suggest that larger
amounts of co-creation occur on this Platform compared to Twitter and Instagram.
Additionally, Facebook is the Platform that allows for group formation based on
common interests or brand communities. Popular brands such as Harley Davidson,
Canon and Apple all have multiple dedicated fan pages or groups on Facebook, in
which content centered around their shared interest in the brand is shared numerous
times each day. Consumers derive personal benets from involvement in branded
Facebook pages, increasing both their levels of engagement and the perceived value
generated by such co-creative experiences (Dineva et al.,2017). Facebook also permits
the widest array of content to be posted and shared among consumers and brands.
This allows for more free form of communication to take place without restrictions on
character count (present on Twitter), ability to include clickable links (cannot be
included on individual Instagram posts) or video/graphic requirements imposed by the
other Platforms. Accordingly, the following hypothesis is proposed:
H5. Users with a desire to engage in co-creation will be attracted more to Platforms
with a broad array of communications mechanisms.
To test the hypotheses listed above, the authors developed a survey to investigate how consumers
usage intentions and social media co-creation behavior differ across various types of social media
Platforms. Although a wide array of social media Platforms exist, Facebook, Twitter and
Instagram were the Platforms selected in this investigation based on the results of the exploratory
study and U&G theoretical support. Specically, Facebook is hypothesized as the platform with
the broadest array of communication mechanisms (H
), Twitter has an emphasis on real-time
information (H
), and Instagram focuses on hedonic experiences, visual content and minimal text
(H3,H4). The research team recruited a total of 1,050 compensated, English-speaking, US-based
customers from the Amazon Mechanical Turk national online panel database. The online panel
allowed for a large sample of real-world brand experiences via social media.
To ensure quality online respondents, the study included various attention checks,
respondent screening policies and a requirement of written text. Attention checks included
asking respondents to select Strongly disagreefor one item placed within a scale toward
the middle of the survey, as well as asking the respondent to conrm the social media
Platform they were answering the survey for, as well as conrming in two places the brand
they reported to interact with via social media. Additionally, respondents recruited via
Amazon Mechanical Turk had to meet specic requirements including residing in the USA,
taking the survey from only one IP address, and having a HIT approval rating of 95% or
greater. This type of screening policy follows recommendations set forth byother marketing
researchers using research panels (i.e. Meyer et al.,2017). A total of 45 surveys were dropped
for substantial missing data through listwise deletion (Hair et al.,2010), or for failure to pass
attention check measures. This left a total of 1,005 usable responses, including 331 Facebook
users, 339 Twitter users and 335 Instagram users. Within the nal sample, 59% were male,
and the average age of respondents was32 years.
Analysis of
social media
The survey instructed respondents to think of a time in the past six months that they co-
created with a brand via one of the three social media Platforms (Facebook, Twitter and
Instagram). To ensure participants understood the meaning of co-creation, the recruitment
message used for panel recruitment provided both a denition and examples of co-creation
(i.e. you helped promote a brand online). Extant scales adapted from the literature measured
the usage intentions and social media co-creation constructs, as well as brand involvement
used as a control variable (Vernette and Hamdi-Kidar, 2013;Chang, 2009;Escalas and
Bettman, 2005;Ko et al., 2005). All scale items were made of seven-point scales ranging from
1 = Strongly disagree to 7 = Strongly agree or 1 = Never to 7 = Always.
The reliability of the scale items was assessed, and each exhibited an acceptable level of
reliability (
0.70; Nunnally and Bernstein, 1994). A conrmatory factor analysis, using
AMOS 22, assessed the unidimensionality, convergent validity and discriminant validity of the
latent constructs. The validity tests indicated an acceptable t(Hu and Bentler, 1999)ofthe
model to the data (
= 1,611.22, df = 401, Comparative Fit Index (CFI) = 0.95, Incremental Fit
Index (IFI) =0.95, Root Mean Square Error of Approximation (RMSEA) = 0.05). Table 2 shows
a complete list of results from the CFA, along with composite reliability for each construct.
Average variance extracted (AVE) calculations tested the scalesconvergent and
discriminant validity of each construct. As Fornell and Larcker (1981) recommend, calculating
the shared variance between constructs indicated that the average variance extracted was at
least 0.50 for each construct, providing evidence of convergent validity. Further, no shared
variance between constructs exceeded the average variance extracted, indicating evidence of
discriminant validity. Table 3 displays the means, standard deviations and correlations
between variables, and the square root of AVE for each variable. A single latent construct was
included in the analysis to test common method bias (Podsakoff et al.,2003). This factor
included a specied relationship to each scale item to account for any systematic bias within
the latent constructs. A non-signicant Chi-square difference indicated common method bias
was not a signicant concern. This is consistent with the recommendations put forth by Fuller
et al. (2016) that show the single-factor test only fails to detect bias when common method
variance is exceedingly high.
A comparison of mean responses using multivariate analysis of covariance (MANCOVA)
tested statistically signicant differences between the three different social media Platforms
regarding consumer usage intentions and social media co-creation. MANCOVA is an
appropriate method for this analysis as it allows for analysis of multiple dependent
variables simultaneously, with sufcient power, while controlling for the respondents age
and brand involvement as the covariate (Hair et al.,2010). The brand involvement covariate
was signicant (F= 4.44, p= 0.01) and accounted for any effect based on degree of
involvement with the reported brand on the relationships between the Platforms and
dependent variables. The results from the MANCOVA are shown in Table 4.
The results of the MANCOVA showed a statistically signicant difference between
the three social media Platforms for the usage intentions and co-creation constructs (F(12,
1992) = 12.00; Wilks lambda = 0.87, p<0.001). To nd which specic variables
contributed to the signicant differences between Platforms, a Tukeyspost hoc analysis
was conducted as shown in Table 5.
The rst hypothesis states that users with social purpose usage intentions will be
attracted more to Platforms with a broad array of communications mechanisms. The results
indicate that there was a signicant difference between Facebook and the other two
Platforms (F= 13.96, p<0.05); however, the ndings were reversed from what was
hypothesized. Facebook users reported signicantly lower usage intentions for social
purposes (SocialFacebook = 4.19) than Twitter and Instagram users (SocialTwitter = 4.70,
SocialInstagram = 4.64), denying support for H1.
The second hypothesis states that users with informational purpose usage intentions will
be attracted more to Platforms with an emphasis on real-time information. H
Table 2.
Conrmatory factor
and reliability
Social media engagement items
Standardized factor
Social media co-creation (CR = 0.91)
- Promoted a product or brand online 0.88 **
- Helped other consumers by answering brand-related questions 0.86 35.46
- Collaborated with a brand 0.79 30.66
- Posted a comment concerning a product or service 0.85 34.43
Brand involvement (CR = 0.92)
- The posts made by this brand really hold my attention 0.94 **
- The posts made by this brand draw me in 0.96 60.68
- The content this brand posts really intrigues me 0.89 48.72
- The content that this brand posts reminds me of experiences or feelings Ive
had in my own life
0.63 23.86
Use for entertainment (CR = 0.86)
-Its enjoyable 0.93 **
-Its entertaining 0.93 45.46
- I just like to look through my newsfeed 0.57 20.35
Use for convenience (CR = 0.84)
-Its convenient to use 0.84 **
- I can communicate with others for less effort 0.75 25.67
- I can use it anytime, anywhere 0.80 27.92
Use for information (CR = 0.91)
-Its a good way to catch up on news 0.78 **
- I can learn about useful things 0.94 33.13
- I can learn about things I dont know 0.91 32.28
Use for social (CR = 0.75)
- I want to express myself freely 0.75 **
- I want to meet people with my interests 0.70 23.50
- I wonder what other people say 0.67 19.07
Notes: **denotes a constrained relationship to 1.00 for identication; CR: composite reliability; model t
= 1611.22, df = 401, p<0.001; CFI = 0.95, IFI = 0.95, RMSEA = 0.05
Table 3.
Means, standard
deviations, square-
root of AVEs and
correlations of
Mean (SD) SQRT AVE 1 2 3 4 5 6
1. Social media co-creation 2.63 (1.36) 0.84 1
2. Brand involvement 3.31 (1.15) 0.86 0.47 1
3. Use for entertainment 5.32 (1.14) 0.83 0.23 0.26 1
4. Use for convenience 5.32 (1.21) 0.80 0.24 0.29 0.68 1
5. Use for information 4.51 (1.53) 0.87 0.33 0.27 0.49 0.48 1
6. Use for social 4.51 (1.39) 0.71 0.40 0.33 0.57 0.54 0.61 1
Notes: SD: standard deviation; SQRT AVE: square root of average variance extracted
Analysis of
social media
supported as there was a signicant difference between Platforms (F= 19.26, p<0.05), with
Twitter showing the largest mean (Information
= 4.28, Information
= 4.92,
= 4.31; F= 19.26, p<0.05). Additionally, signicant differences were
found across Platforms for entertainment intentions (F= 10.71, p<0.01), with Instagram
users exhibiting the highest usage intentions for entertainment purposes compared to
Facebook and Twitter users (Entertainment
= 5.12, Entertainment
= 5.32,
= 5.52), in support of H3.
suggested that users with convenience purpose usage intentions will be attracted more to
Platformswithanemphasisonvisualcontentandminimaltext.Nosignicant differences
between Platforms were found for the convenience usage variable, although it is important to note
that all means for convenience usage exceeded 5.0. This result implies that consumers nd all
three Platforms convenient, which intuitively makes sense given the rise of mobile devices and
smartphone application use.
The nal hypothesis claims that users with a desire to engage in co-creation will be attracted
more to Platforms with a broad array of communications mechanisms. Results again show a
signicant difference between the social media Platforms (F=3.28,p<0.05), but in the reverse
hypothesized order. Contrary to expectations, Facebook was signicantly lower (Co-creation
= 2.49) for social media co-creation than Instagram (Co-creation
= 2.76). Twitter showed no
statistical difference between either Facebook or Instagram users. Specically, Instagram users
reported the highest levels of social media co-creation, then Twitter and Facebook.
Overall, the results support signicant differences between Platforms, and for the
majority of the hypotheses. In general, Twitter users visit the Platform for informational and
social purposes, whereas Instagram users log in for both social and entertainment purposes.
Instagram further shows the highest levels of social media co-creation among its users.
Surprisingly, Facebook reported the lowest levels of usage intentions and co-creation, despite
being the largest overall network, and the most favored by marketing managers. This is not
to say that Facebook users do not seek informational, social benets from the Platform, nor
that either/both Facebook and Twitter users do not seek entertainment benets from those
Platforms. Rather, it suggests that the ability of the three Platforms to provide those U&G
benets to consumers is actually inverse of the size and reach of the three Platforms, with
important implications for both scholars and practitioners.
Table 4.
results: mean (SD)
Variables Facebook Twitter Instagram F-stat p-value
Use for social 4.19 (0.08) 4.70 (0.08) 4.64 (0.07) 13.96 0.00
Use for convenience 5.38 (0.07) 5.24 (0.07) 5.34 (0.07) 1.23 0.29
Use for information 4.28 (0.08) 4.92 (0.08) 4.31 (0.08) 19.26 0.00
Use for entertainment 5.12 (0.06) 5.32 (0.06) 5.52 (0.06) 10.71 0.00
Social media co-creation 2.49 (0.08) 2.64 (0.07) 2.76 (0.06) 3.28 0.03
Table 5.
Individual platform
signicance levels (p-
Variables Facebook vs Twitter Facebook vs Instagram Twitter vs Instagram
Use for social 0.00 0.00 0.56
Use for convenience 0.12 0.65 0.28
Use for information 0.00 0.79 0.00
Use for entertainment 0.02 0.00 0.02
Social media co-creation 0.15 0.01 0.25
Furthermore, the results for Facebook did not support the hypotheses for social usage intentions
or social media co-creation. For the co-creation hypotheses, these results may stem from users
wanting to use the Platform more for personal purposes instead of interacting with brands.
Additionally, users with a large number of friendssimply cannot process all the posts from
their friends, their groups and the companies. Thus, brands that wish to interact with customers
via Facebook must try to have their content embedded early in the news feed stream, which may
only be possible through paid, sponsored ads instead of mere organic content. In terms of the
results for social usage intentions, it is possible the results may stem from how respondents
interpreted the items. Friends on Facebook are often well-known contacts that the user knows on
a personal level, whereas the same is not necessarily true for the other two Platforms. If a user
wants to meet people with my interestsor nd what others are saying,they might not turn to
their existing social circle but instead reach out to a more diverse group of public users on
Instagram or Twitter. This represents an area for future research addressed in the Discussion
section that follows.
Social networks have continually grown and evolved over time, with the differences among
Platforms becoming increasingly more pronounced. As Platforms seek to differentiate
themselves by offering unique capabilities and fullling various consumer needs, social
media users have gravitated toward using multiple sites to accomplish their goals. Shown in
the usage percentages for Facebook, Twitter and Instagram, a great deal of overlap exists
across Platforms, with many active users using numerous sites daily.
While social media users may frequent all three Platforms investigated in this study, each site
offers differing value propositions regarding the type of social engagement that takes place. For
example, Facebook, being the largest and most demographically diverse social media Platform,
can be used to communicate with millions of users through text-based posts, pictures, video or
chat-based communications. Although Facebook allows for the widest array of communication
mechanisms across the largest overall consumer network, it showed the lowest social usage
intentions of all the social networking sites measured. Perhaps, this nding stems from the sheer
size of Facebooks user base. While being social with close friends in an intimate setting seems
possible, the same type of social interaction may not be possible in a large convention hall with
everyone you have ever known present.
Conversely, Twitter and Instagram place greater restrictions on the manner in which
communication on the Platform may take place. For instance, communication via Twitter is
limited to only 280-character messages, whereas Instagram requires picture and video messages to
be posted. Regardless of the communication restrictions, these sites demonstrated signicantly
higher levels of not only social usage intentions but also exhibited higher levels of co-creation
intentions. Furthermore, the character restriction on Twitter seems to provide satisfactory
amounts of information to fulll informational usage intentions, while not overwhelming the user.
These ndings suggest that network size and communication capabilities alone do not necessarily
equate to consumers using the social media Platform to interact with brands. By understanding
what consumers are looking for on each individual Platform, social media practitioners can tailor
their marketing strategies to be more effective by delivering higher levels of customer value/
Managerial implications
In older forms of media, the size of a communication network has long served as a proxy for its
utility as a marketing instrument (McAlister et al., 2007;Rust et al.,2004); these ndings beg a
question of that logic. The ability to entertain, and to inform, and to thereby engage a customer
Analysis of
social media
with a brand were all clearly stronger in this study among the smaller Platforms, even though
recent practitioner-based surveys have shown a strong bias for Facebook as a social media
promotional channel of choice. This is not to say that larger social media Platforms are useless,
but for maximum effectiveness, the rm must decide the ultimate goal of their social media
promotion, and then taking into consideration the consumer usage intentions, decide which
Platform can best accomplish this goal while engaging the maximum number of desirable users.
Consumers visit each social media Platform for various usage intentions; therefore, one size
ts allsocial media marketing strategies are not appropriate. Practitioners must think beyond
social media strategyas a singular concept and examine more complex models regarding the
true value proposition of each Platform. Consideration of the intended target market and their
corresponding usage intentions by Platform can assist marketers in developing more effective
social media marketing campaigns. Firms should align their social media promotional messages,
as well as their expectations of customer engagement, with the value being sought by consumers
through the use of the particular social media Platform.
Theoretical implications
While valuable research insights have been gained through prior explorations of consumer
usage and engagement via social media, a majority of the research to-date has been
conducted using a sample obtained from a single social media Platform. While single-
Platform research provides great depth into understanding consumer engagement on a
specic Platform, it cannot be assumed that the results can be generalized across the entirety
of social media Platforms. The ndings presented in this study and the dynamic nature of
social media as a communication and promotional channel suggest that consumer research
that does not adequately segment social media may miss key insights into usage.
Examination of Platform by value proposition, target markets and co-creator characteristics
remain insufciently rened. Future research should further explore the role of Platform tin
examining how social media contributes to the performance of a rms advertising efforts.
Advertising research has indicated that specic advertising content and the media content in
which it is embedded impose reciprocal inuences on the brand and the media source (Simonin
and Ruth, 1998;Sternthal et al.,1978). The ndings presented here suggest that t between a
desired brand image and the purpose for which a Platform is used matters. Customer experiences
help co-create brands on social media (Singh and Sonnenburg, 2012), and the reasons that
customers use Platforms will inuence how customers perceive brand messages. This is
particularly important given that brand messages may be surrounded by content created by
other Platform users, and those brand messages may even be inuenced and altered by other
Platform users (Peters et al.,2013). Accordingly, research is needed on the role that Platform t
plays in supporting (or undermining) brand image and brand equity.
Limitations and future research
A cross-sectional data collection was used for this study. As social media continually evolves, it
would be a worthwhile endeavor to collect longitudinal data to measure the effects of sustained
communication across multiple social media Platforms over time. Longitudinal data could
additionally provide insights into understanding how changes in a Platform impact a rms
social media effectiveness. Furthermore, supplementing these ndings with a practitioner data
collection could compare promotional social media goals with actual consumer usage intentions.
This would uncover whether or not practitioner strategies and consumer social media intentions
are aligned. Consumers could further be asked how they perceive advertisersgoals on each
Platform, and how effective these rms are at achieving such goals.
To further investigate the unexpected Facebook results, it is recommended that future studies
separate the social usage dimension into two categories. Categories could be constructed
exploring both the usersdesire to engage with existing personal connections from their physical
environment, as well as users looking to build more social contacts through their solely on-line
communities in which they have not met face-to-face. Additionally, as the main study only
examined co-creation activities that took place on a single Platform, it would be helpful to see if
similar results hold across multiple Platforms. Future studies could make greater comparisons by
asking respondents to talk about co-creation experiences with a brand that occurred across two
or more social media Platforms. As respondents in this research were asked to recall a specic
interaction with a brand via social media over the past six months, it is possible that respondents
could have exhibited recency bias by reporting only their most recent interaction. It is therefore
recommended that future studies specically ask respondents when the interaction took place
and use this measure as a control variable in analyses.
This study did not specically examine the various types of brand-related content the sample
consumed/produced on social media. Therefore, this study does not attempt to delve into the many
and varied forms of information, entertainment or social interaction that social media Platforms
have to offer and how that may change user interaction. For example, lack of trust and lack of
shared values have been shown to be barriers to online co-creation (Chepurna and Rialp Criado,
2018). Further, research has noted a tendency for individuals to seek out sources of news that agree
with their preconceived notions (Purnawirawan et al., 2015). However, from a U&G perspective,
these differing individuals would still be seeking information. Additionally, we did not explore the
levels of gratications stemming from usage of the Platforms and how that might relate to the
effectiveness of promotional messages. This is something that could be explored in future studies.
This suggests vast and rich opportunities for future research to explore differences in uses and
gratications of different Platforms based on differences in the content individuals seek.
Asano, E. (2017), How much time do people spend on social media?,availableat:www.
(accessed 3 March 2019).
Ashley, C. and Tuten, T. (2015), Creative strategies in social media marketing: an exploratory study of
branded social content and consumer engagement,Psychology and Marketing, Vol. 32 No. 1,
pp. 15-27.
Balaji, M.S. and Roy, S.K. (2017), Value co-creation with internet of things technology in the retail
industry,Journal of Marketing Management, Vol. 33 Nos 1/2, pp. 7-31.
Carlson, J., Rahman, M., Voola, R. and De Vries, N. (2018), Customer engagement behaviours in social media:
capturing innovation opportunities,Journal of Services Marketing, Vol. 32 No. 1, pp. 83-94.
Chang, C. (2009), Being hookedby editorial content: the implications for processing narrative
advertising,Journal of Advertising, Vol. 38 No. 1, pp. 21-34.
Chen, Q. and Wells, W.D. (1999), Attitude toward the site,Journal of Advertising Research, Vol. 39
No. 5, pp. 27-38.
Chepurna, M. and Rialp Criado, J. (2018), Identication of barriers to co-create on-line: the perspectives of
customers and companies,Journal of Research in Interactive Marketing, Vol. 12 No. 4, pp. 452-471.
Cooper, P. (2019), 28 Twitter statistics all marketers need to know in 2019, available at: https://blog. (accessed 3 March 2019).
Cyca, M. (2018), Stop posting the same message on social media and do this instead, available at: (accessed 3 March 2019).
Analysis of
social media
Dessart, L. (2017), Social media engagement: a model of antecedents and relational outcomes,Journal
of Marketing Management, Vol. 33 No. 5, pp. 375-399.
Dimmick, J., Chen, Y. and Li, Z. (2004), Competition between the internet and traditional news media: the
gratication-opportunities niche dimension,The Journal of Media Economics, Vol. 17 No. 1, pp. 19-33.
Dineva, D.P., Breitsohl, J.C. and Garrod, B. (2017), Corporate conict management on social media
brand fan pages,Journal of Marketing Management, Vol. 33 Nos 9/10, pp. 679-698.
Dolan, R., Conduit, J., Fahy, J. and Goodman, S. (2016), Social media engagement behaviour: a uses and
gratications perspective,Journal of Strategic Marketing, Vol. 24 Nos 3/4, pp. 261-277.
Ducoffe, R.H. (1996), Advertising value and advertising on the web,Journal of Current Issues and
Research in Advertising, Vol. 17 No. 1, pp. 21-21.
Economist (2015), A brand new game, available at:
game (accessed 11 March 2016)
Eighmey, J. (1997), Proling user responses to commercial web sites,Journal of Advertising Research,
Vol. 37 No. 3, pp. 59-67.
Elder, J. (2014), Social media fail to live up to early marketing hype, available at: http://online.wsj.
com/articles/companies-alter-social-media-strategies-1403499658 (accessed 1 July 2014).
Escalas, J.E. and Bettman, J.R. (2005), Self-construal, reference groups, and brand meaning,Journal of
Consumer Research, Vol. 32 No. 3, pp. 378-389.
Fornell, C. and Larcker, D.F. (1981), Evaluating structural equation models with unobservable
variables and measurement error,Journal of Marketing Research, Vol. 18 No. 1, pp.39-50.
Frier, S. (2018), Instagram looks like facebooks best hope, available at:
features/2018-04-10/instagram-looks-like-facebook-s-best-hope (accessed 18 October 2018).
Fuller, C.M., Simmering, M.J., Atinc, G., Atinc, Y. and Babin, B.J. (2016), Common methods variance
detection in business research,Journal of Business Research, Vol. 69 No. 8, pp. 3192-3198.
Gremler, D.D. (2004), The critical incident technique in service research,Journal of Service Research,Vol.7
No. 1, pp. 65-89.
Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2010), Multivariate Data Analysis, 7th ed.,
Pearson Prentice Hall, Upper Saddle River, NJ.
Hanna, R., Rohm, A. and Crittenden, V.L. (2011), Were all connected: the power of the social media
ecosystem,Business Horizons, Vol. 54 No. 3, pp. 265-273.
Hatch, M.J. and Schultz, M. (2010), Toward a theory of Brand co-creation with implications for brand
governance,Journal of Brand Management, Vol. 17 No. 8, pp. 590-604.
Hennig-Thurau, T., Gwinner, K.P., Walsh, G. and Gremler, D.D. (2004), Electronic word-of-mouth via
consumer-opinion platforms: what motivates consumers to articulate themselves on the
internet?,Journal of Interactive Marketing, Vol. 18 No. 1, pp. 38-52.
Hewett, K., Rand, W., Rust, R.T. and van Heerde, H.J. (2016), Brand buzz in the echoverse,Journal of
Marketing, Vol. 80 No. 3, pp. 1-24.
Hollebeek, L.D., Glynn, M.S. and Brodie, R.J. (2014), Consumer brand engagement in social media:
conceptualization, scale development and validation,Journal of Interactive Marketing, Vol. 28 No. 2,
pp. 149-165.
Hu, L.T. and Bentler, P.M. (1999), Cutoff criteria for t indexes in covariance structure analysis:
conventional criteria versus new alternatives,Structural Equation Modeling: A Multidisciplinary
Journal, Vol. 6 No. 1, pp. 1-55.
Huang, R., Ha, S. and Kim, S.H. (2018), Narrative persuasion in social media: an empirical study of luxury
brand advertising,Journal of Research in Interactive Marketing, Vol. 12 No. 3, pp. 274-292.
Jahn, B. and Kunz, W. (2012), How to transform consumers into fans of your brand,Journal of Service
Management, Vol. 23 No. 3, pp. 344-361.
Kao, T.Y., Yang, M.H., Wu, J.T.B. and Cheng, Y.Y. (2016), Co-creating value with consumers through
social media,Journal of Services Marketing, Vol. 30 No. 2, pp. 141-151.
Kaplan, A. and Haenlein, M. (2010), Users ofthe world, unite! the challenges and opportunities of social
media,Business Horizons, Vol. 53 No. 1, pp. 59-68.
Katz, E. (1959), Mass communications research and the study of popular culture: an editorial note on a
possible future for this journal,Studies in Public Communication, Vol. 2, pp. 1-6.
Kemp, S. (2019), Digital trends 2019: every single stat you need to know about the internet, available
need-to-know-about-the-internet/ (accessed 18 October 2018).
Kietzmann, J.H., Hermkens, K., McCarthy, I.P. and Silvestre, B.S. (2011), Social media? Get serious!
understanding the functional building blocks of social media,Business Horizons, Vol. 54 No. 3,
pp. 241-251.
Ko, H., Cho, C.H. and Roberts, M.S. (2005), Internet uses and gratications: a structural equation model
of interactive advertising,Journal of Advertising, Vol. 34 No. 2, pp. 57-70.
Kolowich, L. (2019), The ultimate list of instagram stats 2019, available at:
marketing/instagram-stats (accessed 3 March 2019).
Korgaonkar, P.K. and Wolin, L.D. (1999), A multivariate analysis of web usage,Journal of Advertising
Research, Vol. 39 No. 2, pp. 53-68.
Lufkens, M. (2018), Twiplomacy study 2018, available at:
study-2018/ (accessed 3 March 2019).
Luo, X. (2002), Uses and gratications theory and e-consumer behaviors: a structural equation
modeling study,Journal of Interactive Advertising, Vol. 2 No. 2, pp. 34-41.
McAlister, L., Srinivasan, R. and Kim, M. (2007), Advertising, research and development, and
systematic risk of the rm,Journal of Marketing, Vol. 71 No. 1, pp. 35-48.
Malthouse, E., Haenlein, M., Skiera, B., Wege, E. and Zhang, M. (2013), Managing customer
relationships in the social media era: introducing the social CRM house,Journal of Interactive
Marketing, Vol. 27 No. 4, pp. 270-280.
Matsa, K. and Shearer, E. (2018), News use across social media platforms 2018,availableat:www. (accessed 3 March 2019).
Mawhinney, J. (2018), 45 Visual content marketing statistics you should know in 2018, available at: (accessed 28 October 2018).
Meyer, T., Barnes, D.C. and Friend, S.B. (2017), The role of delight in driving repurchase intentions,
Journal of Personal Selling and Sales Management, Vol. 37 No. 1, pp. 61-71.
Nunnally, J.C. and Bernstein, I.H. (1994), Psychometric Theory, 3rd ed., McGraw-Hill, New York, NY.
Papacharissi, Z. and Rubin, A.M. (2000), Predictors of internet use,Journal of Broadcasting and
Electronic Media, Vol. 44 No. 2, pp. 175-196.
Perrin, A. (2015), Social Media Usage: 2005-2015, Pew Internet and American Life Project, Washington, DC.
Peters, K., Chen, Y., Kaplan, A.M., Ognibeni, B. and Pauwels, K. (2013), Social media metricsa
framework and guidelines for managing social media,Journal of Interactive Marketing, Vol. 27
No. 4, pp. 281-298.
Pew Research (2018), Social media fact sheet, available at:
media/ (accessed 8 October 2018).
Phua, J., Jin, S.V. and Kim, J.J. (2017), Uses and gratications of social networking sites for bridging
and bonding social capital: a comparison of Facebook, Twitter, Instagram, and Snapchat,
Computers in Human Behavior, Vol. 72, pp. 115-122.
Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P. (2003), Common method biases in
behavioral research: a critical review of the literature and recommended remedies,Journal of
Applied Psychology, Vol. 88 No. 5, pp. 879-903.
Analysis of
social media
Pricewaterhouse Coopers (2018), Global entertainment and media outlook 20182022, available at: (accessed 16 September 2018).
Purnawirawan, N., Eisend, M., De Pelsmacker, P. and Dens, N. (2015), A meta-analytic investigation of
the role of valence inonline reviews,Journal of Interactive Marketing, Vol. 31 No. 1, pp. 17-27.
Ruggiero, T.E. (2000), Uses and gratications theory in the 21st century,Mass Communication and
Society, Vol. 3 No. 1, pp. 3-37.
Rust, R.T., Lemon, K.N. and Zeithaml, V.A. (2004), Return on marketing: using customer equity to
focus marketing strategy,Journal of Marketing, Vol. 68 No. 1, pp. 109-127.
Severin, W.J. and Tankard, J.W. (1997), Communication Theories: Origins, Methods, and Uses in the
Mass Media, 4th ed., Longman, New York, NY.
Simonin, B.L. and Ruth, J.A. (1998), Is a company known by the company it keeps? Assessing the
spillover effects of Brand alliances on consumer Brand attitudes,Journal of Marketing
Research, Vol. 35 No. 1, pp. 30-42.
Singh, S. and Sonnenburg, S. (2012), Brand performances in social media,Journal of Interactive
Marketing, Vol. 26 No. 4, pp. 189-197.
Smith, A. and Anderson, M. (2018), Social media use in 2018, available at:
03/01/social-media-use-in-2018/ (accessed 14 October 2018).
Soboleva, A., Burton, S., Mallik, G., Khan, A. (2017), Retweet for a chance to...: an analysis of what
triggers consumers to engage in seeded eWOM on twitter,Journal of Marketing Management,
Vol. 33 Nos 13/14, pp. 1120-1148.
Stelzner, M. (2018), Social media marketing industry report, available at: www.socialmediaexaminer.
com/social-media-marketing-industry-report-2018/ (accessed 3 March 2019).
Sterling, G. (2017), Mobile now accounts for nearly 70% of digital media time, available at: https://
(accessed 19 October 2018)
Sternthal, B., Dholakia, R. and Leavitt, C. (1978), The persuasive effect of source credibility: tests of
cognitive response,Journal of Consumer Research, Vol. 4 No. 4, pp. 252-260.
Triantallidou, A. and Siomkos, G. (2018), The impact of Facebook experience on consumers
behavioral Brand engagement,Journal of Research in Interactive Marketing, Vol. 12 No. 2,
pp. 164-192.
Vernette, E. and Hamdi-Kidar, L. (2013), Co-creation with consumers: who has the competence and
wants to cooperate,International Journal of Market Research, Vol. 55 No. 4, pp. 539-561.
Yang, S., Lin, S., Carlson, J.R. and Ross, W.T. (2016), Brand engagement on social media: will rms
social media efforts inuence searching engine advertising effectiveness?,Journal of Marketing
Management, Vol. 32 Nos5/6, pp. 526-557.
Zhu, Y. and Chen, H. (2015), Social media and human need satisfaction: implications for social media
marketing,Business Horizons, Vol. 58 No. 3, pp. 335-345.
Corresponding author
Mark J. Pelletier can be contacted at:
For instructions on how to order reprints of this article, please visit our website:
Or contact us for further details:
... The past literature documented the motivations and engagement behaviour among social media users using the Uses and Gratifications theory as their theoretical framework mainly applied to understand motivation and social media engagement from the perspective of customers and marketers (e.g., Buzeta et al., 2020;Cao et al., 2020;Dolan et al., 2016;De Vries et al., 2017;Enginkaya & Yılmaz, 2014;Muntinga et al., 2011;Pelletier et al., 2020). Few studies have focused on social media users other than them. ...
... All social media platforms were considered. Certain articles seemed to be irrelevant for the review, for instance, papers with the keywords such as " electronic word of mouth (e-WOM)" by Wang et al. (2017) and ; papers on "social media branding", "social media marketing" by Pelletier et al. (2020); "social media advertising" by Dodoo & Youn, (2021); "customer social media engagement", "luxury marketing" by Pentina et al. (2018); "employee engagement" by Ewing et al. (2019) and Jiang & Luo (2020) and "customer engagement" by Chen et al. (2020). A few descriptive qualitative papers on "social media engagement", "consumer brand stories", by Saleem & Iglesias (2020); "engagement leading to action" by Smith & Gallicano (2015) were excluded. ...
Full-text available
This article uses a systematic literature review (SLR) technique to study research literature that deals with motivation for social media engagement using the Uses and Gratification theory as a theoretical framework. A total of 352 articles published between 2011 and 2021, indexed in credible research databases e.g., Science Direct, Taylor & Francis, Emerald Insight, and Google Scholar, have been reviewed. The result shows motivations for social media use are information seeking and sharing, socialising, social investigation, entertainment, social enhancement, professional use, affection, self-discovery and surveillance. Along with this, social media engagement behaviour identified comes under consumption, contribution, and creation. The study will help organisations, social media developers and researchers to understand how people consume social media and for what purposes. The findings of the study may be used for planning various communication campaigns using social media. The study will further encourage future researchers to take up inquiries on the 'development perspective' of social media e.g., use of social media for social development leaving aside its application for complete commercial gain.
... This perspective conceptualizes individuals as proactive and utilitarian decision makers who select media content based on the extent to which it gratifies their needs. The theory was further extended to apply to gratifications on social media [16,43,44] by examining how consumers engage with social media content that provides them with a value [16,45], and dividing consumer needs into two main orientations: a social relationship orientation and a self-orientation [46][47][48]. Previous research on consumer behavioral engagement with social media posts was found to be dependent on factors such as post content [49,50], characteristics [51,52], and quality [53,54]. ...
Full-text available
The purpose of this study is to establish which message appeal is more effective in generating consumer engagement with social media posts of small and medium-sized agri-food businesses that promote direct-to-consumer sales during a COVID-19 type crisis. Using quantitative content analysis, 1024 posts from 48 Israeli farmers' Facebook brand pages were categorized into altruistic messages (ethnocentric, toward farmers, toward the environment, and maintaining public health) and egoistic messages (economic, emotional, functional, and hedonic values). The effectiveness of the message appeals was determined by consumer behavioral engagement (comments, shares and likes) with the posts. The results show that farmers used more egotistic arguments (mainly functional and hedonic motives) than altruistic arguments during the three stages of the crisis. However, a one-way ANOVA test revealed that posts with altruistic messages (specifically, altruism toward farmers) or posts that combine altruistic and egoistic motivations equally yielded significantly more consumer behavioral engagement. Practical recommendations regarding agri-food communications in times of crisis are given.
... Twitter states its own purpose as serving the public conversation, bringing diverse perspectives together (Twitter, 2020). While the different social media platforms share an interest in encouraging engagement and conversation, Twitter in particular can be seen as a platform users go to for information and social interaction (Pelletier et al., 2020). ...
Full-text available
Social media impact not only our communication and social interactions but also our relationships to the natural environment. Social media can increase understanding of our environment by offering information and sharing calls to action, while at the same time, they might present a glamourised, standardised picture of nature and distract from actual outdoor interactions. The COVID‐19 pandemic presents a unique opportunity to study the spaces created for interactions between the online and offline natural world, especially in countries where movement and thus outdoor activities were restricted during lockdowns. To understand these interactions, we investigated the social media communication of nature conservation and outdoor organisations by analysing Twitter posts of four prominent NGOs in Scotland. We found that during the first COVID‐19‐induced UK lockdown in spring 2020, Scottish nature conservation and outdoor organisations made distinctive efforts in supporting followers to connect with nature in the face of restrictions. Organisations showed signs of moving towards community‐building through sharing experiences often related to nearby nature, while calls for environmental action, more prominent in the previous year, receded in relative importance. Emphasis was put on sensory engagement with, and finding solace in the rhythm of, nature. References to taking action to protect nature now became linked to a green recovery from the pandemic. We conclude that NGOs used social media not as a space separate from the outdoors, but as an augmented space where online and offline interactions were interwoven and a space in which during the COVID‐19 pandemic, new avenues for engagement were being explored. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog.
Social media is an excellent medium for sharing content to promote destinations and engage tourists. This study aimed to examine the impact of content characteristics of social media posts shared by destination marketing organisations (DMOs) on tourist engagement. An analysis of over 12,000 posts and 3.65 million tourist impressions recorded on 16 official Indian DMOs’ Facebook and Twitter handles was undertaken. Tourist engagement was measured by likes, comments/tweets, and shares/retweets counts. The analysis revealed that interactive and informative posts gained maximum engagement on Facebook and Twitter, respectively. The varied effect of content richness and content elaborateness were explicated. The study contributes to the emerging literature on tourist engagement and provides practical prescriptions for DMOs to effectively design cross-platform content.
The popularity of social networking platforms has increased dramatically in recent years, impacting how people communicate, exchange ideas and exert influence on others. These platforms have provided new opportunities for people to connect and engage with each other, ultimately reshaping their sense of belonging and constructing their identity. The current study focuses on how Qatari youth use social media networks as a tool for identity interaction. By examining the motives for, perceptions about and impacts of social media usage, this study provides insights into how the Qatari youth use these platforms. The research employed a quantitative method, collecting data via an online survey administered through Google Forms. A total of 532 Qatari youth responded to the study. This study’s findings illustrate that most youth use social networks frequently, with half stating that they are always connected. In addition, over 40 per cent report subscribing to one to five groups on social networks. The primary motivation for joining these groups is to engage in discussion about social and political issues as well as to stay up-to-date on the news about their community. According to this study, the most popular social media platform among Qatari youth is Instagram, followed by WhatsApp and Twitter. People use these platforms for different reasons, but many find them to be helpful in staying connected with friends and family, sharing news and experiences and staying up-to-date on current events. Moreover, nearly half of the youth who took part in this study claimed that social media had contributed to creating role models in society. This indicates that social media may play a significant role in shaping young people’s identity and their sense of belonging. A significant number of respondents reported that social media role models influenced their personal choices such as dress, perfumes, language and fashion. This suggests that social media play an unmissable part in shaping individuals’ personal preferences and their cultural identities.
Brands increasingly use social media to engage with consumers as part of their marketing efforts. This study analyzes the Instagram strategies used by three global outdoor-sports brands and their respective effects on consumer-brand engagement, operationalized as the number of ‘likes’ and comments received by posts. Content analysis conducted on Instagram posts from Arc’teryx, Salomon, and Patagonia focused on messages’ textual, visual, and technical attributes. The results indicate that task- and interaction-oriented posts received more ‘likes’ than self-oriented ones. Brand messages that were shorter, included photos and/or ‘cute’ visuals, or mentioned other Instagram users were found to motivate consumer engagement on Instagram. These findings will facilitate social media marketers’ development of effective Instagram branding strategies.
Full-text available
The games as a service model have enabled game developers to reach worldwide audiences and regard games as services rather than products, opening up new avenues to establish value propositions. Freemium–premium gaming models of value co-creation have been studied in the past. Fostering the conversion of free users to premium subscribers and retaining those premium users are critical objectives for premium service providers. It is critical to effectively enable value co-creation through appropriate value propositions when the logic shifts from products to services such as depicted in the service-dominant logic. Since value propositions are the cornerstone of value, they must include insights about the customer’s preferences, capabilities, and expectations, which can be gathered through the customer’s value co-creation activities. Furthermore, little is known about the value realization that is assessed after using premium gaming services. The current study, which builds on the conceptual foundations of S-D logic, intends to investigate the gaming players’ in-game co-creation experiences in the premium gaming setting through value co-creation activities. The model was tested using structural equation modeling (SEM)-based partial least based on survey data collected from 346 online gamers who used in-game premium services. The findings indicate that superior functionality, competition, sociability, personalization, and self-indulgence all have a substantial impact on players’ desire to co-create with gaming service providers. Furthermore, the data revealed a significant outcome of value realization, which is appraised based on the premium gaming players’ co-creation experience aspects. The findings of study 1 were further validated through qualitative intuitions to ensure the robustness of the valuable key insights, which confirms that different premium gaming motivations are necessary to enhance the value co-creation ties and gamer’s overall co-creation experience positively. To improve premium players’ co-creation experiences, online game service providers should route co-creation media into premium gaming settings.
The current study seeks to extend the network paradigm in public relations research by exploring the role of online opinion leaders in Twitter conversations around anthem protests by prominent athletes. The aim of the study is twofold: (1) identify opinion leaders involved in Twitter conversations related to anthem protests by Colin Kaepernick and Megan Rapinoe, and (2) further understand how and why social media users participate in conversations online about controversial subjects. The study combines social network analysis with in-depth interviews to adopt a more holistic framework for studying online opinion leadership in the context of public relations research. Ultimately, results from this study extend the network paradigm in public relations by examining the role of individual users in the construction of the discursive landscape around issue networks. Additionally, findings suggest that online opinion leaders should be differentiated from social media influencers in public relations scholarship as they reflect the movement away from Homo Economicus toward Homo Dialogicus (Kent & Taylor, 2016) and their capacity to facilitate the formation of publics and counterpublics around particular issues.
Purpose User-generated content (UGC) refers to semantic and behavioral traces created by users on various social media platforms. While several waves of platforms have come and gone, the long-term sustainability of UGC activities has become a critical question that bears significance for theoretical understanding and social media practices. Design/methodology/approach Based on a large and lengthy dataset of both blogging and microblogging activities of the same set of users, a multistate survival analysis was applied to explore the patterns of users' staying, switching and multiplatforming behaviors, as well as the underlying driving factors. Findings UGC activities are generally unsustainable in the long run, and natural attrition is the primary reason, rather than competitive switching to new platforms. The availability of leisure time, expected gratification and previous experiences drive users' sustainability. Originality/value The authors adopted actual behavioral data from two generations of platforms instead of survey data on users' switching intentions. Four types of users are defined: loyal, switcher, multiplatformer and dropout. As measured by the transitions among the four states, the different sustainability behaviors are thereby studied via an integrated framework. These two originalities bridge gaps in the literature and offer new insights into exploring user sustainability in social media.
Full-text available
The branding literature has long recognized the power of storytelling to provide meaning to the brand and practitioners have used storytelling to enhance consumers' connections with brands. The premise of brand storytelling has been that the story and its content, production, and distribution are the brand owner's realm and the consumer primarily a listener. The emergence of social media has changed the consumers' role in storytelling from that of a passive listener to a more active participant. Our paper uses the metaphor of improvisation (improv) theater to show that in social media brand owners do not tell brand stories alone but co-create brand performances in collaboration with the consumers. The first and foremost contribution of such a conceptualization is that it offers a semantic framework that resolves issues in storytelling, demonstrates the necessity of co-creation in storytelling, and identifies the core of an inspiring story. The improv theater metaphor also helps identify the following three propositions relevant for branding in social media: (i) the process of improvisation is more important than the output, (ii) managing brands is about keeping the brand performance alive, and (iii) understanding the audience and its roles is the prerequisite for a successful brand performance.
Full-text available
Purpose Value co-creation is an important topic of interest in marketing domain for the past decade. Co-creation via the internet has received a particular attention in the literature (O’Hern and Rindfleisch, 2010). Although there have been substantive number of studies of what motivates customers to participate in value co-creation in the internet-based platforms, there is a lack of research of what the deterrents are that may prevent customers from contributing their ideas online. This research was undertaken to define the deterrents from the customers and companies’ point of view. Furthermore, the difference, if exists, between the users’ and marketing professionals’ ranking of the inhibitors to co-creation online is also studied. Design/methodology/approach This exploratory qualitative research is based on 20 in-depth semi-structured interviews with customers and 20 in-depth semi-structured interviews with marketing specialists from different companies. Spearman’s rank correlation is applied to explore the relationship between the internet users’ and marketers’ responses. Findings There are nine constraining factors. The results show that although there is a repetition of the mentioned constraining factors indicated by the both groups of the interviewees, the ranking of the barriers is distinctive. Research Implications New conceptual information is received on what restrains customers from co-creation from both customers’ and companies’ point of view. Practical Implications This paper explains the potential problems to be confronted when launching a co-creation project in the internet-based platforms and offers managers a preliminary guide to comprehension of the users’ deterrents rating. Originality The paper that defines deterrents to co-creation online.
Full-text available
Purpose Social media brand pages have become instrumental in enabling customers to voluntarily participate in providing feedback/ideas for improvement and collaboration with others that contribute to the innovation effort of brands. However, research on mechanisms which harness these specific customer engagement behaviours (CEB) in branded social media platforms is limited. Based on the stimulus–organism–response paradigm, this study investigates how specific online-service design characteristics in social media brand pages induce customer-perceived value perceptions, which in turn, stimulate feedback and collaboration intentions with customers. Design/methodology/approach Data collected from 654 US consumers of brand pages on Facebook were used to empirically test the proposed framework via structural equation modelling. Findings The theoretical framework found support for most hypothesized relationships showing how online-service design characteristics induce an identified set of customer value perceptions that influence customer feedback and collaboration intentions. Research limitations/implications The sample is restricted to customer evaluations of brand pages on Facebook in the USA. Practitioners are advised to maximize online-service design characteristics of content quality, brand page interactivity, sociability and customer contact quality as stimulants that induce brand learning value, entitativity value and hedonic value. This then translates to customer feedback and collaboration intentions towards the brand page. Originality/value The findings have important implications for the design and optimization of online services in the customer engagement-innovation interface to harness CEBs for innovation performance.
Full-text available
A recent development in the literature on social media brand fan pages is the investigation of hostile consumer-to-consumer interactions. Existing research has thus far concentrated on the reasons why consumers engage in such online conflicts. In comparison, this study focuses on how online conflicts can be best managed. Based on direct observations of six brand fan pages on Facebook, we offer a first conceptualisation of corporate conflict management strategies. Our results reveal five main conflict management strategies: non-engaging, censoring, bolstering, informing and pacifying. By drawing on existing suggestions from the marketing literature, we provide managerial implications and suggest avenues for future research.
Marketing executives are being urged to speak in the language of finance to gain internal support for marketing initiatives. Responding to this call, the authors examine the impact of a firm's advertising and its research and development (R&D) on the systematic risk of its stock, a key metric for publicly listed firms. They hypothesize that a firm's advertising and R&D expenditures create intangible assets that insulate it from stock market changes, lowering its systematic risk. They test the hypotheses using a panel data on 644 publicly listed firms between 1979 and 2001, consisting of five-year moving windows. They scale the firm's advertising and R&D expenditures by its sales. After controlling for factors that accounting and finance researchers have shown to be associated with systematic risk, the authors find that advertising/sales and R&D/sales lower a firm's systematic risk. The article's findings extend prior research that has focused primarily on the effect of marketing initiatives on performance metrics without consideration of systematic risk. For practice, the ability of advertising and R&D to reduce systematic risk highlights the multifaceted implications of advertising and research programs. The article's findings may surprise senior management, some of whom are skeptical of the financial accountability of advertising programs.
The authors examine the growing and pervasive phenomenon of brand alliances as they affect consumers’ brand attitudes. The results of the main study (n = 350) and two replication studies (n = 150, n = 210) together demonstrate that (1) consumer attitudes toward the brand alliance influence subsequent impressions of each partner's brand (i.e., “spillover” effects), (2) brand familiarity moderates the strength of relations between constructs in a manner consistent with information integration and attitude accessibility theories, and (3) each partner brand is not necessarily affected equally by its participation in a particular alliance. These results represent a first, necessary step in understanding why and how a brand could be affected by “the company it keeps” in its brand alliance relationships.
Purpose This paper aims to investigate the effectiveness of social media communication in luxury brand advertising from a narrative persuasion perspective. Specific purposes are to examine how characteristics of a message giver (i.e. comprehension fluency, imagery fluency) and message receiver (i.e. transportability, need for affect) influence the narrative persuasion process which further affects consumers’ subsequent responses (i.e. positive affect, brand social networking services [SNS] attitudes and intentions) within the luxury hotel industry. Design/methodology/approach An online survey was performed via Amazon MTurk. A total of 193 usable responses from SNS users were obtained. The structural equation modeling approach was used to test the proposed model. Findings Results show that comprehension fluency and imagery fluency as message-giver factors and transportability as a message-receiver factor positively affect narrative transportation. In addition, narrative transportation leads to positive affect, brand SNS attitudes and visit intentions, while positive affect also influences brand SNS attitudes and visit intentions. Furthermore, additional analyses indicate that narrative transportation mediates the effects of comprehension fluency on affect and brand SNS as well as the effects of transportability on positive affect, brand SNS attitude and visit intention. Originality/value Characteristics of a message giver and message receiver altogether are not well understood in the current literature. Empirical evidence in this study contributes to the social media marketing and brand advertising research fields.
Purpose The aim of the present study is twofold. First, it measures Facebook users’ experience in a holistic way by taking into account the various dimensions of Facebook experience (i.e. entertainment, flow, escapism, challenge, learning, socializing and communitas); second, it tests the effects of these dimensions in relation to consumers’ brand engagement on Facebook. Design/methodology/approach Two online surveys were conducted using self-administered questionnaires. Respondents were recruited through the snowball sampling technique. Findings The findings suggest that the different experiential elements of Facebook usage have varying effects on the two brand engagement factors (consuming and contributing) on Facebook. Specifically, the passive element (consuming) is positively influenced by the dimensions of flow and communitas (i.e. feelings of belongingness), while escapism is found to be a negative predictor. The active element of engagement (contributing) is positively affected by dimensions such as entertainment, flow, socializing and communitas. Practical implications Brand managers should design Facebook pages for their brands that entertain and immerse consumers, while enabling them to socialize and bond with others to increase levels of consumers’ engagement with brands on Facebook. However, brand managers should be cautious regarding the fantasy experience (escapism) offered by their Facebook pages, as this can distract consumers from the content of the brand page. Originality/value To date, most studies on Facebook usage have been conducted under the uses and gratifications framework, while the various elements that comprise Facebook users’ experience have not received sufficient attention in previous conceptualizations of Facebook experience. In addition, the present study enhances the research by examining consumers’ brand engagement on Facebook as a potential consequence of the various Facebook experience dimensions.
Twitter provides an important channel for brands to seed electronic word of mouth (eWOM) by followers retweeting brand messages, but prior research has not established a theoretical framework for how brands can maximise eWOM. This study presents and tests a theoretical model incorporating interactive, textual and visual tweet features to predict eWOM, using tweets by leading brands from three industries. Industry was found to be an important moderator of the effect of tweet features; after controlling for the reach and frequency of tweets, hashtags, retweet requests and photos were consistently associated with a higher retweet rate across industries, but the effect of URL links, non-initial mentions and video varied across industries, in some cases decreasing the retweet rate. Implications for research and practice are discussed.
This article investigates individual-level antecedents and relational outcomes of social media engagement. Social media engagement approached in this study is a three-dimensional construct composed of affective, cognitive and behavioural dimensions. Surveying more than 48 Facebook pages, spanning nine product categories and 448 consumers, the results show that product involvement, attitude towards the community and online interaction propensity all impact social media engagement. The study also reveals that high social media engagement increases brand relationships significantly, particularly affecting brand trust, commitment and loyalty. Additionally, community engagement appears as a precursor of brand engagement. These findings provide insight into antecedents and outcomes of engagement for academic research and bring value to online brand and community management.