DOI QR코드

DOI QR Code

How YouTube Influencers Impact Customers' Purchase Intention: An Empirical Study of Cosmetic Brands in Vietnam

  • LE, Thanh Vi (School of Business, Ho Chi Minh City International University (IU), Vietnam National University Ho Chi Minh City (VNUHCMC)) ;
  • ALANG, Tho (School of Business, Ho Chi Minh City International University (IU), Vietnam National University Ho Chi Minh City (VNUHCMC)) ;
  • TRAN, Quang Tri (Faculty of Garment Technology and Fashion, Ho Chi Minh City University of Technology and Education)
  • 투고 : 2021.05.15
  • 심사 : 2021.08.02
  • 발행 : 2021.09.30

초록

This study investigates the impact of heuristic factors on customers' perception of information credibility of influencers on YouTube channels, and the association between customers' perception of information credibility and brand attitude, brand credibility, and purchase intention of cosmetic products in Vietnam. A quantitative approach is employed, with a survey of 270 females who are frequent viewers of beauty content on YouTube channels. The data reliability and validity go through various statistical tests including exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Also, structural equation modeling (SEM) is applied to test the hypotheses. The results reveal that there is a positive association between heuristic factors and the perception of information credibility. This perception of information credibility also influences positively on customers' attitudes toward the brand and brand credibility. Purchase intention is also found to be positively associated with the two latter variables. The study's main findings not only offer advice to practitioners on how to choose the right product endorsers and advertising platforms, but they also offer novel insight from the Vietnamese context that could help to extend the heuristic-systematic model and customers' buy intention behavior.

키워드

1. Introduction

Customers’ fascination with watching online videos is increasing every day, and YouTube has fast become beauty influencers’ favorite social media platform to work on (Dankwa, 2021). In 2020, YouTube, a site that incorporates both streaming and social elements, had over 2 billion subscribers globally and was the second-largest search engine behind Google (Cooper, 2019). Fashion and beauty-related contents such as makeup and skincare tips, cosmetics hauls, and product reviews were among the most popular topics among the millions of contents on YouTube, with over 169 billion video views in 2018 (Clement, 2019). About 33 percent of female YouTuber users reported watching YouTube beauty influencers occasionally and ranked YouTube higher than television regarding its appeal for inspirational beauty content (Clement, 2019).

Vietnam is not an exception, seeing that social media is rapidly growing and spreading across the country (Ao & Nguyen, 2020; Pham et al., 2021). A report from Pixability (2014) pointed out that the most popular sites for watching beauty vlogs were YouTube and Facebook, in which females accounted for about 75 percent and those in the age group of 13 to 24 were more than 45 percent. Specifically, ages from 18 to 24 years old spent about 10 hours per month watching beauty vlogs.

However, despite the fact that Vietnamese beauty influencers have turned their names into brands on social media, have a large number of YouTube subscribers, and have the ability to create new trends in cosmetic product use and makeup styles in recent years, there is still a scarcity of research on the phenomenon. In addition, previous studies on endorsement were mostly focusing on celebrity and their credibility perceived by customers (Wang et al., 2017). Since traditional celebrity advertising in Vietnam has gradually faded and been replaced by the popularity of influencers, the necessity to research the impact of influencers on customers has grown. In addition, YouTube has become one of the most popular social media sites for influencers and customers alike. (Rodrigues et al., 2018, Rosara & Luthfia, 2020). As such, researchers have called for more studies on YouTube influencers’ information credibility and its impact on customer behavior (Lou & Xie, 2020; Xiao et al., 2018).

By employing a heuristic-systematic model, this study aims to investigate the impact of heuristic factors on customers’ perception of information credibility of beauty influencers on YouTube channels, and the association between customers’ perceived information credibility and brand attitude, brand credibility, and purchase intention of cosmetic products in Vietnam. The significance of this study lies in its attempts to extend the heuristic-systematic model by focusing on a specific cosmetic brand and linking it to customers’ purchasing intention behavior, which is not often considered when studies to evaluate perceived credibility are undertaken (Corrêa et al., 2020; Xiao et al., 2018). This study may also suit the needs of cosmetic business practitioners in Vietnam in terms of selecting acceptable product endorsers and advertising venues. This would provide them a better understanding of how people seek information and buy cosmetics, which has been increasing at an unprecedented rate in Vietnam (Pham, 2021).

The rest of the paper is structured as below. First, we review the relevant literature on perception of information credibility, heuristic information cues, and brand attributes, and purchase intention. This section also provides hypothesis development and research framework. Second, we outline the methodology utilized in this study before presenting the results. Finally, we present our discussion and conclusions.

2. Literature Review

2.1. Perception of Information Credibility

A message’s credibility is defined as the extent to which consumers perceive an online source of information as being impartial, believable, and factually based (Rebelo, 2017). As digital development grows exponentially, consumers frequently tend to recognize influencers as a more credible source of information than other traditional sources, such as salespersons (Lim et al., 2017). In this research, perceived information credibility can be understood as the believability of the message presented in the videos by influencers on their YouTube channels. Empirical experiments have shown that the heuristic retrieval factors affecting an individual’s interpretation of information include source credibility, social influence, and interactivity between message senders and receivers (Zhang et al., 2018).

2.2. Heuristic Information Cues

Heuristic information cues describe how convincing messages are interpreted and processed (Chen & Chaiken, 1999). Chen and Chaiken (1999) claimed that individuals may interpret messages either heuristically or systematically. The systematic analysis uses cautious and analytical factors to process a document to easily assess the message, whereas heuristic analysis takes advantage of simplifying rules or heuristic factors. When a customer has a large number of alternatives and each alternative contains many attributes, they tend to use simplified strategies to make their purchase decision; hence, some attributes may be ignored since the customers focus solely on a few available attribute information - or heuristic information cues (Dankwa, 2021).

2.3. Heuristic Information Cues: Source-Related Factors

The theory of source credibility states that certain communicator traits (i.e., trustworthiness, expertise, attractiveness, and homophily) have a significant effect on the message’s persuasiveness (Metzger & Flanagin, 2013). Lou and Yuan (2019) found that the better an influencer has embraced these characteristics, the more customers are accepting the messages. Trustworthiness is the quality considered by message receivers as a combination of believability, respectability, and honesty embodied by the communicator (Dinh & Doan, 2019; Metzger & Flanagin, 2013; Munnukka et al., 2016). When the listener assumes that the communicator is trustworthy, they may conclude that the transmitted message is strongly believable. Individuals’ appraisal of message credibility and the persuasiveness of a message are heavily influenced by trustworthiness (Pornpitakpan, 2004; Rodrigues et al., 2018). The communicator is deemed as being persuasive when he or she is trustworthy, whether or not he or she is an expert.

The extent to which the communicator is assessed as a source, who can make good claims is classified as expertise (Xiao et al., 2018). Being well-educated in a field, having plenty of experience in doing something, or even having a reputable degree, such as a doctoral degree, for example, leads to the growth of the communicator’s perceived expertise (Gass & Seiter, 2011). Previous studies suggest that the communicator’s perceived expertise has a significant impact on the process of altering the behavior of people (Janssen et al., 2020), and the audiences are likely to agree with the communicators they perceive as an expert or are knowledgeable about the topic they are talking about (Hughes et al., 2019).

Attractiveness is defined as the extent to which the endorser is viewed as appealing, sophisticated, lovely, elegant, and sensual by the audience (Choi & Rifon, 2012; Pornpitakpan, 2004; Wang et al., 2017). A substantial amount of advertisement and communication analyses show that physical appearance plays a vital role in the initial judgment of another person by an individual (Wang et al., 2017). Also, the beauty of the source specifically affects the efficacy of a communication message. An attractive endorser can influence consumers because they accept the information sent out by these endorsers easily (Van der Waldt et al., 2009). Attractive endorsers are usually more successful in promoting products and grabbing consumers’ attention. (Lou & Yuan, 2019; Nguyen, 2020).

Homophily implicates the similarity between the information source and the message receiver (Xiao et al., 2018). Previous literature has found that the homophily between the source and receiver promotes communication effectiveness (Xiao et al., 2018). Homophily between message receivers and senders also impacts the receiver’s perception of the message and the senders’ credibility. The resemblance between a spokesman and a customer may have a powerful effect on the credibility of the source. Previous research has shown that race-based correlations, sexual orientation, gender, and language have a huge effect on the credibility of spokespersons (Morimoto & LaFerle, 2008). Based on the above literature review, the following hypothesis is proposed:

H1: Trustworthiness, expertise, attractiveness, and homophily have positive associations with viewer’s perception of information credibility.

2.4. Heuristic Information Cues: Platform-Related Factors

Nowadays, digital developments allow an individual’s message(s) to be broadcasted to the public community using social platforms without much cost and risk to achieve a purpose or deliver the message content (Geho & Dangelo, 2012). YouTube channel is considered as a social network that impacts users’ expectation of information credibility (Corrêa et al., 2020; Rosara & Luthfia, 2020). The presence of comment sections is one of YouTube’s prominent characteristics. It offers a virtual platform for viewers to share their opinions with others about the videos they have watched on the YouTube channels. It also enables influencers to interact with their audiences (Dankwa, 2021). There are two factors relating to this platform including social advocacy and interactivity (Xiao et al., 2018). Social advocacy is defined as peer influence or pressure online among individuals (Chen & Chaiken, 1999). This means that when many people deem the video’s message as a reliable source, other individuals are more likely to trust the message too (Rosara & Luthfia, 2020). On YouTube channels, viewers of one video usually communicate with each other and share their thoughts via the comment sections, which may affect other viewers’ perceptions of the information credibility provided by the influencers’ videos (Xiao et al., 2018). The hypothesis below is therefore proposed:

H2: Social advocacy has a positive association with the viewer’s perception of information credibility.

Not only does the comment section encourage audiences to engage and affect each other, but it also encourages influencers to connect with their fans or subscribers. Empirical research supports the idea that one of the variables which may impact the perceived credibility of information is interactivity (Dinh & Doan, 2019; Metzger & Flanagin, 2013). Burgoon et al. (2002) clarify the idea of interactivity as the extent of contact or communication between the uploader and the video audiences. As one of the potential variables to affect people’s perception of credibility, Metzger (2007) included interactive features, such as the rapid response time of customer services. Bickart et al. (2012) also urged brands to increase blog interactions to boost the perceived reputation of brands. Investigating the factors under a heuristic-systematic perspective, Sundar (2008) included interpersonal interactivity that influences the online information credibility judgment of consumers. A strong association between interactivity and the perceived information credibility was also found by Xiao et al. (2018). Given these pieces of evidence, the following hypothesis is put forward:

H3: Interactivity has a positive association with the viewer’s perception of information credibility.

2.5. Brand Attributes and Purchase Intention

Attitude toward the brand is a reasonably comprehensive brand assessment that presumably energizes the consumers’ actions (Spears & Singh, 2004). Previous studies have found that celebrity endorsement impacts the attributes of a product and brand (Kumar & Polonsky, 2019). Particularly, celebrity endorsement could be considered as an influence of attitude or credibility of the brand. For example, Rifon et al. (2004) discovered a positive association between the website sponsors’ perceived credibility and the customers’ attitude towards the sponsor. Choi and Rifon (2012) found a direct and optimistic link between perceived credibility and attitude towards the brand. Chu and Kamal (2008) noticed that once blog readers read a high-quality blog written by a credible blogger, they are more likely to have a favorable opinion of the brand listed in the blog. Besides, a previous study has argued that a consumer’s credibility from a source would improve or undermine his or her attitude towards the brand (Wang et al., 2017). The following hypothesis is suggested considering the close association between perceived information credibility and consumer’s brand attitude.

H4: Viewer’s perception of information credibility has a positive association with their attitude toward the cosmetic brand mentioned in the video.

Brand credibility is defined as the believability of the product information contained in a brand, which requires that consumers perceive that the brand has the ability (i.e., expertise) and willingness (i.e., trustworthiness) to continuously deliver what has been promised (in fact, brands can function as signals since if and when they do not deliver what is promised their brand equity will erode) (Erdem & Swait, 2004). In order to be considered, brands need to have the potential and ability to continuously produce what it has promised. Brand credibility is particularly important as it is one of the signals of product positioning that has a significant impact on the process of brand consideration. This is because it can help to reduce the perceived risks of the consumers and minimize the information gathering and cost processing happening during the consumer decision-making process (Erdem & Swait, 2004). Because the endorsement process entailed promoting some of the endorsed brand’s attributes, there’s a good probability the brand will inherit the endorser’s credibility to some extent. A positive association between the endorser’s perceived credibility and brand credibility is also found by Wang et al. (2017). Therefore, it is argued that the credibility of the endorsed brand can be associated with the credible information presented by the influencer:

H5: Viewer’s perception of information credibility has a positive association with the credibility of the cosmetic brand mentioned in the video.

Purchase intention is a personal pattern associated with a brand, as well as the desire and likelihood of customers purchasing a product (Lloyd & Luk, 2010). Among its many predictors, attitude toward brand and product is considered the most reliable factor (Lloyd & Luk, 2010). Several studies have shown that brand attitude has a positive effect on customers’ buying intention (Schivinski & Dabrowski, 2014; Wu & Lo, 2009). Previous studies have also shown that a customer’s perceived brand credibility influences their ability to buy endorsed products (Erdem & Swair, 2004; Wang et al., 2017). Choi and Rifon (2012) have claimed that through their attitude towards brands, celebrity endorsers have a significant and positive impact on customers’ purchase intention. The following hypotheses are thus established:

H6: Viewer’s attitude toward the cosmetic brand mentioned in the video has a positive association with the purchase intention for that cosmetic brand.

H7: The credibility of the cosmetic brand mentioned in the video has a positive association with the purchase intention for that cosmetic brand.

The conceptual framework of this study, including seven proposed hypotheses, is presented in Figure 1 as below.

OTGHEU_2021_v8n9_101_f0001.png 이미지

Figure 1: Conceptual Model of Research

3. Methodology

3.1. Data Collection and Sampling

A questionnaire was constructed by adopting the measurement scales from previous studies (e.g., McMillan & Hwang, 2002; Ohanian, 1990; Strolovitch, 2006; Wu & Chang, 2005). The target population was females between 18 to 22 years old who live in Ho Chi Minh City and watch YouTube beauty-related videos occasionally. Females’ choice as the target population was rational as women account for over 89% of beauty and cosmetic views on YouTube, with 39.9 percent being women between 18 to 24 years old (Blattberg, 2015). Respondents were provided with both printed questionnaires and online Google Forms. The researchers also spread the questionnaires on Facebook’s beauty groups as many target respondents operate on these groups.

The location chosen to spread the printed questionnaires was Ho Chi Minh City International University, where many target respondents were located. While the printed questionnaires were delivered directly to the target audience, who are all females, the online questionnaire forms being spread through Facebook did not restrict the gender or age of the respondents. After three months of collecting data (20th of August to the 5th of December 2020), a total of 282 online and offline questionnaires/forms were collected. After filtering out invalid questionnaire answers, 270 questionnaires were deemed usable.

3.2. Measurement Scales

There were two parts to the questionnaire. The first part included close-ended demographic questions, while the second part consisted of 45 questions for measuring perceived information credibility and the relationship with its heuristic antecedents and three other factors – brand credibility, attitude toward the brand, and purchase intention. These questions were under the 5-point Likert scale, a type of psychometric response scale in which responders specify their level of agreement to a statement typically in five points: (1) Strongly disagree; (2) Disagree; (3) Neither agree nor disagree; (4) Agree; (5) Strongly agree. In order to measure the four dimensions of source credibility, four constructs were adopted from the study of Ohanian (1990). Social advocacy had two items which were adopted from Strolovitch (2006), while the construct for interactivity came from McMillan and Hwang (2002) and Wu and Chang (2005). Perceived information credibility’s construct had seven items borrowed from the study of Xiao et al. (2018), while brand credibility and brand attitude adopted seven items from Erdem and Swait (2004) and Spears and Singh (2004), respectively. Last, three items belong to the purchase intention variable, which were adopted from Pornpitakpan (2004).

3.3. Data Analysis Procedure

First, descriptive analysis was conducted to define in mathematical terms the key characteristics of the data set. To verify the reliability or the internal consistency of measurement scales, Cronbach’s alpha and composite reliability (C.R.) were applied (Wells & Wollack, 2003). Exploratory factor analysis (EFA) was then employed to eliminate invalid factors from the measurement scale. The factor loading of the item should be greater than 0.5, and the difference between absolute factor loadings should be greater than 0.3 if distributed in more than one component.

Confirmatory factor analysis (CFA) was performed to evaluate the model fit, convergent validity, and discriminant validity of the constructs (Suhr, 2006). To confirm convergent validity, all factor loadings in standardized regression weights have to be greater than 0.5 (Hair et al., 1995). And average variances extracted (AVE) values related to all constructs should be equal to or greater than 0.5 (Fornell & Larcker, 1981). To achieve discriminant validity, all correlations’ estimated values should be greater than 0.9, which guarantees the discriminant validity between each pair of variables (Campbell & Fiske, 1959). Moreover, specific measurement model fit indices must meet the thresholds: ratio must be smaller than 3, comparative fit index (CFI) must be greater than 0.90, Goodness-of-Fit Index (GFI) must be greater than 0.8, Tucker Lewis Index (TLI) must be near one and root mean square error of approximation (RMSEA) must be smaller than 0.10 (Bentler & Hu, 1999; Hair et al., 1995).

In the final step, structural equation modeling (SEM) was applied to test hypotheses (that is the relation between observed and latent variables) in the research model (Suhr, 2006). Similar to fit indices of the measurement model, fit indices of the structural model include, comparative fit index (CFI), Goodness-of-Fit Index (GFI), and root mean square error of approximation (RMSEA) (Bentler & Hu 1990; Hair et al., 1995). In addition, p-values should be smaller than 0.05 for a significant relationship to exist among the variables.

4. Results

Among the 270 valid respondents, all of whom were females, respondents between 18–22 years took up most of the data pool, accounting for 96.3% of respondents and the balance surveyed individuals belonged to the 23–30 age group. Most of them spent under an hour per week on beauty influencer videos (64%), usually at the weekend in their free time, while those who spent 1 to 3 hours make up 17 percent of the population. Regarding the respondents’ favorite influencers, ‘mega’ influencers with more than 1 million YouTube subscribers Trinh Pham and Trang Ngo made up 42.5% of the respondents, while macro-influencers, namely An Phuong and Chloe Nguyen, accounted for 15.4% and 14.4%, respectively.

Descriptive analysis, reliability, dimensionality, model fit, and discriminant and convergent validity of the measurement model were assessed, and results were summarized in Table 1. It is seen that Cronbach’s Alpha and composite reliability of all variables were greater than 0.7, ensuring the reliability of the measurement model. Dimensionality was supported as all factor loadings were greater than 0.5, and no regrouping was needed.

Table 1: Measurement Scale Reliability and Validity

OTGHEU_2021_v8n9_101_t0001.png 이미지

Table 1: Continued

OTGHEU_2021_v8n9_101_t0002.png 이미지In the CFA test, variables’ average variance extracted (AVE) scores and factor loadings were also greater than 0.5, indicating the validity of the measurement model. Estimate values of all correlations were also smaller than 0.9 (see Table 2), exhibiting good discriminant validity. The fit indices of the measurement model were also deemed good as Chi-square test (χ2 = 1325.764, p < 0.001, df = 695) with χ2/df ratio (1325.764/695 = 1.908) being lower than the benchmark of 3. In addition, the value of comparative fit index (CFI = 0.911), Goodness-of-Fit Index (GFI = 0.803), Tucker Lewis Index (TLI = 0.900) and root mean square error of approximation (RMSEA = 0.058), also showed a good fit.

Table 2: Correlation Analysis

OTGHEU_2021_v8n9_101_t0003.png 이미지

Note: ***, ** and * indicates significant at 1%, 5% and 10% level of significance.

The structural model exhibited good fit indices (χ2 = 1131.710, p < 0.001, df = 726, χ2/df ratio = 1.834, CFI = 0.914, GFI = 0.804, CFI = 0.914, and RMSEA = 0.056). Furthermore, all estimates (β) were positive, and p-values (P) were lower than 0.05 (see Table 3), indicating a significant positive association among the variables. To be more specific, hypothesis H1 was supported as the four dimensions of source credibility-expertise, trustworthiness, attractiveness, and homophily – were found to be significantly associated with perceived information credibility. It is noteworthy that trustworthiness is the factor that had the most impact on credibility among the 4 source credibility factors.

Table 3: Hypothesis Test Results

OTGHEU_2021_v8n9_101_t0004.png 이미지

Note: ***, ** and * indicates significant at 1%, 5% and 10% level of significance.

Social advocacy and interactivity also had positive associations with perceived information credibility, supporting H2 and H3. Perceived information credibility had also been found to be positively associated with both brand credibility and brand attitude; hence H4 and H5 had been confirmed. In addition, perceived credibility had been found to have a stronger impact on brand credibility rather than brand attitude. Lastly, H6 and H7, which denoted positive associations between brand attitude and brand credibility with purchase intention, had also been supported, with brand attitude being the factor that has a stronger impact.

5. Discussion and Conclusion

First, this study finds that trustworthiness, expertise, attractiveness, and homophily had positive associations with the beauty influencer’s perceived information credibility. It could lead to the claim that these dimensions of source credibility impact the effectiveness and persuasiveness of messages from YouTube channels. While this finding is similar to previous studies, we find that trustworthiness had the most impact on source credibility (Corrêa et al., 2020; Hughes et al., 2019; Nguyen, 2020); hence, it could be argued that trustworthiness generates more opinion changes compared to other heuristic factors (i.e., expertise, attractiveness, and homophily). This phenomenon could also be explained by the fact that, in light of the prevalence of false information on Vietnam’s social media these days, Internet users value a reliable source of information more. An interesting finding of this study is that the honesty of influencers (TR2) had the lowest degree of agreement among the trustworthiness scale, which can be explained by the fact that some viewers may be unsure if the influencers are reviewing a product based on actual experience or if they are concealing certain aspects of the product for profit. (Rosara & Luthfia, 2020).

Expertise was also ranked second in the impact the four characteristics have on heuristic information processing, according to the structural model’s standardized regression weight. The attractiveness of the influencer, which is also a heuristic feature related to source credibility, ranked after expertise. The descriptive analysis pointed out that While most respondents believed their favorite influencers were attractive, they did not link sensuality with them, which is the difference between this study and previous studies (Choi & Rifon, 2012; Ohanian, 1990; Pornpitakpan, 2004; Wang et al., 2017). This anomaly could be explained by the fact that Vietnamese people are more conservative in nature, and attractiveness is viewed in a more conventional light; as a result, adjectives like attractive, lovely, or classy are more typically used to express beauty than sensuality. In addition, while still related, homophily was the heuristic characteristic with the least impact on source credibility, confirming prior research findings (Metzger & Flanagin, 2013).

Second, social advocacy was found to have a significant positive association with perceived information credibility. This finding resonates with the previous literature findings (Dinh & Doan, 2019), which enunciates that YouTube viewers choose a heuristic shortcut to evaluate the credibility of the influencer, such as reading the comments below the video. As most YouTube viewers like to discuss what they have watched with each other under the comment sections, viewers with opposing judgments may change their opinion under peer pressure to feel a sense of immersing with the online group (Corrêa et al., 2020; Xiao et al., 2018). Interactivity was another heuristic factor that was found to be associated with perceived information credibility; thus, this further supports the findings of previous studies which point out that an out-going influencer may be regarded as being more credible (Metzger & Flanagin, 2013). However, the majority of respondents regarded their influencer as not being interactive enough, which could be because these respondents prefer mega and macro-influencers whose videos have hundreds to thousands of comments each, and thus cannot connect with every viewer in the comment box.

Third, hypotheses 4 and 5, which exhibit a positive association among the influencer’s perceived information credibility with the respondents’ attitude toward the endorsed brand and the brand’s credibility, were supported. This result aligns with previous studies and reaffirms the significance of perceived information credibility in forming brand attitudes and brand credibility (Dankwa, 2021; Lou & Xie, 2020). However, the findings of this study show that perceived information credibility was found to have a bigger impact on brand credibility. Hypotheses 6 and 7 were also supported, as there were positive correlations between the respondent’s desire to purchase the introduced brand’s products and both the respondent’s attitude toward the brand and the brand’s credibility. This finding is in line with previous research (Dankwa, 2021; Mohan, 2020; Wang et al., 2017) even though these studies’ product category is different from our present study. It also seems that in the beauty industry context, purchase intention is higher when the feeling is involved, as the analytical results revealed that brand attitude had a more significant impact than that of brand credibility.

Theoretically, this study could extend the heuristic systematic model by focusing on a specific cosmetic brand and linking it to customers’ purchase intention behavior, which has not been widely investigated when studies to assess perceived credibility in emerging countries like Vietnam have been conducted. (Corrêa et al., 2020). It could be argued that perceived information credibility on social media (i.e., YouTube) has a positive impact on customers’ attitudes to the brand and their perceived brand credibility. These indicators would be a good predictor of customers’ intent to buy. Also, YouTube should be viewed as a good option for viewers, and heuristic considerations should be used to help viewers determine the content’s believability.

In practice, these findings give practitioners, in this case, cosmetic brands, a better understanding of how the primary viewers of YouTube beauty videos, that is young females, evaluate beauty influencers and their buy intentions, which are indirectly linked to those influencers. Analytical results suggest that cosmetics brands should look for influencers who have the reputation of being trustworthy as this heuristic factor is the most important than expertise or attractiveness when it comes to quick evaluation of the influencer’s credibility. Furthermore, for cosmetic brands that already collaborate with or sponsor particular beauty influencers, a communication strategy in which the influencer improves their contact with the viewers leads to an increase in perceived information credibility. The comment area will also be used by new viewers to heuristically assess the influencer’s reliability. For the influencers, they could leverage the analysis on heuristic factors in this study to improve their reputation, gaining more followers. The cosmetic brand should invest more in influencer marketing on YouTube. However, it should be careful in selecting the right influencers to endorse for its products because if the influencers are deemed as untrustworthy, this negatively affects the credibility of the brand as well as the consumer’s attitude toward the brand and ultimately, sales of products.

There are limitations within this study that should be addressed and taken into caution. First, a minority of male viewers was not taken into consideration in this study. In addition, the chosen sample size of 270 may not be big enough to reflect the perception of gen Z females in general. Furthermore, older age groups, such as millennials from 23 to 35 or gen X who are above 36 years old, who have been reported to use cosmetic products the most, were not the main focus of the present study. The distribution of the questionnaires was limited to Ho Chi Minh City. As a result, the study does not reflect the entire Vietnamese population. Furthermore, a wider scope, including respondents from other cities across Vietnam or from rural areas, are suggested for future studies to discover new findings on beauty influencer’s credibility literature. It is recommended that future research explore other potential heuristic factors that may affect credibility, for example, the word-of-mouth effect. Also, a look into other product categories is highly suggested.

참고문헌

  1. Ao, H. T., & Nguyen, C. V. (2020). The reaction of Vietnam's generation Z to online TV advertising. Journal of Asian Finance, Economics, and Business, 7(5), 177-184. https://doi.org/10.13106/jafeb.2020.vol7.no5.177
  2. Bentler, P. M., & Hu, L. T. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
  3. Bickart, B. A., Brunel, F. F., Kim, S. J., & Pai, S. (2012). Can your business have 1 million friends? Understanding and using blogs as one-to-one mass media. Rochester, NY: Social Science Research Network.
  4. Blattberg, E. (2015). The demographics of YouTube, in 5 charts. https://digiday.com/media/demographics-youtube-5-charts/
  5. Burgoon, J. K., Bonito, J. A., Ramirez, A., Dunbar, N. E., Kam, K., & Fischer, J. (2002). Testing the interactivity principle: Effects of mediation, propinquity, and verbal and nonverbal modalities in interpersonal interaction. Journal of Communication, 52(3), 657-677. https://doi.org/10.1111/j.1460-2466.2002.tb02567.x
  6. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105. https://doi.org/10.1037/h0046016
  7. Chen, S., & Chaiken, S. (1999). The heuristic-systematic model in its broader context. In: Chaiken, S. & Trope, Y. (Eds.), Dual-process theories in social psychology (pp. 73-96). New York, NY: The Guilford Press.
  8. Choi, S., & Rifon, N. (2012). It is a match: The impact of congruence between celebrity image and consumer ideal self on endorsement effectiveness. Psychology and Marketing, 29(9), 639-650. https://doi.org/10.1002/mar.20550
  9. Chu, S. C., & Kamal, S. (2008). The effect of perceived blogger credibility and argument quality on message elaboration and brand attitudes: An exploratory study. Journal of Interactive Advertising, 8(2), 26-37. https://doi.org/10.1080/15252019.2008.10722140
  10. Clement, J. (2019). Most popular YouTube beauty and style channels as of March 2020, ranked by a number of subscribers. https://www.statista.com/statistics/627448/most-popular-YouTube-beauty-channels-ranked-by-subscribers/
  11. Cooper, P. (2019). 23 YouTube statistics that matter to marketers in 2020. https://blog.hootsuite.com/YouTube-stats-marketers/
  12. Correa, S. C. H., Soares, J. L., Christino, J. M. M., Gosling, M. D. S., & Goncalves, C. A. (2020). The influence of YouTubers on followers' use intention. Journal of Research in Interactive Marketing, 14(2), 173-194. https://doi.org/10.1108/JRIM-09-2019-0154
  13. Dankwa, D. D. (2021). Social media advertising and consumer decision-making: The mediating role of consumer engagement. International Journal of Internet Marketing and Advertising, 15(1), 29-53. https://doi.org/10.1504/IJIMA.2021.112786
  14. Dinh, H., & Doan, T. H. (2019). The impact of senders' identity on the acceptance of electronic word-of-mouth of consumers in Vietnam. Journal of Asian Finance, Economics, and Business, 7(2), 213-219. https://doi.org/10.13106/jafeb.2020.vol7.no2.213
  15. Erdem, T., & Swait, J. (2004). Brand credibility and its role in brand choice and consideration. Journal of Consumer Research, 31(1), 191-99. https://doi.org/10.1086/383434
  16. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312
  17. Gass, R. H., & Seiter, J. S. (2011). Credibility. In: Bowers, K. Zalesky, J. & Lentz, M. (Eds.), Persuasion: Social influence and compliance gaining (pp. 72-90), New York, NY: Pearson.
  18. Geho, P. R., & Dangelo, J. (2012). The evolution of social media as a marketing tool for entrepreneurs. The Entrepreneurial Executive, 17(1), 61-68.
  19. Hair, J., Anderson, R., Tatham, R. L., & Black, W. C. (1995). Multivariate data analysis with readings. Englewood Cliffs, NJ: Prentice-Hall.
  20. Hughes, C., Swaminathan, V., & Brooks, G. (2019). Driving brand engagement through online social influencers: An empirical investigation of sponsored blogging campaigns. Journal of Marketing, 83(5), 78-96. https://doi.org/10.1177/0022242919854374
  21. Janssen, L., Schouten, A. P., & Verspaget, M. (2020). Celebrity vs influencer endorsements in advertising: the role of identification, credibility, and product-endorser fit. International Journal of Advertising, 39(2), 258-281. https://doi.org/10.1080/02650487.2019.1634898
  22. Kumar, P., & Polonsky, M. J. (2019). In-store experience quality and perceived credibility: a green retailer context. Journal of Retailing and Consumer Services, 49(1), 23-34. https://doi.org/10.1016/j.jretconser.2019.02.022
  23. Lim, X. J., Radzol, A. M., Cheah, J., & Wong, M.W. (2017). The impact of social media influencers on purchase intention and the mediation effect of customer attitude. Asian Journal of Business Research, 7(2), 19-36. https://doi.org/10.14707/AJBR.170035
  24. Lloyd, A. E., & Luk, S. T. K. (2010). The devil wears Prada or Zara: a revelation into customer perceived value of luxury and mass fashion brands. Journal of Global Fashion Marketing, 1(3), 129-141. https://doi.org/10.1080/20932685.2010.10593065
  25. Lou, C., & Xie, Q. (2020). Something social, something entertaining? How digital content marketing augments consumer experience and brand loyalty. International Journal of Advertising, 40(3), 376-402. https://doi.org/10.1080/02650487.2020.1788311
  26. Lou, C., & Yuan, S. (2019). Influencer marketing: how message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58-73. https://doi.org/10.1080/15252019.2018.1533501
  27. McMillan, S. J., & Hwang, J. S. (2002). Measures of perceived interactivity: An exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity. Journal of Advertising, 31(3), 29-42. https://doi.org/10.1080/00913367.2002.10673674
  28. Metzger, M. J., & Flanagin, A. J. (2013). Credibility and trust of information in online environments: The use of cognitive heuristics. Journal of Pragmatics, 59(1), 210-220. https://doi.org/10.1016/j.pragma.2013.07.012
  29. Metzger, M. J. (2007). Making sense of credibility on the web: Models for evaluating online information and recommendations for future research. Journal of the American Society for Information Science and Technology, 58(13), 2078-2091. https://doi.org/10.1002/asi.20672
  30. Mohan, G. (2020). The role of retargeted advertisements in dealing with deflecting customers and its impact on the online buying process. International Journal of Internet Marketing and Advertising, 14(4), 417-432. https://doi.org/10.1504/IJIMA.2020.111050
  31. Morimoto, M., & La Ferle, C. (2008). Examining the influence of culture on perceived source credibility of Asian Americans & the mediating role of similarity. Journal of Current Issues & Research in Advertising, 30(1), 49-60. https://doi.org/10.1080/10641734.2008.10505237
  32. Munnukka, J., Uusitalo, O., & Toivonen, H. (2016). Credibility of a peer endorser and advertising effectiveness. Journal of Consumer Marketing, 33(3), 182-192. https://doi.org/10.1108/JCM-11-2014-1221
  33. Nguyen, N. T. (2020). The influence of celebrity endorsement on young Vietnamese consumers' purchasing intention. Journal of Asian Finance, Economics, and Business, 8(1), 951-960. https://doi.org/10.13106/jafeb.2021.vol8.no1.951
  34. Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers' perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39-52. https://doi.org/10.1080/00913367.1990.10673191
  35. Pham, H. T., Hoang, K. T., Nguyen, T. T., Do, P. H., & Mar, M. T. C. (2021). Sharing economy: Generation Z's intention toward online fashion rental in Vietnam. Journal of Asian Finance, Economics, and Business, 8(3), 997-1007. https://doi.org/10.13106/jafeb.2021.vol8.no3.0997
  36. Pixability. (2014). Beauty on YouTube. https://www.pixability.com/insights-reports/beauty-YouTube-2014/
  37. Pornpitakpan, C. (2004). The effect of celebrity endorsers' perceived credibility on product purchase intention. Journal of International Consumer Marketing, 16(2), 55-74. https://doi.org/10.1300/J046v16n02_04
  38. Rebelo, M. (2017). How influencers' credibility on Instagram is perceived by consumers and its impact on purchase intention [Doctoral Dissertation, The Catholic University of Portugal]. The Catholic University of Portugal Repository. http://repositorio.ucp.pt/bitstream/10400.14/23360/1/TESE_FINAL% 20PDFA.pdf
  39. Rifon, N. J., Choi, S. M., Trimble, C. S., & Li, H. (2004). Congruence effects in sponsorship: The mediating role of sponsor credibility and consumer attributions of sponsor motive. Journal of Advertising, 33(1), 30-42. https://doi.org/10.1080/00913367.2004.10639151
  40. Rodrigues, L. C., Riscarolli, V., Zucco, F. D., & Falaster, C. (2018). Innovations in communication and advertising: A perspective from small firms in southern Brazil. International Journal of Internet Marketing and Advertising, 12(4), 325-339. http://dx.doi.org/10.1504/IJIMA.2018.10016357
  41. Rosara, N. A., & Luthfia, A. (2020). Factors influencing consumer's purchase intention on beauty products in Youtube. Journal of Asian Finance, Economics, and Business, 18(6), 37-46. https://doi.org/10.15722/jds.18.6.202006.37
  42. Schivinski, B., & Dabrowski, D. (2014). The effect of social media communication on consumer perceptions of brands. Journal of Marketing Communications, 9(1), 1-26. http://dx.doi.org/10.1080/13527266.2013.871323
  43. Spears, N., & Singh, S. N. (2004). Measuring attitude toward the brand and purchase intentions. Journal of Current Issues and Research in Advertising, 26(2), 53-66. https://doi.org/10.1080/10641734.2004.10505164
  44. Strolovitch, D. Z. (2006). Do interest groups represent the disadvantaged? Advocacy at the intersections of race, class, and gender. The Journal of Politics, 68(4), 894-910. https://doi.org/10.1111/j.1468-2508.2006.00488.x
  45. Suhr, D. D. (2006). Exploratory or confirmatory factor analysis. San Francisco, CA: SAS Institute Inc.
  46. Sundar, S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In: Metzger, M. & Flanagin, A. (Eds.), Digital media, youth, and credibility (pp. 73-100). Cambridge, MA: MIT Press.
  47. Van der Waldt, D., Van Loggerenberg, M., & Wehmeyer, L. (2009). Celebrity endorsements versus created spokespersons in advertising: a survey among students. SAJEMS, 12(1), 110-114. https://doi.org/10.4102/sajems.v12i1.263
  48. Wang, S. W., Kao, G. H. Y., & Ngamsiriudom, W. (2017). Consumers' attitude of endorser credibility, brand, and intention with respect to celebrity endorsement of the airline sector. Journal of Air Transport Management, 60(1), 10-17. https://doi.org/10-1710.1016/j.jairtraman.2016.12.007
  49. Wells, C. S., & Wollack, J. A. (2003). An instructor's guide to understanding test reliability. Madison: University of Wisconsin.
  50. Wu, J. J., & Chang, Y. S. (2005). Towards understanding members' interactivity, trust, and flow in the online travel community. Industrial Management & Data Systems, 7(105), 937-954. https://doi.org/10.1108/02635570510616120
  51. Wu, S. I., & Lo, C. L. (2009). The influence of core-brand attitude and consumer perception on purchase intention towards the extended product. Asia Pacific Journal of Marketing and Logistics, 21(1), 174-194. https://doi.org/10.1108/13555850910926317
  52. Xiao, M., Wang, R., & Chan-Olmsted, S. (2018). Factors affecting YouTube influencer marketing credibility: A heuristic-systematic model. Journal of Media Business Studies, 15(3), 1-26. https://doi.org/10.1080/16522354.2018.1501146
  53. Zhang, X., Yang, H., Yan, Y., Liu, K., & Huang, C. (2018). Exploring the effect of social media information quality, source credibility and reputation on informational fit-to-task: Moderating role of focused immersion. Computers in Human Behaviour, 79(1), 227-237. https://doi.org/10.1016/j.chb.2017.10.038