This study aims to examine the influence of short-form social media reels on shaping entrepreneurial intentions within the hospitality SME sector.
This study examines the relationships between destination telepresence, short reels and entrepreneurial intention using the Stimulus-Organism-Response framework and telepresence theory. An online survey of 631 short reel viewers in Italy (e.g. Facebook, Instagram and TikTok) was analyzed through structural equation modeling.
Results reveal that telepresence, attitudes toward short reels, perceived informativeness and vividness significantly enhance utilitarian value, which positively influences entrepreneurial intention. These findings underscore the importance of immersive, vivid and informative short reels in shaping entrepreneurial attitudes and behaviors.
By highlighting the role of realistic and engaging content, the study provides actionable insights for policymakers, researchers and practitioners in leveraging short reels for hospitality marketing and fostering nascent entrepreneurial activities in the hospitality sector.
1. Introduction
The hospitality industry, dominated by SMEs, plays a pivotal role in Italy’s tourism economy (Del Chiappa and Rashidin, 2024) but has faced disruptions due to the global downturn and COVID-19 (Della Corte et al., 2022). These challenges accelerated the adoption of Industry 4.0 technologies, including AI, IoT, blockchain and automation, reshaping business models and supporting SME revitalization (Javaid et al., 2022). Digital platforms have facilitated innovation, online learning and remote collaboration (Shahriar et al., 2022). Among these, social media, particularly short-form video platforms like TikTok, Instagram Reels and Facebook Shorts, has emerged as a powerful influencer of consumer behavior and entrepreneurship (Ong and Toh, 2023; Rashidin et al., 2025). While digital marketing broadly targets business outcomes (Ahmed et al., 2025), short-form videos offer visually engaging, fast-paced content geared toward attention and engagement (Ong and Toh, 2023). Influencers use them to promote destinations, cultural experiences and entrepreneurial ventures (Omeish et al., 2024). These videos integrate entertainment and information, shaping perceptions and behaviors (Pinto, 2015). Though social media’s role in consumer behavior and knowledge sharing is established (Kothari et al., 2025; Riaz et al., 2024), the influence of short reels on entrepreneurial intent in tourism remains underexplored (Cifci and Cetin, 2024; Islam et al., 2025).
To fill this gap, our research investigates the influence of short-form tourism advertisements on key psychological and perceptual factors, specifically telepresence, attitudes, perceived vividness, informativeness, and utilitarian value and how these factors collectively shape entrepreneurial intentions among hospitality SMEs in Italy. However, to validate our conceptual model, we integrate three theoretical frameworks: the Stimulus-Organism-Response (SOR) model, Telepresence Theory and the Destination Advertising Response (DAR) model. This integration offers a comprehensive framework wherein telepresence serves as the primary stimulus, organismic emotional (attitudes, vividness) and cognitive (informativeness, utilitarian value) responses that mediate entrepreneurial intention. This dual-path mediation provides a nuanced understanding of how immersive advertising stimulates entrepreneurial engagement. While previous research connects digital content to travel intentions (Liu et al., 2024; Ying et al., 2021), our study uniquely examines its influence on entrepreneurship in the European hospitality SME context.
Grounded in SOR theory, advertising content acts as the stimulus (e.g. telepresence), eliciting cognitive appraisals (informativeness, utilitarian value, attitudes) and emotional responses that collectively shape entrepreneurial intention. This study focuses on Italy’s hospitality SMEs to explore how short-form social media videos (e.g. TikTok, Instagram Reels) influence perceived vividness, telepresence, attitudes and entrepreneurial outcomes (Qiu et al., 2023). Integrating the SOR, DAR and Telepresence frameworks, the research offers insights into how digital content can drive audience engagement and entrepreneurial decision-making. The findings contribute to the digital entrepreneurship literature and offer practical guidance for destination marketers and hospitality entrepreneurs seeking to harness the power of immersive short-reels content.
2. Theoretical background and hypothesis development
2.1 Stimulus–organism–response and telepresence with DAR
The SOR framework explains behavior by illustrating how external stimuli evoke internal cognitive and emotional states which lead to influence behavioral responses (Mehrabian and Russell, 1974; Taheri et al., 2020). Within this model, stimuli initiate reactions, the organism processes internal states (e.g. emotions, experiences), and responses reflect behavioral outcomes (Vieira, 2013). SOR theory is widely applied in technology-related research to investigate behavioral intentions (Zhou et al., 2024; Vatankhah et al., 2023). Telepresence theory complements this by suggesting that immersive digital experiences (e.g., virtual tours or social media reels) intensify emotional and cognitive engagement, influencing attitudes and entrepreneurial intent (Steuer, 1992). Similarly, the DAR model emphasizes how vivid imagery, emotional appeal and informativeness shape tourism-related decisions (Park et al., 2012). In our study integrates SOR, Telepresence and DAR Model to explain how immersive content influences decision-making in technology-mediated entrepreneurial contexts.
This research, telepresence experiences with short-form reels act as the stimulus, shaping attitudes (Lim and Childs, 2020) perceived vividness (Kim and Ko, 2019) informativeness and utilitarian value (Overby and Lee, 2006), which lead to influence entrepreneurial startup decision. However, traditional models, e.g. Unified Theory of Acceptance and Use of Technology (UTAUT), primarily address cognitive aspects but fail to investigate the emotional and psychological influences (Bayaga and Du Plessis, 2023). Similarly, the Technology Acceptance Model (TAM) overlooks emotional and ethical considerations (Mustofa et al., 2025), while the Theory of Planned Behavior and Gamification theories struggle to account for emotions and spontaneous decisions in consumer behavior (Hagger and Hamilton, 2025; Yang et al., 2024). In contrast, our integrated model, combining SOR, DAR and Telepresence theory, offers a more comprehensive framework for understanding entrepreneurial behavior in digital context. These integrated models connect environmental stimuli (short reels) to cognitive and emotional responses (attitudes, vividness, informativeness, utilitarian value), which drive entrepreneurial intentions. This framework effectively explains how immersive digital content influences decision-making in technology-mediated hospitality contexts.
2.2 Social reels and entrepreneurial intention
Short reels commonly featured on social media, e.g. Facebook, Instagram and TikTok. Typically, last under one minute and have emerged as powerful marketing tools, emphasizing locations, attracting business advertising and experiences in a visually engaging and easily useful format for potential entrepreneurs (Ahmed, 2023). Social media usage reflects individual motives and socio-psychological factors, while also supporting the exchange of entrepreneurial ideas and information (Menon, 2022). The widespread presence of short reels on platforms such as Facebook and Instagram highlights their role in shaping modern business perceptions and enhancing entrepreneurial decision-making (Noor and Zafar, 2024). This study emphasizes the emotional resonance, immersive features of short videos, thereby reflect emerging entrepreneurial intention (Dong and Bao, 2024). Moreover, Short reels play a critical role in promoting business interest, enabling personalized content creation and enhancing telepresence and informativeness. These elements influence entrepreneurial decision-making and offer valuable insights for engaging viewers within digital marketing and business environments (Sharma and Arora, 2024; Dias et al., 2022)
2.3 Utilitarian value
Utilitarian value, defined as the evaluation of functional benefits and risks which plays a key role in behavioral and purchase decisions (Vlassi et al., 2024). It involves systematic assessment of product, service and price attributes, exerting stronger influence than hedonic value on perceived benefits, risks and decision outcomes (Longoni and Cian, 2020; Prebensen and Rosengren, 2016). Rooted in cognitive evaluations like “value for money” (Voss et al., 2003) and convenience (To et al., 2007), utilitarian value enables users to compare merchants, assess price-quality ratios and gather business insights from social media reels (Álvarez-Monzoncillo, 2022). While linked to extrinsic motivations (Levesque et al., 2010), its cognitive orientation emphasizes its primacy in this study.
2.4 Effect of telepresence on attitudes toward short reels, perceived vividness, perceived informativeness, utilitarian value and entrepreneurial intention
Telepresence theory examines the perception of existence inside a virtual environment (Steuer, 1992). Previous studies have demonstrated that telepresence is essential in digital destination marketing and experience of being physically present in a domain through a communication medium, while present refers to being in the physical world (Saleem et al., 2024). Telepresence refers to the extent of user experience that enhances the feeling of presence through social reels. Furthermore, a recent study has examined users’ behavioral intention under the framework of presence theory (Wei et al., 2018). The inclusion of comprehensive narrative descriptions in short video productions facilitates the development of a sense of presence among viewers (Wu and Ding, 2023). Our research investigates how presence forms perceived vividness, perceived informativeness, utilitarian value and entrepreneurial intention. Therefore, telepresence has been shown to positively influence perceived vividness in the study of virtual reality experience (Jafar et al., 2024). Within the realm of this research, investigators have viewed telepresence as a catalyst for fostering a positive involvement on perceived informativeness (Choi et al., 2015), finding that a greater degree of telepresence results in increased levels of perceived vividness and perceived informativeness (Coyle and Thorson, 2001). In addition, telepresence enhances product value (Nah et al., 2011) and experiential quality, influencing startup or behavioral intentions (Latifi et al., 2024). Utilitarian values positively impact users’ entrepreneurial intentions (Fauzi, 2023). While prior research has predominantly focused on the telepresence–behavioral intention relationship, with little attention given to the impact of telepresence on attitude, perceived vividness, perceived informativeness and utilitarian value. According to Fara and Hartono (2024) and Othman et al. (2022), the experience of telepresence affects user perception of utilitarian value and facilitates entrepreneurial education for becoming an entrepreneur. Thus:
Telepresence has a positive influence on attitudes toward short reels.
Telepresence has a positive influence on perceived vividness.
Telepresence has a positive influence on perceived informativeness.
Telepresence has a positive influence on utilitarian value.
Telepresence has a positive influence on entrepreneurial intention.
2.5 Effect of attitude toward short reels on utilitarian value and entrepreneurship intention
In business research, examining users’ attitudes toward short reels – particularly within SMEs – reveals implications for business planning and user behavior (Shahbaznezhad et al., 2020). Positive attitudes reflects viewers’ perceptions, with engagement in visual content influencing both perceived utilitarian value (Ayoubi and Sadiqi, 2024) and entrepreneurial intentions (Cetin et al., 2022). Researchers have highlighted the significance of understanding how viewers’ attitudes toward short reels affect their information processing, emotional responses and behavioral intentions concerning business activities. Previous research on the impact of short reels on users’ intentions indicated that attitude, perceived vividness and informativeness lead to user utilitarian value (Yao and Shao, 2019). Fauzi (2023) examine how attitudes toward behaviors are influenced by past experiences. Positive experience strengthens relationships and enhances entrepreneurial intentions (Cetin et al., 2022). Besides, utilitarian value can be defined as an overall judgement of functional benefits and risk (Overby and Lee, 2006). Positive attitudes influence entrepreneur’s mental image and lead to new entrepreneurial intention (Sharifi-Tehrani, 2022). Thus:
Attitude toward short reels has a positive influence on utilitarian value.
Attitude toward short reels has a positive influence on entrepreneurship intention.
2.6 Effect of perceived vividness on utilitarian value and entrepreneurship intention
According to Steuer (1992), “vividness refers to the degree to which mediated environments can communicate information to users’ senses”. He categorized it into two dimensions: sensory width (e.g. continuous presentation); and depth (e.g. resolution of each channel). Continuous presentations refer to the advertisement of products, services or businesses globally through social media reels, which influence the emergence of new entrepreneurs (Singh, 2024). The breadth and depth of information in continuous social reels facilitate sensory and social immersion (Hwang et al., 2011) and enhance the richness of the experience with a company, thus increasing vividness. Previous research found that social media creates a vivid and mediated environment that influences users to take initiative and increases the attractiveness of using reels (Zhou, 2024). However, satisfaction and attraction boost an individual’s conscious mindset, encouraging them to start a new venture or establish new entrepreneurship values (Erpe and Kotnik, 2022). According to Mehrabioun (2023), in-depth continuous information assists users in building self-belief and trust in a particular event, which subsequently leads to a higher utilitarian value. Consumers are influenced by favorable product information in social media advertisements, which in turn positively impacts their decision to become new entrepreneurs. Thus:
Vividness has a significant impact on utilitarian value.
Vividness has a significant impact on entrepreneurship intention.
2.7 Effect of perceived informativeness on utilitarian value and entrepreneurship intention
Continuous destination and product reels have their characteristic convenience and entertainment value. The playful presentation of information is associated with enhanced utilitarian value (Hsu et al., 2021), offering enough information about the destination or business to allow a thorough evaluation and development of the business attributes and mental satisfaction (e.g., benefit) (Erpe and Kotnik, 2022). When reels provide relevant, sufficient and correct information about activities, lodging and transportation, users save time and effort in searching for information, and they are pleased with the company’s prospective offering (Kolvereid and Isaksen, 2005). Informativeness encourages users’ reasonable judgement of the tentative entrepreneurship intention, allowing them to make more efficient decisions (Chen and Liu, 2024). Consequently, the authors propose that higher perceived informativeness will positively affect users’ utilitarian value. Thus:
Perceived informativeness has a positive influence on users’ utilitarian value.
Perceived informativeness has a positive influence on users’ entrepreneurship intention.
2.8 Effect of utilitarian value on behavioral decisions
Utilitarian value reflects users’ evaluations of a product or service’s functional benefits (Hsu et al., 2021), shaped through cognitive and affective assessments of their experiences (Rodríguez-Ardura et al., 2023). These evaluations generate emotional responses based on how well outcomes align with prior expectations (Phillips and Baumgartner, 2002). In the context of business-oriented short reels, examining how telepresence, attitude, vividness and informativeness contribute to mental satisfaction (e.g. perceived benefits) helps clarify their influence on entrepreneurial intentions, revealing the interaction between psychological drivers, experiential content and business decision-making (Dabbous et al., 2023). High-quality information and user experiences further enhance psychological benefits and motivate individuals to pursue entrepreneurship (Xie et al., 2021). Thus:
Utilitarian value has a positive influence on entrepreneurial intentions.
2.9 Indirect effects
This study investigates dual mediations within the Destination Advertising Response (DAR) model, emphasizing both cognitive and emotional responses drawn though advertising (Park et al., 2012). It focusses on telepresence, attitude, perceived vividness, informativeness, utilitarian value and behavioral decision-making (Vlassi et al., 2024). The dual mediation hypothesis suggests that advertising enhances user engagement and significantly shapes decision-making though influencing both cognitive and emotional responses (Vieira, 2013). Stienmetz et al. (2013) highlight the decision-making stage as essential in shaping attitudes toward advertisements. This hypothesis emphasizes the interplay between informational processing (cognitive) and emotional engagement which provides a holistic understanding of how advertising impacts behavior (Vlassi et al., 2024). In digital media context, dual mediation explains how elements such telepresence, vividness and perceived utilitarian value contribute to shaping entrepreneurial intentions. Social short-form videos play as a key driver in this process. Short-reels video promotes audience interaction through enhanced telepresence (Nah et al., 2011), improving information visualization and increasing perceived vividness all of which influence user attitudes and engagement (Dong and Bao, 2024). Moreover, utilitarian value emphasizes the long-term benefits of entrepreneurship such as equity growth, financial stability and personal satisfaction which collectively enhance motivation to engage in entrepreneurial activities (Latifi et al., 2024). Therefore, understanding these factors provides deeper insights into the mechanisms driving advertising effectiveness and consumer decision-making. Figure 1 presents an integrated framework that depicts the interconnections among the key variables. Thus:
The conceptual framework is divided into sections labelled S, O, and R. Telepresence is placed under S and connects to three constructs: attitude toward reels, perceived vividness, and perceived informativeness. These paths are labelled H1, H2, and H3. A direct path labelled H4 connects telepresence to utilitarian value. Attitude toward reels, perceived vividness, and perceived informativeness each connect to utilitarian value with paths labelled H6, H7, and H8. Attitude toward reels also connects directly to entrepreneurial intention with path H9. Utilitarian value influences entrepreneurial intention with path H12, while perceived informativeness also has a direct path to entrepreneurial intention labelled H11. Finally, utilitarian value and attitude toward reels are shown to have combined influences on entrepreneurial intention through paths H10 and H12.Proposed model
Source: Authors’ own work
The conceptual framework is divided into sections labelled S, O, and R. Telepresence is placed under S and connects to three constructs: attitude toward reels, perceived vividness, and perceived informativeness. These paths are labelled H1, H2, and H3. A direct path labelled H4 connects telepresence to utilitarian value. Attitude toward reels, perceived vividness, and perceived informativeness each connect to utilitarian value with paths labelled H6, H7, and H8. Attitude toward reels also connects directly to entrepreneurial intention with path H9. Utilitarian value influences entrepreneurial intention with path H12, while perceived informativeness also has a direct path to entrepreneurial intention labelled H11. Finally, utilitarian value and attitude toward reels are shown to have combined influences on entrepreneurial intention through paths H10 and H12.Proposed model
Source: Authors’ own work
Telepresence effects attitudes toward social short reels, utilitarian value and entrepreneurial intention.
Telepresence effects perceived vividness, utilitarian value and entrepreneurial intention.
Telepresence effect perceived informativeness, utilitarian value and entrepreneurial intention.
Telepresence influences attitudes toward social short reels and entrepreneurial intentions.
Telepresence effects perceived vividness and entrepreneurial intention.
Telepresence affects perceived informativeness and entrepreneurial intention.
3. Methodology
3.1 Research design, sample profile
Italy was chosen for this study due to its highly active social media environment, with over 91% of the population regularly engaging with platforms like Facebook, Instagram and TikTok (Rashidin et al., 2025). In mid-2025, Italy reported 42.8 million active internet users, with digital trends significantly influencing female fashion bloggers specializing in skincare, clothing and cosmetics (Kemp, 2025). Italy’s global reputation for entrepreneurship and branding, home to iconic labels such as Armani, Gucci, Prada and Fendi, further justifies its selection as a relevant context for studying influencer marketing and entrepreneurial behavior (Leonaviciute et al., 2024; De Cicco et al., 2020). Additionally, Italy remains a top global tourist destination with rich cultural heritage, increasingly shaped by digital content and influencer engagement. With 53.3 million internet users (89.9% penetration) and 42.2 million social media users, YouTube alone reaches 74% of Gen Z (Kemp, 2025), offering fertile ground for tourism entrepreneurs to blend tradition with digital innovation. To calculate the required sample size, G*Power 3.1 was used, based on a medium effect size (0.50), alpha = 0.05, and power = 0.80, yielding a minimum sample of 55 participants (Hair et al., 2017). However, to increase robustness, 665 responses were collected using convenience sampling, suitable for hard-to-reach groups like SME owners active on social media (Sekaran and Bougie, 2016; Etikan et al., 2016). After screening, 631 valid responses remained. The survey was developed in English, translated into Italian, and administered online via SurveyMonkey (Tanner, 2018). Back-translation was conducted and reviewed by bilingual experts for linguistic accuracy (Behr, 2017). A pilot study (April–August 2024) helped refine the instrument’s clarity, cultural relevance and validity through expert feedback. However, this study was conducted in accordance with institutional ethical guidelines/approval for research involving human participants. Prior to data collection, all participants were provided with a comprehensive information sheet outlining the study’s objectives, procedures and their rights as research participants. Informed consent was obtained from all individuals involved in the study with participants explicitly agreeing to the following:
the purpose of the research;
the confidentiality and anonymity of their responses;
the secure storage and restricted use of their data solely for research purposes; and
acknowledgment of minimal risks associated with participation.
However, participants were informed of their right to withdraw from the study at any time without penalty.
3.2 Measurements and survey development
We used validated scales from prior research to measure key variables, including telepresence, psychological distance, attitude, perceived informativeness, vividness, utilitarian value and entrepreneurial intention. The survey had three sections: study introduction, variable items, and demographics. All items were rated on a five-point Likert scale (1 = strongly disagree to 5 = strongly agree). Telepresence was measured using Kim and Ko’s (2019) scale; attitude and vividness from Kim and Kim (2020); informativeness from Holdack et al. (2020); utilitarian value from Overby and Lee (2006); and entrepreneurial intention from Linán and Chen (2009) and Kolvereid and Isaksen (2005). However, demographics included gender, age, education and income.
3.3 Analytical technique
The proposed research model was evaluated using structural equation modelling (SEM) i.e. SPSS AMOS (version 23) (Javed et al., 2021). SEM was chosen for its suitability in exploring complex relationships and providing insights into prediction. It allowed simultaneous assessment of the measurement and structural models, making it suitable for testing the proposed hypotheses and understanding the interplay between the constructs. However, While SEM provides point estimates, PROCESS enables precise estimation of indirect effects with bias-corrected bootstrap confidence intervals, enhancing the robustness and interpretability of mediation results (Hayes, 2013). In addition, PROCESS Model 6 supports multi-step mediation (i.e. serial mediation), which allows testing chains of mediators (e.g. telepresence → attitude → utilitarian value → entrepreneurial intention) that SEM cannot easily model without custom constraints. We used SEM (via AMOS) to validate the measurement model (CFA) and assess overall model fit, while PROCESS provided granular mediation analysis and bootstrapped inference. Using both techniques offers methodological triangulation, thereby increasing the credibility of our findings (Preacher and Hayes, 2008).
4. Analysis
4.1 Sample characteristics of participation
The demographic highest frequencies were observed in the following categories: female (59%) rather than male (41%), and their average age ranged from 24 to 29 years (54%) to 18–23 years (27%), to above 35 (19%). Of cluster members, 58.2% possessed a bachelor’s degree, followed by master’s (28.6%) and doctoral degrees (13.2%). The average monthly income of 39.6% of the sample was between 1,000 and 2,000 euros, followed by below €1,000 (44.2%), €2,000–4,000 (13.4%) and over €4,000 (2.8%) ( Appendix 1).
4.2 Common method variance and ethical approval
The study uses SPSS 25.0 to conduct a Harman single-factor test (Podsakoff and Organ, 1986) on key variables in our conceptual model, including telepresence, attitude toward short reels, perceived vividness, informativeness, utilitarian value and entrepreneurial intention. The total variance is 34.419%, below the recommended threshold of 41%, indicating that common method bias is not contaminating our result. Other results of the ULMC test indicate that the substantive factor loadings (R1) are significant, while most method factor loadings (R2) are not statistically significant. The average substantive variance (R12) is 0.354, and the average method variance (R22) is 0.0047, yielding a ratio of 75:1, well above the 42:1 threshold recommended (Liang et al., 2007). This substantial difference suggests that the variance in our data is primarily driven by substantive constructs rather than measurement artifacts, indicating no significant presence of common method bias ( Appendix 2).
4.3 Measurement model evaluation
We conducted an analysis using version 23 of SPSS AMOS graphics. We conducted confirmatory factor analysis (CFA) to evaluate the reliability and validity of latent variables using a measurement model. The results of the CFA suggest that the model is good [χ2 (650.801), df = 261, χ2/df = 2.493, CFI = 0.927; NFI = 0.919; IFI = 0.910; RMSEA = 0.0321; SRMR = 0.035] (Hu and Bentler, 1999). The various statistical fit indices show that the indicators accurately assess all six latent components. Appendix 3 indicates that all constructs exhibit reliability, as the CR values surpass the 0.70 threshold (Hair et al., 2011). And shows that all construct items’ factor loadings are higher than the minimum level (>0.70), and average variance extracted (AVE) is higher than the recommended cut-off level (Fornell and Larcker, 1981) of >0.50, which means that the scale is convergent (Hair et al., 2010). Table 1 demonstrates that the square root of the AVE is greater at the corresponding row and column values, and that the correlation between the constructs does not exceed 0.85, thus ensuring discriminant validity (Fornell and Larcker, 1981).
Discriminate validity
| # | Constructs | Mean | SD | VIF | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Telepresence | 3.41 | 0.902 | 1.281 | 0.928 | |||||
| 2 | Attitude toward Reels | 3.05 | 1.034 | 1.039 | 0.342** | 0.902 | ||||
| 3 | Perceived vividness | 3.40 | 1.094 | 1.009 | 0.141 | 0.167*** | 0.937 | |||
| 4 | Perceived informativeness | 3.49 | 0.436 | 1.431 | 0.278 | 0.239 | 0.173* | 0.908 | ||
| 5 | Utilitarian value | 3.53 | 1.049 | 1.017 | 0.049* | 0.029** | 0.029 | 0.321** | 0.915 | |
| 6 | Entrepreneurial intention | 3.81 | 1.099 | 1.041 | 0.021 | 0.261 | 0.131* | 0.091** | 0.391** | 0.907 |
| # | Constructs | Mean | 1 | 2 | 3 | 4 | 5 | 6 | ||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Telepresence | 3.41 | 0.902 | 1.281 | 0.928 | |||||
| 2 | Attitude toward Reels | 3.05 | 1.034 | 1.039 | 0.342 | 0.902 | ||||
| 3 | Perceived vividness | 3.40 | 1.094 | 1.009 | 0.141 | 0.167 | 0.937 | |||
| 4 | Perceived informativeness | 3.49 | 0.436 | 1.431 | 0.278 | 0.239 | 0.173 | 0.908 | ||
| 5 | Utilitarian value | 3.53 | 1.049 | 1.017 | 0.049 | 0.029 | 0.029 | 0.321 | 0.915 | |
| 6 | Entrepreneurial intention | 3.81 | 1.099 | 1.041 | 0.021 | 0.261 | 0.131 | 0.091 | 0.391 | 0.907 |
Italic digits in the diagonal are square root of AVE. p < 0.100, *p < 0.050, **p < 0.010, ***p < 0.001
4.4 Structural model fit
We evaluated the model fitness and postulated relationships in the proposed model using the maximum likelihood technique. Numerous statistical indices, including χ2, CFI, AGFI, GFI, IFI, TLI, AGFI, RMSEA and SRMR (Hair et al., 2010), indicate the model’s fitness. Model fit was satisfactory [χ2 (1.429), df = 1, χ2/df = 1.345; AGFI = 0.981; CFI = 0.975; TLI = 0.945; RMSEA = 0.036)]. All fit indices fell within the permissible range of 0.90–1.00. A CFI value of 0.90 or higher is generally considered acceptable, while values above 0.95 indicate excellent model fit. A high CFI, approaching 1, suggests that the model effectively captures the underlying patterns in the data, reflecting a reliable and well-structured model (Schreiber, 2008). Similarly, a lower root mean square error of Approximation (RMSEA) indicates a better fit, with values below 0.06 commonly interpreted as evidence of good model fit. An RMSEA under 0.06 suggests that the model closely approximates the true population structure without overfitting, thereby enhancing interpretability and generalizability.
4.5 Assessment of structural model
The variance inflation factor (VIF) score indicates that all components had VIF scores within the specified range of 3, implying that multicollinearity is not a problem in our data set. The testing of the hypotheses found that telepresence had a significant effect on attitude toward short reels (β = 0.365, t = 6.378, p < 0.001), perceived vividness (β = 0.275, t = 6.194, p < 0.001), perceived informativeness (β = 0.364, t = 4.583, p < 0.001), utilitarian value (β = 0.378, t = 5.638, p < 0.001) and entrepreneurial intention (β = 0.092, t = 1.801, p > 0.553); hence, H1, H2, H3, H4 were accepted, and H5 was not supported (β = 0.092, t = 1.801, p < 0.553). Furthermore, in the case of short reels, attitude toward short reels (β = 0.409, t = 4.519, p < 0.001), perceived vividness (β = 0.326, t = 8.264, p < 0.001) and perceived informativeness (β = 0.285, t = 6.321, p < 0.001) had a significant impact on utilitarian value, supporting H6, H7 and H8. Moreover, attitude toward short reels (β = 0.259, t = 3.428, p < 0.001), vividness (β = 0.220, t = 3.468, p < 0.001) and perceived informativeness (β = 0.462, t = 4.811, p < 0.001) had significant impact on entrepreneurial intention, therefore we accepted H9, H10 and H11. However, H12 was also supported because utilitarian with short reels led to behavioral decisions (entrepreneurial intention) (β = 0.209, t = 5.103, p < 0.001) (Table 2).
Findings of direct path
| Indices | Direct paths | Standardized estimates | t-value | Relationship |
|---|---|---|---|---|
| χ2 (1.429), df = 1, χ2/df = 1.345; AGFI = 0.981; CFI = 0.975; TLI = 0.945; RMSEA = 0.036 | Direct paths | |||
| H1. TEP → ATTR | 0.365 | 6.378 | Supported | |
| H2. TEP → PV | 0.275 | 6.194 | Supported | |
| H3. TEP → PI | 0.364 | 4.583 | Supported | |
| H4. TEP → UT | 0.378 | 5.638 | Supported | |
| H5. TEP → EI | 0.092 | 1.801 | Not supported | |
| H6. ATTR → UT | 0.409 | 4.519 | Supported | |
| H7. PV → UT | 0.326 | 8.264 | Supported | |
| H8.PI → UT | 0.285 | 6.321 | Supported | |
| H9.ATTR → EI | 0.259 | 3.428 | Supported | |
| H10.PV → EI | 0.220 | 3.468 | Supported | |
| H11.PI → EI | 0.462 | 4.811 | Supported | |
| H12.UV → EI | 0.209 | 5.103 | Supported | |
| Indices | Direct paths | Standardized estimates | t-value | Relationship |
|---|---|---|---|---|
| χ2 (1.429), df = 1, χ2/df = 1.345; AGFI = 0.981; CFI = 0.975; TLI = 0.945; RMSEA = 0.036 | Direct paths | |||
| H1. | 0.365 | 6.378 | Supported | |
| H2. | 0.275 | 6.194 | Supported | |
| H3. | 0.364 | 4.583 | Supported | |
| H4. | 0.378 | 5.638 | Supported | |
| H5. | 0.092 | 1.801 | Not supported | |
| H6. | 0.409 | 4.519 | Supported | |
| H7. | 0.326 | 8.264 | Supported | |
| H8. | 0.285 | 6.321 | Supported | |
| H9. | 0.259 | 3.428 | Supported | |
| H10. | 0.220 | 3.468 | Supported | |
| H11. | 0.462 | 4.811 | Supported | |
| H12. | 0.209 | 5.103 | Supported | |
p < 0.553; p < 0.100, *p < 0.050, **p < 0.010, ***p < 0.001
Moreover, by following Cohen (1988) approach, we also assessed the substantive effect size (ƒ2) of research model. The suggested threshold for effect sizes by Cohen (1988) is as follows: small effect is 0.02, medium effect is 0.15 and large effect is 0.35. However, very small effect following Kutner et al. (2005) approach which is below f2 = 0.02 and R2 = 0.01.We found that effect size of TEP → ATTR ƒ2 = 0.407, r2 = 0.289; TEP → PV ƒ2 = 0.384, r2 = 0.277; TEP → PI ƒ2 =0.174, r2 = 0.210; TEP → UT ƒ2 = 0.318, r2 = 0.241; TEP → EI ƒ2 = 0.032, r2 = 0.031; ATTR → UT ƒ2 = 0.305, r2 = 0.234; PV → UT ƒ2 = 0.682, r2 = 0.406; PI → UT ƒ2 = 0.399, r2 = 0.285; ATTR > EI ƒ2 = 0.118, r2 = 0.105; PV → EI ƒ2 = 0.120, r2 = 0.107; PI → EI ƒ2 = 0.232, r2 = 0.189; UV → EI ƒ2 = 0.260, r2 = 0.206. Indirect effect: TEL → ATTR → UT → EI: ƒ2 = 0.002, r2 = 0.002; TEL → PV → UT → EI ƒ2 = 0.017, r2 = 0.017; TEL → PI → UT → EI ƒ2 = 0.004, r2 = 0.004; TEL → ATTR → EI ƒ2 = 0.016, r2 = 0.016; TEL → PV → EI ƒ2 = 0.010, r2 = 0.010; TEL → PI → EI ƒ2 = 0.004, r2 = 0.005.
Mediation analysis was run using PROCESS Model 6 (Hayes, 2013). We took telepresence as independent variable, entrepreneurial intention as the dependent variable, attitude toward reel, perceived vividness, perceived informativeness and utilitarian value as mediators (using 5,000 bootstrap samples) ( Appendix 4). The total effect of telepresence on entrepreneurial intention was significant where TEL → EI (b = 1.0103, SE = 0.075, t = 4.613; p < 0.001). The results showed that the indirect effect of telepresence, attitude toward short reels, utilitarian value and entrepreneurial intention was significant where TEL → ATTR → UT → EI (b = 0.034, SE = 0.065, 95% CI: 0.017, 0.029; p < 0.001), so was the indirect effect of telepresence, perceived vividness, utilitarian value and entrepreneurial intention is TEL → PV → UT → EI (b = 0.037, SE = 0.028, 95% CI: 0.004, 0.027); p < 0.001, so was the indirect effect of telepresence, perceived informativeness, utilitarian value and entrepreneurial intention where TEL → PI → UT → EI (b = 0.031, SE = 0.049, 95% CI: 0.005, 0.018, p < 0.001), so was the indirect effect of telepresence, attitude toward short reels and entrepreneurial intention where TEL → ATTR → EI (b = 0.039, SE = 0.030, 95% CI: 0.002, 0.010), so was the indirect effect of telepresence, perceived vividness and entrepreneurial intention where TEL → PV → EI (b = 0.033, SE = 0.032, 95% CI: 0.003, 0.026), so was the indirect effect of telepresence, perceived informativeness and entrepreneurial intention where TEL → PI → EI (b = 0.029, SE = 0.041, 95% CI: 0.021, 0.019); therefore, we accepted H13a, H13b, H13c, H13d, H13e, H13f. However, the direct effect of telepresence on entrepreneurial intention was insignificant (b = 0.092, SE = 0.463, t = 5.001. p = 0.531).
5. Discussion
The findings offer important insights into the role of telepresence in shaping perceptions of short-reels video content. The strong positive relationship between telepresence and attitudes toward short reels highlights the power of immersive environments in enhancing content engagement. This aligns with prior studies highlighting the role of telepresence in encouraging user interaction with multimedia (Buhalis et al., 2023). Telepresence also shows strong positive associations with both perceived vividness and informativeness which suggests that immersive short reels can simultaneously entertain and inform. The sense of “being there” increases the content’s perceived utilitarian value, especially when relation between entrepreneurial and destination-related narratives (Bagheri et al., 2023). Visually rich narratives generate more immersive content which engage users and foster positive attitudes toward entrepreneurial ventures (To et al., 2007).
Further, positive attitudes toward short reels significantly influence utilitarian value and entrepreneurial intention were reaffirming the role of emotionally engaging content in shaping behavioral outcomes (Vodă and Florea, 2019). The positive relation between vividness and utilitarian value highlights how visual appeal can enhance perceived usefulness, influencing motivation to act. Interestingly, while telepresence increases utilitarian value, it shows a negative relationship with entrepreneurial intention. This may be due to the potential for excess information where highly immersive content, despite being engaging, overwhelms users and raises perceived risk and ultimately lead to decision-making (Chen and Xie, 2008). This study integrates with SOR, Telepresence and DAR theories establishing as a dual-force mechanism where it simultaneously enhances marketing and emotional-cognitive engagement. This emotional digital content has a meaningful impact on SMEs’ marketing effectiveness and entrepreneurial engagement in tourism and hospitality contexts.
However, telepresence enhances emotional engagement, perceived vividness, and informativeness which is key drivers of attitude, utilitarian value and entrepreneurial motivation. Therefore, our findings also highlight the need to manage digital content carefully to prevent cognitive excess which can hamper decision-making. By integrating these insights, businesses can craft more effective, emotionally resonant marketing strategies. This contributes to both academic understanding and practical guidance on how digital media (particularly short reels) can influence entrepreneurial behavior and support sustainable innovation and growth within tourism and hospitality.
6. Conclusion
This study provides key theoretical and practical insights into how social media short reels shape entrepreneurial intentions in tourism and hospitality. By integrating the S-O-R, Telepresence Theory and the DAR model highlights that immersive digital experiences (especially telepresence) trigger organismic responses (vividness, informativeness, utilitarian value and attitudes) that significantly predict entrepreneurial intention. These effects operate through both affective (e.g. vividness, attitudes) and cognitive (e.g. informativeness, utilitarian value) pathways. Our findings extend the S-O-R and DAR models to entrepreneurial contexts and expand Telepresence Theory by linking it to insight of entrepreneurial decision-making. While prior research has focused on travel behavior, this study highlights how short reels can spark entrepreneurial ideation, especially among hospitality SMEs (Buhalis et al., 2023). Practically, the results offer guidance for content creators, destination marketers and SME stakeholders on using emotional storytelling, VR-enhanced visuals and data-driven personalization to drive engagement and inspire entrepreneurial action. Ultimately, short-form digital content is not just a promotional tool but a catalyst for innovation and motivation. When strategically crafted, social reels can support SME growth and foster a more resilient, digitally driven hospitality sector.
6.1 Theoretical implications
This study offers several key theoretical contributions to tourism, hospitality and entrepreneurship research by uncovering how social media short reels influence entrepreneurial intentions among hospitality SME stakeholders. It bridges existing gaps in digital content marketing and entrepreneurship literature through an integrated application of the S-O-R framework, Telepresence Theory and the DAR model.
First, the study positions short-reel videos (e.g. Instagram Reels, TikTok) not merely as promotional tools but as immersive digital experiences that foster entrepreneurial ideation. While prior research has explored social media’s role in branding and consumer engagement, few have investigated its influence of on entrepreneurial behavior through short-reel content (Rashidin et al., 2025; Ahmed et al., 2025). Addressing this gap responds to calls for deeper insight into how digital platforms drive not only consumer responses but also economic development and entrepreneurial emergence (Blanco-González-Tejero et al., 2024). Second, we extend the S-O-R framework by introducing telepresence as a technologically induced stimulus. This deepens the virtual experience and activates organismic responses such as perceived vividness (sensory richness), informativeness (cognitive clarity), attitudes toward reels (evaluative appraisal) and utilitarian value (functional benefit), all of which contribute to the response: entrepreneurial intention (Zhou et al., 2024). This application expands the S-O-R model’s utility beyond consumer behavior into entrepreneurial domains, while also enriching Telepresence Theory with empirical support for its cognitive and affective influence on decision-making.
Third, the study advances the DAR model, traditionally used to explain travel behavior, by demonstrating its applicability to entrepreneurial intention. We empirically validate a dual-path mediation model where both affective (vividness, attitudes) and cognitive (informativeness, utilitarian value) mechanisms jointly influence entrepreneurial action (Stienmetz et al., 2013). This holistic view enhances understanding of how destination-based content inspires entrepreneurial outcomes. Fourth, we introduce time distortion as a novel theoretical mechanism. High telepresence and vividness can cause viewers to lose track of time, which encourages deeper cognitive engagement and mental simulation (Yu et al., 2025). This implicit psychological state encourages entrepreneurial intention which is underexplored in hospitality and entrepreneurship research. Finally, the proposed integrated model links immersive digital marketing with entrepreneurial psychology, advancing discourse on digital entrepreneurship in hospitality. It confirms the role of mediating psychological variables in entrepreneurial decision-making and offers a replicable framework for future research on emerging digital formats in tourism and related sectors.
6.2 Practical implications
This study provides critical insights for tourism and hospitality practitioners aiming to enhance digital engagement and entrepreneurial behavior through short-reel advertisements. The results highlight how elements such as telepresence, attitudes toward content, vividness, informativeness and utilitarian value collectively influence entrepreneurial intention and offering a comprehensive framework for strategic content development (Chong et al., 2024). Practitioners should prioritize immersive storytelling techniques to elevate telepresence. This includes using narrative-driven content with evocative visuals, sensory cues (e.g. ambient sounds, dynamic movement) and interactive features to simulate authentic destination experiences, thereby heightening emotional and sensory engagement (Chang and Suh, 2025). Attitudes toward short-form video content are shaped though both its emotional resonance and perceived relevance.
To influence these attitudes positively, hospitality marketers should focus on producing emotionally compelling reels that emphasize authentic stories which highlight local entrepreneurial journeys, or behind-the-scenes destination narratives. This content strategy cultivates favorable attitudes when aligned with user values and objectives, directly stimulating entrepreneurial ideation. Advancing perceived vividness requires high-resolution visuals, cinematic techniques and immersive technologies such as virtual reality (Zhang et al., 2023). Integrating panoramic views or real-time walkthroughs intensifies mental imagery, subsequently increasing visit intention and entrepreneurial venture engagement. Informativeness plays a pivotal role in shaping user evaluations and behavioral intentions. Reels that deliver clear, concise and relevant information (e.g. details about accommodations, startup costs or tourism infrastructure) equip viewers with the cognitive resources necessary for entrepreneurial planning.
Providing comparative insights into successful hospitality SMEs can further strengthen the perceived informativeness and inspire action (Neupane et al., 2025). Utilitarian value, or the perception of functional benefit, can be elevated through data-driven personalization strategies. By analyzing user interaction data (e.g. viewing time, likes, and engagement patterns) hospitality firms can deliver targeted content aligned with specific interests and decision-making styles. Personalizing short-reel content ensures that users receive high-relevance and high-utility experiences that are more likely to translate into business-oriented intentions.
6.3 Limitations and recommendations
While offering novel insights into telepresence’s impact on business intentions for Italian hospitality SMEs though short-reels video ads (e.g. Facebook, Instagram, TikTok Reels). While study offers valuable insights and several limitations should be acknowledged. First, findings may lack generalizability beyond Italy due to cultural differences affecting digital engagement perceptions. Second, focusing solely on three major platforms limits applicability to emerging or niche channels with distinct user dynamics. Third, examining only short-form video overlooks more immersive technologies like AR, VR and 3D tours. Consequently, future research should validate these results across diverse cultural and regional contexts; assess the effectiveness of short-form video content across a broader range of platforms, including newer social media. Additionally, integrate advanced immersive technologies such as LiDAR in VR to evaluate their comparative impact on user engagement, emotional responses and behavioral intentions within the hospitality sector.
References
Further reading
Appendix 1
Sample characteristics of participants
| Socio-demographic characteristics | (n = 631) | |
|---|---|---|
| Frequency (N) | % | |
| Gender | ||
| Male | 258.7 | 41 |
| Female | 372.3 | 59 |
| Age | ||
| 18–23 | 170.3 | 27 |
| 24–29 | 340.7 | 54 |
| Above 35 | 120 | 19 |
| Qualification | ||
| Graduation | 367.2 | 58.2 |
| Masters | 180.4 | 28.6 |
| PhD | 83.2 | 13.2 |
| Monthly income | ||
| Below 1000 € | 278.9 | 44.2 |
| 1001–2000 € | 249.8 | 39.6 |
| 2001–4000 € | 84.5 | 13.4 |
| Above 4000 € | 17.6 | 2.8 |
| Socio-demographic characteristics | (n = 631) | |
|---|---|---|
| Frequency (N) | % | |
| Gender | ||
| Male | 258.7 | 41 |
| Female | 372.3 | 59 |
| Age | ||
| 18–23 | 170.3 | 27 |
| 24–29 | 340.7 | 54 |
| Above 35 | 120 | 19 |
| Qualification | ||
| Graduation | 367.2 | 58.2 |
| Masters | 180.4 | 28.6 |
| PhD | 83.2 | 13.2 |
| Monthly income | ||
| Below 1000 € | 278.9 | 44.2 |
| 1001–2000 € | 249.8 | 39.6 |
| 2001–4000 € | 84.5 | 13.4 |
| Above 4000 € | 17.6 | 2.8 |
Appendix 2
Analysis of common method bias
| Variables | Factors | Substantive Factor loading (R1) | R12 | Method Factor Loading (R2) | R22 |
|---|---|---|---|---|---|
| Telepresence | TE_1 | 0.911*** | 0.829 | 0.091* | 0.0081 |
| TE_2 | 0.645*** | 0.416 | 0.039*** | 0.0015 | |
| TE_3 | 0.610*** | 0.372 | 0.041** | 0.0050 | |
| Attitude toward Reels | ATT_1 | 0.490*** | 0.240 | −0.038* | −0.0014 |
| ATT_2 | 0.582*** | 0.338 | 0.083** | 0.0068 | |
| ATT_3 | 0.411*** | 0.168 | −0.060* | 0.0036 | |
| ATT_3 | 0.528*** | 0.278 | 0.055 | 0.0030 | |
| Perceived vividness | PV_1 | 0.362*** | 0.131 | 0.090** | 0.0081 |
| PV_2 | 0.579*** | 0.335 | 0.010* | 0.0001 | |
| PV_3 | 0.721*** | 0.519 | 0.067** | 0.0044 | |
| Perceived informativeness | PI_1 | 0.549*** | 0.294 | −0.070* | −0.0049 |
| PI_2 | 0.619*** | 0.383 | −0.030* | 0.0009 | |
| PI_3 | 0.369*** | 0.136 | 0.201*** | 0.040 | |
| Utilitarian value | UT_1 | 0.583*** | 0.339 | 0.070*** | 0.0049 |
| UT_2 | 0.610*** | 0.372 | 0.040* | 0.0016 | |
| UT_3 | 0.682*** | 0.465 | 0.048*** | 0.0023 | |
| UT_4 | 0.530*** | 0.280 | 0.045 | 0.0020 | |
| Entrepreneurial intention | EI_1 | 0.410*** | 0.168 | 0.080 | 0.0064 |
| EI_2 | 0.513*** | 0.263 | 0.039* | 0.0015 | |
| EI_3 | 0.649*** | 0.421 | 0.040 | 0.0016 | |
| EI_4 | 0.834*** | 0.695 | 0.059 | 0.0034 | |
| Average | 0.580 | 0.354 | 0.031 | 0.0047 | |
| Variables | Factors | Substantive Factor loading (R1) | R12 | Method Factor Loading (R2) | R22 |
|---|---|---|---|---|---|
| Telepresence | TE_1 | 0.911*** | 0.829 | 0.091* | 0.0081 |
| TE_2 | 0.645*** | 0.416 | 0.039*** | 0.0015 | |
| TE_3 | 0.610*** | 0.372 | 0.041** | 0.0050 | |
| Attitude toward Reels | ATT_1 | 0.490*** | 0.240 | −0.038* | −0.0014 |
| ATT_2 | 0.582*** | 0.338 | 0.083** | 0.0068 | |
| ATT_3 | 0.411*** | 0.168 | −0.060* | 0.0036 | |
| ATT_3 | 0.528*** | 0.278 | 0.055 | 0.0030 | |
| Perceived vividness | PV_1 | 0.362*** | 0.131 | 0.090** | 0.0081 |
| PV_2 | 0.579*** | 0.335 | 0.010* | 0.0001 | |
| PV_3 | 0.721*** | 0.519 | 0.067** | 0.0044 | |
| Perceived informativeness | PI_1 | 0.549*** | 0.294 | −0.070* | −0.0049 |
| PI_2 | 0.619*** | 0.383 | −0.030* | 0.0009 | |
| PI_3 | 0.369*** | 0.136 | 0.201*** | 0.040 | |
| Utilitarian value | UT_1 | 0.583*** | 0.339 | 0.070*** | 0.0049 |
| UT_2 | 0.610*** | 0.372 | 0.040* | 0.0016 | |
| UT_3 | 0.682*** | 0.465 | 0.048*** | 0.0023 | |
| UT_4 | 0.530*** | 0.280 | 0.045 | 0.0020 | |
| Entrepreneurial intention | EI_1 | 0.410*** | 0.168 | 0.080 | 0.0064 |
| EI_2 | 0.513*** | 0.263 | 0.039* | 0.0015 | |
| EI_3 | 0.649*** | 0.421 | 0.040 | 0.0016 | |
| EI_4 | 0.834*** | 0.695 | 0.059 | 0.0034 | |
| Average | 0.580 | 0.354 | 0.031 | 0.0047 | |
***p < 0.001, **p < 0.01, *p < 0.05
Appendix 3
Statistics of CFA and convergent validity
| Confirmatory factor analysis | ||||
|---|---|---|---|---|
| Statistics | Statements | Items | SFL | Reference |
| CR = 0.950, α = 0.890, AVE = 0.863 | I forgot about my physical location | TE_1 | 0.887*** | Kim and Ko, 2019 |
| I felt like I was in the arena | TE_2 | 0.943*** | ||
| I felt my mind was inside the arena | TE_3 | 0.956*** | ||
| CR = 0.946, α = 0.832, AVE = 0.814 | I believe that the places that appear on reality travel variety programs are good, albeit short reels | ATT_1 | 0.808*** | Kim et al.,2020 |
| Short reels make me believe that the places that appear on reality travel variety programs are good places to do new startup | ATT_2 | 0.949*** | ||
| I like the places that appear on reality travel variety programs | ATT_3 | 0.986*** | ||
| Based on short reels, I find the places featured on reality travel variety programs to be attractive and gather idea for startup | ATT_4 | 0.855*** | ||
| CR = 0.956, α = 0.891, AVE = 0.879 | I thought the sensory information provided by the screen was highly vivid | PV_1 | 0.928*** | Kim and Ko, 2019 |
| I thought the sensory information provided by the screen was highly rich | PV_2 | 0.899*** | ||
| I thought the sensory contents provided by the screen was highly detailed | PV_3 | 0.984*** | ||
| CR = 0.934, α = 0.856, AVE = 0.826 | Short reels provides me with useful information about the travel destination and their new startup idea | PI_1 | 0.982*** | Holdack et al., 2020 |
| Short reels provides information that helps me in my idea of startup decision | PI_2 | 0.856*** | ||
| Short reels provides information to compare different startup | PI_3 | 0.884*** | ||
| CR = 0.954, α = 0.901, AVE = 0.838 | The advertisement of the product and/or services information create trust on new startup | UT_1 | 0.828*** | (Overby and Lee, 2006) |
| When I use social reels, I save time to understand | UT_2 | 0.981*** | ||
| I find what I do (entrepreneurship involvement) feasible | UT_3 | 0.807*** | ||
| To use reels on new ideas, its help me learn about start up | UT_4 | 0.855*** | ||
| CR = 0.949, α = 0.841, AVE = 0.824 | I am willing to do whatever it takes for my idea/project/startup | EI_1 | 0.925*** | Liñán and Chen (2009), Kolvereid and Isaksen (2005) |
| I will make every possible effort to run my idea/project/startup | EI_2 | 0.880*** | ||
| I am determined to create my own startup | EI_3 | 0.955*** | ||
| In one year from now I have the intention to work full time for my idea/project/startup | EI_4 | 0.869*** | ||
| Confirmatory factor analysis | ||||
|---|---|---|---|---|
| Statistics | Statements | Items | Reference | |
| CR = 0.950, α = 0.890, | I forgot about my physical location | TE_1 | 0.887 | |
| I felt like I was in the arena | TE_2 | 0.943 | ||
| I felt my mind was inside the arena | TE_3 | 0.956 | ||
| I believe that the places that appear on reality travel variety programs are good, albeit short reels | ATT_1 | 0.808 | Kim et al.,2020 | |
| Short reels make me believe that the places that appear on reality travel variety programs are good places to do new startup | ATT_2 | 0.949 | ||
| I like the places that appear on reality travel variety programs | ATT_3 | 0.986 | ||
| Based on short reels, I find the places featured on reality travel variety programs to be attractive and gather idea for startup | ATT_4 | 0.855 | ||
| I thought the sensory information provided by the screen was highly vivid | PV_1 | 0.928 | ||
| I thought the sensory information provided by the screen was highly rich | PV_2 | 0.899 | ||
| I thought the sensory contents provided by the screen was highly detailed | PV_3 | 0.984 | ||
| Short reels provides me with useful information about the travel destination and their new startup idea | PI_1 | 0.982 | ||
| Short reels provides information that helps me in my idea of startup decision | PI_2 | 0.856 | ||
| Short reels provides information to compare different startup | PI_3 | 0.884 | ||
| CR = 0.954, α = 0.901, | The advertisement of the product and/or services information create trust on new startup | UT_1 | 0.828 | ( |
| When I use social reels, I save time to understand | UT_2 | 0.981 | ||
| I find what I do (entrepreneurship involvement) feasible | UT_3 | 0.807 | ||
| To use reels on new ideas, its help me learn about start up | UT_4 | 0.855 | ||
| I am willing to do whatever it takes for my idea/project/startup | EI_1 | 0.925 | ||
| I will make every possible effort to run my idea/project/startup | EI_2 | 0.880 | ||
| I am determined to create my own startup | EI_3 | 0.955 | ||
| In one year from now I have the intention to work full time for my idea/project/startup | EI_4 | 0.869 | ||
SFL = standardized factor loadings, CR = composite reliability, AVE = average variance extracted, α = Cronbach’s alpha; telepresnce(TE), attitude toward reel (ATT), perceived vividness (PV), perceived informativeness (PI) utilitarian value (UT), entrepreneurial value (EI). ***p < 0.01, **p < 0.05, *p < 0.1
Appendix 4
Findings of indirect effects
| Indirect paths | Standardized indirect effect | Boot SE | Bias Corrected CI, 95% | Relationship |
|---|---|---|---|---|
| Total effect (direct and indirect) | ||||
| TLE → EI | 1.103*** | 0.075 | t: 4.613 | <0.001 |
| Indirect effect | ||||
| H13a.TEL → ATTR → UT → EI | 0.034*** | 0.065 | [0.017, 0.029] | Supported |
| H13b.TEL → PV → UT → EI | 0.037*** | 0.028 | [0.004, 0.027] | Supported |
| H13c.TEL → PI → UT → EI | 0.031*** | 0.049 | [0.005, 0.018] | Supported |
| H13d.TEL → ATTR → EI | 0.039*** | 0.030 | [0.002, 0.010] | Supported |
| H13e.TEL → PV → EI | 0.033*** | 0.032 | [0.003, 0.026] | Supported |
| H13f.TEL → PI → EI | 0.029*** | 0.041 | [0.021, 0.019] | Supported |
| Direct effect | ||||
| TLE → EI | 0.092 | 0.463 | [0.064, 0.052] | <0.554 |
| Indirect paths | Standardized indirect effect | Boot | Bias Corrected CI, 95% | Relationship |
|---|---|---|---|---|
| Total effect (direct and indirect) | ||||
| 1.103*** | 0.075 | t: 4.613 | <0.001 | |
| Indirect effect | ||||
| H13a. | 0.034 | 0.065 | [0.017, 0.029] | Supported |
| H13b. | 0.037 | 0.028 | [0.004, 0.027] | Supported |
| H13c. | 0.031 | 0.049 | [0.005, 0.018] | Supported |
| H13d. | 0.039 | 0.030 | [0.002, 0.010] | Supported |
| H13e. | 0.033 | 0.032 | [0.003, 0.026] | Supported |
| H13f. | 0.029 | 0.041 | [0.021, 0.019] | Supported |
| Direct effect | ||||
| 0.092 | 0.463 | [0.064, 0.052] | <0.554 | |
The PROCESS path TLE → EI indicates the total effect, while the other TLE → EI reflects the direct effect Appendix 4. Both effects were non-significant, confirming that H5 is not supported in either the structural or mediation model. p < 0.553. p < 0.100, *p < 0.050, **p < 0.010, ***p < 0.001

