Abstract
Purpose
This study aims to understand pathways to success for food video bloggers (food vloggers) by identifying the drivers of positive reception among audiences. It examines how entertainment, information and interaction values affect attitudes toward food videos and vloggers. Additionally, it investigates the potential for product placement by studying the effects of attitudes toward food videos and vloggers on consumers’ behavioral intention regarding purchasing featured food ingredients.
Design/methodology/approach
An integrated model informed by theories (uses and gratification and stimulus-organism-response) was developed. An online survey was administered to 339 Vietnamese social media users. The data were analyzed using partial least square structural equation modeling (PLS-SEM).
Findings
The results show that food videos’ entertainment and information value positively impact the attitude toward food videos. However, the interaction value does not have a significant impact. All three values (entertainment value, information value and interaction) impact the attitude toward food vloggers. Both attitudes significantly influence purchase intention, showing that there is a pathway to product placement. The frequency of social media use can moderate these relationships, with a negative effect on the attitude toward food videos and a positive effect on the attitude toward food vloggers.
Originality/value
These findings provide insights into vlogger success pathways, not only in terms of audience reception but also in terms of product placement. This study offers comprehensive suggestions on pathways for success that are interesting for vloggers, food business operators, restaurant managers and audiences on how to design effective food videos and potentially encourage consumer purchases. These pathways can also be valuable for other behaviors, such as food safety advice and food waste reduction.
Keywords
Citation
Nguyen, T.M.N., Le, B.N., Leenders, M.A.A.M. and Poolsawat, P. (2024), "Food vloggers and their content: understanding pathways to consumer impact and purchase intentions", Journal of Trade Science, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JTS-01-2024-0005
Publisher
:Emerald Publishing Limited
Copyright © 2024, Thi My Nguyet Nguyen, Bao Ngoc Le, Mark A.A.M. Leenders and Pimpika Poolsawat
License
Published in Journal of Trade Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
The widespread availability of the Internet and the prevalence of social networking sites have empowered consumers to access information and take control of their shopping experiences (Agnihotri, 2020). Social media platforms have created an environment where users can generate and disseminate content through blogs, influencing fellow consumers and providing valuable insights about products or services. This user-generated content, called electronic word-of-mouth (eWOM), is used by companies for advertising (Smith et al., 2012) and is highly influential in guiding purchasing decisions (Abubakar and Ilkan, 2016; Litvin et al., 2008). Consumers often rely on eWOM when making risky purchases (Tellis et al., 2019), such as buying unfamiliar food, which can entail travel costs (Tellis et al., 2019) and contribute to food waste (Aschemann-Witzel et al., 2015). Food safety is a global concern, and contaminated food causes numerous diseases and deaths annually and research into safety information can be required when purchasing unfamiliar food from an unknown source (Wang et al., 2018). Consumers increasingly use food-based videos as a means of “sale assistance” to quickly gain valuable insights into food experiences and reduce uncertainty when purchasing (Carter and Egliston, 2021).
Many types of videos are posted by food bloggers (food vloggers), including content on food, recipes, restaurant reviews and food-related travel content (Luong and Ho, 2023). Food videos are more appealing to consumers than traditional textual blogging due to their multisensory nature as they combine images, motion and textual descriptions to convey information through verbal and non-verbal language (Sokolova and Kefi, 2020). They provide an exciting platform for sharing information among food enthusiasts and can showcase outdoor setups and include narration (Filieri et al., 2023). As a result, they create entertainment, curiosity and interest in viewers, making them potential tools for food brands to promote products, such as food videos encouraging consumption of nutritious food and healthy diets (Rajput and Sharma, 2021). Many food brands have sponsored food vloggers to endorse their products but food videos also have various framing styles, which may impact viewer attitude and behavior differently. For instance, Chi et al. (2024) highlighted that information-focused and emotion-focused short food tourism videos tend to be more effective when stimulating viewer positive attitude, enhancing sharing and visiting intention. Therefore, food brand owners who want to collaborate with food vloggers to advertise their products (product placement) should understand the factors motivating consumers to watch each type of food video.
Despite the popularity of food videos, few studies have been conducted in this field. Most of the existing research refers to food videos as a source of information focus their investigations on the effect of source credibility when it comes to consumer choices (Luong and Ho, 2023). Little is known about the factors that initially drive consumers to watch food videos as some research has only explored the determinants of intention for watching mukbang videos (Song et al., 2023). However, mukbang content, also known as “eating broadcasts”, is controversial due to its association with eating disorders and food waste (Lee and Wan, 2023). Furthermore, food vloggers promote food-based content on their channels and establish social relationships with viewers by encouraging interactions through comments and feedback (Song et al., 2023). Some vloggers have gained high levels of trust and recognition among their viewer community to the extent that they can persuade their followers to buy a product (Farahdiba, 2022). Therefore, it is necessary to fully understand consumer response to content and for food video content creators to design effective influencer marketing strategies. Moreover, current literature on food video consumption has overlooked the influence of individual conditions on consumer purchasing behavior. Single-person households are becoming more common worldwide (Ortiz-Ospina, 2019) which has led to an increase in the number of people dining alone, resulting in more social media use as solo diners often use digital devices to combat loneliness and boredom during daily eating experiences (Lemke and Schifferstein, 2021). One-person households with more available time and space, financial security and independence often exhibit generous spending on food consumption (Lee and Han, 2013). Therefore, the impact of individual differences on consumer behavior toward food videos should be considered. In addition, Kanaveedu and Kalapurackal (2022) have highlighted the need for more research on influencer marketing in emerging markets. The Asian region has the highest number of social networking platform users, followed by the Americas (Statista, 2023a, b) but input from these countries is currently limited, and additional studies in emerging markets are necessary, especially given that influencer marketing is still a developing field (Chetioui et al., 2020).
This study is informed by the Stimulus-Organism-Response (S-O-R) and Uses and Gratification theory (U&G), which incorporates motivations to watch food videos (i.e. entertainment, information and interaction value) into the research model as stimuli and examines how these motivations affect attitudes toward food videos and food vloggers (organism), which eventually results in the purchase intention of food items. This study screens the extant literature and identifies three key motivations (i.e. information, entertainment and interaction value) that can contribute to attitudes toward food videos and attitudes toward food vloggers. Given that consumers who frequently use social media are more likely to visit and dine in restaurants they see on social media (Arceo et al., 2018), this study also examines the moderating role of social media use frequency to explore whether the impact of two types of attitude on consumer response is contingent on consumers’ frequency of social media use. Essentially, the research questions of this study are threefold:
How does the information, entertainment and interaction value of food videos affect consumers’ attitudes toward food videos and attitudes toward food vloggers?
How do consumer attitudes toward food videos and vloggers affect their intention to purchase food products?
Does the frequency of social media use interact with two types of attitudes to influence consumer purchase intention of food products?
This research makes significant contributions to both theory and practice in various aspects. First, by integrating S-O-R and U&G theories, this study provides a comprehensive understanding of multiple motivations behind consumers watching food videos and making subsequent purchases. This insight can help food brand owners strategically collaborate with food vloggers and suggest ways for vloggers to build virtual proximity with their viewers. Second, this study conducts a moderation analysis to understand the boundary conditions of the impact of motivation and consumer attitude on purchase intention. These findings collectively assist food brand owners in deciding their influencer marketing strategy. Third, by validating the research model using data from Vietnam’s food industry, this study addresses the need for more research on influencer marketing in emerging markets. Vietnam, known for its high social media use (Statista, 2023a, b) and increasing consumer concern for food safety (Ha et al., 2019), was chosen for the focus of this study.
2. Theoretical background and hypothesis development
2.1 Food vloggers
Video bloggers, also called vloggers, produce and publish videos to share their encounters with products, services and brands (Lee and Watkins, 2016). Vloggers typically plan and appear directly in their videos, acting as regular consumers who discuss various aspects, including locations, pricing and menus. Their motivation for sharing opinions and experiences varies, ranging from a desire for fame and community to a genuine interest in food and a commitment to helping others (Chatzopoulou et al., 2020; Hennig-Thurau et al., 2004).
In today’s society, vloggers have become prominent opinion leaders and valuable sources of information in specific domains or product categories on social media (Goodman and Jaworska, 2020). In addition to specializing in creating videos centered around food, food vloggers also showcase food concepts and recipe ideas in their videos. Previous studies on food vlogs have examined the effect of food vlogger characteristics on parasocial interactions (Farahdiba, 2022) and the influence of food vlogs on sharing and purchase intention (Luong and Ho, 2023; Mainolfi et al., 2022) and revealed that food vloggers have the potential to significantly impact consumer perceptions and purchase decisions.
2.2 Uses and gratifications theory (U&G)
The U&G theory, introduced by Katz et al. (1974), is widely regarded as a highly-effective paradigm for understanding motivations behind media use in mass communication research (LaRose and Eastin, 2004) and has been applied to explain why consumers choose specific new digital media (Gogan et al., 2018; Song et al., 2023). According to the U&G theory, individuals actively select media based on their specific needs and motivations. Need refers to something essential or desirable that individuals lack at a given time (Song et al., 2023), and motivation to fulfill a need is a crucial driver of media use (Papacharissi and Rubin, 2000). Motivation provides reasons for individuals to engage with specific types of media and guide media choices, including considering potential gratification. Additionally, user motivation for media use reflects their expectations of the benefits they will acquire from using media (Gogan et al., 2018).
Previous research has identified entertainment, information and social interactions as crucial motivations for using social media platforms (Shao, 2009) and emphasized that the information these platforms provide is entertaining and easy to process and share (Sokolova and Perez, 2021). Within food blogging, studies have highlighted the importance of informativeness and entertainment in evaluating an influencer’s performance (Luong and Ho, 2023; Song et al., 2023) and the need for socializing has been found to drive social media use significantly (Gogan et al., 2018). Thus, in the conceptual model proposed by this study, entertainment, information and interaction value are considered motivations to fulfill unmet needs and represent the anticipated gratifications from watching food videos.
2.3 Stimulus-organism-response (S-O-R) theory
The S-O-R theory, proposed by Mehrabian and Russell (1974), suggests that environmental cues can elicit internal reactions in individuals (organisms), leading to specific behavioral responses. Previous research has adopted this theory to investigate consumers’ emotional and behavioral outcomes in various online purchase contexts. For example, Song et al. (2023) reported that attitude toward mukbang (organisms) mediated the relationships between vicarious satisfaction, enjoyment and information (stimuli) and consumer intention to watch mukbangs (responses). Similarly, Gogan et al. (2018) confirmed the effectiveness of the S-O-R theory by explaining the influence of entertaining value, social participation and information consumption on users continued use of Weibo through satisfaction. In summary, this theory has been applied to identify individual behavioral outcomes in diverse online contexts, making it suitable for exploring individual viewer behavior in food videos.
In accordance with the S-O-R framework, this study considers motivations to watch food videos as environmental stimuli, assigns attitudes toward food videos and food vloggers to the organism, and identifies the intention to purchase the recommended food products as the response.
2.4 Entertainment, information, interaction value and attitude
Entertainment value represents the fun and emotional aspects of an activity and refers to how enjoyable an activity is considered to be (Luong and Ho, 2023). Users often turn to social media for stress relief, choosing platforms that provide high enjoyment (Gogan et al., 2018).
Social media can satisfy consumers’ information needs (Gogan et al., 2018). Vo et al. (2024) highlighted that accurate, relevant and timely information from social media posts can stimulate cognitive and affective responses in users. Food videos can serve as a source of information (Muda and Hamzah, 2021) and information value measures how effectively food videos convey information, such as food ingredients and cooking techniques to consumers. Consumers are more likely to develop a positive attitude toward content when they perceive a vlog as a reliable source of expertise and knowledge (Muda and Hamzah, 2021).
Social interaction fulfills an individuals’ social needs and plays a significant role in the continued use of social media (Gogan et al., 2018) as humans naturally seek social relationships and online social platforms enable users to connect with fellow community members (Gogan et al., 2018). Food videos give users the opportunity to interact and build social relationships through features such as “Like”, “Comment” or “Share”. Users can form online friendships with content owners or other members of the virtual community who share the same interest in food videos.
The value users obtain from entertainment, information and interaction on a social media platform contributes to their satisfaction with the platform (Gogan et al., 2018). This study proposes that the more food videos satisfy consumer need for entertainment, information and interactions, the more positively consumers will feel about the content. Additionally, as the vlogger typically guides food videos, consumers can develop a positive attitude toward the content owner. Thus, the following hypotheses are developed:
Entertainment value is positively related to attitude toward food videos.
Entertainment value is positively related to attitude toward food vloggers.
Information value is positively related to attitude toward food videos.
Information value is positively related to attitude toward food vloggers.
Interaction value is positively related to attitude toward food videos.
Interaction value is positively related to attitude toward food vloggers.
2.5 Attitudes and intention to purchase
Attitude refers to an individual’s evaluative judgment of a concept. When individuals form positive or negative judgments, their attitude influences their intention to engage in or abstain from certain behaviors (Ajzen, 1991). The theory of planned behavior (TPB) suggests a positive relationship between attitude and behavioral intention (Ajzen, 1991). Previous research in social media consumption has confirmed the positive influence of attitude on the intention to watch content on video-sharing platforms and the purchase of recommended products.
Furthermore, the relationship between food vloggers and their viewers is parasocial, as viewers can withdraw if they find the watching experience unsatisfactory. A particular food can be featured in multiple vlogs, and vloggers typically receive brand sponsorships based on the spectrum of their network, intensifying the competition among vloggers. Therefore, in addition to video content, consumers’ intention to buy featured food items can be affected by their overall evaluation of the vlogger. The following hypotheses are formulated:
Attitude toward food videos is positively related to purchase intention.
Attitude toward food vloggers is positively related to purchase intention.
2.6 The moderating role of social media use frequency
Prior research has shown that food videos can encourage consumer food intake (Tazeoglu and Bozdogan, 2022). Consumers can acquire more information about the food by engaging in discussions with food vloggers, such as asking questions in the comment section, and as a result, will better evaluate recommended food. Consequently, consumers can make informed purchase decisions, strengthening their purchase intention. Previous research has identified knowledge as one of the strong predictors of consumer purchase intention (Younus et al., 2015) and consumers who spend more time on social media are more likely to acquire additional food information from vloggers, contributing to greater purchase intention.
However, one major drawback of using ICT devices is the rise of distraction (Lemke and Schifferstein, 2021) because when consumers dedicate more screen time to watching multiple videos, their focus on eating can wane. In addition, if food videos convey similar information, it can lead to information confusion. Dang’s study (2020) revealed that this confusion can cause psychological distress, which drives users away from using social networking sites. Since social media algorithms often present videos with similar content to consumers (Tazeoglu and Bozdogan, 2022), spending excessive time shifting between videos featuring the same food product can overwhelm consumers with information and diminish their interest in tasting the food. Based on these arguments, the following hypotheses have been formed (see Figure 1):
Social media use frequency negatively moderates the relationship between attitude toward food videos and purchase intention.
Social media use frequency positively moderates the relationship between attitude toward food vloggers and purchase intention.
3. Research method
3.1 Measures
As shown in Table 2, all constructs and measurement scales in this study were adopted from previous literature due to their high validity and reliability (Lee and Ma, 2012; Kim et al., 2007; Dodds et al., 1991; Liu et al., 2019; Paek et al., 2011; Dimofte et al., 2003). Before the main study, in-depth interviews were conducted with business academics, industry experts and selected consumers to ensure that the survey questions fit the research context. Some minor adjustments were made to the items and questionnaire based on the feedback. A seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree) was used to measure the items of the research variables. Table 2 presents all the constructs and measurement items in this study.
3.2 Sample and data collection
Convenience sampling was used in the absence of a sampling frame and the sample consisted of respondents who watched food videos shared on YouTube. YouTube was chosen because it is the most popular video-sharing platform, enabling users to share experiences of buying and using products with other users (Muda and Hamzah, 2021).
The number of followers an account has on social media platforms often signifies the source’s credibility and information sources with large followings are considered reliable (Lee et al., 2020). Lee et al. (2020) proposed that the ideal number of followers is 200 and food vloggers with at least 200 followers were selected for this study. According to their social media profiles and the latest rankings from NoxInfluencer (2023), eight food-related YouTube channels were eligible for the study: Hanoi Food (450,000 followers), PM Food (391,000 followers), Ninh Tito (846,000 followers), Bếp trưởng Review (335,000 followers), Ăn sập Hà Nội (326,000 followers), Food Oscar (427,000 followers), Khoai Lang Thang (2,240,000 followers) and Pít Ham ăn (1,550,000 followers). From May to July 2023, an online self-administered questionnaire was developed and distributed through the comment section of the chosen YouTube food channels. A total of 391 questionnaires were collected, and 339 of these were valid. Table 1 presents the demographic profiles of respondents in this study.
3.3 Analysis methods
This study utilized quantitative methods to analyze the data. The data analysis incorporated Smartpls 4.0 software, specifically applying structural equation modeling based on the partial least squares method (PLS-SEM) which was chosen over the covariance-based structural equation modeling (CB-SEM) for having several advantages. First, PLS-SEM is particularly effective for exploratory research to build upon existing theories (Hair et al., 2022; Reinartz et al., 2009). This study, which regards three types of motivations as stimuli and manifests organisms as two types of attitudes, is seen as an extension of the S-O-R and U&G theories rather than a confirmation. Second, PLS-SEM enables accurate parameter estimation even with a limited sample size, eliminating the need for a large sample size (Reinartz et al., 2009). Third, PLS-SEM deals effectively with complex models such as the ones in this research, including those with moderators. In this study, a two-step approach was employed using structural equation modeling (Hair et al., 2019): (1) validity and reliability of the instruments evaluated through the measurement model; and (2) hypotheses tested by analyzing the bootstrapping results in the structural model.
Following the suggestions of Tazeoglu and Bozdogan (2022), Hafeez et al. (2017) and Garcia and Grande (2010), this study controlled the effects of social media use frequency, with age, food expenses, marital status and BMI as the dependent variables.
4. Results
4.1 Measurement model assessment
The research reliability analyses showed that Cronbach’s alpha and composite reliability (CR) exceeded 0.70 for all latent constructs, indicating this was a reliable measurement instrument for this study. The loading values of all items exceeded the cutoff value of 0.7, and the latent constructs’ average variance extracted (AVE) values were above the cutoff value of 0.5. Thus, convergent validity was acceptable in this study (Hair et al., 2019) (Table 2).
Heterotrait-monotrait (HTMT) ratios were utilized to assess the measurement model’s discriminant validity. As listed in Table 3, all HTMT ratios fall within the range of 0.376–0.657, below the threshold of 0.85 which confirms that the current research model demonstrates discriminant validity (Henseler et al., 2015).
Two different statistical methods were applied to check for common method bias (CMB). First, Harman’s one-factor test was used. The results showed that the first factor accounted for 45.122% of the variance, under the 50% threshold (Podsakoff et al., 2003). Additionally, a full collinearity assessment, as recommended by Kock (2015), was conducted to detect CMB. The variance inflation factor (VIF) values should be lower than the cutoff value of 3.3 (Kock, 2015). In this study, the full collinearity test revealed that all latent variable VIFs were below the threshold of 3.3, indicating minimal concern for common method bias.
4.2 Structural model assessment
Table 4 and Figure 2 show the outcomes of the analysis. Entertainment value (β = 0.393, p = 0.000) and information value (β = 0.288, p = 0.000) were found to have a significant effect on attitudes toward food videos. In contrast, the interaction value (β = −0.030, p = 0.329) did not significantly affect attitude toward food videos. Hence, hypotheses H1a and H2a were confirmed, while H3a was rejected. Our results show that entertainment value (β = 0.365, p = 0.000), information value (β = 0.245, p = 0.000) and interaction value (β = 0.162, p = 0.009) explained attitude towards a food vlogger. Thus, hypotheses H1b, H2b and H3b were supported. Attitude towards food videos (β = 0.335, p = 0.000) and attitude towards a food vlogger (β = 0.236, p = 0.000) significantly influenced purchase intention, supporting H4 and H5.
In addition, the results in Table 4 and Figure 2 reveal that the interaction effect between the frequency of social media use and attitude towards food videos is significantly and negatively associated with purchase intention (β = −0.214, p = 0.000). Therefore, H6a is supported. However, the findings also indicate that the interaction effect between the frequency of social media use and attitude toward food vloggers is significantly and positively associated with purchase intention (β = 0.177, p = 0.000), supporting H6b.
Among all control variables, only marital status (β = 0.630, p = 0.000) and the frequency of social media use (β = 0.178, p = 0.000) had a positive relationship with consumer purchase intention. Other control variables were not statistically and significantly associated with consumers’ purchase intention. This result indicates that demographics did not play an essential role in forming consumer intention to purchase food products after watching food videos.
5. Discussion of findings and implications
5.1 Discussion of the main findings
The primary objective of this research was to advance understanding of how motivations for watching food videos affect food purchasing behavior. As suggested by the S-O-R theory, the results reveal that consumer motivation to watch food videos shape their attitude towards food videos and food vloggers, leading to purchase intention. This study explicitly finds a positive relationship between information and entertainment value and consumers’ attitudes toward food videos which extends prior work of Song et al. (2023), who found that information and entertainment value jointly shape consumer attitude toward mukbang content.
The study finds that attitude towards food videos is primarily influenced by entertainment value, followed by information value. This finding partly contradicts the findings of Chi et al. (2024), who reported a stronger correlation between information-focused videos and consumer attitude, rather than emotion-focused videos and consumer attitude, in the context of short food tourism videos. A potential explanation could be that consumers watch food videos primarily to alleviate loneliness and isolation by connecting and sharing similar interests with a virtual community (Kircaburun et al., 2020). Consequently, they seek entertaining content that is easily shared with their virtual peers.
Findings suggest consumer attitude toward food vloggers is affected mainly by entertainment value, followed by information value and then interaction value, and again confirm the work of previous studies that highlight enjoyment and information as important factors for consumers when watching food videos (Chi et al., 2024). One interesting finding is that interaction value does not significantly affect consumer attitude toward food videos despite it influencing attitude towards food vloggers. This contradicts the findings of Sokolova and Perez (2021), who reported a strong effect of social interaction on viewers’ attitudes toward fitness influencer YouTube videos. One possibility for this discrepancy is that consumers’ willingness to engage with a food video depends more on their evaluation of the food vlogger than on the video content which underlines the role of food vloggers in stimulating interaction.
The frequency of social media use negatively moderates the relationship between consumer attitude towards food videos and their purchase intention. It positively moderates the relationship between consumer attitude towards food vloggers and their purchase intention. Consumers often watch food videos when seeking information about new foods. However, since multiple reviews of the same product from different food vloggers are available, watching repetitive content can lead to boredom, weakening the influence of food videos on consumer responses.
Conversely, if food vloggers provide engaging content, such as using the glamourized visual presentation of cooking or eating, they can capture consumers’ attention and motivate them to purchase. This finding adds to prior research by Chen (2021), who noted that consumers hesitant to try new or unfamiliar foods tend to make purchase decisions based on their attitudes toward vloggers. If vloggers convincingly demonstrate that certain new foods are delicious, they can alleviate consumers’ fear of unfamiliar food.
5.2 Theoretical implications
This study makes several important contributions to influencer marketing and food consumption literature. First, it extends the S-O-R and U&G theories to influencer marketing by testing an integrated model that describes how consumer motivation influences attitude toward food videos and vloggers, eventually leading to intention to buy recommended food products. The model proposed and tested in this study highlights that the S-O-R and U&G theories can be used as a theoretical framework for tracing the influence of food vloggers on consumer impact and behavioral outcomes.
Second, this study sheds new light on the role of two distinct attitudes in the relationship between consumer motivation and purchase intention. Previous literature primarily focused on consumer attitude towards food videos, neglecting to consider that food vlogs enable the content creator’s presence in the pre-recorded videos. The positive impact of two types of attitudes underscores the complex process linking consumer motivation (i.e. entertainment, information and interaction value) to their attitude towards food videos and vloggers and, ultimately, their purchase intention. These findings will be valuable for future researchers exploring the interplay between consumer motivation and emotional and behavioral responses to food videos.
Third, this study outlines a boundary condition, specifically the frequency of social media use, through which food videos influence consumers’ purchase intention. The research enriches existing knowledge by indicating that frequent social media use can amplify the impact of consumer attitude toward food vloggers on their purchase intention. However, frequent social media use can also be a double-edged sword, as it can diminish the influence of consumer attitude toward food videos on their purchase intention. The findings indicated that forming stronger purchase intention after watching food videos often requires a high frequency of viewer social media consumption, to the extent that it does not undermine the positive influence of their attitude towards food videos. These moderating mechanisms paint a comprehensive picture of how individual differences affect consumers’ attitudes and purchase intentions, which have been overlooked in the literature.
Finally, this study, focusing on Vietnam, fills the research void about the impact of influencer marketing, specifically food videos, on consumer behavior in emerging markets, which has been relatively unexplored (Kanaveedu and Kalapurackal, 2022). As food safety systems in these markets are currently undergoing a transformation towards more stringent measures due to increased demand for safer food (Wongprawmas and Canavari, 2017), the findings provide initial foundations and implications for researchers studying consumer responses to food videos in emerging markets.
5.3 Managerial implications
From a managerial perspective, this study offers strategic recommendations for food vloggers and food brand managers. First, this study provides food vloggers with fresh insights into designing food videos to influence favorable consumer attitude and purchase intention. The findings suggest that entertainment value has the greatest impact on fostering a positive attitude towards food videos, followed by information value. Therefore, a strategic approach for food vloggers to engage and appeal to audiences is to deliver informative content while maintaining transparency.
Second, food videos offer opportunities for food brand managers to showcase the history or culture behind a food, such as local cuisines, local eating habits and original recipes. The findings suggest that, apart from sponsoring food vloggers to taste and review their products, food business owners can collaborate with vloggers to create entertaining content, such as online contests or fun quizzes, for their consumers. These would enhance consumers’ positive attitudes toward the food video and the vlogger, increasing the likelihood of purchase. Considering the importance of food safety and reducing food waste, food videos can also educate consumers about food products’ healthiness, cleanliness and nutritional benefits. Music, images and animation effects can enhance delivering comprehensive and easily understandable information.
Third, since the frequency of social media use can amplify the impact of attitude toward food vloggers on purchase intention, selecting the right food vlogger becomes crucial. Food business owners should seek partnerships with food vloggers who align with their brands and target consumers. Additionally, as single people tend to spend more time on social media, food vloggers should consider incorporating interactive features in their videos to create a sense of belonging for single viewers who dine alone, as these people often use technology during meals to combat feelings of loneliness.
Furthermore, due to the frequency of social media potentially diminishing the impact of attitude towards food videos on purchase intention, it is essential to constantly refresh the content of food videos. However, it is worth noting that food vloggers should avoid solely focusing on viral food trends, as this may lead to viewer boredom due to a sense of repetitiveness.
6. Limitations and future directions
Several limitations in this study should be acknowledged and addressed in future research. First, the sample only comprised YouTube users in Vietnam, which may limit the generalizability of the findings. Second, this study focused exclusively on food vloggers. To expand the scope of research, future studies could investigate the research model using other content genres, such as beauty vloggers, gaming vlogs and lifestyle vlogs. Third, although cross-sectional data is commonly used in consumer behavior studies, it may introduce bias when determining causal relationships between variables. Therefore, future research should collect longitudinal data to better assess the long-term effect of food video viewing. Moreover, given the increasing uptake of TikTok among young audiences and its growing emphasis on food-centric content, another avenue for future research is to examine whether consumers’ motivations to watch food videos vary with platforms. In addition, considering the positive effect of marital status on purchase intention, future research should explore incorporating this variable as a moderator in the research model.
Figures
Demographics of respondents
| Variable | Items | Frequency | % | Variable | Items | Frequency | % |
|---|---|---|---|---|---|---|---|
| Gender | Male | 118 | 34.81 | Individual monthly food expenses (FoEx) | <VND 1,000,000 | 30 | 8.85 |
| Female | 221 | 65.19 | VND 1,000,000–3,000,000 | 129 | 38.05 | ||
| Age | Gen Z | 198 | 58.41 | VND 3,000,000–5,000,000 | 99 | 29.20 | |
| Gen Y | 102 | 30.09 | >VND 5,000,000 | 81 | 23.89 | ||
| Gen X | 39 | 11.50 | Frequency of social media use daily (TiIn) | <1 h | 48 | 14.16 | |
| Educational level | High school | 81 | 23.89 | 1–3 h | 132 | 38.94 | |
| University | 198 | 58.41 | 3–8 h | 108 | 31.86 | ||
| Postgraduate | 60 | 17.70 | >8 h | 51 | 15.04 | ||
| Marital status (MaSt) | Single | 146 | 43.07 | BMI | BMI<18 | 39 | 11.50 |
| Married | 193 | 56.93 | 18 < BMI < 25 | 225 | 66.37 | ||
| BMI > 25 | 75 | 22.12 |
Source(s): Created by authors
Reliability and validity of measurement scales
| Source | Items | Outer loadings | Cronbach’s alpha | CR | AVE |
|---|---|---|---|---|---|
| Information value (IFVA) | |||||
| Lee and Ma (2012) | Food video helps me to store useful information about food | 0.812 | 0.873 | 0.876 | 0.663 |
| Food video is good for retrieving information about food when I need it | 0.833 | ||||
| Food video is useful to keep up to date on the latest news and events about food | 0.818 | ||||
| Information from food video is very useful to me | 0.835 | ||||
| Food video is useful for finding information about food | 0.773 | ||||
| Entertainment value (ENVA) | |||||
| Kim et al. (2007) | I have fun with food video | 0.861 | 0.880 | 0.886 | 0.734 |
| Watching food video provides a lot of enjoyment | 0.883 | ||||
| I enjoy watching food video | 0.855 | ||||
| Watching food video makes me excited | 0.828 | ||||
| Interaction value (INVA) | |||||
| Liu et al. (2019) | I can connect with vlogger and other people through food video | 0.830 | 0.877 | 0.879 | 0.732 |
| I can exchange information with vlogger and other people through food video | 0.901 | ||||
| Food vlogger usually interacts with me through food video | 0.845 | ||||
| Food vlogger usually interacts with me directly or indirectly through social media | 0.845 | ||||
| Attitude towards food video (VIAT) | |||||
| Paek et al. (2011) | I like watching food video | 0.888 | 0.847 | 0.847 | 0.766 |
| It is worthwhile watching food video | 0.886 | ||||
| Food video has interesting content | 0.851 | ||||
| Attitude towards food vlogger (VLAT) | |||||
| Dimofte et al. (2003) | Food vlogger is very nice | 0.932 | 0.908 | 0.909 | 0.845 |
| Food vlogger has high reliability | 0.931 | ||||
| Food vlogger is sincere | 0.895 | ||||
| Purchase intention (PUIN) | |||||
| Dodds et al. (1991) | I would consider buying food products I watch on food video | 0.952 | 0.958 | 0.950 | 0.906 |
| I will buy food products used in food video | 0.953 | ||||
| I am willing to buy food products used in food video | 0.950 | ||||
Source(s): Created by authors
Heterotrait-monotrait ratio
| ENVA | IFVA | INVA | PUIN | VIAT | VLAT | |
|---|---|---|---|---|---|---|
| ENVA | ||||||
| IFVA | 0.645 | |||||
| INVA | 0.617 | 0.606 | ||||
| PUIN | 0.560 | 0.550 | 0.376 | |||
| VIAT | 0.622 | 0.573 | 0.390 | 0.627 | ||
| VLAT | 0.657 | 0.601 | 0.549 | 0.572 | 0.611 |
Source(s): Created by authors
Hypotheses results
| Model 1 | Model 2 | Model 3 | Results | |
|---|---|---|---|---|
| H1a: ENVA → VIAT | 0.393*** | 0.393*** | 0.393*** | Accepted |
| H1b: ENVA → VLAT | 0.365*** | 0.365*** | 0.365*** | Accepted |
| H2a: IFVA → VIAT | 0.288*** | 0.288** | 0.288*** | Accepted |
| H2b: IFVA → VLAT | 0.245*** | 0.245*** | 0.245*** | Accepted |
| H3a: INVA → VIAT | −0.030NS | −0.030NS | −0.030NS | Rejected |
| H3b: INVA → VLAT | 0.162** | 0.162** | 0.162** | Accepted |
| H4: VIAT → PUIN | 0.392*** | 0.343*** | 0.335*** | Accepted |
| H5: VLAT → PUIN | 0.322*** | 0.210*** | 0.236*** | Accepted |
| Age → PUIN | 0.017NS | 0.016NS | ||
| BMI → PUIN | 0.046NS | 0.035NS | ||
| MaSt → PUIN | 0.636*** | 0.630*** | ||
| FoEx → PUIN | 0.026NS | 0.013NS | ||
| TiIn → PUIN | 0.194*** | 0.178*** | ||
| H6a: TiIn × VIAT → PUIN | −0.214*** | Accepted | ||
| H6b: TiIn × VLAT → PUIN | 0.177*** | Accepted | ||
| Adjusted | 38.9 | 51.9 | 54.6 |
Note(s): ***p < 0.001, ** <0.01, * <0.05 NS: Not significant
Source(s): Created by authors
Funding: The research is funded by Thuongmai University, Hanoi, Vietnam.
Conflicts of interest/competing interests: The authors declare no conflicts of interest.
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