Keywords

Influencer Marketing, Cyber Entrepreneurial Intentions, Self-Efficacy, Social Media Learning Behaviour.

Introduction

The rise of influencer marketing has significantly impacted the livelihoods of many influencers, enabling them to scale or pivot into other businesses by leveraging their digital skills and online fame (Hudders & Lou, 2023). Influencers are defined as individuals with large followings who are seen as trusted tastemakers in specific niches (DeVeirman et al., 2016). They often share success stories, endorsement deals, and personal achievements to generate content and inspire followers (Newlands & Fieseler, 2020). Influencer venture success refers to the visible success of influencer-led businesses showcased on social media. This phenomenon is a compelling research area due to the mutual influence between influencers and their followers. Although public displays of wealth and success are not new (Kovácová, 2022), there is limited empirical research on how such displays shape followers' entrepreneurial intentions particularly in the context of influencer marketing and cyber-entrepreneurship.

Existing studies have examined influencer marketing’s structure (Campbell & Farrell, 2020), its impact on consumer behavior (Jin et al., 2019), and its effects on children (De Veirman et al., 2019). Influencer marketing is generally seen as a revenue stream where influencers promote brands through organic content (Vrontis et al., 2021; Ye et al., 2021).

Cyber-entrepreneurship, or internet entrepreneurship, involves business conducted online and has been explored in relation to factors like locus of control, planned behavior, and student intentions (Tseng et al., 2022; Vafaei-Zadeh et al., 2023). However, gaps remain, particularly concerning the influence of social factors like influencer success. While influencer marketing’s impact on consumer behavior and brand equity is well documented (Cornwell et al., 2023), its influence on followers’ cyber-entrepreneurial intentions especially among college students remains unexplored. Some influencers have expanded into diverse entrepreneurial fields such as beauty, agriculture, food, fashion, and stationery (Ahmadi et al., 2022), making the study of their business success highly relevant. Research has largely focused on followers’ purchase behavior (Venciute et al., 2023), engagement (Syrdal et al., 2023), and hedonic experiences (Barta et al., 2023), overlooking how influencer success may shape followers’ entrepreneurial goals. This study addresses that gap by examining how influencer venture success influences cyber-entrepreneurial intentions and introduces social media learning behavior as a mediating factor.

This paper contributes to the literature by conceptualizing influencer venture success and exploring its impact on college students’ entrepreneurial behavior, specifically cyber-entrepreneurial intentions. It further highlights the mediating roles of self-efficacy and social media learning behavior, grounded in Evolutionary Theory and Friedkin and Johnsen’s model.

Theoretical Foundation and Hypotheses Development

This study applies the evolutionary theory to explain how influencer venture success can shape the traits and behaviors of followers. Observing influencer success may trigger a desire among followers to adopt similar traits motivated by the potential for comparable benefits. From this perspective, social media learning behavior and self-efficacy function as mechanisms through which followers internalize and emulate influencer traits, leading to cyber-entrepreneurial intentions. In this sense, the inheritance of traits is metaphorically fulfilled as followers seek to "evolve" from observers to cyber-entrepreneurs. This study extends evolutionary theory into the entrepreneurial domain by framing digital emulation as a modern form of trait transmission. To complement this view, Friedkin and Johnsen’s (1990) model of social influence provides additional explanatory power. The model suggests that individuals form and update their beliefs based on information from their social network (Friedkin & Johnsen, 2011). Influence flows through both direct and indirect relationships. In today’s digital environment, where influencers occupy central positions within online networks, their behavior and success are especially impactful. Influencers, acting as “parent figures” in these networks, transmit values and norms through content. Followers, in turn, rationally interpret influencer success as a viable path to similar outcomes, motivating them to pursue cyber entrepreneurship (Friedkin & Johnsen, 2003). Influencers' centrality within online networks amplifies their influence. Their visibility and perceived success catalyze behavioral shifts in followers, inspiring transitions from passive observers to active entrepreneurs—and potentially, influencers themselves. In this way, influencer venture success contributes to a digital cycle of entrepreneurial evolution. Figure 1 illustrates the proposed relationships among these constructs.

Influencer Venture Success and Cyber-Entrepreneurial Intentions

Influencer marketing has emerged as a dynamic business model where individuals, known as influencers, leverage their large social media followings to promote brands and drive engagement (Guinez-Cabrera & Aqueveque, 2022). Influencers act as cultural figure heads, shaping trends and narratives online (Souza-Leão et al., 2022). Their success often brings fame, wealth, and a glamorous lifestyle, making influencer marketing both profitable and aspirational (Vrontis et al., 2021). This success serves as powerful content for promotion and brand messaging (Stoldt et al., 2019). Drawing on Friedkin and Johnsen’s (1990) model, this study proposes that influencers’ lifestyle posts influence followers to emulate them particularly by pursuing cyber entrepreneurship (Hudders & De Jans, 2022; Gupta et al., 2023). Followers engage with this content through likes, shares, and comments, signaling responsiveness to social cues (Lou, 2022; Wilkie et al., 2022). Influencer venture success thus functions as an evolutionary signal, shaping follower behavior (Isiwu & Onwuka, 2017). Accordingly, the following hypothesis is proposed:

H₁: Influencer venture success positively and significantly predicts cyber-entrepreneurial intentions.

Influencer Venture Success and Self-Efficacy

The role of self-efficacy in shaping behavioral intentions is reported (Hudders & De Jans, 2022). Influencers have been shown to stimulate social self-efficacy among followers through their content (Ouvrein, 2024; Tiwari et al., 2024). Drawing on Friedkin and Johnsen’s (1990) concept of network centrality, influencer content frequently shared and widely visible can influence followers’ perceived behavioral control. Studies have found that exposure to influencer content fosters a belief in personal capability. For instance, Ouvrein (2024) found that viewing influencers in specific niches enhances follower self-efficacy, while Germic et al. (2021) reported a similar effect among mothers following “mum influencers.” These findings suggest that influencer behavior can meaningfully shape follower perceptions.

Building on this, our study proposes that exposure to influencer venture success such as posts showcasing business achievements boosts followers' self-efficacy. This, in turn, fosters the intention to transition from follower to founder, driven by a sense of perceived competence (Soltwisch, 2021). Accordingly, the following hypothesis is proposed:

H₂: Influencer venture success positively and significantly predicts self-efficacy.

Self-Efficacy and Cyber-Entrepreneurial Intentions

Self-efficacy refers to an individual’s perception of control regarding things that occur in their life (Wang et al., 2024). Prior research has established some connection between self-efficacy and cyber entrepreneurial intentions (Al Amimi & Ahmad, 2023; Li, 2024). Chang et al. (2020) for example investigated the moderating role of positive thinking on the relationship between cyber entrepreneurial self-efficacy and cyber entrepreneurial intentions. Their findings revealed that cyber entrepreneurial self-efficacy has a significant positive effect on cyber entrepreneurial intentions. entrepreneurial self-efficacy is viewed as one of the important predictors of entrepreneurial intentions (Chang et al., 2020), and this same effect has been observed within the domain of cyber entrepreneurship (Ahmed & Islam, 2023; Li, 2024). An individual’s belief that they can create a new business through Internet and digital technology is a positive precursor to behavioural intentions to establish a cyber-business (Chang et al., 2020; Kumar & Shuklar, 2022). Thus, our study also proffers that self-efficacy can have a positive and significant effect on cyber entrepreneurial behavioural intentions, leading to the following hypothesis:

H₃: Self-efficacy positively and significantly predicts cyber-entrepreneurial intentions.

Influencer Venture Success and Social Media Learning Behaviour

Johnsen and Friedkin’s (1990) model highlights the role of network cues in influencing consumer behaviour (Nafees et al., 2021). Over the years, various network effects through tangible and intangible cues have been used to promote behaviour change (Sigurdsson et al., 2020). Our study theorises influencer venture success as an evolutionary and network signal that can impact the behaviour of social media followers who subscribe to the content of influencers. Our argument is embedded in the notion that the success influencers achieve and share through video and imagery online has a symbolic effect on followers (Kim et al., 2023). These displays of success evidenced through the acquisition of material things, properties and luxury goods are signals that impact follower behaviour within the online environment (Hazari & Sethna, 2023). Social media has become an important communication and interaction tool that is used by millions all over the world (Singh et al., 2012). Most influencers establish their niche first on social media before expanding to other channels, and this makes social media one of the competencies that influencers develop to create impact (Hilmelboim & Golan, 2023; Gu et al., 2024). The signalling effect of influencer venture success can trigger followers to develop interest, especially in the content that influencers share (Tafesse & Wood, 2021). Through influencers, individuals are now able to gain access to specialised knowledge that contributes to overall improvement in life (Hudders et al., 2021; Enke & Borchers, 2021). Based on the above discussions, the following hypothesis is advanced:

H₄:Influencer venture success positively and significantly predicts social media learning behaviour.

Social Media Learning Behaviour and Cyber-Entrepreneurial Intentions

Previous authors have attempted to establish the link between social media use and entrepreneurial intentions (Huang & Zhang, 2020; Abdelfattah et al., 2022). The use of social media by consumers facilitates knowledge acquisition and sharing behaviour, a phenomenon that reflects the signalling timeline propounded by Connelly et al. (2011).

Per the social network structure advanced by Friedkin and Johnsen (1990), individuals share content online which facilitates learning by others. Social media therefore represents a signalling environment that facilitates learning (Haenlein et al., 2020). The extant literature has revealed that social media use predicts entrepreneurial intention (Chakraborty & Biswal, 2023; Shi et al., 2024), and this effect forms the basis for the argument proffered by this study in relation to the effect of social media learning behaviour on cyber entrepreneurial intentions. Individuals who indulge in social media learning are more likely to form cyber entrepreneurial intentions than those who do not (Do et al., 2020; Mir et al., 2023). Recently, Al Halbusi et al.’s (2023) study examined the role of social media in the formation of e-entrepreneurial intentions and confirmed the vital role social media plays in the formation of entrepreneurial intentions. Judging from such evidence, this study finds ample reason to propose the following hypothesis:

H₅: Social media learning behaviour positively and significantly predicts cyber entrepreneurial intentions.

Mediating Role of Self-Efficacy

Self-efficacy indubitably is instrumental in the formation of entrepreneurial intentions (Rosique-Blasco et al., 2018). Over the years, a large body of evidence has proved this assertion to be true as scholars have established the positive and significant effects of self-efficacy in the formation of behavioural intentions (Piperopoulos & Dimov, 2015). Perceived behavioural control has been deconstructed into two components namely: self-efficacy and controllability (Ajzen, 2002), thus making it logical to construe the effect of self-efficacy on behavioural intentions. Significantly, there are copious volume of studies that have tested for the mediating effect of self-efficacy and found it to be suitable in connecting predictors to behavioural intentions, especially within the domain of entrepreneurship (Taneja et al., 2024). The studies by Mishra and Singh (2024), and Otache et al. (2024) are among the few recent studies that have confirmed the mediating effect of self-efficacy. In view of this, this study makes the following proposition:

H₆: Self-efficacy mediates the relationship between influencer venture success and cyber-entrepreneurial intentions

Mediating Role of Social Media Learning Behaviour

Social media’s role as a mediating variable in entrepreneurial-related studies has received some attention (Pekkala et al., 2022). Social media has been found to facilitate learning behaviour among consumers and has mediated various relationships between entrepreneurial-related predictors and outcomes (Susanto et al., 2023). For example, Do et al. (2020) tested the mediating effect of social media acceptance on the relationship between entrepreneurial personality and entrepreneurial intention. Their study revealed that social media partially mediated the relationship between entrepreneurial personality and intention. Equally, the study by Wibowo et al. (2023) found social media to partially mediate the relationship between entrepreneurial education and entrepreneurial intention. An individual’s ability to use social media for acquisition of knowledge is a signal that implies a willingness to explore new possibilities.

Thus, we theorise social media learning behaviour as an important individual signal that can facilitate the effect of influencer venture success on cyber entrepreneurial intentions. After all, in the organisational context, previous studies have confirmed the role of learning capabilities as a mediator between firm related antecedents and entrepreneurial intentions (Tang et al., 2024). Thus, our study proposes that a similar effect can be possible in an individual context. In view of the above, the following hypothesis is proposed:

H₇: Social media learning behaviour mediates the relationship between influencer venture success and cyber-entrepreneurial intentions

Methodology

A quantitative approach featuring a survey design was used to collect primary data from three hundred and fifty (350) college students from the University of Professional Studies Accra (See Kosiba et al., 2022). The study sought to test the effects of influencer venture success on the cyber entrepreneurial intentions of college students. A questionnaire was developed to measure the constructs in a conceptual model. Before the administration of questionnaires, a pilot test with thirty (30) students was conducted to assess face and content validity as recommended by various scholars (Soori, 2024). This led to the refinement of the instrument, with the final instrument comprising 21 items measuring the four (4) constructs. Five (5) items were developed to measure influencer venture success, whilst five (5) items measuring social media learning behaviour were adapted from Khan and Khan (2019) and Asghar et al., (2023). Self-efficacy was measured using five (5) items adopted from Chang et al. (2020). Cyber entrepreneurial intentions were measured using six (6) items adopted from Vafaei-Zadeh et al. (2023). Voluntary sampling was used in selecting respondents, and out of the three hundred and fifty (350) questionnaires administered, three hundred and forty-seven (347) were retrieved, representing a 99.1% retrieval rate. The data was analysed using SPSS version 28 and AMOS 28 software.

Results

This study sought to ensure that there were no issues with common method bias or variance. As a result, a few measures and tests were undertaken. Respondents were not given any indication of which of the variables were independent or dependent variables (Podsakoff et al., 2003; Kock et al., 2021). We conducted a 3-stage SEM analysis using AMOS 28 software.

The confirmatory factor analysis was used to assess unidimensionality and examine whether the hypothesised model fitted the actual data (Hair et al., 2019; Hair Jr et al., 2021). An initial twenty-one (21) items were modelled using the Maximum Likelihood estimation technique. After a few iterations, the final measurement model yielded an output of eighteen (18) items representing the four (4) constructs. Three (3) items were deleted to improve model fitness. Two items (SMLB3; SMLB4) from social media learning behaviour and one item (CEI4) from cyber entrepreneurial intentions were deleted respectively. The internal consistency of scale items was also assessed using the factor loadings, Cronbach alpha (CA) and composite reliability (CR).

Table 2 reveals the values of the factor loadings ranged from 0.785 to 0.944, thereby confirming good indicator reliability. Similarly, the values for the Cronbach alpha ranged between 0.914 to 0.942 suggesting that the constructs had a very high degree of reliability. The CR values ranged from 0.882 to 0.948 also demonstrating that the scale items were robust and had good internal consistency. The average variance extracted (AVE) was used to check for convergent validity. The AVE results displayed in Table 2 ranged from 0.704 to 0.784, exceeding the minimum threshold of 0.50 proposed by Fornell and Larcker (1981) and thereby confirming convergent validity.

Table 2 CFA Results for Final Measurement Model
Construct	Mean	Standard Deviation	Factor Loadings	T-value	CR	AVE	CA
Influencer Venture Success IVS1 IVS2 IVS3 IVS4 IVS5	4.33 4.39 4.39 4.37 4.23	.964 .993 .985 1.022 1.094	.857 .944 .928 .885 .806	Fixed 25.859 24.977 22.690 19.113	0.948	0.784	.942
Self-Efficacy SE1 SE2 SE3 SE4 SE5	4.29 4.10 3.96 3.96 3.99	1.085 1.106 1.102 1.078 1.125	.816 .826 .841 .870 .839	Fixed 18.022 18.493 19.456 18.434	0.922	0.704	.920
Social Media Learning Behaviour SMLB1 SMLB2 SMLB5	3.452 3.366 4.098	1.089 1.138 .933	.785 .925 .821	Fixed 18.256 16.495	0.882	0.715	.914
Cyber Entrepreneurial Intentions CE11 CEI2 CEI3 CEI5 CEI6	4.09 4.15 4.09 3.99 4.12	1.152 1.092 1.096 1.175 1.095	.908 .917 .901 .760 .832	Fixed 27.853 26.624 18.522 22.082	0.937	0.749	.937

The square root of the AVEs were also evaluated to ascertain whether discriminant validity had been achieved. Based on the results in the AVE values extracted were greater than the inter-item correlation. Discriminant validity was therefore also achieved, confirming the satisfactory nature of the measurement items.

NB: INVS= Influencer Venture Success; SEFF= Self Efficacy; SMLB= Social Media Learning Behaviour; CYBIN= Cyber Entrepreneurial Intentions

Structural Model Assessment and Hypothesis Testing

The structural model was analysed to examine the hypothesised paths. From the results obtained, influencer venture success positively and significantly impacted on college student cyber entrepreneurial intentions (β= 0.68, p <0.001). The model’s explanatory power was 47% when the effect of influencer venture success was tested on the dependent variable. However, with the presence of the mediating variable self-efficacy, the R2 was 55%, indicating that the model explained 55% of the variance in cyber entrepreneurial intentions. The results further indicated that influencer venture success has a positive and significant effect on both self-efficacy (β= 0.69, p< 0.001) and social media learning behaviour (β= 0.55, p< 0.001). Further, self-efficacy (β=0.38, p<0.001) and social media learning behaviour (β= 0.20, p<0.001) also positively and significantly impact cyber entrepreneurial intentions as presented in Table 3. Thus, hypotheses H1 to H5 were all supported.

Table 3 Results of Hypothesised Relationships
Hypotheses	Structural Paths	Β Estimate	T-value	p-value	R2	Results
H1	IVS → CEI	.68	17.359	0.000***	.47	Supported
H2	IVS → Self Efficacy	.69	17.673	0.000***	.47	Supported
H3	Self Efficacy → CEI	.38	7.649	0.000***		Supported
H4	IVS → SMLB	.55	12.181	0.000***	.30	Supported
H5	SMLB → CEI	.20	4.478	0.000***		Supported

Testing the mediating role of self-efficacy and social media learning behaviour

To test H6 and H7, the bootstrapping of specific indirect effects was conducted, as recommended (Hayes, 2009; Hayes & Preacher, 2010) proposes. Table 3 reveals that both specific indirect effects (through self-efficacy and social media learning behaviour) are positive and significant. Therefore, self-efficacy mediates the relationship between influencer venture success and cyber entrepreneurial intentions. These mediation effects are partial because the direct effect is significant (β=0.68, p<0.001). The indirect effect is stronger through self-efficacy (β=0.263; p<0.001) than social media learning behaviour (β= 0.112; p<0.001). Table 4 provides a summary of these results.

Table 4 Results of Mediation Analysis
H	Relationships	Direct without Mediator	Direct with Mediator	Indirect Effect	Results	Outcome
H6	IVS → SEFF → CEI	0.68(***)	0.42(***)	0.263(0.001)	Partial	Supported
H7	IVS → SMLB → CEI	0.68(***)	0.57(***)	0.112(0.001)	Partial	Supported

Discussion

This study examined how influencer venture success (IVS) affects followers’ intentions to pursue cyber entrepreneurship. Findings show that IVS has a positive and significant direct effect on cyber entrepreneurial intentions, suggesting that influencers’ business success—online or offline—increases followers' likelihood of pursuing similar ventures. From an evolutionary theory perspective, IVS functions as a signal influencing follower behavior, aligning with prior research linking influencer lifestyles to follower intentions (Jin et al., 2019; Sokolova & Pereze, 2021; Cabeza-Ramirez et al., 2022).

Secondly, results provide empirical evidence that IVS enhances social media learning behavior among college students. Influencers' success encourages followers to engage in knowledge acquisition and sharing, improving their ability to use social media. This aligns with studies identifying influencers as digital educators (Kim et al., 2023; Hsieh, 2023; Taddeo, 2023). Viewed through Friedkin and Johnsen’s (1990) framework, this confirms the influence of network centrality on follower behavior. Social media learning behavior was also found to positively and significantly impact cyber entrepreneurial intentions, echoing previous research on social media’s role in fostering entrepreneurship (Turan & Kara, 2018; Abdelfattah et al., 2022; Chakraborty & Biswal, 2023). Similarly, self-efficacy showed a strong positive effect on cyber entrepreneurial intentions. Individuals confident in their ability to leverage social media for business were more likely to pursue online ventures—consistent with past findings (Chang et al., 2020; Yeh et al., 2021; Al Amimi & Ahmad, 2023; Li, 2024).

Lastly, both social media learning behavior and self-efficacy partially mediated the relationship between IVS and cyber entrepreneurial intentions. This supports Friedkin and Johnsen’s (1990) model, confirming that behaviors within a social network—particularly learning—shape individual decisions. The mediation effects remained statistically significant, affirming their partial influence. Overall, the study demonstrates that IVS is a key predictor of cyber entrepreneurial intentions, with self-efficacy and social media learning behavior acting as important mediators. These findings align with previous research on the mediating role of self-efficacy (Hoang et al., 2020) and social media variables (Fang et al., 2022; Susanto et al., 2023) in entrepreneurial outcomes.

Contributions to Knowledge

The concept of influencer venture success as a concept reflecting the gains made through influencing business which are tangible and visible to followers. Over the past decade, there have been a plethora of studies on influencer marketing and its effects on consumer behaviour. However, apart from the study by Newlands and Fieseler (2020), there has been limited attention on how the success of influencers in their online and other entrepreneurial ventures can contribute to entrepreneurial intentions among followers. Teng et al. (2020) explored how celebrity business ventures appeal to fans and non-fans, but again, the focus of that study was not on how the success of these ventures trigger entrepreneurial intentions. For this reason, this study has made a unique contribution by bringing to the fore the role of influencer venture success in stimulating cyber entrepreneurial intentions among followers, especially college students. Our findings reveal that influencers need not be perceived as negative influences on their followers (Durau, 2022), but rather as agents of change that can influence followers to establish their online businesses.

The growth of influencer marketing has contributed to reducing unemployment by providing creative individuals with viable career opportunities.

The digital revolution, driven by widespread internet and smartphone access, has further enabled participation in cyber entrepreneurship. This study adds to influencer marketing practice by showing its domino effect on consumer behavior—particularly in shaping entrepreneurial intentions.

Conclusions

This study examines the concept of Influencer Venture Success (IVS) and its impact on the cyber entrepreneurial intentions of followers. The study also investigated the roles of social media learning behavior and self-efficacy among college students in a developing economy. Results show that IVS significantly and positively influences cyber entrepreneurial intentions. Both social media learning behavior and self-efficacy were also found to have a positive effect. These findings support the study’s core proposition: that the business success of influencers can inspire similar entrepreneurial aspirations among followers. The study concludes that influencer marketing extends beyond driving consumer purchases—it can also foster entrepreneurial behavior, particularly in the context of cyber entrepreneurship. Given the widespread availability and accessibility of social media, college students are well-positioned to pursue digital ventures. Ultimately, IVS emerges as a significant predictor of cyber entrepreneurial intentions among this demographic.

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Received: 27-Jun-2025, Manuscript No. AMSJ-25-16027; Editor assigned: 28-Jun-2025, PreQC No. AMSJ-25-16027(PQ); Reviewed: 09- Aug-2025, QC No. AMSJ-25-16027; Revised: 12-Aug-2025, Manuscript No. AMSJ-25-16027(R); Published: 19-Aug-2025