Is visual content modality a limiting factor for social capital? Examining user engagement within Instagram-based brand communities

Abstract

In the age of virtual cocreation of value by consumers, the role of the content modality in the development of social capital has been largely overlooked. Given that different modalities lead to varied forms of digital communication, this study examines whether a predominantly visual modality can enhance social capital and improve the collective value perceived by members of an online brand community. Through quantitative analysis, this study demonstrates that the visual modality of Instagram fosters social interactions, shaping the platform’s engagement dynamics. Affect-based visual imagery is persuasive in eliciting responses that match the hedonic nature of the platform. Therefore, fostering a positive emotional connection to both the community and the brand can lead to increased loyalty. This research proposes a different perspective on the interactive social exchange that facilitates the establishment of social capital. Value cocreation engagement is not necessarily dependent on the extensiveness of information depth. Adopting an affective orientation in persuasion has shown efficacy in forming attitudes towards attitudinal objects, particularly the community and brand.

Full text

ARTICLE
Is visual content modality a limiting factor for social
capital? Examining user engagement within
Instagram-based brand communities
Agung Artha Kusuma 1✉, Adi Zakaria Afiff1, Gita Gayatri1& Sri Rahayu Hijrah Hati1
In the age of virtual cocreation of value by consumers, the role of the content modality in the
development of social capital has been largely overlooked. Given that different modalities
lead to varied forms of digital communication, this study examines whether a predominantly
visual modality can enhance social capital and improve the collective value perceived by
members of an online brand community. Through quantitative analysis, this study demon-
strates that the visual modality of Instagram fosters social interactions, shaping the platform’s
engagement dynamics. Affect-based visual imagery is persuasive in eliciting responses that
match the hedonic nature of the platform. Therefore, fostering a positive emotional con-
nection to both the community and the brand can lead to increased loyalty. This research
proposes a different perspective on the interactive social exchange that facilitates the
establishment of social capital. Value cocreation engagement is not necessarily dependent on
the extensiveness of information depth. Adopting an affective orientation in persuasion has
shown efficacy in forming attitudes towards attitudinal objects, particularly the community
and brand.
https://doi.org/10.1057/s41599-023-02529-6 OPEN
1Department of Management, Faculty of Economics and Business, Universitas Indonesia, Depok, Indonesia. ✉email: arthak1007@gmail.com;anak.agung911@ui.ac.id
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Introduction
The rise in social media use among consumers, coupled with
the inherently social nature of consumption, has amplified
consumer-to-consumer interactions. This development is
vital to understanding cocreation among consumers (Brodie et al.
2011; Schau et al. 2009). Online brand communities (OBCs)
based on social media provide fertile ground for examining the
dynamics of consumer networking, leading to mutual value
creation (Brodie et al. 2011; Habibi et al. 2014). With the abun-
dance of social media platforms, it is essential to consider the
specific platform on which the brand community exists. Members
of OBCs engage with each other to consume, produce, and share
information about products, ideas, or experiences associated with
a brand. (Brodie et al. 2013). Consequently, the content modality
of social media can shape the level of engagement within an OBC.
Adefining characteristic that sets the social context of a platform
apart is its content modality, which pertains to the kind of con-
tent that users typically produce or share (Waterloo et al. 2018).
Contemporary social media platforms support a range of content
modalities. However, Instagram stands out as a social networking
platform that emphasises expression through images and short
videos, often enhanced with filters. This implies that visual aes-
thetics are the focus of content generation (Jin and Ryu, 2020;
Kusumasondjaja, 2020), with text serving to provide context or
magnify the meaning of the visuals.
The apparent popularity of networked visual communication
(McCrow-Young, 2021) has positioned Instagram as the second
most significant social media platform for marketing commu-
nication, trailing only Facebook in popularity (Kim et al. 2021).
While methodological reflections have largely centred around
text-driven platforms such as Facebook, Twitter, and discussion
forums (McCrow-Young, 2021), there is a noticeable oversight of
visual-centric social media platforms such as Instagram (Leaver
et al. 2020). This situation prompts questions about the differ-
ences between text-centric social media platforms and those such
as Instagram, which prioritise images over text (Arceneaux and
Dinu, 2018; Yang and Jiang, 2021). Consequently, the quality and
density of information exchanged might be limited (Felbermayr
and Nanopoulos, 2016; Figueiredo et al. 2013), potentially redu-
cing the accumulation of social capital within the network.
Past research has evaluated the efficacy of both visual and
verbal modalities (Zhao et al. 2022), with certain studies indi-
cating that the visual modality exhibits a superior effect (Joffe,
2008; Sundar, 2008). The image modality is considered to convey
heuristic cues (Jeong, 2008), thus facilitating faster information
processing. Moreover, image modality carries emotional, vivid,
and memorable impressions (Joffe, 2008). Numerous studies have
consistently demonstrated that visual information is more per-
suasive than textual content (Childers, 1986; McQuarrie and
Mick, 1999; Smith, 1991). This recapitulation underscores the
potential of image modality for capturing the attention of social
media users and driving engagement (Taecharungroj, 2017).
Consequently, it holds significant potential for the evolution of
social capital through value cocreation within the online
community.
In addressing value cocreation within an OBC, social capital is
defined as a society that promotes cooperation within the net-
work, accumulating shared resources to enhance individual or
collective productivity (Bourdieu and Richardson, 1986; Nahapiet
and Ghoshal, 1998; Putnam, 1993; Watson and Papamarcos,
2002). Continuous interaction is pivotal for the establishment and
growth of social capital, especially within an OBC. Given the
intrinsic link between social interaction and social capital, the
functionality of the community heavily relies on member inter-
activity (Ghahtarani et al. 2020). Given that social capital is an
intangible asset, it is primarily acquired through social
interaction. Through consistent exchanges, community members
collaboratively conceive and disseminate information. This pro-
cess enhances familiarity and elevates the quality of shared
resources (Zarei et al. 2022). As a result, social capital is cultivated
(Cao et al. 2022).
Drawing from the interplay between social interaction and
social capital, members within an OBC have the opportunity to
collaboratively create and exchange value (Wang et al. 2023) that
resonates with their individual interests. Therefore, promoting
engagement that encourages interaction is synonymous with
fostering the exchange of valuable resources. Consequently, social
capital emerges as the crucial foundation for value creation
(Ghahtarani et al. 2020). Therefore, understanding the char-
acteristics of social capital and the impact of these characteristics
on consumers is crucial for enhancing participation and nurtur-
ing cocreative relationships.
By consolidating user interactions, social capital, and content
modality, research objectives that address the research gaps in
the literature can be formulated. Studies on social capital in
social media-based OBCs predominantly focus on text-centric
platforms such as Facebook (Mostafa, 2021;Wong,2023),
online forums (Meek et al. 2019a), or Twitter (Fenton et al.
2021; Garay and Morales, 2020). These developments demon-
strate that textual information remains the primary modality for
electronic social exchanges that create value (Li et al. 2020;
Margaris et al. 2019). In contrast, the scarcity of studies
regarding Instagram’sOBCs(Casalóetal.2017)raisesthe
question of whether Instagram’s image content modality can
accommodate social capital creation.
Previous research primarily studied firm-hosted communities
(Wong and Lee, 2022). This predominance in the research can be
attributed to the consumer durable goods industry phenomenon,
in which there is an apparent prevalence of firm-initiated OBCs
(Gruner et al. 2014). Recently, some studies have examined both
firm-initiated and consumer-initiated social media-based OBCs
(Pedeliento et al. 2020). It has been reported that consumer-run
communities exhibit stronger experience intensity than firm-
initiated communities (Pedeliento et al. 2020). This phenomenon
can be attributed to the highly moderated informational exchange
environment in firm-initiated communities (Jang et al. 2008).
Although firm-initiated communities normally have the advan-
tage of information quality (Raichur et al. 2023), the voluntary
nature of members’participation in customer-initiated commu-
nities provides unbiased and personally valuable experiences that
lead to the strengthening of trust within the community (Raichur
et al. 2023). Furthermore, consumer-initiated communities are
notably more competent at addressing negative experiences
related to the brand compared to firm-initiated communities
(Zhang et al. 2021), which heavily control any unfavourable views
within the community (Dholakia et al. 2004). Thus, the infor-
mation and experience in customer-initiated communities are
perceived to be of higher quality by the members (Gruner et al.
2014). This observation highlights the importance of investigating
this type of community due to its unexplored nature (Wong and
Lee, 2022).
Given that the study is within the context of OBCs, it is
essential to acknowledge that the initial mechanism for partici-
pating in the network is through the social media application
(Dessart and Veloutsou, 2021). Furthermore, the parallel con-
ceptualisation of gratification in social media activity, aligning
with the intrinsic motivation for media use in OBC interaction
(Brodie et al. 2011), suggests that the personal motivations
driving individual engagement in consumer-initiated OBCs have
not been thoroughly explored (Bowden and Mirzaei, 2021; Ped-
eliento et al. 2020; Wong and Lee, 2022).
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Considering the importance of social capital in OBCs,
numerous studies have scrutinised this topic. Table 1below
presents a brief summary of empirical social capital studies
conducted in the context of OBCs over the past three years.
The information from Table 1suggests the need for clarifica-
tion regarding the role of social capital, particularly concerning its
determinants and consequences (Wong and Lee, 2022). This can
be attributed to conceptualising social capital as either a personal
asset (Bourdieu and Richardson, 1986; Granovetter, 1973)ora
collective property (Coleman, 1988). Some works utilised the
bonding and bridging dimensions to postulate the concept of
social capital (Chen and Li, 2017; Reimann et al. 2021), while
others conceptualised it through a multidimensional framework,
namely, considering cognitive, structural, and relational aspects
(Chiu et al. 2006; Lin and Lu, 2011; Nahapiet and Ghoshal, 1998).
This perspective emphasises the necessity for a uniformly
accepted operational definition of social capital. Additionally, it
highlights the limited empirical evidence regarding its dimensions
and the lack of a scale that applies specifically to the context of
OBCs (Jeong et al. 2021).
In response to the aforementioned shortcomings in social
capital research within the OBC context, this study seeks to
address these issues by testing a novel social capital framework
tailored to social media-based OBCs, adopting the con-
ceptualisation proposed by Meek et al. (2019a). The framework
integrates seven subdimensions categorised by collective and
individual social capital properties, representing community and
personal features. The study aims to empirically assess the role of
social capital in strengthening network connections (Meek et al.
2019b). Furthermore, it is crucial to understand the variations in
motivations for social media usage to predict engagement levels
and subsequently impact community participation (Buzeta et al.
2020; Vale and Fernandes, 2018). Hence, this study focuses on
three antecedents: information, social, and recreational factors,
aligning with the propositions made by Lee and Ma (2012) and
Lin et al. (2017).
Next, to encapsulate the triadic relationship, loyalty intentions
towards the community and the brand operate as the terminal
variables. This decision is based on the well-established impact of
commitment to both the community and the brand on outcomes
such as loyalty intentions (Kaur et al. 2020). It should be noted
that some studies distinguish between commitment and loyalty
(Raïes et al. 2015). In a similar vein, this study posits that com-
mitment emerges as a natural consequence of social capital. Such
commitment is perceived as individual feelings shaped by social
capital at the community level, encompassing a sense of
belonging, network ties, and participative behaviour (Meek et al.
2019a,2019b), resulting in the development of loyalty behaviour.
Additionally, the brand-embedded social exchange within the
community fundamentally cultivates brand commitment (Jeong
et al. 2021), which can result in brand loyalty (Bowden et al.
2018).
Last, empirical studies of social capital have illustrated the
complexity of its components (Jeong et al. 2021; Meek et al.
2019b). Therefore, to strike a balance between the comprehen-
siveness of the construct and the efficiency of the research model,
the social capital construct will be formulated as a second-order
factor. This approach aims to preserve the comprehensive con-
ceptualisation of social capital while ensuring analytical efficiency.
This solution can be regarded as an anomaly in the field of
marketing studies unlike in the area of organisational behaviour
and management, where it serves as an effective method for
anticipating intercorrelations among constructs (Lee, 2009;
Zheng, 2010), and a convenient method for analysing the joint
causality and effects of several latent variables (Martínez-Cañas
et al. 2012).
Table 1 Empirical studies on social capital in the online brand community context (brief summary).
Author Year Social capital composition Antecedents Consequences
Yao Cao, Jialing Lin, Zhimin
Zhou
2022 Shared language, Shared vision, Trust,
Reciprocity
–Member inspiration, Value co-
creation
Ning Zhang, Zhimin Zhou,
Ge Zhan, Nan Zhou
2021 Social trust, Reciprocity Controlling Climate, Supportive
Climate
Community identification
So Won Jeong, Sejin Ha,
Kyu-Hye Lee
2021 Interaction, Trust, language, Vision,
Reciprocity, Identification, Shared value,
Bonding, Bridging
–Community commitment, Brand
commitment
Zhimin Zhou, Rixiang Wang 2022 Shared language, Shared vision, Trust,
Reciprocity
–Subjective well being
Shunfeng Zhang, Linghao
Zhang
2023 Identification, Social ties, Shared
narratives
Offline activities, Online reaction,
Interaction support, Immersion
Purchase intention
Amy Wong, Marcus Lee 2022 Social trust, Reciprocity Prosocial behaviour Affective, Cognitive,
Behavioural
Liuliang Yuan, Xiaozhao
Deng, Weijin Zhong
2021 Bonding, Bridging Ease of use, Usefulness Opinion passing, Opinion
seeking
Uttam Chakrabortya,
Santosh Kumar Biswa
2023 Bonding, Bridging Informational, Attitudinal,
Actionable
Brand commitment
Azim Zarei, Ghazale Taheri,
Hadi Ghazvini
2022 Social participation, Common insights,
Information quality, Social trust, Social
commitment
–Brand knowledge, Branding co-
creation, Sense of belonging
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Theoretical background and hypotheses
An understanding of how users’interactions result in resource
accumulation can be achieved by recognising intrinsic motiva-
tions that drive specific behaviours aimed at accomplishing
targeted goals.
Image presentations in social media communications.To
emphasise the significance of visual modality in the domain of
digitally networked social interaction, this study utilises insights
from image act theory. This approach facilitates the exploration
of engagement dynamics specific to Instagram. With social media
becoming an integral part of daily life, there is a growing
emphasis on image sharing as the primary form of customer-to-
customer interaction (C2C) (Akpinar and Berger, 2017; Villarroel
Ordenes et al. 2019).
Image acts involve images created by people and centre around
the behaviours that these images are able to incite. They also have
the capacity to convey thoughts and emotions and elicit responses
from viewers (Bakewell, 1998). Image acts refer to visual expressions
targeted at any objects of attitude, utilising visual content to depict
various behavioural manifestations (Azer et al. 2023). Given the
versatility of images, understanding the behavioural displays of
social media users through visual content holds considerable
importance. This involves not only understanding the impact of
visual content on users but also discerning the ramifications for
brands within the online brand community context.
The image modality plays a significant role in consumer
engagement. Visual content allows for a better representation of
experiences and creates a sense of visibility for intangible
concepts (Akpinar and Berger, 2017; Bakri et al. 2020). Moreover,
image modality offers richer contextual signals, presenting vivid
cues to users. Consequently, it emerges as a powerful and credible
medium for communication (Kress and Van Leeuwen, 2020).
Furthermore, images effectively stimulate users’thoughts and
emotions, invoking the realism heuristic (Sundar, 2008), which
posits that images are inherently perceived as more authentic
than written text. This concept aligns with the distinction that the
brain processes words, whether spoken or written, differently
from images (Townsend and Kahn, 2014).
Visual images are inherently more tangible and are more likely
to evoke an emotional response from viewers. As a result, images
can provide both intimacy and immediacy. Various perspectives
from the communication literature align with the notion that
image-based communication provides a comparatively genuine
and intimate interpersonal experience (Pittman and Reich, 2016).
In the digital economy, where attention serves as currency,
images stand out as effective and efficient means of conveying
thoughts and feelings (Pittman and Reich, 2016). Acknowledging
the significance of visual presentations in consumer-to-consumer
interactions (C2C) underlines the pivotal role of images in
enhancing social exchange.
Motivations for online engagement. Personal motivation is
typically categorised into intrinsic and extrinsic motivations
(Ryan and Deci, 2000). As social media usage behaviours are
generally voluntary, they are fundamentally rooted in personal
intentions and motives (Rauniar et al. 2014). Thus, when defining
usage activities based on inherent interest, personal inquiries,
enjoyment, and social relatedness, intrinsic motivations emerge as
the more dominant factor in determining content generation and
consumption (Zhang et al. 2017).
A primary intrinsic motivation in social media settings is
curiosity. As such, information seeking measures the extent to
which users adopt information from social media to satisfy their
need for relevant information (Whiting and Williams, 2013). This
motivation is the core of social media usage, among other
fundamental motivations (Whiting and Williams, 2013). Using
social media for information gathering also allows users to
observe others’opinions on specific topics.
When seeking to satisfy information requirements, Instagram has
asignificant advantage over other social media platforms (Pittman
and Reich, 2016). This is signified by the effectiveness and credibility
of visual representation as a potent mode of communication, as
emphasised in the research of Kress and Van Leeuwen (2020).
Derived from the principles of image act theory, visual images
convey both the cognitive thoughts and emotional sentiments a user
holds towards a brand, effectively directing their intentions to a
greater degree. (Bakewell, 1998). Furthermore, images are processed
more rapidly, prompting increased emotional and cognitive
elaboration. Thus, a heightened level of information absorption is
evoked and accelerated, thereby contributing to the elicitation of
intentions (Blackwood, 2019; Kjeldsen, 2015). Combining this with
consumer engagement studies, intentions are ultimately reflected in
engagement behaviour (Bowden et al. 2018;Brodieetal.2013).
When people feel a connection to a community as a source of
information, they enjoy interacting with its members and value
their input (Bailey et al. 2021). In this situation, social media
serves as a substitute for interpersonal communication, with
relationship maintenance being essential for its sustained use.
Hence, the motivation to socialise cultivates stronger relation-
ships within the community.
Furthermore, engaging in social interactions on social media often
results in enjoyment derived from the perception of cultivating
friendships (Colwell and Payne, 2000). Enjoyment can heighten
involvement, leading to positive experiences that encourage user
interaction. Participating in a community through actions such as
photo sharing, commenting, and liking posts constitutes content
contribution. Furthermore, social media interactions offer enjoyment
not only through community engagement but also through solitary
recreation. Given Instagram’s visually driven platform, content that
is aesthetically appealing easily captivates users seeking recreational
gratification (Tiggemann and Zaccardo, 2015). They are inclined to
interact with captivating images, innovative graphics, and engaging
short videos, potentially resulting in increased counts of likes,
comments, and shares (Song et al. 2021). Furthermore, as suggested
by Weinstein (2018), motivation driven by entertainment is more
likely to enhance the experience of positive emotions, thereby
promoting self-expression. Combined with the platform’sinteractive
features, engaging with content and other users can trigger feelings
of happiness, a sense of intimacy, and alleviate the sensation of being
disconnected and lonely (Lu and Lin, 2022; Pittman and Reich,
2016). Thus, the propositions concerning intrinsic motivations for
online engagement are similar to the concepts of uses and
gratifications of social media (Whiting and Williams, 2013). In the
aforementioned study, three of the top ten most common
gratifications for social media usage were social interactions,
information seeking, and recreation. Therefore, the hypotheses
representing personal motivation can be stated as follows.
H1. Information seeking via Instagram is positively related
to the collective social capital of shared language, shared
vision, reciprocity, and social trust.
H2. Socialising via Instagram is positively related to the
collective social capital of shared language, shared vision,
reciprocity, and social trust.
H3. Recreation via Instagram is positively related to the
collective social capital of shared language, shared vision,
reciprocity, and social trust.
Social capital. Various standpoints exist regarding the definitions
of social capital. However, it is generally agreed that social capital
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is derived from the structure of the social network between people
in the community, which yields collective productivity (Cao et al.
2022; Coleman, 1988,1994; Granovetter, 1985; Nahapiet and
Ghoshal, 1998). The components that constitute social capital are
frequently discussed in the literature related to communities.
Nahapiet and Ghoshal (1998) asserted that the conceptualisation
of social capital becomes clearer when its characteristics are
divided into three categories. The first is the relational dimension.
This encompasses the perceived closeness between individuals,
mutual trust, the recognition of obligations, and expectations
concerning the relationship (Granovetter, 1985; Nahapiet and
Ghoshal, 1998). Reciprocity and social trust are the accepted
conventions that best represent this aspect (Nahapiet and
Ghoshal, 1998; Watson and Papamarcos, 2002). Reciprocity
symbolises moral responsibility and the core attribute of an
authentic group (Muniz and O’Guinn, 2001). Social trust illus-
trates how information, opinions, and views are critical to the
functionality of an OBC (Zhou et al. 2022). Within a community,
members generate diverse content. When interactions are
grounded in social trust, the shared information is perceived as
more reliable and is more likely to be adopted.
The second is the cognitive dimension. It refers to a shared
understanding, language, and interpretations that foster colla-
borative activity (Nahapiet and Ghoshal, 1998). Central to this
dimension are shared language and shared vision (Chiu et al.
2006). A shared language consists of a specific vocabulary used
routinely to enhance efficiency in social exchanges. Conversely, a
shared vision embodies the community’s collective values and
orientation, which facilitates the integration of its members and
fosters personal connections (Meek et al. 2019a). Last is the
structural dimension. It represents the nonpersonal patterns of
associations among group members (Granovetter, 1985). This
includes the ties that define their relationships and the intensity of
their interactions (Liao and Chou, 2012). These ties are often
referred to as network ties (Meek et al. 2019a). Thus, network ties
reflect stronger personal-level relationships due to relational and
cognitive dimensions (Muniz and O’Guinn, 2001).
Furthermore, social capital at the collective level drives the
routine interaction between members, resulting in increased
participative behaviour (Meek et al. 2019a). When members fully
assimilate into the community, they develop the ability to foster a
sense of belonging within the group (Bagozzi and Dholakia, 2002;
Chakraborty and Biswal, 2023). Building on the concept of social
capital, Wellman and Frank (2017) argued that social capital
involves networked resources. These resources are created,
maintained, and utilised through social relations facilitated by
mediated communication. This postulation implies that the
manifestation of social capital within the community is shaped
by the content modality that mediates the social interaction
through which ideas or information are expressed. In conclusion,
the relational and cognitive dimensions enrich network ties, build
a sense of belonging, and facilitate ongoing interactions that are
mediated by the visual modality presentation. Thus, the
hypotheses can be stated as follows.
H4. Social capital is positively related to participative
behaviour.
H5. Social capital is positively related to sense of belonging.
H6. Social capital is positively related to network ties.
Personal consequences of social capital. The result of collectively
shared social capital is the development of commitment to the
community, driven by participative behaviour, a sense of
belonging, and network ties. Together, these elements nurture a
sense of self-identification with a group, thereby enhancing social
cohesion and leading to social conformity (Fonseca et al. 2019).
When an individual is perceptively aware of a social group
membership, the emotional significance tied to that membership
can motivate them to align more closely with the group’sdefining
characteristics or values, such as by supporting a specific brand
(Dholakia et al. 2004). The importance of perceived self-
identification in brand community studies is apparent (Bagozzi
and Dholakia, 2002; Heere et al. 2011). This perception enhances
positive evaluations of the social group, reinforcing their asso-
ciation as a display of behavioural loyalty within the community
(Heere et al. 2011), reflected through contributions, interactions,
and relationships (Stokburger-Sauer, 2010). A deep connection
with a community results in self-congruence with its core aspect,
which in this context is the brand, subsequently fostering brand
loyalty (Hollenbeck and Kaikati, 2012). Consequently, the
hypotheses can be constructed as follows.
H7. Participative behaviour positively impacts brand loyalty
behaviour.
H8. Participative behaviour positively impacts community
loyalty behaviour.
H9. Sense of belonging positively impacts brand loyalty
behaviour.
H10. Sense of belonging positively impacts community
loyalty behaviour.
H11. Network ties positively impact brand loyalty behaviour.
H12. Network ties positively impact community loyalty
behaviour.
Research framework
Drawing from individual motivations, social capital, and the
personal consequences of social capital, this study investigates the
effects of motivations on social capital through interaction within
an OBC. Furthermore, this research also examines the subsequent
spillover effects on both the brand and the community. Figure 1
displays the research framework representing the hypotheses in
this study.
Methodology
Research context. This study is centred around automotive
communities on Instagram. This particular category was chosen
due to its inherent capacity to evoke emotion and foster
engagement (Algesheimer et al. 2005). Considering the pre-
valence of automotive communities on Instagram, specific criteria
need to be in place to guarantee adequate interaction. First, a
community should have at least 1 K followers or members,
ensuring established social interaction and indicating a shared
perceived value among its members. Second, active engagement,
which is evident from a post being made on the community’s
main timeline in the past thirty days, confirms continuous col-
laboration between administrators and members. Last, Indonesia
is the fourth largest Instagram user by country (Dixon, 2023).
With many Indonesians primarily accessing the internet via
mobile devices, this signifies the presence of a mobile-first cul-
tural approach, influencing how they interact with and consume
social media content (Puspitasari and Ishii, 2016). Therefore,
taking these factors into account, the Indonesian market is
deemed suitable for this study.
Participants and data collection. A pretest was conducted to
assess the suitability of the research instrument. An online survey
link created using Alchemer was disseminated to 34 members of
automotive OBCs on Instagram, which is a commonly accepted
size for a psychometric-based preliminary test utilising SPSS.
Based on the feedback from five randomly selected participants,
small adjustments were made to certain aspects of the ques-
tionnaire, such as wording, layout, and structure. This was done
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to facilitate more straightforward and convenient responses, and
more importantly, to avoid ambiguity. For the main test, we
contacted community administrators via direct message and
proposed a collaboration. We sought their participation in the
study by inviting the community’s members to complete the
questionnaire. After our outreach to community administrators,
540 valid responses were collected. These were gathered using
invitational posts (both Instastory and timeline) shared by the
administrators of the targeted communities. In addition, we
employed the snowball method, where one member recom-
mended the survey to another, to expedite the data collection
process.
In Instagram’s consumer-initiated automotive OBCs, the
community is centred around individual brands (e.g., Camry,
CR-V, Mazda 2) instead of the corporate brand (e.g., Toyota,
Honda, and Mazda). Nevertheless, the fundamental orientation of
both types of communities remains aligned with the brand. The
sole distinction is that one represents the company’s brand, while
the other embodies admiration for a specific brand or product
line. In contrast to other types of communities that are
consumption-oriented, where the brand revolves around the
centrality of the community, often a particular lifestyle, it is thus
classified as a subculture community (Canniford, 2011). Under-
standing the nuanced distinctions between these communities is
essential for the scope of our study. Therefore, this rationale
aligns with our research objectives and is unlikely to influence the
outcome of the data analysis.
The sample’s demographic characteristics, as presented in
Table 2, indicate that male respondents accounted for most of the
sample, comprising 95 percent of the participants. This result
aligns with previous research on the automotive category, as
reported by Algesheimer et al. (2005) and Pedeliento et al. (2020).
Regarding age distribution, most respondents (46%) were in the
30–40 age group. Moreover, 54% of the respondents had an
undergraduate educational background, while the predominant
segment, accounting for 42% of the sample, had a membership
length greater than 2 years.
Scale and measurements. The measurement items employed in
this study utilised a 5-point Likert scale based on previously
validated instruments. Although these instruments were devel-
oped in different contexts, they remain pertinent to the study’s
psychological scope. The original sources of these instruments
have shown consistent reliability and validity. Moreover, given
their basis in virtual settings, the items can be readily adapted and
Fig. 1 Conceptual framework. The objective of the framework is to evaluate elements of social capital, that influenced by motivations behind user’s
engagement, and their long term effects on the community’s sustainability.
Table 2 Sample demographics (n=540).
Demographics Frequency Percentage (%)
Gender Male 514 95
Female 26 5
Age >18–25 years 75 14
>25–30 years 137 25
>30–40 years 246 46
>40–50 years 77 14
>50 years 5 1
Educational Tertiary 202 37
Undergraduate 291 54
Postgraduate 45 8
Doctoral 7 0
Membership <6 months 58 11
>6–12 months 114 21
>1–2 years 143 26
>2 years 225 42
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adjusted, pertaining to the accuracy of construct measurements
and making their application more straightforward for the target
population.
Information seeking was measured with three items from
Asghar (2015), socialising was assessed with three items from Lee
and Ma (2012), and recreation was evaluated using three items
from Agarwal and Karahanna (2000). Regarding social capital
factors, shared language and shared vision of the cognitive
dimension were measured using three items derived from Chiu et
al. (2006). The three units measuring social trust of the relational
dimension originate from Liao and Chou (2012), while
reciprocity comprises three items from both Mathwick et al.
(2007) and Liao and Chou (2012). As consequences of social
capital, three constructs are highlighted. Among them, the first is
the sense of belonging, measured with three items from Chiu
et al. (2006). The second is participative behaviour, determined
via three items extracted from Kamboj and Rahman (2017).
Finally, network ties were verified based on three items (Liao and
Chou, 2012).
The first terminal variable is brand loyalty intentions,
measured with four items that constitute the purchase intention
defined by Algesheimer et al. (2005), Kaur et al. (2020), along
with positive word of mouth (Goyette et al. 2010). The second
terminal variable is community loyalty, validated through four
items (Chen, 2007; Woisetschläger et al. 2008)reflecting usage
continuity and positive recommendation.
In the structural equation model, the maximum likelihood
procedure is employed, initiated by the estimation of the
measurement model. The reliability and validity of each construct
are then confirmed using confirmatory factor analysis (CFA)
(Hair et al. 2014). Structural model testing was performed by
applying overall model fit analysis and path coefficients based on
the constructed hypotheses.
Data analysis and results
Measurement model. Amos 24.0 was utilised to analyse the
measurement model, which incorporated all latent constructs.
Additionally, social capital was included as a second-order factor,
encompassing four underlying components: shared language,
shared vision, social trust, and reciprocity. The resulting pooled
measurement model yielded a statistically satisfactory fit between
the data and the model (χ2=1571.579; p< .001; df=621; χ2/
df=2.531; CFI =0.943; SRMR =0.041; RMSEA =0.053) (Hair
et al. 2014). For reliability measurements, as detailed in Table 3,
all the constructs’Cronbach’s alpha scores ranged between 0.795
and 0.937, surpassing the recommended cut-off value of 0.7.
Correspondingly, composite reliability (CR) for all constructs
exceeded 0.7, indicating that reliability was achieved (Hair et al.
2014).
For validity measures, the average variance extracted (AVE) of
all constructs surpassed the threshold of 0.5 (Hair et al. 2014).
However, the discriminant validity measures, based on HTMT.85
analysis (Henseler et al. 2015), reveal significant correlation issues
between two exogenous variables (information seeking-to-socia-
lising) and endogenous variables representing the consequences
of social capital (participative behaviour-to-network ties and
participative behaviour-to-sense of belonging). Therefore, it is
imperative to scrutinise previous studies to address these
concerns.
The statistical indifference between information-seeking and
socialising mirrors the definition of information-seeking beha-
viour on social media: a utilitarian cognitive need that
encompasses social experiences, question-asking, knowledge
acquisition, and search for information (Asghar, 2015). This
exposition highlights the wide spectrum of information-seeking
engagement on social media. However, a challenge may arise
when attempting to measure a construct that represents the
breadth and depth of psychosocial motives by solely concentrat-
ing on desired and acquired gratifications (Asghar, 2015).
Building on this understanding of information-seeking behaviour,
theoretical reasoning suggests that information-seeking and
socialising on social media merge both active-passive and
interactive-extractive informational techniques (Mostafa, 2021;
Yuan et al. 2021). Recognising the dual nature of actively and
passively searching for information, information seeking and
socialising are consequently combined into the “informational”
variable. This measure aligns with the recommendations by
Schroeder et al. (1990). It aims to stabilise the variances of
problematic coefficients by merging independent variables with-
out undermining the theoretical foundation of the model.
Participative behaviour correlates with two other constructs
simultaneously portraying the consequences of collective-level
social capital. Hence, combining participative behaviour with
either a sense of belonging or network ties will be redundant.
Referring to the conception by Granovetter (1973), in gaining
new social resources, people engage in relationships characterised
by weak ties. Thus, the bridging effect of social capital occurs
(Putnam, 1993). In social media, online social networks serve as
mediums for strengthening weak ties through collective action.
This suggests that participative behaviour is not only limited to
the personal level but also manifests on the collective level, e.g.,
Meek et al. (2019a), where increased participation results in
building trust, further developing the potential of social capital for
the community (Kobayashi et al. 2006). Given the premise that
participative behaviour also contributes to the building of
collective social capital, omitting the variable as a consequence
of social capital is justifiable.
The revised measurement model reached the recommended
goodness-of-fit index criteria (χ2=1289.763; p< 0.001; df=531;
χ2/df=2.229; CFI =0.950; SRMR =0.042; RMSEA =0.051)
(Hair et al. 2014). For reliability measures, each construct
achieved a Cronbach’s alpha (CA) score above 0.7. Additionally,
the construct reliability (CR) values exceeded 0.7, and the average
variance extracted (AVE) values were greater than 0.5, as
recommended (Hair et al. 2014). Furthermore, the altered model
performed appropriately in the HTMT0.85 analysis. Table 4
reveals that each construct is statistically distinguishable. Finally,
using principal axis factoring, Harman’s single factor test was
performed to avoid common method bias risk. The test generated
a 49.3 percent explanation of covariance for entire constructs,
marginally passing the recommended threshold of <50%
(Podsakoff et al. 2003). Conclusively, there is no evidence of
intercorrelations of constructs, as shown in Table 4; hence,
common method bias risks are unlikely.
Structural model. The structural model displays a reasonable fit
(χ2=1709.449; p< 0.001; df=542; χ2/df=3.154; CFI =0.922;
NFI =0.891; RMSEA =0.063). The model’s reliability, referring
to squared multiple correlation results, explained 42% of the
variance in “brand loyalty”, 66% of the variance in “community
loyalty”, 66% of the variance in “network ties”, 73% of the var-
iance in “sense of belonging”, and 72% of the variance in “social
capital”. The structural model confirmed all the relationships
stipulated in the hypotheses, as demonstrated in Table 5. Both
informational (β=0.72, p< 0.001) and recreational motivations
(β=0.46, p< 0.001) have a positive impact on social capital.
These results confirm that motivations that induce active parti-
cipation will lead to cooperative interaction. Furthermore, social
capital positively affects both sense of belonging (β=0.86,
p< 0.001) and network ties (β=0.82, p< 0.001).
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This result confirms that engaging in social interactions
provokes collective action, creating positive thoughts and
recognition towards the community. Finally, sense of belonging
has a positive impact on both brand loyalty (β=0.31, p< 0.001)
and community loyalty (β=0.26, p< 0.001). Similarly, network
ties significantly influence brand (β=0.39, p< 0.001) and
community loyalty (β=0.61, p< 0.001). These findings suggest
that sharing brand experiences through social exchange reinforces
cognition and attitude, resulting in favourable behaviour towards
the brand. Similarly, the resonance of common interest will
develop a sense of ingroup-outgroup distinction that stimulates
ingroup favouritism. A summary of this study is shown in Fig. 2.
Table 3 Measurement model characteristics.
Constructs and items Std. loading Mean CA CR AVE
Information seeking 0.84 0.84 0.64
This community is the place to learn about things related to my interest that I’m not familiar with 0.78 4.36
I feel that to know more about a brand, I must follow its community 0.83 4.23
I think reading the community feeds is informative 0.78 4.25
Socialising 0.82 0.79 0.57
I can interact with people when sharing news or information in the community 0.68 4.30
I join the community to keep in touch with people with similar interest 0.76 4.26
It is effective to exchange ideas with other people on the community 0.81 4.18
Recreational 0.88 0.89 0.68
I often spend more time on the community than I had intended 0.90 3.83
Time appears to go by very quickly when I am on the community 0.84 3.78
Using the community provides me with a lot of enjoyment 0.85 3.93
Social capital 0.94 0.93 0.79
Shared language
Community members use common terms or jargon 0.87 4.13
Community members use understandable language during discussions 0.90 4.15
Community members use understandable narrative forms to post messages 0.85 4.14
Shared vision
Members of the community share a goal of helping others 0.86 4.31
Members of the community share the same goal of learning from each other 0.85 4.35
Members of the community share the same idea that helping each other is pleasant 0.88 4.34
Social trust
Members of the community will not take advantage of others even if opportunities arise 0.76 4.06
Members of the community will always keep the promises they make to one another 0.84 3.93
Members of the community are honest in dealing with one another 0.90 4.07
Reciprocity
When I receive help from the community, I feel it is only right to give back and help others 0.74 4.21
Members should return favours when the community is in need 0.82 4.07
My behaviour in the community will lead to cooperation from other members in the future 0.85 4.18
Sense of belonging 0.87 0.86 0.69
I feel a strong connection to this community 4.08
I have a strong positive feeling toward the community 4.21
I am proud to be a member of the community 4.24
Participative behaviour 0.79 0.79 0.56
I am a participant in the activities of this community 0.77 4.18
I spend a lot of time sharing information and opinions on the community 0.79 4.09
I frequently provide or share useful information online to the other members in the community 0.67 3.85
Network ties 0.86 0.86 0.68
I maintain close social relationships with some members of this community 0.83 4.07
I spend a lot of time interacting with some members of this community 0.83 3.91
I know some members of this community on a personal level 0.82 4.14
Brand loyalty 0.86 0.85 0.60
I intend to buy this brand in the near future 0.62 4.08
I have strong preference for this brand 0.74 3.94
I am going to spread positive words about the brand 0.83 4.12
I will recommend this brand to other customers 0.87 3.95
Community loyalty 0.89 0.90 0.69
I will continue to use the community to gain information or share experiences in the future 0.766 4.20
I would like to continue my participation in the future activities held in the community 0.87 4.05
I am going to spread positive word about the community 0.87 4.02
I will recommend this community to other customers 0.81 3.97
Table 4 HTMT results.
12345 67
Informational (1)
Recreational (2) 0.68
Network Ties (3) 0.67 0.73
Sense of Belonging (4) 0.71 0.69 0.85
Brand Loyalty (5) 0.53 0.59 0.62 0.63
Community Loyalty
(6)
0.63 0.69 0.82 0.78 0.79
Social Capital (7) 0.84 0.74 0.79 0.84 0.643 0.75
Discriminant validity results marked in bold according to the HTMT0.85 criterion.
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Discussion
This study deepens our understanding of virtual social capital
formation by highlighting a specific social media content mod-
ality that may impose constraints on information quality and
density. The main purpose of this study is to facilitate a con-
clusive social capital interpretation in the context of social media-
based consumer-initiated OBCs by emphasising social capital
evolution via image modality communication. The findings reveal
significant relationships for all the hypotheses tested. Aligned
with previous studies, information needs drive social interaction
(Meek et al. 2019a; Whiting and Williams, 2013). While other
studies with different contexts (e.g., Facebook) delineate social,
information, and erudition aspects regarding informational
gratification (Asghar, 2015; Lee and Ma, 2012), this study suggests
that the visual modality, being particularly engaging, encapsulates
informational drives as both active interaction and passive
involvement. The enhanced engagement facilitated by the visual
modality influences the attitude formation process for content
encountered within the community.
Recreational motives also significantly affect social capital. This
showed that hedonic motives critically increase the perception of
bonding and bridging for accruing social capital (Tan et al. 2018).
Table 5 Hypothesis testing.
Hypothesis Std. estimates t-Values Support
Informational →Social capital 0.72 14.61 Yes*
Recreational →Social capital 0.46 11,78 Yes*
Social capital →Sense of belonging 0.86 15.71 Yes*
Social capital →Network ties 0.82 14.96 Yes*
Sense of belonging →Brand loyalty 0.31 4.49 Yes*
Sense of belonging →Community loyalty 0.26 4.66 Yes*
Network ties →Brand loyalty 0.39 5.50 Yes*
Network ties →community loyalty 0.61 9.61 Yes*
Squared Multiple Correlations
Brand loyalty 0.42
Community loyalty 0.66
Network ties 0.66
Sense of belonging 0.73
Social capital 0.72
Model Fit Statistics
χ2/df=3.154 CFI =0.922 NFI =0.891 RMSEA =0.063
Notes. *p< 0.001.
Fig. 2 Results of the study. Values displayed in the figure represent standard estimates, t-values, and squared multiple correlations.
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Notably, Instagram, with its dominant visual modality, effectively
enhances these hedonic-related drives (Kusumasondjaja, 2020).
The visual content’s affective appeal not only fulfils recreational
motives but also fosters greater interaction and affiliation among
users (Tan et al. 2018). By emphasising the motivational aspects,
as highlighted in this study, image modality has a distinct
advantage in initiating engagement. These findings validate the
assertion of the image modality’s superiority in capturing users’
attention (Taecharungroj, 2017).
Collective social capital significantly correlates with both sense of
belonging and network ties. Congruent with the interpretation of
OBC as a structured network of weak ties (Meek et al. 2019a), this
study signifies that the visual modality plays an important role in
enhancing community cohesion through its ability to transmit
feelings of connectedness (Maclean et al. 2022). Moreover, image-
based content is a medium that effectively generates social presence
within a nonpersonal virtual society (Sundar, 2008). Therefore,
perpetual interaction and cooperation foster a stronger relationship
reflected in an increased sense of belonging and improved network
ties (Muniz and O’Guinn, 2001). The relational (social trust, reci-
procity) and cognitive (shared language, shared vision) dimensions
of social capital have a positive impact on engagement (Wong and
Lee, 2022;Zhouetal.2022). These findings emphasise that while
the visual content modality might use limited text, it can still
facilitate effective communication and minimise perceived risks in
adopting knowledge and exchanging information. In support of this
notion, Pittman and Reich (2016) stated that an Instagram image is
worth more than a thousand words written on Twitter. Social
media users perceive pictures as being more authentic, offering
greater intimacy, and being able to convey information more effi-
ciently (Pittman and Reich, 2016).
Thus, sense of belonging and network ties denoting structural
dimensions that significantly influence brand and community
loyalty signal a convergence of social capital and social identity
that is rarely articulated in OBC studies. When an individual fully
integrates into a social group, it creates satisfaction based on the
value they receive, which in turn encourages them to maintain the
relationship (Muniz and O’Guinn, 2001). Furthermore, self-
identification with a community will build self-esteem that
inspires altruistic behaviour (Dholakia et al. 2004; Schau et al.
2009). Additionally, when community integration causes brand
values to align with personal identity, as a consequence, the
community exercises effort towards the brand’s success (Zhang
and Zhang, 2023).
Last, differing in content modality from previous social capital
research contexts, this study examines the efficacy of the frame-
work developed by Meek et al. (2019a). The structure suggests
that incorporating either engagement, commitment, or both as
factors is redundant when social capital is central to the research
model. This model views the entire cognitive and behavioural
process of social capital accumulation as a manifestation of
engagement and involvement.
Conclusions and theoretical implications. This study con-
tributes to the literature on social capital and OBC in general.
First, it is the first to begin an investigation of OBCs’social capital
evolution with the limited use of text in the visual content
modality. Given that prior studies have predominantly focused on
text-centric social media (Leaver et al. 2020; McCrow-Young,
2021), this points to a promising avenue for further exploration,
especially concerning content modality and social capital. Second,
this study highlights the type of motivations prescribed differently
by the environment that social media provides (Buzeta et al.
2020). Previous studies stated that information and entertainment
needs could be satisfied without active engagement (Buzeta et al.
2020; Vale and Fernandes, 2018). However, due to the hedonic
nature of Instagram’s image modality, through perceived
vibrancy and interactivity, users could be driven into active
engagement by both informational and entertainment motiva-
tions, leading to the accumulation of social capital.
This aligns with findings that demonstrate the potency of the
informative and emotional appeal of image modality to drive
engagement (Rietveld et al. 2020). Images are inherently endowed
with high-arousal visual cues that capture attention and prompt
evaluation. Given that users consume vast amounts of content
through their social media streams, an image’s high-arousal
appeal serves as a means to break through the clutter of
information (Rietveld et al. 2020). When users are emotionally
aroused, affective cues come into play, conditioning them to react
(Zhang and Su, 2023). In this scenario, heightened engagement
occurs. Hence, the image content modality plays a significant role
in defining the OBC’s engagement dynamics. Third, social capital
is conceivably theorised as a multifaceted concept (Chiu et al.
2006; Jeong et al. 2021; Meek et al. 2019a; Nahapiet and Ghoshal,
1998). Thus, as this study has shown, translating this aspect into a
parsimonious second-order factor can be considered an alter-
native method for retaining the comprehensiveness of the concept
without compromising the integration with various concepts that
capture the OBC dynamics.
Practical implications. Based on the results of this study, it is
essential to appreciate the persuasiveness of the image modality
for attracting engagement (Yang and Jiang, 2021). Practitioners
must understand that engagement in value cocreation is not
necessarily due to the prevalence of information depth, nor is it
cognitively oriented (Jia et al. 2022). Conversely, interaction can
be stimulated using affective-based visual imagery
(Kusumasondjaja, 2020), and affective-based persuasion is
quicker in eliciting a response (Jin et al. 2023). Since the brand-
embedded interaction on Instagram is primarily hedonic, it
secures an initial step to form a positive emotional connection
with the brand. Therefore, to optimise the potential capabilities of
Instagram’s content modality, practitioners must find the right
balance between information density and affectionate appeal to
accommodate informational and recreational needs.
Considering the minimal use of text in the image content
modality, practitioners should encourage common language
creation by using particular jargon or phrases to improve
communication efficiency and information quality (Bullock
et al. 2019). Specialised and technical vocabulary is linked to
fostering a sense of belonging, arousing curiosity, and establishing
connections (Shulman et al. 2020). Hence, affect-based visual
appeal not only supports community objectives and knowledge
building but also benefits from a decrease in the demand for text-
heavy information (Jin et al. 2023).
To effectively engage members within online brand communities,
both marketers and administrators should account for the varied
psychological states of each member. Segmentation based on
membership length is a practical approach to designing messages
that resonate with both experienced and inexperienced members.
Affect-rich visuals are effective for attracting new members’
attention and promoting active engagement. In contrast, established
members often resonate more with content that has a cognitive
appeal, focusing on collaborative knowledge interaction (Yang et al.
2021). Thus, the mixture of cognitive and affective appeal must be
appropriately synergised to enrich social capital.
Limitations and future research. The concluding section of this
study outlines the limitations and suggests directions for future
research. The primary limitation is that this is a single-domain
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study focused exclusively on the automotive category, and it per-
tains only to customer-initiated communities. Since automotive
products convey significant utilitarian and hedonic value, this might
affect how members cognitively and behaviourally assimilate into a
community. Thus, the results of this study must be considered with
precautions. For future research, it is suggested to examine social
capital in a combination of consumer-initiated and company-
initiated communities on Instagram. This exploration should also
consider different product types and characteristics, as each com-
munity is formed with distinct orientations. Hence, comparing how
each community utilises image modality for value cocreation
activities is an interesting proposition.
The second limitation of this study is the omission of
experience factors. Consuming, participating, and creating
content for the community can generate varied and distinct
experiences. Additional factors reflecting consumer experience in
an OBC should include sensory, affective, intellectual, and
behavioural factors.
Data availability
The datasets analysed in this study are publicly available through
the Dataverse repository, accessible via: https://doi.org/10.7910/
DVN/6ERFWM. These datasets were acquired through surveys,
and personal information has been anonymised to ensure con-
fidentiality and ethical handling of data.
Received: 30 May 2023; Accepted: 8 December 2023;
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Author contributions
AAK (corresponding author) performed the conception and design of the study. AAK
and AZA conducted the literature review and contributed to drafting. AAK and GG were
responsible for analysis, methodology, and data collection. AAK and SRHH were
involved in data collection, data interpretation, and analysis tools. AZA supervised the
study. All authors made substantial contributions, provided critical reviews of the study,
and approved the final version.
Competing interests
The authors declare no competing interests.
Ethical approval
All procedures performed in this study followed the ethical standards of the Universitas
Indonesia Ethical Committee on Medical and Clinical Research. Ethical clearance and
approval were granted by the Post-graduate Management Studies unit committee (S-
0606A/UN2.F6.D.PIM/PDP.00.01/2022).
Informed consent
Before beginning the survey, participants were informed about the purpose and nature of
the study and their right to withdraw at any time. Additionally, all participants provided
their consent by actively choosing to complete and submit the survey.
Additional information
Correspondence and requests for materials should be addressed to Agung Artha
Kusuma.
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