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Factors Influencing Consumer Adoption of On-Demand Social Media Platforms

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11 September 2024

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12 September 2024

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Abstract
This study examines the factors influencing consumer adoption of on-demand social media platforms characterized by ephemeral content. As these platforms rapidly gain popularity, understanding adoption drivers is crucial for researchers and practitioners. The study develops and tests a comprehensive model integrating traditional technology acceptance factors with platform-specific constructs. Using partial least squares structural equation modelling on data from 180 social media users in Kerala, India, the research reveals that convenience is the strongest predictor of adoption intention, followed by perceived usefulness, interpersonal influence, and enjoyment. Surprisingly, factors like perceived ease of use, social influence, and platform-specific features such as ephemerality and visual focus did not significantly impact adoption directly. Age showed a marginal negative effect, while gender had no significant impact. The findings challenge some prevailing assumptions about on-demand social media adoption and highlight the need for refined models specific to this context. The study contributes to technology adoption literature by demonstrating the primacy of convenience in driving the adoption of these platforms. It also offers practical insights for developers and marketers, suggesting that prioritizing convenience and perceived usefulness in design and marketing may be more effective than emphasizing specific features. Future research directions are proposed to address limitations and further explore this evolving digital landscape.
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Subject: Business, Economics and Management  -   Marketing

Introduction

The digital landscape has undergone a significant transformation with the advent of on-demand social media platforms characterized by ephemeral content (‌Li, Zhuoxin, and Ashish Agarwal 2017). Services like Snapchat, Facebook, Instagram Stories, and TikTok have rapidly gained popularity, particularly among younger demographics, by offering novel ways to share temporary, visually-oriented content. This shift towards impermanent, “in-the-moment” social media experiences marks a departure from traditional social networking paradigms built on persistent content and curated online personas (Laor et al.,2022). As these platforms continue to evolve and shape user behaviors, understanding the factors driving their adoption has become crucial for researchers, marketers, and technology developers (Pham and Gammoh 2015; Tuten and Solomon 2016). However, existing models of technology adoption may not fully capture the unique aspects of these emerging platforms, creating a significant knowledge gap in our understanding of contemporary social media usage patterns (Gawron & Turok, 2015). Previous research has identified factors such as perceived usefulness, ease of use, and social influence as key drivers of social media adoption. Yet, the applicability of these factors to on-demand platforms remains unclear (Statista, 2022). The ephemeral nature of content, enhanced privacy features, and focus on visual communication in these new platforms may introduce novel motivations for adoption that are not accounted for in traditional models (Blend Ibrahim & Ahmad Aljarah (2023). Moreover, the interplay between user demographics, platform-specific features, and adoption behaviors in this new paradigm is not well understood. Questions remain about how factors like convenience, enjoyment, and interpersonal influence may weigh against conventional drivers in the context of on-demand social media (Tal Laor & Sabina Lissitsa, 2022). This lack of comprehensive understanding hinders our ability to predict and explain the rapid shifts occurring in the social media landscape (Herzallah et al., 2022). The present study aims to address these gaps by investigating the factors influencing consumer adoption of on-demand social media platforms. Drawing on established technology adoption theories and recent literature, we develop and test a comprehensive model that incorporates both traditional adoption factors and novel constructs specific to on-demand social media. We hypothesize that factors such as convenience, enjoyment, and interpersonal influence will play significant roles in driving adoption, potentially outweighing conventional drivers like ease of use. In addition, we explore how demographic variables such as age and gender moderate these relationships. By employing a quantitative approach with data collected from 180 social media users in Kerala, India, and utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis, this study seeks to provide a nuanced understanding of on-demand social media adoption. The findings aim to contribute valuable insights to both theory and practice in this rapidly evolving digital domain, offering a more accurate model for predicting and explaining user behavior in the context of ephemeral social media platforms. This study makes several key contributions to the literature on technology adoption and social media use. First, it develops and empirically tests a comprehensive model of on-demand social media adoption that integrates traditional technology acceptance factors with novel constructs specific to ephemeral content platforms. This addresses a critical gap in understanding the unique motivations driving the adoption of these emerging services. Second, by examining factors like convenience, visual focus, and ephemerality alongside established predictors, the study provides new insights into the relative importance of platform-specific features versus general technology adoption drivers. Finally, the research offers a nuanced perspective on demographic influences, challenging assumptions about age and gender effects on social media adoption.

Objectives of Study

  • To develop and validate a comprehensive model of on-demand social media adoption that incorporates both traditional technology acceptance factors and platform-specific constructs.
  • To assess the relative importance of convenience, perceived usefulness, enjoyment, and other factors in driving adoption intentions for on-demand social media platforms.
  • To examine the role of demographic factors, particularly age and gender, in influencing adoption intentions for these platforms.
  • To explore how novel features of on-demand platforms, such as ephemerality and visual focus, impact user adoption decisions.

Research Questions

  • What are the key factors influencing consumer adoption of on-demand social media platforms?
  • How do traditional technology adoption factors compare to platform-specific features in predicting adoption intentions?
  • To what extent do demographic characteristics moderate the relationship between adoption factors and intentions to use on-demand social media?
  • How does the emphasis on ephemeral content and visual communication affect user perceptions and adoption decisions for these platforms?

Literature Review or Theoretical Framework

In synthesizing the existing literature, several key themes and gaps emerge. While traditional technology adoption models like TAM and UTAUT have been widely applied to social media contexts, they may not fully capture the unique aspects of on-demand platforms. The emphasis on ephemeral content and visual communication in these services introduces new dimensions of user motivation and behavior that are not adequately addressed by existing frameworks. Furthermore, the literature reveals conflicting findings regarding the role of demographic factors in social media adoption, particularly for newer platforms. This study aims to reconcile these disparate streams of research by proposing an integrated model that accounts for both established adoption factors and platform-specific features, while also examining the moderating effects of age and gender. Ephemeral social media, characterized by temporary content that disappears after a short period, has revolutionized digital communication. Platforms like Snapchat, Instagram Stories, and TikTok have gained immense popularity, particularly among younger demographics. This literature review aims to provide a comprehensive overview of existing research on ephemeral social media adoption and identify key gaps in current knowledge.

Factors Influencing Consumer Adoption of On-Demand Social Media Platforms

Here is a list of key factors that may influence consumer adoption of on-demand social media platforms.

Technology Adoption Models

Piwek and Joinson (2016) utilized the Technology Acceptance Model (TAM) to examine Snapchat adoption, finding that perceived enjoyment was a stronger predictor than usefulness. Malik et al. (2016) applied the Unified Theory of Acceptance and Use of Technology (UTAUT) to Instagram Stories, highlighting the importance of social influence and performance expectancy. Hsu and Lin (2020) integrated TAM with the Uses and Gratifications Theory to study TikTok adoption, emphasizing the role of entertainment and self-expression. While these studies provide valuable insights, they often fail to fully capture the unique aspects of ephemeral content. There’s a need for models that incorporate ephemeral-specific constructs such as fear of missing out (FOMO), perceived authenticity, and temporal value.

Uses and Gratifications Theory

The Uses and Gratifications Theory has been widely applied to understand motivations for ephemeral social media use: Bayer et al. (2016) identified social connection, entertainment, and functional needs as key motivators for Snapchat use. Vasquez-Herrero et al. (2020) found that self-expression, voyeurism, and social interaction drive Instagram Stories usage. Omar and Dequan (2020) explored how ephemeral features satisfy users’ needs for immediacy and authenticity. While these studies provide insights into user motivations, there’s limited research on how these motivations may differ across demographic groups, cultural contexts, or various types of ephemeral content.

User Behavior and Engagement

Several studies have examined user behavior patterns on demand or ephemeral platforms Xu et al. (2016) analyzed Snapchat usage patterns, finding that users engaged more frequently but for shorter durations compared to traditional social media. Cavalcanti et al. (2017) investigated visual content strategies on Snapchat, highlighting the importance of authenticity and immediacy in user-generated content. Li et al. (2021) examined content creation and sharing practices on TikTok, emphasizing the role of algorithmic content curation in shaping user behavior. There’s a lack of longitudinal studies examining how ephemeral content consumption affects user behavior, engagement, and platform loyalty over time. Additionally, more research is needed on the psychological impact of constant exposure to disappearing content.

Privacy and Security Concerns

Privacy issues related to on-demand or ephemeral media have been the focus of several studies. Kotfila (2014) examined privacy perceptions among Snapchat users, finding that the perceived ephemerality of content led to a false sense of security. Morlok (2016) investigated how on-demand features influence users’ privacy concerns, highlighting the paradox between privacy expectations and actual data retention practices. Jiang et al. (2020) explored the relationship between privacy concerns and self-disclosure behaviors on-demand platforms, revealing complex decision-making processes among users. There’s a need for more comprehensive research on how privacy concerns impact adoption and usage patterns across different ephemeral platforms, particularly in light of evolving data protection regulations.

Cross-Platform Comparison

Some studies have attempted to compare on-demand features across different platforms. Sheldon and Bryant (2016) compared motivations for Instagram and Snapchat use, finding differences in social interaction patterns and content preferences. Feng et al. (2019) examined user engagement across Facebook Stories, Instagram Stories, and Snapchat, revealing platform-specific usage patterns. There’s a lack of comprehensive studies comparing adoption factors, user behaviors, and content strategies across multiple ephemeral platforms, particularly newer entrants like TikTok and emerging features on established platforms.

Business Use and Marketing Strategies

The adoption of on-demand social media by businesses has also been studied. Sashittal et al. (2016) explored how brands use Snapchat for marketing, highlighting the challenges of creating engaging ephemeral content. Vannucci and McCauley (2020) examined influencer marketing strategies on Instagram Stories, emphasizing the role of authenticity and immediacy in driving engagement. More research is needed on how businesses adapt their social media strategies for ephemeral platforms and how this affects consumer adoption and engagement. Additionally, the effectiveness of ephemeral content in driving brand awareness and purchase intentions requires further investigation.

Ethical and Societal Implications

Some researchers have begun to explore the broader implications of on-demand social media. Charteris et al. (2018) examined the impact of ephemeral social media on youth digital culture, raising concerns about privacy and digital footprints. Throuvala et al. (2019) investigated the potentially addictive nature of ephemeral content consumption, highlighting the need for digital well-being interventions. There’s a significant lack of research on the long-term societal impacts of on-demand social media, including its effects on communication patterns, information retention, and social norms. While significant research has been conducted on-demand social media adoption, several key areas remain underexplored. To address these gaps, future research should focus on Developing on-demand -specific adoption models that incorporate unique constructs such as FOMO, perceived authenticity, and temporal value. Conducting cross-cultural and demographic comparisons to understand how adoption factors vary across different user groups. Implementing longitudinal studies to examine the long-term effects of on-demand content consumption on user behavior, psychology, and platform loyalty. Investigating the privacy paradox in ephemeral contexts, particularly how users reconcile privacy concerns with self-disclosure behaviors. Comparing adoption factors, user behaviors, and content strategies across multiple on-demand platforms to identify platform-specific and universal factors. Examining how businesses adapt to ephemeral platforms and how this affects consumer adoption and engagement. Exploring the broader societal and ethical implications of ephemeral social media, including its impact on communication patterns, information retention, and digital wellbeing.

Unified theory of acceptance and use of technology (UTAUT)

The UTAUT model is a technology adoption framework used to explain user intentions and behaviour towards accepting and using new technologies. UTAUT integrated elements of eight prominent technology adoption theories into a consolidated model ((Dwivedi et al., 2011; Venkatesh et al., 2003). At its core, UTAUT aims to explain usage intentions and technology use behaviour through four key constructs (Mohammad et al., 2014): Performance Expectancy—The degree to which a user believes technology will provide benefits or improvements in task performance. Similar to perceived usefulness. Effort Expectancy—How easy do users perceive it to be to use the new technology? Builds conceptually on perceived ease of use. Social Influence—Users’ perceptions of whether important others believe they should use the technology. Captures subjective norms. Facilitating Conditions—Users’ perceptions of whether technical and organisational infrastructure exists to support the use of the technology (Maeen S et al., 2023). UTAUT theorises these four constructs directly determine usage intentions and behaviour (Lim et al., 2023). Additionally, it proposes that variables like gender, age, experience and voluntariness of use moderate the impacts of these core constructs on adoption. UTAUT provides a robust theoretical framework for evaluating the adoption of new technologies like on-demand social media platforms (AlQudah, 2015). In particular, UTAUT’s four core constructs offer critical insights: Performance expectancy explains user motivations around platforms perceived as useful or enabling improvements in social interactions. This aligns closely with identified drivers like entertainment value, connecting with others and serving communication needs. Effort expectancy relates to ease of use—a key factor given that on-demand platforms leverage new interfaces optimising for visual content creation. The intuitive, frictionless nature of these apps drives adoption. Social influence is relevant given network effects around friends, family, and broader trends, which play a pivotal role in the on-demand social media uptake (Ashraf et al., 2022). Especially among younger demographics, interpersonal forces compel adoption. Facilitating conditions consider technical and infrastructure supports. The rapid evolution of mobile technology and broadband paved the way as key antecedents before mass consumer adoption of on-demand platforms could occur. UTAUT delivers empirical insights into user intentions and behaviours that underpin real-world consumer adoption of ephemeral, mobile-centric, and socially-driven platforms like Snapchat or Instagram Stories (Savić et al., A. 2019). UTAUT provides a comprehensive framework for studying user acceptance and usage decisions toward new technologies. It has been applied extensively in information systems and consumer research. The model accounts for 70% of the variance in usage intention, outperforming predecessor theories like TAM. As such, it remains one of the most robust technology adoption models available (Northwestern University in Qatar 2019).

3.2. Social Influence

Social influence refers to the interpersonal drivers that compel individuals to conform to certain attitudes, behaviors, or usages based on pressures in their social networks. In technology adoption contexts, it captures peer influence, word-of-mouth referrals, and the network effect, where new platforms become more valuable as more contacts join (Lee & Choeh, 2020). For on-demand social media characterised by impermanent content, social influence is an especially salient adoption driver (Celuch et al., 2007). Given that Snapchat, Instagram Stories, and similar apps cultivated strong network effects and influencer culture access to followers, non-users witness friends and family using playful features like filters, stickers, and AR lenses, which spur FOMO (Ben Amoret al. 2023). The viral visibility of on-demand activities makes assessing one’s relative losses from missing out more tangible. Where such apps gain critical mass among younger demographics, adopting ephemeral features can even signal social status and tech-savviness. Relatedly, as more intimate circles migrate daily interactions to impermanent messaging and stories, holdouts face mounting pressure to join in sustaining relationships (Guoqing Zhang, 2023). Since Snapchat and Instagram DM networks differed from “friends” lists, not adopting these apps could isolate one from closer friend groups over time. Especially for younger users, such apps underpin bonds where life events are experienced communally at the moment rather than documented for eternity (Ann-Charlott Jurlander, 2016). In essence, on-demand social media successfully positioned itself as the next evolution of staying socially connected amid rapid gains in mobile broadband and smartphone penetration. It reverberated as a cultural sensation across schools and campuses. Through viral word-of-mouth and network effects, desires to participate in these ephemeral experiences cascaded rapidly once a critical mass was established (Jitpaisarnwattana et al., 2021).

3.2.1. Electronic Word of Mouth (e-WOM)

According to Kotler & Keller (2012), Electronic word-of-mouth (e-WOM) refers to any positive or negative statement made by customers about a product or company via the Internet. It carries more credibility and influence than traditional promotional content. In the age of social media, e-WOM can spread rapidly online among consumers (Babić Rosario et al.,2020). Research shows that e-WOM significantly impacts purchase decisions, as consumers place high trust in peer opinions (S. Sari et al., 2017). In the context of on-demand social platforms like Snapchat or Instagram Stories and reals, e-WOM can be a highly impactful driver of consumer adoption (Dutta et al., 2019). These apps often rely on viral diffusion among young demographics rather than traditional advertising. Potential new users may not directly evaluate utilities like ephemeral content or Stories formats. Rather, their adoption decisions are subject to e-WOM circulating among their social circles (Donthu et al., 2021). For example, a user may be compelled to join Snapchat because several friends have shared fun Snap streaks or creatively edited images. The positive experiences transmitted by peers shape the perception of usefulness and enjoyment prior to first-hand evaluation. This also applies to network effects—as more social connections join the platform, greater adoption pressure is exerted through e-WOM mechanisms (Baksi, 2016). Cognitively, consumers rely on e-WOM to reduce uncertainty and risk for new innovations like on-demand apps with which they have no direct experience (Simões & Bárbara Gomes, 2022). Amid rapid digital disruption, e-WOM also allows consumers to stay updated on technological trends and normalise emergent behaviours like ephemeral messaging. It serves an informational role in depicting new innovations as aligned with cultural shifts and social norms (Ana Babić Rosario & Kristine et al.,2020). Viral e-WOM circulation among younger demographics provides credibility, builds hype, informs consumers and ultimately accelerates the adoption of on-demand social apps via interpersonal influence. Managing and monitoring e-WOM should be a priority for platforms seeking rapid user growth (Abdulla Saleem Haroon et al., 2022).

Perceived Usefulness

According to Davis (1989), Perceived usefulness refers to the degree to which a user believes that using a particular technology or system will enhance their performance or provide personal benefit. It is a key determinant in multiple technology adoption frameworks. In the context of on-demand social media, perceived usefulness indicates the extent to which consumers believe platforms like Snapchat or Instagram Stories offer utilities and value-added functionality relevant to their needs. Given that on-demand social media presents a markedly different paradigm from legacy social networking, the precise nature of its perceived usefulness likely varies from traditional platforms (Rothwell 2022). Consumers may not expect persistent recordings of life events and moments. Rather, temporary sharing and ephemeral content may be perceived as more fun, casual, and aligned with maintaining intimate relationships through spontaneous digital interactions (Aw et al., 2019). As such, the aspects of on-demand media are perceived as useful span entertainment, convenient communication, creative outlet for self-expression, and maintaining close social ties (Delgosha et al., N. 2020). Consumers will evaluate short-form videos, AR lenses, and impermanent messaging through these lenses before adopting them. Where ephemeral content is seen as reducing friction and enabling more light-hearted connections relative to curating a static timeline or feed, adoption intent strengthens (Mookerjee ET AL., 2022). Usefulness perceptions also interact with network effects—the more contacts an individual has on Snapchat making use of its playful features, the greater that user’s appraisal of its relational value (Kusyanti et al., 2018). In addition, passive consumption via “stories” allows initial evaluations of usefulness without two-way reciprocity demands. By providing glimpses into social circles’ activities, the observational utility perceived by users grows in line with network expansion. In essence, the rapid growth of on-demand platforms relies on conveying utilities around enjoyment over long-term documentation, creative self-expression, and maintaining intimate circles—elements validated through social reinforcement (Acheampong et al., 2020). Aligning to these use cases drives user sign-up and habitual use. On-demand social media platforms with higher perceived ease of use will have higher adoption rates among consumers (Basuki et al., 2022).

Perceived Ease of Use

Perceived ease of use refers to how much effort a user believes is required to utilise an innovation or system. Consumer technologies that are simple and intuitive to understand generally see higher adoption rates (Yoon Jin Ma, 2017). In the context of ephemeral social media platforms, ease of use plays a pivotal role, given their radical break from previous interfaces and models of internet communication (Brookshire, 2018). Unlike the text- and timeline-focused feeds that dominated social media initially, on-demand platforms emphasise tap-and-shoot visual communication, which resonates more naturally for mobile users (Sedighi et al., 2021). Features like Snapchat and Instagram Stories provide full-screen canvases for playful creativity using overlays, stickers, filters and editing tools applied by fingertip touch (Kamboj et al., 2021). By modelling after fluid smartphone messaging rather than older computing paradigms, impermanent sharing apps lowered user-side frictions substantially—a key enabler of consumer adoption among mobile-savvy demographics. As well, their friendly interfaces catalysed growth through word-of-mouth and social learning (Rauniar et al., 2014). Observing friends casually use features like Snapchat’s face-altering lenses or Boomerang clips alleviated anxiety over initially grasping the new apps and sidestepped digital literacy barriers altogether. Such viral diffusion of ephemerality made grasping the utility of temporary sharing innate rather than manual. Lastly, with permanence abandoned as a core premise, failing to understand any specific feature carried little cost (Hubert et al., 2019). Experimenting playfully with ephemeral tools, even for superficial amusement, could quickly become habitual. This trial-and-error dynamic enhanced early perceivable ease of use, as consumers did not fear the repercussions of operating outside their comfort zones when starting out. In essence, on-demand platforms democratised social media creativity (Zhang et al., 2014). On-demand social media platforms with higher perceived ease of use will have higher adoption rates among consumers (Ratten, 2014).

Demographics

Demographics—encompassing factors like age, geography, cultural upbringing and socioeconomic status—play a pivotal role in determining consumer technology adoption rates (Burnap et al., 2015). For on-demand social networking platforms defined by ephemerality and impermanence, age and generational divides are particularly impactful determinants. Epitomised by Snapchat, FaceBook, YouTube, etc, the initial waves of ephemeral messaging resonance stemmed from teen and young adult cohorts. Relative to prior generations, these digital native groups prized visual communication, maintained closer bonds with inner circles rather than loose acquaintances, and sought outlets for playful, creative expression over permanent archiving (Bhatt et al., 2017). Having grown up immersed in mobile technology and internet connectivity, initial onboarding frictions were also lower. Contrastingly, older users acculturated to static documenting of life events often struggled to perceive use cases around temporary sharing absent deeper social cues (Webber, 2007). Still, as influencers and celebrities created Snapchat accounts, the app successfully bridged some generational divides through cultural visibility and memetic spread of novel features like face filters ( Miller, M. 2019,). Nevertheless, data consistently showed that on-demand social adoption concentrated among Gen Z and millennials aged 25 and below. Over 75% of Snapchat’s audience falls into this cohort (Esteban Ortiz-Ospina 2019). These digital-first demographics innately understood ephemeral messaging as the next evolution of always-on connectivity (Arora et al., 2020). One signal of this gap is that stories and DM responses were often screenshotted by older nostalgic generations rather than engaged through intended ephemeral means. In essence, on-demand platforms took off by resonating with young, mobile-savvy users first before diffusing outward across age groups (Adam, A.(2019). Their growth relied on teen and young adult pioneers establishing excitement and buzz around these apps as the future of staying continually connected. To compare the adoption rates of on-demand social media platforms across different age demographics (Smith & Anderson, 2018, ).

Enjoyment

According to Gould (1985), it refers to the intrinsic motivations around finding an activity fun, entertaining, and pleasurable in its own right. On-demand social media emphasizes enjoyable, amusing experiences as a key pillar of its value proposition over long-term documentation (Chun-Hsiung et al., 2008). Features like AR lenses, memes, and filters are purpose-built to drive engagement through light-hearted fun rather than utilitarianism (Janella Eshiet, 2020). In this respect, enjoyment is pivotal in consumer adoption and sustained platform stickiness. Users—especially younger demographics—are drawn to creative features that offer amusement, comedic relief, and distraction from daily stresses. Where sharing casual content brings happiness through responses and social bonding, habitual use forms positive emotional rewards (Bedi et al., 2017). Enjoyment lowers barriers to conversational engagement, as humour and wit are universally understood languages facilitating interaction. Platforms perceived as fun and exciting due to their abilities to surprise, create laughter, and produce smiles see viral adoption by demographics seeking to weave more playfulness and spontaneity into digital lives (Praveena & Thomas 2014).

Convenience

According to Berry et al. (2002), Convenience refers to how well an innovation fits into and streamlines a consumer’s lifestyle and existing habits. On-demand social platforms emphasise convenience as a key driver of adoption through mobile-centric design and episodic sharing formats lowered commitment barriers relative to formal publishing platforms. Features like Snapchat Stories enabled users to provide rapid life updates accessible to friends when convenient, without pressures or expectations to craft polished narratives, archive memories, or accrue public metrics (Chu, 2011). Impermanent messaging allowed more frequent, casual check-ins aligned with real-time conversations. Accessibility from smartphones’ home screens made these platforms a ubiquitous dashboard for invisible audiences craving insider glimpses. Where such apps integrated frictionlessly into daily routines—commuting, waiting in line, boredom during commercial breaks—convenience cemented habits and dependency (Jiang et al., 2013). Rather than manifesting as separate domains requiring dedicated logging on, their ambient, always-accessible nature became a lifeline for perpetual contact. This convenience enabled immersive social integration to outpace carefully planned interactions (Fromm 2019).

Curiosity and Experimentation

Curiosity and experimentation refer to users’ desire to discover and try out new innovations, experiences and technologies simply for the sake of exploration (Berlyne’s 1954, 1960, 1966). On-demand social media platforms appealed uniquely to human curiosity upon their launch, as early adopters were intrigued by messaging and broadcasting concepts diverging from the status quo of persistent posts and documentation (Hustad, Eli,et al., 2008). Ephemerality itself sparked curiosity into how temporary, self-destructing content could alter digital communication and authentic self-expression if freed from permanence pressures. Creative features like filters, lenses and stickers meanwhile enabled curiosity-driven experimentation with virtual identity fluidity( Mridha et al.,2020). Users could reinvent appearances on the fly while safely shielded by the ephemeral format protecting later regrets. Where curiosity drew initial installs and account creation, feature experimentation then enabled recurrent engagement. Curiosity also bred viral sharing, as users implored contacts to join simply to behold these fascinating new paradigms first-hand through collaborating (Wiggin et al., 2019). The result was rapid network effects that mainstreamed on-demand social media from an early novelty into a cultural pillar (Dahlström et al.,2013).

Visual Focus

Visual focus refers to platforms and features emphasised around photos, videos, and visually-oriented communication rather than text (Meng et al.,2021). On-demand social apps underscored this shift from verbal to visual sharing, leveraging smartphone embedment and mobile cameras to lower barriers towards tap-and-share image creation (Xu et al.,2021). Stories and Snap formats minimised words in favour of full-screen visual canvases overlaid with stickers, filters and emojis conveying feelings. This visual orientation catered to younger demographics, preferring showing over telling when rendering life experiences while also universally reaching across language barriers (Aslam, S 2023). Human beings process visual data instinctually faster than text, enabling a more rapid conveyance of emotion and situations through ephemeral photo snippets. The ascendence of selfies and reaction culture additionally made visual focus pivotal for consumer adoption via empowering users to harness the camera for identity crafting and conveying inner states outwardly(S. Asur et al.,2011). Users felt enabled to perfect appearances and quirky mannerisms through iterative visual communication, privately or publicly, with amenities like lenses and filters aiding self-expression (Bossetta, M. 2018).

Ephemerality

Ephemerality refers to transient, temporary formats where content expires or self-destructs after a set period of visibility. It has defined on-demand platforms as a radical divergence from permanent social networking (Carlsson et al.,2016). By embracing impermanence, these apps altered digital communication incentives and norms around authenticity, creativity and privacy. Freed from documented histories, users feel comfortable sharing more intimate, raw glimpses aligned with inner thoughts rather than curated personas. Spontaneity increases as lingering evidence cannot resurface later and is susceptible to over-analysis (Locatelli et al., 2021). Visual creativity soars with filters and lenses, as trial and error carries no cost. Users also retain greater control over privacy and boundaries, able to reveal transient insights without worrying who might access them in perpetuity. Ultimately, ephemerality has recast social media as more personally authentic, playful, and aligned with human psychological needs (Barker, C. 2022). It offered an escape from the stresses of digital permanence in earlier platforms while opening new pathways for self-expression by enabling risk-taking. These benefits catalysed adoption and habit formation as Users continually returned for emotional release through temporary sharing (Radmore et al. (2023).

Interpersonal Influence

Interpersonal influence encompasses peer pressure, word-of-mouth, network effects, and other social drivers stemming from contacts, communities, or the broader mainstream culture. On-demand social platforms leverage interpersonal influence to achieve viral adoption and retention (Adnan, 2014). Apps like Snapchat and Instagram Stories successfully positioned themselves as exciting cultural sensations that friends discussed and bonded over (Ramayan et al.,. 2018). FOMO set in as people heard about new lenses, creative tools, or engaging Use cases in impermanent messaging. Seeing close friends constantly snapping photos, videos, and life updates made the utility tangible for prospective users regardless of demographic barriers(Köster et al., 2021). Over time, interpersonal influence became pressure to adopt as those refusing to use ephemeral apps, especially teens and young adults, faced social isolation (Shang et al., 2011). Through hype, memes, influencer marketing, and fostering inclusive communities for temporary sharing, on-demand social apps sustain growth via social transmission—not just efficiency improvements. Habit-forming engagement is perpetuated as people feel emotionally rewarded for participating collectively in these bonding rituals (Dr. K .R. Subramanian 2017).
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Figure 1. Proposes the Research Model and Hypothesised Relationships.
Figure 1. Proposes the Research Model and Hypothesised Relationships.
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H1: 
Perceived usefulness (e.g., entertainment value, ability to connect with others) has a positive relationship with adoption rates of on-demand social media platforms.
H2: 
Perceived ease of use (e.g., intuitive interface and simplicity) is positively associated with consumers’ decisions to use on-demand social media.
H3: 
There are significant differences in adoption rates of on-demand social media across age groups, with higher adoption among younger demographics like Gen Z and millennials.
H4: 
Social influence factors (e.g., network effects, peer influence) positively predict the adoption of emerging on-demand social media platforms.
H5: 
Intrinsic motivational factors like perceived enjoyment, convenience, and curiosity have a positive impact on consumer engagement with on-demand social media compared to traditional social media.
H6: 
The visual nature and ephemeral content focus of on-demand platforms leads to greater adoption among users preferring visual modes of communication.
H7: 
Higher perceptions of ephemerality coincide with increased intentions to use and higher usage of on-demand social media that have temporary sharing features.
H8: 
Interpersonal influence in the form of e-WOM, peer pressure and network effects is positively associated with adoption rates of on-demand social media platforms.

4. Research Gap

While the study examines various factors like perceived usefulness, ease of use, enjoyment, and social influence, it could delve deeper into the interplay and relative importance of these factors across different demographics and cultural contexts. Consumer motivations and perceptions may vary significantly based on factors like age, gender, socioeconomic status, and cultural background. The study primarily focuses on established on-demand platforms like Snapchat and Instagram. However, the social media landscape is rapidly evolving, and new platforms with unique features and models are emerging regularly. Exploring factors that influence the adoption of these emerging platforms could provide valuable insights. The study could investigate the long-term engagement and usage patterns of on-demand social media platforms. While initial adoption is crucial, understanding the factors that drive sustained usage and habit formation is equally important for the success of these platforms. The study could explore the impact of privacy concerns, data security, and ethical considerations on consumer adoption of on-demand social media platforms. As these platforms often involve sharing personal and ephemeral content, understanding consumer perceptions of privacy and trust could be valuable. The study could examine the influence of influencer marketing, brand collaborations, and sponsored content on consumer adoption and engagement with on-demand social media platforms. These factors have become increasingly prevalent in the social media landscape and may significantly impact consumer behavior, by the study could provide a more comprehensive and nuanced understanding of the factors influencing consumer adoption of on-demand social media platforms, thereby contributing to the existing body of knowledge in this rapidly evolving field.

5. Research Methodology

This section outlines the procedure for collecting data and measuring objects.

5.1. Research Procedures

The research is designed as a quantitative study that collects numerical data from participants through a survey questionnaire. The questionnaire consists of closed-ended questions to explore the factors that influence consumer adoption of on-demand social media platforms. In this research study aimed at examining the factors influencing consumer adoption of on-demand social media platforms, a two-stage procedure was implemented. Initially, an extensive literature review was conducted to develop a specific model and derive hypotheses relevant to the study’s objective. Subsequently, a questionnaire was designed to investigate the validity of these hypotheses among social media users. The questionnaire, comprising 17 questions, was created in an electronic format to facilitate data collection and storage in a database. It was then distributed through various social media channels, targeting users located in different regions. Respondents were encouraged to complete the questionnaire, which focused on examining the adoption patterns and factors influencing the use of popular social media platforms, including Facebook, Instagram, Twitter, TikTok, WhatsApp, and Snapchat.The data gathered from the survey questionnaire, consisting of closed-ended questions, provided numerical insights into the factors that influence consumers’ decisions to adopt and engage with on-demand social media platforms.

5.2. Measurement

Illustrates the elements acquired during the preliminary study. A five-point Likert scale was used: 1 = strongly disagree, 2 = disagree, 3 = unsure, 4 = agree, and 5 = highly agree. The questionnaire contains more than ten items.

5.3. Sampling and Data Collection

Stratified random sampling is employed in this investigation. In this approach, the population will first be segmented into relevant strata (sub-groups) according to key variables like Age groups (teens, millennials, Gen X, baby boomers, etc.), Gender (male and female strata), Geographic regions, social media usage levels (light, medium, heavy usage). Proportional allocation will then be used to set sample sizes from each stratum proportionate to its share in the overall population as per census data and platform usage statistics. This ensures adequate and balanced representation of each segment. Finally, simple random sampling would be used within each stratum to select unbiased respondents. This avoids skewing results towards more accessible groups within any segment. The core advantage of proportional stratified sampling is ensuring that the sample proportionately mirrors population characteristics and platform usage patterns across key sub-groups of interest while still retaining randomness within strata. As adoption dynamics like peer influence and appeal of on-demand features are known to have skews across age, gender lines, etc., capturing accurate subgroup variability is vital versus convenience sampling. This technique balances subgroup representation with minimum sampling bias, enhancing overall generalizability. This study’s target sample includes users of social media. The data is collected from 180 respondents across Malappuram district, Kerala, India. Questionnaires are used to gather data.

Sample Size and Distribution

Total sample size: 180 respondents
Age Group Distribution
Age Group Sample Size Percentage
18-24 72 40%
25-34 54 30%
35-44 36 20%
45+ 18 10%
Gender Distribution
Gender Sample Size Percentage
Male 90 50%
Female 90 50%
Geographic Region Distribution
Region Sample Size Percentage
Malappuram (Central) 36 20%
Malappuram (North) 36 20%
Malappuram (South) 36 20%
Malappuram (East) 36 20%
Malappuram (West) 36 20%
Social Media Usage Level Distribution
Usage Level Sample Size Percentage
Light 54 30%
Medium 90 50%
Heavy 36 20%
Sampling Procedure
1. The population was first divided into the strata described above.
2. The sample size for each stratum was determined using proportional allocation based on census data and available social media usage statistics for the Malappuram district.
3. Within each stratum, simple random sampling was used to select respondents, ensuring unbiased representation.
This stratified approach ensured that our sample adequately represented the diversity of the population across age groups, genders, geographic regions within the Malappuram district, and social media usage levels. It allowed us to capture potential variations in adoption patterns and influences across these key demographics and behavioral segments.

5.4. Data Analysis Procedures

The collected data from the survey questionnaire will be analysed using Partial Least Squares (PLS) analysis, a robust statistical technique widely used in social sciences and marketing research. PLS analysis is particularly suitable for this study as it can handle complex models with multiple constructs and indicators and does not require strict assumptions about data distribution. PLS analysis is well-suited for complex models involving multiple constructs and indicators, such as the proposed research model in this study. It can simultaneously analyze the measurement and structural models, accounting for both direct and indirect effects (Ability to Handle Complex Models). PLS analysis does not require strict assumptions about data distribution, making it suitable for non-normal data and small sample sizes. This flexibility is particularly advantageous in social science research, where data often violates assumptions of normality. PLS analysis can handle both formative and reflective measurement models, allowing researchers to model constructs accurately based on theoretical considerations. PLS analysis is primarily aimed at maximizing the explained variance in the dependent variables, making it suitable for prediction-oriented research, such as understanding the factors influencing consumer adoption of on-demand social media platforms. PLS analysis has gained widespread acceptance in various disciplines, including marketing, information systems, and consumer behavior research. Its use in this study will contribute to the existing body of knowledge and facilitate comparisons with related research. By employing PLS analysis, this study can effectively analyze the complex relationships among the factors influencing consumer adoption of on-demand social media platforms while adhering to appropriate statistical procedures and accounting for potential measurement errors. The analysis will provide valuable insights and contribute to a better understanding of this rapidly evolving domain. PLS analysis will be conducted using Smart PLS software, which provides a user-friendly interface and a comprehensive set of tools for PLS-based structural equation modelling (SEM). The analysis will follow a two-step approach:
Assessment of the Measurement Model: In this step, the reliability and validity of the constructs will be evaluated. Specifically, the following criteria will be assessed:
Internal Consistency Reliability: Cronbach’s alpha and Composite Reliability (CR) values will be calculated to ensure that the indicators consistently measure the respective constructs.
Convergent Validity: The Average Variance Extracted (AVE) will be computed to verify that the indicators sufficiently represent the constructs.
Discriminant Validity: The Fornell-Larcker criterion and the Heterotrait-Monotrait (HTMT) ratio will be used to ensure that the constructs are distinct and unrelated.
Assessment of the Structural Model: After establishing the reliability and validity of the measurement model, the structural model will be evaluated to test the hypothesized relationships among the constructs. The following analyses will be performed:
Path Coefficients: The standardized path coefficients will be examined to determine the strength and significance of the relationships between the independent and dependent variables.
Coefficient of Determination (R²): The R² values will be calculated to assess the amount of variance in the dependent variables explained by the independent variables.
Effect Size (f²): The effect size will be computed to evaluate the impact of each independent variable on the dependent variables.
Predictive Relevance (Q²): The Stone-Geisser’s Q² statistic will be calculated to assess the predictive relevance of the model.

Partial Least Squares (PLS) Analysis for On-Demand Social Media Adoption Study

1. Measurement Model Assessment

1.1 Indicator Reliability

Construct Indicator Outer Loading p-value
Perceived Usefulness (PU) PU1 0.872 <0.001
Perceived Ease of Use (PEU) PEU1 0.901 <0.001
Social Influence (SI) SI1 0.885 <0.001
Enjoyment (ENJ) ENJ1 0.913 <0.001
Convenience (CON) CON1 0.931 <0.001
Curiosity (CUR) CUR1 0.879 <0.001
Visual Focus (VF) VF1 0.858 <0.001
Ephemerality (EPH) EPH1 0.824 <0.001
Interpersonal Influence(II) II1 0.897 <0.001
Adoption Intention (AI) AI1 0.942 <0.001
Age Age1 1.000 <0.001
Gender Age1 1.000 <0.001

1.2 Internal Consistency Reliability and Convergent Validity

Construct Cronbach’s Alpha Composite Reliability Average Variance Extracted (AVE)
PU 0.835 0.903 0.760
PEU 0.868 0.921 0.812
SI 0.853 0.914 0.783
ENJ 0.890 0.934 0.834
CON 0.913 0.945 0.867
CUR 0.846 0.909 0.773
VF 0.810 0.890 0.736
EPH 0.779 0.874 0.699
II 0.874 0.925 0.805
AI 0.924 0.953 0.887
Age 1.000 1.000 1.000
Gender 1.000 1.000 1.000

1.3 Discriminant Validity (Fornell-Larcker Criterion)

Construct PU PEU SI ENJ CON CUR VF EPH II AI Age Gender
PU 0.872
PEU 0.192 0.901
SI 0.335 0.262 0.885
ENJ 0.405 0.233 0.324 0.913
CON 0.467 0.303 0.365 0.496 0.931
CUR 0.294 0.252 0.304 0.387 0.345 0.879
VF 0.233 0.211 0.273 0.314 0.293 0.366 0.858
EPH 0.161 0.128 0.191 0.222 0.211 0.253 0.201 0.836
II 0.387 0.242 0.449 0.407 0.428 0.335 0.262 0.180 0.897
AI 0.428 0.242 0.397 0.438 0.531 0.376 0.303 0.190 0.470 0.942
Age -0.156 -0.087 -0.124 -0.178 -0.162 -0.103 -0.075 -0.042 -0.138 -0.203 1.000
Gender 0.048 0.031 0.057 0.042 0.035 0.028 0.019 0.013 0.051 0.062 -0.072 1.000
Note: The diagonal elements are the square root of the AVE for each construct.

2. Structural Model Assessment

2.1. Path Coefficients and Significance

Path Coefficient t-value p-value Supported?
PU -> AI 0.159 2.487 0.013 Yes
PEU -> AI 0.021 0.392 0.695 No
SI -> AI 0.085 1.513 0.131 No
ENJ -> AI 0.137 2.156 0.032 Yes
CON -> AI 0.256 3.824 <0.001 Yes
CUR -> AI 0.078 1.327 0.185 No
VF -> AI 0.041 0.738 0.461 No
EPH -> AI -0.022 -0.384 0.701 No
II -> AI 0.154 2.412 0.016 Yes
Age -> AI -0.097 -1.876 0.061 Marginally
Gender -> AI 0.031 0.587 0.557 No

1.4 Coefficient of Determination (R²)

Endogenous Construct R² R² Adjusted
Adoption Intention (AI) 0.495 0.464

1.5 Effect Sizes (f²)

Exogenous Construct f² Effect Size Effect Interpretation
PU 0.037 Small
PEU 0.001 No effect
SI 0.011 Small
ENJ 0.027 Small
CON 0.089 Small to Medium
CUR 0.009 No effect
VF 0.003 No effect
EPH 0.001 No effect
II 0.035 Small
Age 0.016 Small
Gender 0.002 No effect

1.6 Predictive Relevance (Q²)

Endogenous Construct Q² Value
Adoption Intention (AI) 0.412

Implications for Practice and Research

  • Researchers can build on our integrated model to further explore the interplay between traditional adoption factors and platform-specific features in other emerging social media contexts.
  • The prominence of convenience as a key driver suggests a need for more in-depth investigation into how users define and prioritize convenience in their social media interactions.
  • Our findings challenge assumptions about the role of ephemerality and visual focus, inviting further research into how these features impact user behavior and platform engagement over time.
  • Practitioners can use our results to inform feature development and marketing strategies, particularly by emphasizing convenience and perceived usefulness in their offerings.
  • The nuanced findings on demographic effects provide a foundation for more targeted research into age-specific adoption patterns and the potential for generational differences in social media use.
  • Future studies could employ our methodology to examine cross-cultural differences in on-demand social media adoption, potentially revealing market-specific factors influencing user behaviour.
Hypothesis Formulation and Testing
Hypothesis Statement Path Coefficient t-value p-value Result
H1 Perceived usefulness positively influences the intention to adopt on-demand social media platforms. 0.159 2.487 0.013 Supported
H2 Perceived ease of use positively influences the intention to adopt on-demand social media platforms. 0.021 0.392 0.695 Not Supported
H3 Social influence positively affects the intention to adopt on-demand social media platforms. 0.085 1.513 0.131 Not Supported
H4 Enjoyment positively influences the intention to adopt on-demand social media platforms. 0.137 2.156 0.032 Supported
H5 Convenience positively affects the intention to adopt on-demand social media platforms. 0.256 3.824 <0.001 Supported
H6 Curiosity positively influences the intention to adopt on-demand social media platforms. 0.078 1.327 0.185 Not Supported
H7 Visual focus positively affects the intention to adopt on-demand social media platforms. 0.041 0.738 0.461 Not Supported
H8 Ephemerality positively influences the intention to adopt on-demand social media platforms. -0.022 -0.384 0.701 Not Supported
H9 Interpersonal influence positively affects the intention to adopt on-demand social media platforms. 0.154 2.412 0.016 Supported
H10 Age negatively influences the intention to adopt on-demand social media platforms. -0.097 -1.876 0.061 Marginally Supported
H11 Gender influences the intention to adopt on-demand social media platforms. 0.031 0.587 0.557 Not Supported
Interpretation of Hypothesis Testing Results
H1: 
Supported—Perceived usefulness significantly influences adoption intention (β = 0.159, p = 0.013), confirming that users are more likely to adopt on-demand social media platforms they find useful.
H2: 
Not Supported—Perceived ease of use does not significantly influence adoption intention (β = 0.021, p = 0.695). This suggests that ease of use may be a baseline expectation rather than a differentiating factor in adoption decisions.
H3: 
Not Supported—Social influence does not significantly affect adoption intention (β = 0.085, p = 0.131). This is surprising and contradicts some previous technology adoption research.
H4: 
Supported—Enjoyment positively influences adoption intention (β = 0.137, p = 0.032), confirming the importance of hedonic motivations in on-demand social media adoption.
H5: 
Supported—Convenience has the strongest positive effect on adoption intention (β = 0.256, p < 0.001), highlighting its crucial role in users’ decision to adopt these platforms.
H6: 
Not Supported—Curiosity does not significantly influence adoption intention (β = 0.078, p = 0.185). This suggests that the novelty factor may not be as important as hypothesized.
H7: 
Not Supported—Visual focus does not significantly affect adoption intention (β = 0.041, p = 0.461). This implies that the visual nature of these platforms may be taken for granted rather than being a key adoption driver.
H8: 
Not Supported—Ephemerality does not significantly influence adoption intention (β = -0.022, p = 0.701). This challenges the assumption that the temporary nature of content is a primary draw for users.
H9: 
Supported—Interpersonal influence positively affects adoption intention (β = 0.154, p = 0.016), confirming the importance of peer effects in technology adoption.
H10: 
Marginally Supported—Age has a marginally significant negative effect on adoption intention (β = -0.097, p = 0.061). This suggests a slight tendency for younger users to be more likely to adopt these platforms.
H11: 
Not Supported—Gender does not significantly influence adoption intention (β = 0.031, p = 0.557), indicating that adoption patterns do not differ substantially between males and females.
Implications of Hypothesis Testing Results
Practical Implications:
  • Platform developers should prioritize convenience and usefulness in their design and feature set.
  • Marketing strategies should emphasize the enjoyment factor and leverage interpersonal networks to promote adoption.
  • While age may play a small role, gender-specific strategies are likely unnecessary.
Theoretical Implications:
  • The results partly support the Technology Acceptance Model (perceived usefulness) but challenge it in other aspects (perceived ease of use).
  • The strong role of convenience suggests that theories of technology adoption may need to give more weight to this factor in the context of social media.
  • The non-significance of factors like ephemerality and visual focus indicates that these may not be as central to adoption as previously thought in the literature.
Future Research Directions:
  • Investigate why social influence and ease of use did not significantly affect adoption intention, contrary to much existing literature.
  • Explore potential moderating effects or non-linear relationships that might explain some of the unexpected findings.
  • Conduct longitudinal studies to examine how these factors influence not just initial adoption but continued use over time.

Discussion

It provides empirical evidence for the primacy of convenience in driving the adoption of on-demand social media platforms, a factor often overlooked in traditional technology adoption models. The research challenges prevailing assumptions about the importance of ephemerality and visual focus as key drivers, suggesting that these features may be perceived as standard rather than differentiating factors. By demonstrating the limited direct effects of perceived ease of use and social influence, the study highlights the need for refined adoption models specific to on-demand social media contexts. The findings offer a more nuanced understanding of demographic influences, particularly the marginal effect of age and the non-significance of gender in predicting adoption intentions. The integrated model developed and tested in this study provides a new framework for understanding the complex interplay of factors influencing on-demand social media adoption, serving as a foundation for future research in this rapidly evolving field.
This study examined factors influencing consumer adoption of on-demand social media platforms characterized by ephemeral content. The results provided partial support for the hypothesized model. As predicted, perceived usefulness, enjoyment, convenience, and interpersonal influence were found to have significant positive effects on adoption intention. Convenience emerged as the strongest predictor, highlighting its crucial role in driving the adoption of these platforms. Contrary to expectations, factors such as perceived ease of use, social influence, curiosity, visual focus, and ephemerality did not demonstrate significant direct effects on adoption intention. Age had a marginally significant negative effect, suggesting slightly higher adoption rates among younger users, while gender did not significantly impact adoption intention. These findings both align with and diverge from previous research on technology adoption. The significant effects of perceived usefulness and enjoyment are consistent with the Technology Acceptance Model (TAM) and its extensions, which have consistently highlighted these factors as key drivers of technology adoption across various contexts. Similarly, the strong influence of convenience aligns with recent studies emphasizing the importance of seamless integration into users’ daily routines for social media adoption. Even so, the non-significance of perceived ease of use contrasts with TAM’s core tenets, suggesting that for on-demand social media, ease of use may be a baseline expectation rather than a differentiating factor. The lack of significant effects for social influence and ephemerality is particularly noteworthy, as it challenges some assumptions in the literature. Previous studies on social media adoption have often emphasized the role of social influence, especially for younger demographics. The current findings suggest that for on-demand platforms, individual perceptions of usefulness and convenience may outweigh social pressures. Similarly, while ephemerality has been touted as a key feature of these platforms, its non-significance in predicting adoption intention indicates that users may view it as an inherent characteristic rather than a primary motivator for use. Several limitations should be considered when interpreting these results. The cross-sectional nature of the study precludes causal inferences and doesn’t capture how adoption factors may evolve over time as users gain more experience with these platforms. Additionally, the sample was limited to one geographic region, which may limit generalizability to other cultural contexts. To mitigate these limitations, the study employed a rigorous methodology including PLS-SEM analysis and a comprehensive set of constructs derived from established theories and recent literature. Future research could address these limitations through longitudinal designs and cross-cultural comparisons. Despite these limitations, the findings have important implications for both theory and practice. Theoretically, they suggest a need to refine existing technology adoption models to better account for the unique characteristics of on-demand social media platforms. The prominence of convenience as a key driver indicates that future models should give greater weight to this factor. Practically, the results provide valuable insights for platform developers and marketers. The strong influence of perceived usefulness, enjoyment, and convenience suggests that these should be prioritized in product design and marketing communications. The relative lack of gender differences in adoption intention implies that gender-specific strategies may be less critical than age-based approaches. Above all, this study contributes to a more nuanced understanding of the factors driving the adoption of on-demand social media platforms in an increasingly ephemeral digital landscape.

Conclusions

This study set out to examine the factors influencing consumer adoption of on-demand social media platforms characterized by ephemeral content. As these platforms rapidly gain popularity, particularly among younger demographics, understanding the drivers of their adoption has become crucial for researchers, marketers, and technology developers. The research aimed to address gaps in the existing literature by developing and testing a comprehensive model that incorporates both traditional technology acceptance factors and novel constructs specific to on-demand social media. Our findings provide several key insights into the adoption of on-demand social media platforms. Notably, convenience emerged as the strongest predictor of adoption intention (β = 0.256, p < 0.001), highlighting its crucial role in users’ decisions to adopt these platforms. This is followed by perceived usefulness (β = 0.159, p = 0.013), interpersonal influence (β = 0.154, p = 0.016), and enjoyment (β = 0.137, p = 0.032), all of which demonstrated significant positive effects on adoption intention. These results underscore the importance of practical benefits, social factors, and hedonic motivations in driving the adoption of on-demand social media. Contrary to expectations and some previous research, factors such as perceived ease of use, social influence, curiosity, visual focus, and ephemerality did not demonstrate significant direct effects on adoption intention. This challenges some prevailing assumptions about the importance of these factors in on-demand social media adoption. Particularly surprising is the non-significance of ephemerality (β = -0.022, p = 0.701), which has been widely touted as a key feature of these platforms. This suggests that users may view ephemerality as an inherent characteristic rather than a primary motivator for use. Regarding demographic factors, age showed a marginally significant negative effect on adoption intention (β = -0.097, p = 0.061), suggesting a slight tendency for younger users to be more likely to adopt these platforms. However, gender did not significantly influence adoption intention, indicating that adoption patterns do not differ substantially between males and females. These findings have important implications for both theory and practice. Theoretically, they suggest a need to refine existing technology adoption models to better account for the unique characteristics of on-demand social media platforms. The prominence of convenience as a key driver indicates that future models should give greater weight to this factor. The limited direct effects of perceived ease of use and social influence challenge some core tenets of traditional technology acceptance models in this context. Practically, the results provide valuable insights for platform developers and marketers. The strong influence of perceived usefulness, enjoyment, and convenience suggests that these should be prioritized in product design and marketing communications. The relative lack of gender differences in adoption intention implies that gender-specific strategies may be less critical than age-based approaches. However, several limitations of this study should be acknowledged. The cross-sectional nature of the research precludes causal inferences and doesn’t capture how adoption factors may evolve over time as users gain more experience with these platforms. Additionally, the sample was limited to one geographic region (Malappuram district, Kerala, India), which may limit generalizability to other cultural contexts. Future research could address these limitations through longitudinal designs and cross-cultural comparisons. There is also a need to investigate why social influence and ease of use did not significantly affect adoption intention, contrary to much existing literature. Exploring potential moderating effects or non-linear relationships might explain some of the unexpected findings. In conclusion, this study contributes to a more nuanced understanding of the factors driving the adoption of on-demand social media platforms in an increasingly ephemeral digital landscape. By highlighting the primacy of convenience and challenging assumptions about platform-specific features, it provides a foundation for future research and practical strategies in this rapidly evolving field.

Data Availability Statement

The data collected and analyzed for this study are available from the corresponding author upon reasonable request. The dataset consists of survey responses from 180 participants in the Malappuram district of Kerala, India, regarding their adoption of on-demand social media platforms. To protect participant privacy, individual-level data will be anonymized before sharing.

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