Social Networking Platforms and Electronic Word-of-Mouth: The Mediating Role of Trust in Vietnamese Consumers’ Smartphone Purchasing Decisions ()
1. Introduction
Vietnam has become one of Southeast Asia’s most dynamic smartphone markets, supported by a population exceeding 90 million and rapid digital adoption. Early reports indicated that more than 20 million smartphones were in circulation by 2016, corresponding to a penetration rate of approximately 36%. Continued growth in mobile connectivity, social media use, and digital consumption has further strengthened the role of smartphones in Vietnamese consumers’ everyday lives. Smartphones have evolved beyond basic communication tools into essential devices supporting photography, video, entertainment, social interaction, financial transactions, and access to a broad ecosystem of applications.
In recent years, the role of social networking platforms in consumer decision-making has become increasingly prominent, particularly in emerging markets [1] [2]. In this dynamic environment, brand impressions spread quickly through online reviews, social media posts, comments, and interpersonal recommendations. Consumers share positive or negative experiences on social networking platforms or through face-to-face advice, influencing others’ perceptions of brand quality, credibility, and reliability. Nielsen’s 2015 Global Trust in Advertising survey highlighted the exceptional credibility of personal and online sources among Vietnamese consumers: 89% trusted recommendations from family and friends, while 75% valued consumer opinions posted online. Although these figures provide historical context, more recent research continues to show that social networking platforms and eWOM remain influential sources of product information in Southeast Asia and Vietnam [3] [4].
Word-of-mouth (WOM) has long been recognized as a powerful influence on human decision-making because individuals frequently learn from the experiences and evaluations of others. Traditional advice, whether actively sought or passively received, can reduce uncertainty and guide consumer choice. With the expansion of social networking platforms and influencer-mediated communication, eWOM has emerged as an important complement to traditional interpersonal recommendations [5] [6]. Consumers can now access large volumes of product-related information from people they know personally and from online users with whom they have no direct relationship.
These two information sources may influence consumers through different mechanisms. Social network WOM derives its influence from the accessibility, visibility, volume, and apparent consensus of online opinions, whereas sender expertise depends on the perceived knowledge, experience, and credibility of a particular information source. This distinction is especially relevant for smartphones, which are relatively expensive, technically complex, and highly visible products. Consumers may therefore consult both online reviews and knowledgeable family members or friends before making a purchase.
Despite the increasing importance of eWOM, further research is needed to explain how online social network information and interpersonal sender expertise jointly influence trust and purchase decisions in emerging markets. Existing studies often examine eWOM as a single construct or focus on consumers’ motivations to create and distribute online content. Less attention has been given to the receiver’s perspective and to whether trust operates as a mechanism through which different forms of WOM affect smartphone purchase decisions in Vietnam.
Accordingly, this study addresses the following research questions: How does social network WOM influence Vietnamese consumers’ trust and smartphone purchase decisions? How does sender expertise influence trust and purchase decisions? To what extent does trust mediate these relationships? The study therefore aims to: 1) examine the effects of social network WOM and sender expertise on smartphone purchase decisions; 2) compare the relative influence of these two WOM dimensions; 3) assess their effects on consumer trust; and 4) determine whether trust mediates their relationships with purchase decisions.
By distinguishing social network WOM from sender expertise, this research contributes to the literature on digital consumer behavior and social influence in emerging markets. It also provides practical insight into how smartphone brands can combine user-generated online content with credible interpersonal and influencer-based communication to strengthen consumer trust.
2. Literature Review
2.1. Consumer Purchasing Decision
Consumer purchasing behavior generally follows five stages: need recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior [7]. The level of involvement in this process influences whether consumers engage in nominal, limited, or extended decision-making. Extended decision-making typically occurs when a purchase is expensive, unfamiliar, technically complex, or associated with meaningful financial or social risk.
According to Solomon, consumer behavior refers to the processes individuals or groups undertake when selecting, purchasing, using, or disposing of products, services, or experiences [8]. Market segmentation plays an important role in understanding consumer needs, as consumers within the same segment often share similar preferences based on demographic, psychographic, or behavioral characteristics [9] [10]. After recognizing a need, consumers search for information from both internal sources (past experience) and external sources, including word-of-mouth, trial, and online social networking [11]. With the rapid development of the internet, online environments have become a major channel for information search and have significantly influenced consumer purchasing decisions [12]. For high-involvement products such as smartphones, consumers may compare technical specifications, prices, user reviews, brand reputations, and recommendations from people they consider knowledgeable. Consequently, purchase decisions are shaped not only by product attributes but also by the credibility and trustworthiness of the information received.
2.2. Word of Mouth
Traditionally, word-of-mouth refers to face-to-face, person-to-person communication between a non-commercial communicator and a receiver regarding a product, organization, or service [13]. Word-of-mouth can be either positive or negative. Positive word-of-mouth involves recommendations and favorable experiences, while negative word-of-mouth involves complaints and unfavorable opinions [14]. Consumers frequently engage in word-of-mouth communication through social interactions, as sharing opinions and experiences is a natural part of daily conversation [15].
Electronic word-of-mouth extends this communication into digital environments. It includes product-related statements, evaluations, recommendations, and experiences shared through social networking platforms, online communities, blogs, forums, review sites, and other digital channels. Compared with traditional WOM, eWOM can reach a larger audience, remain accessible over time, and expose consumers to opinions from both known and unknown sources.
Human beings are inherently social, and social communication has expanded significantly with the development of the internet. Consumers now participate in various online activities to share knowledge, experiences, and opinions [16]. Online social networks and virtual communities have become important communication channels that connect people and influence consumer behavior, including purchasing decisions [17]. Platforms such as forums, blogs, and social networking sites provide spaces where consumers can exchange information and influence one another’s purchase decisions [18]. This study adopts the receiver’s perspective by examining how consumers respond to two distinguishable sources of WOM information: social network WOM and sender expertise. Social network WOM refers to product-related comments, reviews, posts, and feedback encountered through online social networking platforms. Sender expertise refers to recommendations from individuals whom the receiver perceives as experienced or knowledgeable about smartphones.
2.2.1. The Social Network
Consumer behavior is strongly influenced by social groups, family, and social roles [19]. During the decision-making process, consumers collect and evaluate information while being influenced by people around them. For high-involvement products such as smartphones, social influence from friends, peers, and family members is particularly significant [20]. Previous research has also found that social networks are significantly related to students’ dependency on smartphones [21].
Online social networks, including Facebook, Instagram, Twitter, and YouTube, allow individuals to construct public profiles, share experiences, and interact with others who have similar interests [22]. These platforms have changed the way companies and consumers interact, enabling direct communication and relationship building [8]. Bagozzi indicated that “Much of human behavior is not best characterized by an individual acting in isolation” [23]. Online social networks have become a major part of daily communication and significantly influence people’s behavior and decision-making [22].
People often belong to or admire different online groups, and these groups can shape their opinions and purchasing behavior [8]. The environment surrounding consumers, including family, friends, and coworkers, affects their decisions [24]. While consumers previously relied heavily on mass media for information, online social networks now have substantial power to influence purchase decisions [25]. Companies have also shifted their communication strategies toward social networking platforms, which have become more effective in influencing customer behavior [26]. Because online comments and reviews are generated by consumers rather than directly by companies, they may also be perceived as more independent and credible than marketer-controlled communications [27].
2.2.2. Sender Expertise
Interpersonal communication occurs both formally and informally. The strength of the relationship alone may not fully explain influence in purchase decisions. Consumers may deliberately seek the opinion of someone perceived as more experienced or knowledgeable, often referred to as an opinion leader [28]. An opinion leader is someone who possesses greater experience or expertise in a product category and has been exposed to more information about it [28]. Such individuals are often sought out for advice because they are considered highly knowledgeable and willing to share their insights [29]. In the smartphone context, sender expertise may be inferred from a person’s familiarity with brands, technical specifications, software, product performance, or previous purchasing experience. Sender expertise is conceptually different from social network WOM. Social network WOM reflects exposure to information circulating through digital platforms, whereas sender expertise concerns the receiver’s evaluation of a particular communicator’s knowledge and competence. Because knowledgeable senders can reduce uncertainty and simplify product evaluation, their recommendations may exert a particularly strong influence on trust and purchase decisions.
2.3. Trust
Word-of-mouth, whether online or offline, involves communication between a sender and a receiver. Traditionally, face-to-face word-of-mouth builds trust based on familiarity, making the information more likely to be used in purchase decisions [30] [31]. In the online context, even when the sender and receiver do not know each other personally, the perceived trustworthiness of the message still significantly affects the impact of electronic word-of-mouth [32].
Trustworthiness is closely related to credibility. During the information search process, consumers often seek opinions from people they perceive as having expertise or experience. They may also look for reviews on brand websites or observe which brands are widely used by others. Commitment and trust are considered key elements in relationship marketing because they encourage cooperation, reduce the attractiveness of short-term alternatives, and lower perceived risk in exchanges [33]. In a smartphone purchase, trust may help consumers accept product information, reduce perceived uncertainty, and develop confidence in a brand or recommendation. In this study, trust is positioned as a mediating variable between the two WOM dimensions, social network WOM and sender expertise, and consumer purchase decisions.
2.4. The Relationship between Word of Mouth and Consumer
Purchasing Decision
Word-of-mouth directly influences purchasing decisions by providing information that consumers use during the pre-purchase, purchase, and post-purchase stages [34]. Consumers who actively search for product information online are more likely to make purchase decisions based on the comments and opinions they find. For smartphones, WOM may reduce uncertainty regarding product quality, functions, usability, durability, and value for money.
Miniard and Engel (2006) emphasized that the environment surrounding consumers, including social status, culture, family, and personal motives, plays a significant role in shaping decisions [35]. Similarly, Senecal and Nantel (2004) found that consumers often favor recommendations from experienced users when making purchase decisions [32]. Information from expert sources tends to carry greater weight and exerts stronger influence on consumers [36]. Social network WOM can influence purchasing decisions by exposing consumers to user experiences, product evaluations, and visible patterns of approval or dissatisfaction. When many users communicate similar opinions, consumers may perceive greater consensus and become more confident in their product evaluations. Sender expertise can also influence purchasing decisions because knowledgeable individuals help consumers interpret technical information and compare alternatives. Therefore, the following hypotheses are proposed:
H1: Word of mouth has a positive relationship with consumer’s purchasing decision.
H1a: Social network directly influences consumer’s purchasing decision.
H1b: The greater the customer perceived expertise of the source, the greater their perceived influence on purchase decision.
2.5. The Impact of Word of Mouth toward Trust
The effectiveness of word-of-mouth is influenced by the characteristics of the sender and receiver, as well as the closeness of their relationship. Consumers tend to trust information more when it comes from someone they know well and perceive as credible. Word-of-mouth is generally more effective when there is a close relationship and good communication between the sender and the receiver [37]. However, previous research has shown mixed results regarding whether strong interpersonal ties always increase receptivity to word-of-mouth [38].
Social network WOM may build trust even when the sender is not personally known to the receiver. Repeated opinions, detailed user experiences, consistency across reviews, and visible agreement among users can create perceptions of credibility. In contrast, sender expertise may generate trust because consumers believe that knowledgeable individuals can provide accurate, relevant, and experience-based advice.
The two WOM dimensions are therefore expected to influence trust through different but complementary mechanisms. Social network WOM builds trust through collective information and perceived consensus, whereas sender expertise builds trust through perceived competence and personal credibility. Accordingly, the following hypotheses are proposed:
H2: Word of mouth has a positive relationship with consumer trust.
H2a: Social network has a positive effect on consumer trust.
H2b: Sender expertise has a positive effect on consumer trust.
2.6. Trustworthiness and Consumer Purchase Decision
Trustworthiness is an important component of information credibility and consumer decision-making. Consumers are not influenced only by the volume of WOM; they also evaluate whether the information, source, product, and brand can be trusted. Brand experience, brand image, perceived quality, and source credibility can all shape the level of trust attached to a recommendation. For smartphone purchases, consumers may seek comments and recommendations from online communities, brand users, family members, and knowledgeable acquaintances. Research has shown that source expertise affects both the receiver’s purchasing decision and perceived trustworthiness [39]. Trust in online purchasing also extends beyond the merchant to include the technological and institutional systems through which transactions occur [40].
When consumers receive a message from a source perceived as trustworthy and expert, they may accept the source’s conclusion without independently evaluating every detail. Trust therefore reduces uncertainty and facilitates the conversion of favorable product information into a purchase decision. Accordingly, the following hypothesis is proposed:
H3: Customer trust has a positive impact on consumer purchase decision.
2.7. The Mediating Role of Trust
When seeking information, consumers rely on the sender to provide honest and accurate information. They trust that the sender understands the importance of the decision and will offer relevant and useful advice. For example, when purchasing a new smartphone, consumers often consider recommendations from friends who have more experience with the product. Das and Teng (2004) defined trust as the willingness to act based on the words, actions, and decisions of another party [41].
Perceived risk may weaken purchase intentions. Kimery and McCord (2002) demonstrated that perceived risk negatively influences purchase intentions in e-commerce environments [42], while Kuhlmeier and Knight (2005) identified a negative relationship between perceived risk and online buying intention [43]. Trust may counteract these risks by increasing consumers’ confidence in both the information received and the purchase decision being considered. The proposed mediation mechanism is therefore sequential. Social network WOM and sender expertise first affect the consumer’s level of trust. Trust, in turn, influences the likelihood that the consumer will accept the recommendation and make a purchase decision. However, WOM may also retain a direct effect on purchase decisions because consumers can respond to social influence, product popularity, or source expertise even when trust does not explain the entire relationship. Figure 1 presents the proposed research model, in which social network WOM and sender expertise influence consumer smartphone purchase decisions both directly and indirectly through trust:
H4: Customer trust has a mediating effect on the relationship between word of mouth and consumer’s purchasing decision.
H4a: Customer trust has a mediating effect on the relationship between social net-work and consumer’s purchasing decision.
H4b: Customer trust has a mediating effect on the relationship between sender expertise and consumer’s purchasing decision.
Figure 1. Research model.
3. Methodology
3.1. Research Design
The research design plays a significant role in ensuring the success of a study, as it determines how data are collected and analyzed. Researchers generally choose between qualitative and quantitative methods, each of which has its own advantages and limitations. Given that the aim of this study is to examine the effects of word-of-mouth on Vietnamese consumers, specifically the influence of recommendations on social networking platforms and sender expertise, a quantitative research approach was adopted.
The target population consisted of Vietnamese consumers aged 16 years or older who were current smartphone users and had experience searching for smartphone-related information when considering or making a purchase. Before completing the questionnaire, respondents were screened to confirm that they currently used a smartphone and had previously consulted online reviews, social networking content, or interpersonal recommendations concerning smartphones. Individuals who did not meet these criteria were excluded from the study. Therefore, the respondents were not general consumers without smartphone-related experience, nor were they required to have purchased a smartphone within a specified recent period.
A structured questionnaire was developed and divided into three main parts. The first part explored how feedback and reviews about smartphones on social networking platforms influence consumers’ purchasing decisions. The second part examined the strength of advice from individuals with sender expertise and its effect on the receiver’s purchasing decision. The third part investigated the relationships among trust, word-of-mouth, and consumer purchasing decisions.
3.2. Research Instrument and Variable Measurement
This study began with a review of existing literature on word-of-mouth to gain a clearer understanding of the research topic. A quantitative method was employed to investigate consumers’ perceptions and the impact of these perceptions on purchase decisions. Data were collected through a questionnaire adapted from previous studies and subsequently analyzed using SPSS statistical software.
The questionnaire consisted of 20 statements measured on a 5-point Likert scale, except for the demographic questions. The statements were carefully designed to avoid bias toward any specific age group or gender. The survey was distributed both online and offline. Offline questionnaires were directly distributed to random respondents at electronic centers, official smartphone stores, and second-hand smartphone stores who met the required characteristics.
Word of Mouth was measured using six statements for the social network dimension and five statements for the sender expertise dimension. These items were adapted from previous studies. Trust was measured using four statements, while Consumer’s Purchasing Decision was measured using five statements. All items were assessed using a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
Social network WOM was operationalized as respondents’ exposure to and reliance on smartphone-related reviews, comments, posts, and feedback available through social networking platforms. The six items assessed whether respondents searched for, paid attention to, trusted, and used smartphone information encountered through online social networks.
Sender expertise was operationalized as the perceived knowledge, experience, and competence of individuals who provided smartphone-related recommendations. The five items assessed whether respondents considered the advice giver knowledgeable about smartphones, experienced with different products or brands, capable of evaluating alternatives, and influential in the respondent’s purchase decision.
Trust was operationalized as the respondent’s confidence that smartphone-related information and recommendations were credible, honest, reliable, and useful. The four trust items measured the extent to which respondents believed and relied on the information received.
Consumer purchase decision was operationalized as the extent to which WOM information influenced respondents’ evaluation, brand preference, purchase intention, and final smartphone choice. The five items measured whether social network information and interpersonal recommendations affected the respondent’s willingness and decision to purchase a smartphone.
3.3. Pre-Test, Reliability and Validity
Before the main data collection, a pre-test was conducted to ensure the quality of the questionnaire. The pre-test involved distributing 10 questionnaires in English to professors in the Department of Business Administration and 20 questionnaires (in both English and Vietnamese) to managers in Vietnam. A total of 30 responses were collected. The results were evaluated for face validity and reliability.
After the pre-test, reliability and validity tests were performed. Face validity was confirmed as there were no major wording problems. The Cronbach’s alpha values for all constructs exceeded 0.7, indicating acceptable internal consistency. Specifically, social network achieved a Cronbach’s alpha of 0.765, sender expertise 0.711, trust 0.723, and consumer’s purchasing decision 0.716.
Construct validity was assessed through exploratory factor analysis. The validity values previously reported in the manuscript refer to the Kaiser-Meyer-Olkin measure of sampling adequacy rather than to a general or unspecified “validity coefficient.” The KMO values were 0.774 for social network WOM, 0.853 for sender expertise, 0.798 for trust, and 0.759 for consumer purchase decision. All values exceeded the commonly accepted threshold of 0.70, indicating that the item correlations were adequate for factor analysis (see Table 1).
The terminology in the original table has therefore been revised from “Validity” to “KMO.” This distinction is important because Cronbach’s alpha assesses internal consistency, whereas the KMO statistic assesses whether the correlation structure among the items is suitable for factor analysis.
Table 1. Reliability analysis.
Reliability Statistics |
N of Items |
Cronbach’s α |
KMO |
Social Network |
6 |
0.765 |
0.774 |
Sender Expertise |
5 |
0.711 |
0.853 |
Trust |
4 |
0.723 |
0.798 |
Consumer’s Purchasing decision |
5 |
0.716 |
0.759 |
3.4. Sampling and Data Collection
This study employed a non-probability sampling technique. Because no complete sampling frame of eligible Vietnamese smartphone consumers was available, convenience sampling was used to recruit respondents who satisfied the screening criteria. A closed-ended questionnaire was distributed to collect the data.
The questionnaire was distributed through multiple channels. First, it was shared online through social networking platforms such as Facebook. Second, questionnaires were directly distributed to respondents at electronics retail locations and smartphone stores. Third, employees at smartphone stores were asked to help distribute the survey to eligible customers. Potential respondents were informed that participation was limited to Vietnamese consumers aged 16 or older who currently used a smartphone and had experience searching for smartphone-related information. Eligibility was confirmed before respondents proceeded to the substantive questionnaire items.
The survey was made available in both Vietnamese and English, and participants could choose their preferred language and method of response. A total of 230 questionnaires were distributed, and 200 valid responses were obtained for analysis. Thirty questionnaires were excluded because they were incomplete or did not satisfy the study’s response-quality and eligibility requirements. Collected data were analyzed using the Statistical Package for the Social Sciences (SPSS), version 20.0.
4. Results
4.1. Descriptive Statistics
Descriptive statistics were used to summarize the demographic characteristics of the respondents and their smartphone usage behavior. A total of 200 valid responses were collected. The majority of respondents were female (82.5%), and most fell within the 16 - 34 age group (77%). In terms of income, 60% of respondents reported a monthly income of less than USD 400. Regarding smartphone usage, 53.6% of respondents currently owned an Apple smartphone, followed by Samsung (24.5%). When asked about their preferred brand, Apple received the highest mean score (M = 4.1), indicating strong preference among Vietnamese consumers. Most respondents (74%) preferred to purchase smartphones from official stores or electronic centers rather than second-hand stores. Additionally, 44% of respondents reported that they “always” searched for smartphone information before making a purchase.
4.2. Correlation Analysis
Correlation analysis was conducted to examine the relationships among the key variables. The results showed significant positive correlations between all variables (p < 0.001). Social network WOM was positively correlated with sender expertise (r = 0.479), trust (r = 0.380), and consumer purchasing decision (r = 0.358). Sender expertise showed a strong positive correlation with trust (r = 0.683) and consumer purchasing decision (r = 0.539). Trust was also positively correlated with consumer purchasing decision (r = 0.505). These findings provide initial support for the proposed relationships in the research model (see Table 2).
Table 2. Correlation test.
|
Mean |
SD |
1 |
2 |
3 |
4 |
1 |
Social network |
3.6925 |
0.74687 |
|
|
|
2 |
Social Expertise |
3.7610 |
0.73086 |
0.479*** |
|
|
3 |
Trust |
3.6213 |
0.86783 |
0.380*** |
0.683*** |
|
4 |
Consumer’s Purchasing Decision |
3.7490 |
0.73313 |
0.358*** |
0.539*** |
0.505*** |
**P < 0.05, **P < 0.01, ***P < 0.001.
4.3. Independent Samples T-Test
An independent-samples t-test was performed to examine gender differences across the study variables. The previously reported F-values of 5.640 and 11.282 were statistics from Levene’s test for equality of variances rather than the independent-samples t-test itself. Accordingly, the gender comparisons should be reported using the group means, t-statistics, degrees of freedom, and exact p-values from the SPSS “Independent Samples Test” output.
For social network WOM, female respondents reported a higher mean score (M = [female mean], SD = [female SD]) than male respondents (M = [male mean], SD = [male SD]), and the difference was statistically significant, t([df]) = [t-value], p = [exact p-value]. Levene’s test was significant, F = 5.640, p = [Levene p-value]; therefore, the “equal variances not assumed” results should be reported if p < 0.05.
For trust, female respondents also reported a higher mean score (M = [female mean], SD = [female SD]) than male respondents (M = [male mean], SD = [male SD]), t([df]) = [t-value], p = [exact p-value]. Levene’s test was significant, F = 11.282, p = [Levene p-value], and the unequal-variances results should therefore be used if the Levene significance value was below 0.05.
No statistically significant gender differences were found for sender expertise or consumer purchase decision, with all corresponding p-values exceeding 0.05.
4.4. One-Way ANOVA
One-way ANOVA was conducted to test for differences across age and income groups. The results showed that all significance values for age and income groups across social network, sender expertise, word of mouth, trust, and consumer purchasing decision were greater than 0.05. This indicates that there were no statistically significant age-group differences found for social network WOM, sender expertise, trust, or consumer purchase decision. Similarly, no significant differences were identified across income groups.
4.5. Regression Analysis
Multiple regression analyses were conducted to test the research hypotheses. H1a proposed that social network directly influences consumers’ buying decision-making process. The results showed a significant positive relationship between social network and consumer purchasing decision (β = 0.351, p < 0.001), supporting H1a.
H1b proposed that sender expertise positively influences consumer purchasing decision. The regression results indicated a significant positive effect (β = 0.540, p < 0.001), thus supporting H1b.
H2a and H2b proposed that both social network and sender expertise have positive relationships with trust. The results confirmed significant positive effects of social network (β = 0.442, p < 0.001) and sender expertise (β = 0.810, p < 0.001) on trust, supporting both hypotheses.
H3 proposed that trust has a positive impact on consumer purchase decisions. The regression analysis showed a significant positive relationship (β = 0.427, p < 0.001), supporting H3.
The mediating role of trust was assessed by examining the direct paths from social network WOM and sender expertise to consumer purchase decision, the paths from the two predictors to trust, and the effect of trust on consumer purchase decision. In the final regression model, social network WOM, sender expertise, and trust were entered simultaneously as predictors of consumer purchase decision.
When trust was added to the regression model, the explanatory power increased from 30.3% to 33.5%. Social network WOM remained a significant predictor of consumer purchase decision (β = 0.190, p = 0.003), while sender expertise also remained significant (β = 0.364, p < 0.001). Trust had an additional significant effect on consumer purchase decision (β = 0.208, p = 0.002).
The reduction in the coefficients for social network WOM and sender expertise after trust was added is consistent with partial mediation. However, changes in regression coefficients and R2 alone do not establish a statistically significant indirect effect. Therefore, the indirect effects must also be tested using bootstrapping or another formal indirect-effect procedure. Because the direct effects remained statistically significant after trust was included, statistically significant indirect effects would indicate partial rather than full mediation. H4 can be considered supported only after both indirect effects have been formally tested (see Table 3).
5. Discussion and Conclusions
This study provides valuable insights into the relationships between social network word-of-mouth, sender expertise, trust, and consumer purchasing decisions in Vietnam’s smartphone market. Beyond examining these direct relationships, the study also investigated how the frequency of searching for smartphone information influences word-of-mouth behavior. The findings revealed that both social network word-of-mouth and sender expertise significantly and positively affect consumers’ trust and purchasing decisions. Among these two factors, sender expertise demonstrated a stronger influence. Furthermore, trust was found to partially mediate the relationships between word-of-mouth dimensions and consumer purchasing decisions. These results are consistent with previous research that also confirmed the mediating role of trust between word-of-mouth and consumer purchasing behavior [44].
Table 3. Moderator and mediator of trust regression analysis.
Independent variables |
Model 1 |
Model 3 |
(Constant) |
1.481*** |
61.393*** |
0 |
0 |
Social Network |
0.351*** |
0.190* |
0 |
−0.003 |
Sender Expertise |
0.540*** |
0.364*** |
0 |
0 |
Trust |
---- |
0.208*** |
|
−0.002 |
F |
42.581 |
32.943 |
P |
0.000 |
0.000 |
R |
0.551a |
0.579a |
R2 |
0.303 |
0.335 |
ΔR2 |
0.296 |
0.325 |
Note. Model 1 includes social network WOM and sender expertise. Model 2 adds trust. The table title has been changed because the analysis tests mediation, not moderation. *p < 0.05; **p < 0.01; ***p < 0.001.
The findings further indicate that consumer purchasing decisions for smartphones are not solely determined by product characteristics or price. Instead, many consumers rely heavily on trust when making decisions. Because smartphones represent a relatively high-involvement and expensive purchase, consumers tend to seek information from highly trusted sources before making a final decision. Some consumers follow the opinions of people they trust, while others are influenced by popular trends or brands widely used within their social circles, regardless of their level of trust in the product.
The data for this study were collected in Vietnam through both online and offline channels, yielding 200 valid responses out of 230 distributed questionnaires. The results confirmed significant relationships among word-of-mouth, trust, and consumer purchasing decisions. In addition, the time consumers spend searching for smartphone information was found to positively influence their engagement in word-of-mouth communication.
Several detailed findings emerged from the analysis. First, the Vietnamese data provide marketers with a localized perspective on WOM behavior. No statistically significant differences were found across age or income groups. However, gender differences were identified for social network WOM and trust, with female respondents reporting higher scores than male respondents. Therefore, the findings do not indicate that WOM-related behavior was identical across all demographic groups. Rather, age and income effects were non-significant, while some gender-related differences were present. This suggests that social networking platforms may be particularly relevant for reaching female consumers in Vietnam, although the gender imbalance in the sample requires cautious interpretation.
Second, despite the relatively low income levels of many respondents (60% earning less than USD 400 per month), a significant proportion owned premium smartphones, with 53.6% owning Apple and 24.5% owning Samsung. Notably, no respondents reported purchasing second-hand smartphones. This pattern suggests that brand preference and social influence may operate alongside price considerations, particularly among the predominantly young respondents in this sample. The strong preference for Apple, reflected in a mean score of 4.1, further indicates the brand’s aspirational appeal.
Third, the study found that the more time consumers spend searching for smartphone information, the more likely they are to engage in word-of-mouth communication. This suggests that active information seekers serve as important disseminators of product opinions within their social networks.
Fourth, although smartphone companies such as Oppo and Samsung received similar favorability scores, Samsung achieved significantly higher ownership rates. One possible explanation is that perceptions of brand familiarity, credibility, and country of origin may affect the conversion of favorable attitudes into actual ownership. However, this interpretation was not directly tested and should therefore be treated as a possible explanation rather than a confirmed finding.
Fifth, Vietnamese consumers showed a clear preference for purchasing smartphones from official stores and electronic centers rather than second-hand markets. Any interpretation of gender differences in confidence when evaluating second-hand devices should be removed unless that variable was directly measured and statistically tested.
Sixth, although only 53.6% of respondents currently owned an Apple smartphone, nearly 89% of all respondents expressed a strong desire to own one. This indicates that Apple retained substantial aspirational value among the respondents, including those who did not currently own the brand.
Finally, the study confirmed that trust played an important role in converting WOM information into purchase decisions. Consumers may be more willing to act on online reviews or interpersonal recommendations when they perceive the information as credible, reliable, and useful. Nevertheless, the continued significance of the direct effects suggests that trust does not completely explain the influence of social network WOM or sender expertise.
5.1. Theoretical Contribution
While previous studies have largely focused on the motivations behind spreading word-of-mouth, this research examined the factors that drive consumer purchasing decisions. The study makes three main theoretical contributions. First, it reveals the process through which word-of-mouth communication on social networking platforms and recommendations from individuals with sender expertise positively influence consumer decision-making. In today’s digital environment, consumers are constantly exposed to comments and experiences shared by people they follow on social networks. When seeking advice, consumers tend to approach individuals they trust, which increases the likelihood that the received information will be accepted and acted upon.
Second, the study conceptualizes trustworthiness as a key construct that is directly influenced by word-of-mouth and, in turn, affects purchasing decisions. Third, the findings provide strong empirical support for the mediating role of trust. The results demonstrate that the impact of word-of-mouth on consumer purchasing decisions becomes stronger when trust is considered as a mediator.
5.2. Practical Implications
The findings of this study offer several practical implications for smartphone marketers in Vietnam. Building consumer trust should be a central focus of marketing strategies, as trust significantly influences purchasing decisions. Based on the results, the following recommendations are proposed:
1) Using Trust for Marketing
Marketers should recognize that trust is built not only through product quality but also through service experience and brand image. Claims concerning gender-specific preferences for camera quality, entertainment applications, security, or performance should be retained only if these variables were included in the questionnaire and statistically analyzed. By consistently delivering reliable products and positive service experiences, brands can strengthen consumer trust over time.
2) Linking Trust with Word-of-Mouth
When consumers trust a product or brand, they are more likely to share their experiences with others. Marketers should encourage satisfied customers to share their opinions on social networking platforms and review sites. Positive WOM generated by credible users can strengthen brand credibility and reach prospective buyers efficiently.
3) Building Brand Image through Trust and Word-of-Mouth
A strong brand image facilitates trust-building, especially among consumers who have not yet used the brand. Marketers should focus on creating consistent and positive brand experiences that encourage word-of-mouth communication, thereby strengthening brand equity.
4) Strategies for the Smartphone Market
To effectively reach Vietnamese consumers, marketers are advised to: a) increase advertising presence on social networking platforms and collaborate with influencers and content creators; b) emphasize authentic customer experiences to build trust; c) conduct targeted research to understand and address trust barriers faced by Chinese smartphone brands; and d) invest in building a strong, positive brand image, as this significantly influences consumer trust and purchase decisions for high-value products such as smartphones.
5.3. Limitations of the Study
This study has several limitations that should be acknowledged. First, the questionnaire was distributed only in Vietnam and focused exclusively on the smartphone industry, which limits the generalizability of the findings to other countries and product categories. Second, the sample was heavily skewed toward female respondents, which may have affected the observed gender differences. Third, although the survey was distributed online and through physical retail locations, convenience sampling may not have captured the full diversity of Vietnamese smartphone consumers. Fourth, most respondents were young, and the sample may have overrepresented urban and digitally engaged consumers. Therefore, the results should not be generalized to rural, older, or less digitally connected populations without further testing.
Future research should employ more balanced probability-based or stratified samples, examine additional Southeast Asian markets, and compare different product categories. Longitudinal or experimental designs could also clarify the causal sequence linking WOM exposure, trust, and actual purchase behavior.
5.4. Conclusions
This study examined the factors influencing Vietnamese consumers’ smartphone purchase decisions, with particular attention to social networking platforms, eWOM, sender expertise, and trust. The findings revealed that social network WOM and sender expertise significantly influenced trust and purchase decisions, with sender expertise demonstrating the stronger effect.
The regression results were consistent with trust partially accounting for these relationships. However, the final conclusion concerning mediation should be based on formal indirect-effect tests and bootstrap confidence intervals. The results contribute to the understanding of digital consumer behavior in emerging markets by showing that online social information and interpersonal expertise operate as complementary sources of influence.
For marketers, the findings highlight the importance of building trust and combining social networking communication with credible interpersonal and influencer-based recommendations. Although the study is limited by its convenience sample, gender imbalance, and focus on a single product category, it provides useful evidence regarding how social influence and trust shape smartphone purchase decisions in Vietnam. Future research should extend the model to other products, demographic groups, and Southeast Asian markets.