The mediating effect of brand image on the relationship between E-WOM and purchase intention: the case study of FOREO skin-care devices

Abstract

Electronic Word of Mouth (eWOM) is increasingly prominent in marketing communication tools. Online buyers tend to research more on the product before deciding to purchase. This paper examines the mediating effect of eWOM on FOREO skin-care device purchase intention in Vietnam, focusing on the mediating role of brand image. SPSS 26 and AMOS 24 software were utilized to process online survey data from 412 respondents. The findings demonstrated that eWOM credibility, quantity, and quality positively affected brand image. Credibility is the most important factor, followed by quality and quantity. The study also indicated that brand image mediates between country-of-origin image and purchase intention. Despite the limitations, the author has proposed the significance of the role of practical management in this research as well as recommendations for future studies.

Full text

MARKETING | RESEARCH ARTICLE
COGENT BUSINESS & MANAGEMENT
2025, VOL. 12, NO. 1, 2471532
The mediating eect of brand image on the relationship between
E-WOM and purchase intention: the case study of FOREO skin-care
devices
Cuong Nguyena , Sam Phamb and Ly Nguyenc
aFaculty of Commerce and Tourism, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam; bDepartment of
Business Studies, HELP University, Kuala Lumpur, Malaysia; cFaculty of Economics and Management, International School,
Vietnam National University, Ha Noi, Vietnam
ABSTRACT
Electronic Word of Mouth (eWOM) is increasingly prominent in marketing communication
tools. Online buyers tend to research more on the product before deciding to purchase.
This paper examines the mediating effect of eWOM on FOREO skin-care device purchase
intention in Vietnam, focusing on the mediating role of brand image. SPSS 26 and
AMOS 24 software were utilized to process online survey data from 412 respondents.
The findings demonstrated that eWOM credibility, quantity, and quality positively
affected brand image. Credibility is the most important factor, followed by quality and
quantity. The study also indicated that brand image mediates between country-of-
origin image and purchase intention. Despite the limitations, the author has proposed
the significance of the role of practical management in this research as well as
recommendations for future studies.
1. Introduction
In digital marketing era, firms faced new opportunities and obstacles when communicating with customers
and disseminating promotional materials online. Because of the Internet’s reach, transparency, and accessi-
bility, word-of-mouth (WOM) marketing still attracts the attention of marketers (Kozinets et al., 2010). When
consumers’ decisions and purchase intentions depend on companies’ online ads, WOM has also helped
drive consumers to the buying phase (Al Halbusi & Tehseen, 2018). Due to Internet technology, WOM has
transformed into eWOM due to technological advancements. The influence of social communities has qui-
etly surpassed traditional media. Electronic word-of-mouth (eWOM) is far greater than in other forms of
traditional advertising. More and more enterprises hire key opinion leaders (KOLs) to write product-related
comments, hoping to influence the purchasing behavior of other users in the community (Mayopu et al.,
2024). Online platforms such as websites, blogs, forums, and social media are utilized for eWOM commu-
nication, which entails words, indirect encounters, anonymous or public comments, and product evaluation
(Bussiere, 2000). In January 2021, statista.com reported 4.66 billion active Internet users, representing 59.5%
of the global population. Consumers can readily communicate their thoughts on multiple online venues,
increasing their ability to reach a large global audience (Goldsmith & Horowitz, 2006; Hennig-Thurau et al.,
2004). Morris (2009) found that consumers have more influence today since people trust those who have
utilized the product or service more than marketers. In a situation where eWOM has the potential to
become an effective marketing strategy, the product information will be more detailed and precise online,
which affects the brand image and customer purchase intention (Evgeniy et al., 2019). Businesses are
© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
CONTACT Cuong Nguyen cuongnguyen4b@gmail.com, nguyenquoccuong@iuh.edu.vn Faculty of Commerce and Tourism, Industrial
University of Ho Chi Minh City, Vietnam
https://doi.org/10.1080/23311975.2025.2471532
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been
published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
ARTICLE HISTORY
Received 11 December
2023
Revised 23 January 2025
Accepted 19 February
2025
KEYWORDS
eWOM; brand image;
purchase intention;
skin-care devices;
CFA-SEM
JEL CLASSIFICATION
M31; L15; L86; D83
SUBJECTS
Cultural Studies;
Information &
Communication
Technology (ICT); Internet
& Multimedia -
Computing & IT

2 C. NGUYEN ETAL.
developing social marketing tactics as more people utilize the Internet and share their experiences (Kaplan
& Haenlein, 2010). Thus, firms must understand how eWOM affects consumers’ purchase intention since the
brand image can affect earnings and sales (Chevalier & Mayzlin, 2006; Liu, 2006). The demand for effective
facial cleansing methods to remove dirt and sebum has recently increased (Vierkötter et al., 2010). Besides,
facial cleansing devices are effective and safe for cleaning the pores and strengthening the skin barrier
(Gold et al., 2019; Jd & Facms, 2019). The FOREO brand makes cosmetic equipment and devices, and it is
famous for its facial washing devices (Mangtani et al., 2020). The increasing use of the internet and the
trend in the digital era have changed the company’s marketing strategy from traditional to digital, so the
unique nature of information exchange on social media is essential to explore its influence (Purwianti &
Niawati, 2022). According to Digital 2023 report, there were 77.93 million internet users in Vietnam at the
start of 2023, when internet penetration stood at 79.1 percent. Vietnam was home to 70.00 million social
media users in January 2023, equating to 71.0 percent of the total population. Hence, this paper has three
main objectives: (1) the effect of eWOM on the brand image of FOREO brand; (2) the essential mediate role
of brand image in the intention to purchase FOREO facial cleansing device; (3) the influence of eWOM on
FOREO brand image among Vietnamese consumers. The study enriches the extant literature by filling gaps
such as improving the generalizability of the findings, providing an integrated framework and using E-WOM
in emerging markets like Vietnam.
2. Literature review
2.1. Perceived eWOM
Word of mouth is considered to be one of the pre-eminent mediums of communication for the consumer
to exchange information regarding product/service which ultimately affects the behaviour of consumers
(Kaushal et al., 2023). eWOM communication refers to any favourable or negative statement made by future,
current, or past customers about the organisation or its products via the Internet (Hennig-Thurau et al.,
2004). In addition, Luís Abrantes et al. (2013) expanded the definition of eWOM to include the informal
exchange of information, advice, or opinions about a product or service via online social networking sites.
Companies utilize eWOM to collect, evaluate, analyze, and infer an individual’s online influence (Jalilvand &
Samiei, 2012). According to Hennig-Thurau et al. (2004), eWOM distribution is any comment about the
company or its products and services that fulfils all three conditions: potential, actual, and prior consumers.
Hervas-Drane (2015) suggest that eWOM may also provide information about items that is not controlled
by the producer, such as bad reviews. Most companies aim to eliminate negative eWOM and boost positive
eWOM (Mayzlin et al., 2014). Companies must realize that these can backfire since consumers assume that
the eWOMs which they access have been controlled, counterfeited, and overstated by the maker about the
product’s goodness and utility (Chevalier & Mayzlin, 2006). Thus, in today’s technology and Internet context,
the corporation must build customer trust and deliver quality items that match its marketing and promo-
tion. In this investigation, the credibility, quantity, and quality of eWOM will be analyzed.
2.2. Research model and hypothesis development
2.2.1. eWOM credibility
As Internet speeds increase, eWOM gives more information, but not all is credible. Previous research has
identified three sources of credibility: competence, trustworthiness, and experience (Di Battista et al.,
2020; Kok Wei & Li, 2013). Tseng and Fogg (1999) define eWOM credibility as a brand’s product or service
reviewer’s truthfulness. Awad and Ragowsky (2008) also identified that eWOM’s credibility positively influ-
ences brand image. Hence, a customer’s tendency to purchase positively correlates with their belief that
the reviewer or review site is credible; if it is unreliable, customers will ignore it, and such reviews are
worthless (Sussman & Siegal, 2003). In addition, previous scientific research has demonstrated that eWOM
credibility helps businesses build a brand image based on the level of trust it engenders, which then
influences purchase intent (Awad & Ragowsky, 2008; Ho et al., 2021; Park et al., 2007; Prendergast et al.,
2010). Siddiqui et al. (2021) report that consumer’s eWOM credibility has effect on brand image leading
to consumer purchase intentions. Hence, the first hypothesis is stated as follow:

COGENT BUSINESS & MANAGEMENT 3
Hypothesis H1: eWOM credibility positively inuences brand image.
2.2.2. eWOM quantity
eWOM quantity is the total amount of comments uploaded to a particular website (Cheung et al., 2008).
eWOM can be calculated based on the number of available reviews or the length of the reviews (Sicilia &
Ruiz, 2010). Online buyers often try to understand more about a product and its usage to avoid uncertainty
and hazards (Cheung & Thadani, 2010; Jeong & Koo, 2015). Reportedly, WOM volume substantially affects
product sales (Chevalier & Mayzlin, 2006). Previous studies also confirm that the quantity of eWOM posi-
tively improves brand image (Lee etal., 2008; Lin et al., 2013; Zhang et al., 2017). Besides, Farzin and Fattahi
(2018) confirmed significance of the constructs consumer trust, informational influence, sense of belonging,
altruism, moral obligation, and knowledge self-efficacy for consumer engagement in eWOM. In Vietnamese
context, Hoang and Tung (2023) report eWOM quanity positively relates to brand image. Therefore, the
commercial success, consumer recognition, and product quality of a product may all be reflected in its
eWOM volume. Hence, the hypothesis was given as follows:
Hypothesis H2: eWOM quantity positively inuences brand image.
2.2.3. eWOM quality
eWOM quality refers to the persuasive power of a message’s embedded comments. The quality of the
information the sender provides increases the message’s persuasiveness (Bhattacherjee & Sanford, 2006).
Consumers will employ high-quality eWOM to reduce purchase anxiety (Chatterjee, 2001) and access
products and services more sympathetically (Cheung et al., 2008; Sussman & Siegal, 2003). The quality of
information influences consumers in the information-seeking phase based on their adoption of eWOM
communication channels (Cheung et al., 2009). Many scholars have determined that eWOM quality pos-
itively influences brand image (Filieri etal., 2015; Ho etal., 2021; Park etal., 2007). Furthermore, Carvalho
et al. (2021) insist that positive eWOM positively influences brand equity, whereas negative eWOM has a
minor influence on brand equity. So, the hypothesis is suggested as follows:
Hypothesis H3: eWOM quality positively inuences brand image.
2.2.4. Brand image
According to Aaker (2009), brand image is how consumers perceive a particular brand and store
brand-associated information in their subconscious consciousness. Dodds et al. (1991) discovered that
brand image is one of the potential factors influencing consumer behaviour. Companies need to work
on building a positive reputation for their brand over time due to the high level of competition in
today’s market (Aaker, 2009; Lee et al., 2008; Park & Kim, 2008). Evgeniy et al. (2019) found that WOM
and eWOM marketing substantially affected consumers’ familiarity with and perception of brands.
Mahmud et al. (2024) also argued that a mediating influence of brand image through eWOM leads to
consumers’ purchase intention. Similarly, Khan et al. (2024) found that brand image mediates the rela-
tionship between eWOM and purchase intention. Farzin and Fattahi (2018) insist that eWOM played a
significant role in shaping brand image in the mind of consumers and their purchase intention. Kala and
Chaubey (2018) confirms the significant effect of eWOM on brand image and the moderating role of the
brand image between eWOM and purchase intention. Hence, the fourth hypothesis is stated as follows:
Hypothesis H4: Brand image positively inuences purchase intention.
2.2.5. Purchase intention
Customer purchase intention is transactional behaviour after evaluating a product or service (Schiffman
& Kanuk, 2010). Customers want to acquire a product or service if they require one that meets their
needs (Evgeniy et al., 2019). Consumers always investigate products before buying them (Wang et al.,
2012). eWOM communication’s most variable outcome is purchase intention (Sher & Lee, 2009).
Consequently, the brand’s image will become either positive or negative based on the level of eWOM.

4 C. NGUYEN ETAL.
All of these factors contribute to the customer’s purchase intent. Shukla (2011) confirm the consistency
between person-to-person or eWOM can influence purchase intent persuasively. On the other hand,
Esparza-Huamanchumo et al. (2024) argued that information usefulness is the eWOM dimension that
most influences purchase intention.
Based on the above arguments, the author proposes the research model in Figure 1.
3. Method
The research method employed a quantitative confirmatory factor analysis (CFA). Data is analysed by
SPSS 26.0 and AMOS 24.0 software to test the reliability and validity of the measuring scale and the
research model’s hypotheses. Ethical approval was obtained for the study by Science and Education
Council of Industrial University of Ho Chi Minh City. The informed consent for participation in the study
has been obtained from respondents by clicking to accept.
3.1. Sample and data collection
The data were obtained by distributing structured questionnaires via Google Forms to customers in
Vietnam using the convenience sampling technique. Respondents have option to choose to participate
or not. If respondents choose to join the questionaire, they will provide their consent by clicking the ‘I
agree’ on Google Forms. Authors informed respondents that all data collected is only used for scientific
purpose only. Data was collected from January to June 2023. The questionaire survey was written in
Vietnamese to ensure participants fully understand the content. The Google Forms link was sent by
respodents who are the members of cosmetic online group and forums in Vietnam. Data sharing for
third party is not allowed. The questionnaire was composed of 28 items organized into three sections.
The first question is a screening question. The second section contains items regarding demographics
and individual behaviour. Twenty items on a 5-point Likert Scale comprise the third section, which con-
sists of the main questions used to measure. According to Hair (2010) calculations, the optimal sample
size would consist of five respondents for each studied item (5:1). Therefore, 412 out of 420 question-
naires are usable for further study. Of the total responses, 119 were males (28.9%) and 293 females
(71.1%). There are 20% of people between the ages of 18 and 25, 31% between the ages of 26 and 31,
19% between the ages of 32 and 37, and 9% between the ages of 38 and 43. The respondents’ monthly
income was broken down as follows: 169 (41%) had an income of less than VND 8 million, 202 (49%)
had an income of between VND 8 and 14 million, 28 (6.7%) had an income of between VND 15 and 20
million, and 13 (3.2%) had an income of more than VND 20 million.
3.2. Questionnaire
Except for demographic and product type questions, all questionnaire items are measured on a five-point
Likert scale (1 = ‘Totally disagree’ to 5 = ‘Totally agree’). Participants were requested to respond to the
queries presented in Table 1.
Figure 1. Proposed research model.

COGENT BUSINESS & MANAGEMENT 5
4. Result
4.1. Measurement scale testing
Confirmatory factor analysis (CFA) was applied to the accomplish framework. One item with upload in
both factor 1 and factor 2 was removed (details shown in Table 1).
According to the results, the degree of freedom is 412, and this model is appropriate for market data
(Chi-square/df = 1.23, CFI = 0.958 > 0.9, GFI = 0.992 > 0.9, TLI = 0.990 > 0.9, and RMSEA = 0.0220.08).
Because brand image and purchase intent scales do not correlate with measurement errors, the observed
variables are unidirectional, whereas eWOM credibility, eWOM quality, and eWOM quantity are not. The
standardized weights of the observed variables range from 0.709 to 0.844, which is acceptable (greater
than 0.5), and the unstandardized weights are statistically significant (P = 0.00) with a 95% degree of
reliability. As a result, the observed variables used to measure concepts attain the necessary level of
convergence. The components attain their unique values as the correlation coefficients of various pair
concepts are statistically significant relative to 1. Cronbach’s alpha reliability and Composite Reliability of
the components are greater than 0.8, and the variance extract is greater than 0.5, as determined by the
concepts’ testing reliability and variance extract. Consequently, all measurement instruments offer high
dependability (Hair, 2010).
4.2. Result of SEM analysis
The results of testing the structural model (Figure 2) indicate that the model has 412 degrees of free-
dom, with a P-value of 0.000.05. The indicators correspond to market data (Chi-square/df3; CFI, GFI, TLI
> 0.9; RMSEA < 0.08).
Table 1. Factor weights of the measurement scale.
Variables Weight References
eWOM credibility (α = 0.846, CR = 0.82, AVE = 0.53)
1 eWC1 I feel condent having discussions with online contacts
about FOREO devices
.816 Bataineh (2015)
Evgeniy et al. (2019)
2 eWC2 Most contacts on my social networking site can be trusted .817 (removed)
3 eWC3 Online comments about FOREO’s devices are reliable .807
4 eWC4 Online comments about FOREO’a devices are honest .816
5 eWC5 I can believe in the contacts on my social networking site .818
eWOM quantity (α = 0.829, CR = 0.83, AVE = 0.62)
6 eWQT1 FOREO’s devices are reviewed and recommended on many
online platforms
.736 Bataineh (2015)
7 eWQT2 The higher the number of FOREO reviews, the more
condent it is to buy
.771
8 eWQT3 The high-ranking review of FOREO proves the credibility
and safety of the product.
.781
eWOM quality (α = 0.841, CR = 0.85, AVE = 0.58)
9 eWQL1 Online shopping for AC enables me to save my time .817 Bataineh (2015)Balroo and
Saleh (2019)10 eWQL2 Online shopping for AC makes it possible to shop at my
convenience (i.e. anytime, anywhere)
.787
11 eWQL3 Overall, shopping on the internet is useful .807
12 eWQL4 I purchase AC online because there is no embarrassment
if I do not buy
.787
Brand Image (α = 0.851, CR = 0.85, AVE = 0.54)
13 BRAIM1 FOREO’s devices are reliable .810 Evgeniy et al. (2019)
Balroo and Saleh (2019)14 BRAIM2 FOREO’s devices discussed in the online reviews/comments
have a distinguished image
.809
15 BRAIM3 FOREO’s devices discussed in the online reviews/comments
are known
.844
16 BRAIM4 The customers prefer FOREO’s devices discussed in the
online reviews/comments
.823
17 BRAIM5 FOREO’s devices discussed in the online reviews/comments
are stable
.815
Purchase Intention (α = 0.808, CR = 0.81, AVE = 0.59)
18 PI1 In the future, I intend to buy the FOREO’s facial cleansing
devices mentioned in the online reviews/comments
.765 Evgeniy et al. (2019)
Schiman et al. (2000)
19 PI2 I will consider buying FOREO’s facial cleansing device after
Reading online reviews/comments about the product
.735
20 PI3 I am willing to recommend others to buy FOREO’s facial
cleansing device
.709

6 C. NGUYEN ETAL.
Table 2 displays the results of estimating the model’s major parameters, which indicates that the mod-
el’s relationships are statistically significant (P < 0.05). As a result, we accept hypotheses H1, H2, H3, and H4.
5. Discussion
5.1. Theoretical implications
This study is the first attempt to investigate and analyze the factors influencing purchase intention in
the beauty field in Vietnam, focusing on a facial cleansing device sold by FOREO via the mediating role
of brand image. The findings indicate that eWOM credibility has a positive impact on brand image and
it is consistent with previous studies (Awad & Ragowsky, 2008; Ho et al., 2021; Prendergast et al., 2010;
Siddiqui et al., 2021). Buyers tend to trust KOLs, celebs, and beauty bloggers who post product reviews
on Facebook, Instagram, YouTube, and blogs (Nguyen & My To, 2022). Hence, eWOM and the intermedi-
ary who examined and gave product feedback lend legitimacy to the business’s brand image, increasing
product appreciation and purchasing ability. The more eWOMs on electronic platforms and online envi-
ronments, the more positive reviews and information about products, and the higher the product rank-
ing the consumer is interested in, the better the brand’s reputation. Moreover, the quality of eWOM must
be considered alongside the quantity of eWOM since the communicator’s online product reviews
Figure 2. Results of SEM analysis of proposed research models (standardized).
Table 2. Regression coecients of relationships in the theoretical model.
Hypothesis Relationships
Unstandardized
coecients
Standardized
coecients Standard errors Critical value P-value
H1 eWC-> BRAIM .420 .465 .059 7.11 0.000
H2 eWQT -> BRAIM .099 .128 .046 2.17 0.030
H3 eWQL -> BRAIM .313 .334 .050 6.25 0.000
H4 BRAIM -> PI .736 .607 .076 9.66 0.000

COGENT BUSINESS & MANAGEMENT 7
(Carvalho et al., 2021; Ho et al., 2021). The comments must be clear, functional, and understood to the
recipient and reaffirm the trust reason to buy from the customers. Their products are worth buying since
they believe the quality of eWOM will improve the brand’s reputation. Therefore, eWOM quality positively
influences brand image and it is consistent with many previous studies (Carvalho etal. (2021; Filieri et al.,
2015; Ho et al., 2021; Park et al., 2007). Finally, the three elements of eWOM affect brand image and
purchase intention. If one of the three eWOM dimensions shifts the other way, the brand image is
affected. Brand image increases product users’ purchasing power, and when customers embraced eWOM
and applied it unwittingly or purposefully, it improved their purchasing decisions and intentions.
Accordingly, focusing on eWOM as a marketing tool will increase the propensity to purchase, the inten-
tion to recommend products to others, and the likelihood of future purchases.
5.2. Practical implications
Based on the findings, the author offers suggestions for how other companies in the beauty industry,
not just FOREO, can use the eWOM tool to create the most positive brand image possible, thereby
increasing customer purchase intent. Marketers should invest in their website’s content, visuals, and
speed to boost eWOM’s reputation and develop a product/service fanpage with all the information
required. Businesses should utilize SEO, landing page, and ad strategies to boost website and fanpage
rankings on Google and seek KLOs, Celebs, and Beauty Bloggers with large followers and interactions,
product/service knowledge, and brand image consistency. They can then indirectly promote the product
online, which boosts its reputation, visibility, and reach to new clients and prospects. It can be said that
eWOM exists online on any platform where customers may share and discuss thoughts and personal
views. Therefore, firms could employ objective marketing efforts to encourage product users to leave
reviews, feedback, and ratings on their personal accounts, blogs, and e-commerce sites. Businesses
should also build a ‘Review about us’ page or forum for the beauty community and customers to freely
exchange information and measure customer voice. Businesses can assess brand image, product/service
quality, and client purchasing intentions. Marketers should develop user interfaces and categorise each
item in product evaluation according to usage, function, origin of product components, and pricing to
give customers clear, intelligible, and detailed information. Marketers can improve eWOM by asking
beauty professionals and doctors to review products on YouTube, Facebook, and TikTok. Expert reviews
boost brand image by demonstrating product quality and reliability. For a company’s brand image to
favourably affect consumers’ propensity to purchase, eWOM must be used effectively. Because eWOM is
created between customers, it is difficult for businesses to control it completely. Thus, product quality
that matches advertising is the only way to reduce negative eWOM. Because unfavourable eWOM is
linked to customer dissatisfaction with products and services. Companies should continually enhance
their products, fix design flaws, and add value to ensure customers get good value for their money.
Most importantly, eWOM will always discuss the company’s innovative and intelligent branded market-
ing plan.
6. Conclusions
Regarding discussion, this study finds the relationship between eWOM and purchase intention. Brand
image plays a full mediating role between eWOM and purchase intention. This study also indicates that
when the degree of eWOM credibility, eWOM quantity and eWOM quality is high, the indirect effect of
eWOM on the purchase intention via brand image is strong; on the contrary, when the degree of the
three dimensions of eWOM is low, the effect of eWOM on the brand image and purchase intention is
weak. This study, like any other, has limitations despite its results. Future research should consider these
limits to maximize results. This study initially solely covers Ho Chi Minh City because the respondents are
there. This study’s methodology cannot accurately reflect Vietnamese consumers’ intent to buy FOREO’s
face-washing equipment. This study exclusively examined FOREO’s skin-care device purchasing intention,
not other brands. Due to limited resources, price, marketing, and corporate social responsibility, which
may potentially influence FOREO customers’ purchasing intentions, are not conducted in this study. Third,

8 C. NGUYEN ETAL.
snowball and convenience sampling yielded 412 respondents that cannot represent all Ho Chi Minh City
residents. Besides, competitive marketing methods, political factors, and economic variations can also
affect buying intention. Future studies should consider these limitations. First, future research should
include other important cities and provinces in Vietnam, not just Ho Chi Minh City, to collect more data.
Second, research should include credibility, quantity, quality, brand image, and the three eWOM aspects.
Moreover, future research should combine qualitative and quantitative methodologies.
Author contributions
Cuong Nguyen was involved in the conception, design, data analysis and interpretation. Sam Phan was involved in
data collection, analysis, and paper drafting. Ly Nguyen was involved in revising it critically for intellectual content.
All authors agree to be accountable for all aspects of the work.
Disclosure statement
No potential conict of interest was reported by the author(s).
About the authors
Assoc. Prof. Dr. Cuong Nguyen is the Dean of the Faculty of Commerce and Tourism at the Industrial University of
Ho Chi Minh City in Vietnam. He received a Bachelor of Business from La Trobe University (Australia), a Master of
Management from the University of Wollongong (Australia) and a PhD degree in Management Science from the
University Paris 1 Panthéon-Sorbonne (France). Assoc. Prof. Dr. Cuong Nguyen is a full member of Sigma Xi, The
Scientic Research Honor Society. His research elds include entrepreneurship, marketing, management and tourism.
Sam Pham received a Bachelor of Business from HELP University (Malaysia). She studied at the Department of
Business Studies, HELP University, Malaysia. MS. Sam Pham completed her thesis under the supervision of Assoc.
Prof. Dr. Cuong Nguyen.
Sam Pham received a Bachelor of Business from HELP University (Malaysia). She studied at the Department of
Business Studies, HELP University, Malaysia. MS. Sam Pham completed her thesis under the supervision of Assoc.
Prof. Dr. Cuong Nguyen.
Ly Nguyen is a lecturer at the Faculty of Economics and Management, International School, VNU Hanoi. She holds a
Master’s degree in Marketing from the University of Kent, UK, and a Bachelor’s degree in International Economics
from the University of Economics and Law, VNU Ho Chi Minh City. Her research interests include marketing, elec-
tronic word-of-mouth (eWOM), and consumer behaviour.
Data availablity statement
The participants of this study did not give written consent for their data to be shared publicly, so due to the sen-
sitive nature of the research supporting data is not available.
ORCID
Cuong Nguyen http://orcid.org/0000-0001-7842-0564
Ly Nguyen http://orcid.org/0000-0002-6129-1556
References
Aaker, D. (2009). Aaker’s brand equity model. European Institute for Brand Management.
Al Halbusi, H., & Tehseen, S. (2018). The eect of Electronic Word-Of-Mouth (EWOM) on brand im-age and purchase
intention: A conceptual paper. SocioEconomic Challenges, 3(2), 83-94. https://doi.org/10.21272/sec.3(2).83-94.2018
Awad, N. F., & Ragowsky, A. (2008). Establishing trust in electronic commerce through online word of mouth: An
examination across genders. Journal of Management Information Systems, 24(4), 101–121. https://doi.org/10.2753/
MIS0742-1222240404
Balroo, S. A., & Saleh, M. A. H. (2019). Perceived eWOM and students’ university enrolment intentions: The corporate
image as a mediator. Journal of Economics, Management and Trade, 24(1), 1–14. https://doi.org/10.9734/jemt/2019/
v24i130152

COGENT BUSINESS & MANAGEMENT 9
Bataineh, A. Q. (2015). The impact of perceived e-WOM on purchase intention: The mediating role of corporate im-
age. International Journal of Marketing Studies, 7(1), 126.
Bhattacherjee, A., & Sanford, C. (2006). Inuence processes for information technology acceptance: An elaboration
likelihood model. MIS Quarterly, 30(4), 805–825. https://doi.org/10.2307/25148755
Bussiere, D. (2000). Evidence and implications of electronic word-of-mouth. Proceedings of the Academy of Marketing
Science Conference, Quecbec, Canada.
Carvalho, L., Brandão, A., & Pinto, L. H. (2021). Understanding the importance of eWOM on higher education institu-
tions’ brand equity. Journal of Marketing for Higher Education, 31(2), 261–279. https://doi.org/10.1080/08841241.20
20.1788196
Chatterjee, P. (2001). Online reviews: Do consumers use them? In: M. C. Gilly, & J. Myers-Levy Provo (eds.), ACR 2001
Proceedings (pp. 129-134). Association for Consumer Research.
Cheung, C. M., Lee, M. K., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: The adoption of online opin-
ions in online customer communities. Internet Research, 18(3), 229–247. https://doi.org/10.1108/10662240810883290
Cheung, C. M., Lee, M. K., & Thadani, D. R. (2009). The impact of positive electronic word-of-mouth on consumer online
purchasing decision. Springer.
Cheung, C. M., & Thadani, D. R. (2010). The eectiveness of electronic word-of-mouth communication: A literature
analysis. BLED 2010 Proceedings. 18. https://aisel.aisnet.org/bled2010/18
Chevalier, J. A., & Mayzlin, D. (2006). The eect of word of mouth on sales: Online book reviews. Journal of Marketing
Research, 43(3), 345–354. https://doi.org/10.1509/jmkr.43.3.345
Di Battista, S., Pivetti, M., & Berti, C. (2020). Competence and benevolence as dimensions of trust: Lecturers’
trustworthiness in the words of Italian students. Behavioral Sciences, 10(9), 143. https://doi.org/10.3390/
bs10090143
Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Eects of price, brand, and store information on buyers’ product
evaluations. Journal of Marketing Research, 28(3), 307–319. https://doi.org/10.2307/3172866
Esparza-Huamanchumo, R. M., Quiroz-Celis, A. V., & Camacho-Sanz, A. A. (2024). Inuence of eWOM on the purchase
intention of consumers of Nikkei restaurants in Lima, Peru. International Journal of Tourism Cities, 10(4), 1551–1567.
https://doi.org/10.1108/IJTC-01-2024-0010
Evgeniy, Y., Lee, K., & Roh, T. (2019). The eect of eWom on purchase intention for Korean-brand cars in Russia: The
mediating role of brand image and perceived quality. Journal of Korea Trade, 23(5), 102–117. https://doi.
org/10.35611/jkt.2019.23.5.102
Farzin, M., & Fattahi, M. (2018). eWOM through social networking sites and impact on purchase intention and brand
image in Iran. Journal of Advances in Management Research, 15(2), 161–183. https://doi.org/10.1108/
JAMR-05-2017-0062
Filieri, R., Alguezaui, S., & McLeay, F. (2015). Why do travelers trust TripAdvisor? Antecedents of trust towards
consumer-generated media and its inuence on recommendation adoption and word of mouth. Tourism
Management, 51, 174–185. https://doi.org/10.1016/j.tourman.2015.05.007
Gold, M., Ablon, G., Andriessen, A., Goldberg, D., Hooper, D., & Mandy, S. (2019). Facial cleansing with a sonic
brush—A review of the literature and current recommendations. Journal of Cosmetic Dermatology, 18(3), 686–691.
https://doi.org/10.1111/jocd.12906
Goldsmith, R. E., & Horowitz, D. (2006). Measuring motivations for online opinion seeking. Journal of Interactive
Advertising, 6(2), 2–14. https://doi.org/10.1080/15252019.2006.10722114
Hair, J.Jr, (2010). Multvariate data analysis. Pearson Prentice Hall.
Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion
platforms: What motivates consumers to articulate themselves on the internet? Journal of Interactive Marketing,
18(1), 38–52. https://doi.org/10.1002/dir.10073
Hervas-Drane, A. (2015). Recommended for you: The eect of word of mouth on sales concentration. International
Journal of Research in Marketing, 32(2), 207–218. https://doi.org/10.1016/j.ijresmar.2015.02.005
Ho, V. T., Phan, N. T., & Le-Hoang, P. V. (2021). Impact of electronic word of mouth to the purchase intention-the case
of Instagram. Independent Journal of Management & Production, 12(4), 1019–1033. https://doi.org/10.14807/ijmp.
v12i4.1336
Hoang, L. N., & Tung, L. T. (2023). A moderated mediation model of situational context and brand image for online
purchases using eWOM. Journal of Product & Brand Management, 32(4), 661–672. https://doi.org/10.1108/
JPBM-02-2022-3857
Jalilvand, M. R., & Samiei, N. (2012). The impact of electronic word of mouth on a tourism destination choice: Testing
the theory of planned behavior (TPB). Internet Research, 22(5), 591–612. https://doi.org/10.1108/10662241211271563
Jd, D. J. G. M., & Facms, A. O. M. F. (2019). A cohort study using a facial cleansing brush with acne cleansing brush
head and a gel cleanser in subjects with mild-to-moderate acne and acne-prone skin. Journal of Drugs in
Dermatology, 18(11), 1140–1145.
Jeong, H.-J., & Koo, D.-M. (2015). Combined eects of valence and attributes of e-WOM on consumer judgment for
message and product: The moderating eect of brand community type. Internet Research, 25(1), 2–29. https://doi.
org/10.1108/IntR-09-2013-0199

10 C. NGUYEN ETAL.
Kala, D., & Chaubey, D. S. (2018). The eect of eWOM communication on brand image and purchase intention to-
wards lifestyle products in India. International Journal of Services, Economics and Management, 9(2), 143–157.
https://doi.org/10.1504/IJSEM.2018.096077
Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media.
Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003
Kaushal, D., Mishra, A. K., & Bisht, S. (2023). Relation between electronic word of mouth and purchase intention:
Exploring the mediating role of brand image. International Journal of Internet Marketing and Advertising, 19(1/2),
86–99. https://doi.org/10.1504/IJIMA.2023.132720
Khan, Z., Khan, A., Nabi, M. K., & Khanam, Z. (2024). Demystifying the eect of social media usage and eWOM on
purchase intention: The mediating role of brand equity. Journal of Economic and Administrative Sciences. Advance
online publication. https://doi.org/10.1108/JEAS-05-2023-0102
Kok Wei, K., & Li, W. Y. (2013). Measuring the impact of celebrity endorsement on consumer behavioural intentions:
A study of Malaysian consumers. International Journal of Sports Marketing and Sponsorship, 14(3), 2–22. https://doi.
org/10.1108/IJSMS-14-03-2013-B002
Kozinets, R. V., De Valck, K., Wojnicki, A. C., & Wilner, S. J. (2010). Networked narratives: Understanding word-of-mouth
marketing in online communities. Journal of Marketing, 74(2), 71–89. https://doi.org/10.1509/jm.74.2.71
Lee, J., Park, D.-H., & Han, I. (2008). The eect of negative online consumer reviews on product attitude: An informa-
tion processing view. Electronic Commerce Research and Applications, 7(3), 341–352. https://doi.org/10.1016/j.eler-
ap.2007.05.004
Lin, C., Wu, Y. S., & Chen, J.-C. V. (2013 Electronic word-of-mouth: The moderating roles of product involvement and
brand image [Paper presentation]. Proceedings of 2013 International Conference on technology innovation and indus-
trial management.
Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box oce revenue. Journal of Marketing, 70(3),
74–89. https://doi.org/10.1509/jmkg.70.3.074
Luís Abrantes, J., Seabra, C., Raquel Lages, C., & Jayawardhena, C. (2013). Drivers of in-group and out-of-group electron-
ic word-of-mouth (eWOM). European Journal of Marketing, 47(7), 1067–1088. https://doi.org/10.1108/03090561311324219
Mahmud, M. S., Islam, M. N., Ali, M. R., & Mehjabin, N. (2024). Impact of electronic word of mouth on customers’
buying intention considering trust as a mediator: A SEM approach. Global Business Review, 25(2_suppl), S184–S198.
https://doi.org/10.1177/0972150920976345
Mangtani, N., Bajpai, N., Sahasrabudhe, S., & Wasule, D. (2020). Importance of articial intelligence and augmented
reality in cosmetic and beauty industry post covid 19. World Journal of Pharmaceutical Research, 9(8), 2296–2308.
Mayopu, R. G., Wang, Y. Y., & Chen, L. S. (2024). Exploring the advertising elements of electronic word-of-mouth in
social media: An example of game reviews. Multimedia Tools and Applications, 83(30), 74685–74709. https://doi.
org/10.1007/s11042-024-18642-w
Mayzlin, D., Dover, Y., & Chevalier, J. (2014). Promotional reviews: An empirical investigation of online review manip-
ulation. American Economic Review, 104(8), 2421–2455. https://doi.org/10.1257/aer.104.8.2421
Morris, N. (2009). Understanding digital marketing: Marketing strategies for engaging the digital generation. Journal
of Direct, Data and Digital Marketing Practice, 10(4), 384–387. https://doi.org/10.1057/dddmp.2009.7
Nguyen, C. Q., & My To, L. P. (2022, April). The impacts of Electronic Word of Mouth (EWOM) on cosmetics purchase
intention among young consumers in Vietnam. Proceedings of the 4th International Conference on Management
Science and Industrial Engineering (pp. 9–16).
Park, D.-H., & Kim, S. (2008). The eects of consumer knowledge on message processing of electronic word-of-mouth
via online consumer reviews. Electronic Commerce Research and Applications, 7(4), 399–410. https://doi.org/10.1016/j.
elerap.2007.12.001
Park, D.-H., Lee, J., & Han, I. (2007). The eect of on-line consumer reviews on consumer purchasing intention: The
moderating role of involvement. International Journal of Electronic Commerce, 11(4), 125–148. https://doi.
org/10.2753/JEC1086-4415110405
Prendergast, G., Ko, D., & Siu Yin, V. Y. (2010). Online word of mouth and consumer purchase intentions. International
Journal of Advertising, 29(5), 687–708. https://doi.org/10.2501/S0265048710201427
Purwianti, L., & Niawati, N. (2022). Analysis of e-WOM, brand attitude, brand image on purchase intention. SEIKO:
Journal of Management & Business, 5(1), 356–366.
Schiman, L. G., & Kanuk, L. L. (2010). Consumer behavior. Pearson Prentice Hall.
Schiman, L. G., Kanuk, L. L., & Wisenblit, J. (2000). Consumer behavior. Prentice Hall.
Sher, P. J., & Lee, S.-H. (2009). Consumer skepticism and online reviews: An elaboration likelihood model perspective.
Social Behavior and Personality: An International Journal, 37(1), 137–143. https://doi.org/10.2224/sbp.2009.37.1.137
Shukla, P. (2011). Impact of interpersonal inuences, brand origin and brand image on luxury purchase intentions:
Measuring interfunctional interactions and a cross-national comparison. Journal of World Business, 46(2), 242–252.
https://doi.org/10.1016/j.jwb.2010.11.002
Sicilia, M., & Ruiz, S. (2010). The eects of the amount of information on cognitive responses in online purchasing
tasks. Electronic Commerce Research and Applications, 9(2), 183–191. https://doi.org/10.1016/j.elerap.2009.03.004
Siddiqui, M. S., Siddiqui, U. A., Khan, M. A., Alkandi, I. G., Saxena, A. K., & Siddiqui, J. H. (2021). Creating electronic
word of mouth credibility through social networking sites and determining its impact on brand image and online

COGENT BUSINESS & MANAGEMENT 11
purchase intentions in India. Journal of Theoretical and Applied Electronic Commerce Research, 16(4), 1008–1024.
https://doi.org/10.3390/jtaer16040057
Sussman, S. W., & Siegal, W. S. (2003). Informational inuence in organizations: An integrated approach to knowledge
adoption. Information Systems Research, 14(1), 47–65. https://doi.org/10.1287/isre.14.1.47.14767
Tseng, S., & Fogg, B. (1999). Credibility and computing technology. Communications of the ACM, 42(5), 39–44. https://
doi.org/10.1145/301353.301402
Vierkötter, A., Schikowski, T., Ranft, U., Sugiri, D., Matsui, M., Krämer, U., & Krutmann, J. (2010). Airborne particle ex-
posure and extrinsic skin aging. The Journal of Investigative Dermatology, 130(12), 2719–2726. https://doi.
org/10.1038/jid.2010.204
Wang, J., Cheng, Y., & Chu, Y. (2012). Product familiarity and learning new information. Journal of Consumer Research,
11(1), 542–550.
Zhang, T. C., Omran, B. A., & Cobanoglu, C. (2017). Generation Y’s positive and negative eWOM: Use of social media
and mobile technology. International Journal of Contemporary Hospitality Management, 29(2), 732–761. https://doi.
org/10.1108/IJCHM-10-2015-0611