Open AccessExploring the Influence of Electronic Word of Mouth and Customer Reviews on Purchase Decisions: The Mediating Role of Trust in the Shopee Marketplace
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The dynamics of consumer behavior within the rapidly evolving e-commerce landscape necessitate a nuanced understanding, particularly in digital marketplaces. This study investigates the complex relationships among Electronic Word of Mouth (e-WoM), customer reviews, trust, and purchase decisions, with a specific focus on Generation Z (Gen Z) consumers utilizing the Shopee platform in Indonesia. Given Shopee's prominence in Indonesia's flourishing e-commerce sector, insights derived from this analysis hold significant implications for both practitioners and scholars. Data were collected from 127 Gen Z respondents in Tangerang, Indonesia, and analyzed using Structural Equation Modeling (SEM). The findings reveal that e-WoM and customer reviews play a crucial role in shaping consumer trust, which in turn, exerts a significant influence on purchase decisions. Trust is identified as a key mediating factor that links e-WoM and customer reviews to purchase intentions, thereby underscoring its importance in the consumer decision-making process. The study further highlights the direct impact of both e-WoM and customer reviews on trust, which subsequently drives purchase behaviors. These results contribute to the broader understanding of consumer behavior in digital environments, emphasizing the strategic importance of fostering trust through e-WoM and customer reviews to enhance brand perception and increase sales. This research offers empirical evidence supporting the critical role of trust as a mediator in the relationship between e-WoM, customer reviews, and purchase decisions, particularly within the context of Gen Z consumers on the Shopee platform. The implications of these findings suggest that businesses should develop targeted marketing strategies that leverage e-WoM and customer reviews to build consumer trust and drive e-commerce growth.1. Introduction
Since its inception, the rapid development of internet technology and social media has significantly transformed various aspects of human interaction, communication, information sharing, and business activities (Ng & Taneja, 2023). According to the survey conducted by the Association of Internet Service Providers in Indonesia (APJII, 2023), the number of Internet users in Indonesia is estimated to reach 225.63 million between 2022-2023, representing 78.19% of the total population of Indonesia, which reached 275.77 million. In the era of digitalization, technology brings about rapid and substantial changes in the trading world, mainly through the evolution of e-commerce.
E-commerce encompasses online product catalogs, product promotions, online ordering, online payments, online sales force access, electronic procurement, electronic market participation, and electronic fulfillment (Cassia & Magno, 2022). It is an innovation for starting businesses, offering conveniences such as providing a place to sell without requiring significant capital. Statistika Market Insights data shows that the number of e-commerce users in Indonesia reached 1,178.94 million in 2022, marking a 12.79% increase compared to the previous year's 158.65 million users. Currently, the number of e-commerce users in Indonesia is expected to continue increasing, projected to reach 196.47 million users by the end of 2023. The upward trend in e-commerce users is predicted to rise over the next four years. In 2027, Statistika projects the number of e-commerce users in the country to reach 244.67 million people. Furthermore, Bank Indonesia (BI) recorded that the value of e-commerce transactions in Indonesia amounted to Rp 476.3 trillion in 2022, derived from 3.49 billion transactions throughout the year (Oktora et al., 2022).
The development of the e-commerce industry in Indonesia continues to show significant growth. Local and international e-commerce companies continue to compete for market share, introducing various innovations, enhancing transaction security, and improving the online shopping experience (Xin et al., 2023). Some rapidly growing e-commerce sites in Indonesia include Shopee, Tokopedia, Lazada, Bibli, JD.ID, and Zalora. One of the chosen research topics is the Shopee e-commerce platform.
Shopee, founded by Sea Group, a technology company headquartered in Singapore, is a marketplace platform (Ramadhani et al., 2022). In 2015, Sea Group diversified its business by entering the e-commerce industry. They launched Shopee as a marketplace platform to enter the growing Southeast Asian market. Shopee became Indonesia's most visited e-commerce platform in the first quarter (Q1) of 2023. Between January and March 2023, Shopee had an average of 157.9 million monthly visitors, far surpassing its competitors. During the same period, Tokopedia averaged 117 million monthly visitors, Lazada 83.2 million, Blibli 25.4 million, and Bukalapak 18.1 million (Nurfadillah et al., 2023).
In the current digital era, especially on the Shopee marketplace, people tend to seek and share their experiences online, both positive and negative. User reviews, testimonials, and recommendations from fellow consumers significantly impact brand reputation and consumer trust (Azizah & Aswad, 2022). Businesses and organizations now pay more attention to and strive to influence online conversations through specific marketing strategies to build a positive image and influence potential consumers.
e-WoM refers to discussions, reviews, or recommendations about products, services, or experiences conveyed through digital platforms such as social media, websites, online forums, or review apps. According to Prasad et al. (2017), e-WoM is any positive or negative statement by potential, actual, or former customers about a product or company available to many people and institutions via the Internet. e-WoM communication has become an essential platform for conveying consumer opinions. The current e-WoM phenomenon is highly significant and extensively influences purchasing decisions and consumer perceptions. When someone seeks information about a product or service, they read user reviews before making decisions. Therefore, understanding and managing e-WoM is crucial in building a good reputation and consistently retaining consumer decisions.
Customer reviews in the marketplace are increasingly becoming the subject of interest for both customers and companies. On the one hand, customer-generated product reviews serve as valuable information sources for customers when making online product choices. Customer reviews are testimonials or evaluations about the products, services, or experiences they have encountered. These reviews are usually published online on various platforms, such as review websites, social media, forums, review apps, or even within the marketplace. Customer reviews can cover product quality, user satisfaction, customer service, pricing, reliability, and more (Ferreira et al., 2023).
e-WoM and customer reviews are closely related. e-WoM is a concept that encompasses all forms of electronic communication and recommendations, primarily through online platforms (Goyal & Taneja, 2023). Customer reviews are one concrete form of e-WoM, where consumers or customers provide reviews or testimonials about products, services, or experiences through online platforms (Wen et al., 2023), especially on the Shopee marketplace. Customer reviews are one of the most common forms of e-WoM (Bondi, 2023). When someone provides product or service reviews online, they share opinions with other customers widely through platforms such as product reviews, social media, blogs, or forums (Baker et al., 2023). The interrelation between the two is that customer reviews are among the strongest forms of e-WoM. These reviews influence potential customers' perceptions of a product or service and can affect purchase decisions. Thus, e-WoM and customer reviews are vital tools in shaping customer opinions and beliefs about a brand, product, or marketplace, especially Shopee.
Gen Z is the most growing segment and has proven to be the most influential in purchase decisions. Gen Z follows Generation Y (Millennials) and precedes Generation Alpha. Gen Z has a birth period from the mid-1990s to the early 2010s. According to Ince et al. (2023), Gen Z individuals are born and grow up with technology. Thus, they have a strong relationship with digital life daily. Gen Z significantly influences purchase decisions in e-commerce, including Shopee. Gen Z is digitally native; they have been accustomed to technology and the internet since childhood. Gen Z also tends to rely on reviews and ratings from other users on Shopee to guide their purchase decisions. By understanding the preferences and behaviors of Gen Z consumers, Shopee and sellers on this e-commerce platform can adapt to shopping experiences to better suit the needs and expectations of this generation and increase their trust, which will influence their purchase decisions.
In e-WoM and customer reviews on Shopee, trust is a crucial element. Trust is the willingness to accept the actions of others based on the expectation that they will perform essential actions for the trust giver, regardless of the other party's ability to monitor or trust those checks (Trivedi & Yadav, 2020). Trust is a crucial factor influencing how customers respond to, understand, and utilize reviews and recommendations in e-WoM and customer reviews on Shopee. Customers feel more comfortable and confident in making online purchase decisions with trust. e-WoM and customer reviews have a significant influence on purchase decisions (Guo et al., 2023). e-WoM and customer reviews strongly impact how customers perceive products or services before ultimately making purchase decisions (Wu & Huang, 2023). Customer reviews or recommendations from other customers can shape perceptions, influence purchase decisions, and increase customer satisfaction and trust. Before making purchase decisions, this is reflected in the e-WoM or customer reviews phenomenon (Kumar & Pandey, 2023).
e-WoM and customer reviews on the Shopee e-commerce platform reflect the interaction between customers, sellers, and the products or services provided. The current phenomenon of e-WoM and customer reviews on Shopee reflects trust, transparency, and interactions between fellow customers based on online shopping experiences. Customer reviews are crucial in shaping perceptions and purchase decisions, creating a stronger relationship between customers and e-commerce platforms. Therefore, based on the above phenomenon, this study aims to investigate and prove the influence of e-WoM and customer reviews on purchase decisions with trust as a mediating variable in Gen Z on the Shopee marketplace.
Despite the growing importance of e-WoM and customer reviews in influencing purchase decisions on e-commerce platforms like Shopee, there still needs to be a comprehensive understanding of the interrelationships between these variables and their impacts on Gen Z consumers. Furthermore, the role of trust as a mediating factor in this relationship has yet to be thoroughly explored. Therefore, there is a need for empirical research to fill this gap and provide valuable insights for businesses operating in the e-commerce sector, particularly on the Shopee platform.
Limited research has investigated the specific influence of e-WoM and customer reviews on purchase decisions among Gen Z consumers in the Shopee marketplace.
- More studies need to be conducted to examine the mediating role of trust in the relationship between e-WoM, customer reviews, and purchase decisions among Gen Z consumers.
- Existing literature predominantly focuses on general consumer behavior in e-commerce, neglecting Gen Z consumers' unique characteristics and preferences.
- Previous studies often need to pay more attention to the dynamic nature of e-WoM and customer reviews, failing to capture real-time trends and shifts in consumer behavior on platforms like Shopee.
The research questions of this study are as follows:
• Is there an influence of e-WoM on trust?
• Is there an influence of customer reviews on trust?
• Is there an influence of e-WoM on purchase decisions?
• Is there an influence of customer reviews on purchase decisions?
• Is there an influence of trust on purchase decisions?
• Is there an influence of e-WoM on purchase decisions mediated by trust?
• Is there an influence of customer reviews on purchase decisions mediated by trust?
The research objectives of this study are as follows:
• To determine the influence of e-WoM on trust.
• To ascertain the influence of customer reviews on trust.
• To examine the influence of e-WoM on purchase decisions.
• To analyze the influence of customer reviews on purchase decisions.
• To assess the influence of trust on purchase decisions.
• To investigate the influence of e-WoM on purchase decisions mediated by trust.
• To explore the influence of customer reviews on purchase decisions mediated by trust.
2. Literature Review
Information Processing Theory focuses on how consumers receive, process, and store information, subsequently influencing their purchase decisions. According to this theory, consumers undergo a series of stages, including attention, comprehension, acceptance, and retention, as they process information (Bettman, 1979). In this study, e-WoM and customer reviews are considered information that consumers evaluate before making a purchase decision. This process determines how trust is developed based on the assessment of the information obtained from e-WoM and customer reviews, which influences purchase decisions.
Social Influence Theory posits that individual behavior, including purchase decisions, is influenced by social norms, opinions, and the actions of others within a social context (Kelman, 1958). This theory is particularly relevant in the context of e-WoM and customer reviews, as it suggests that online reviews and recommendations shape consumers’ purchase decisions. Trust acts as a mediator, where the trust built from e-WoM or customer reviews strengthens the social influence on the decision-making process.
ECT was introduced by Oliver (1980) to explain consumer satisfaction based on the fulfillment or non-fulfillment of expectations. The theory posits that satisfaction occurs when the performance of a product or service meets or exceeds the consumer’s prior expectations. This study applies ECT to understand how trust, developed through e-WoM and customer reviews, affects purchase decisions. When the trust established aligns with consumer expectations, it increases the likelihood that consumers will proceed with a purchase decision.
By integrating these three theories, this study provides a robust theoretical foundation for understanding how e-WoM, customer reviews, and trust influence purchase decisions. Information Processing Theory offers a framework for understanding the cognitive processes consumers undergo when evaluating information; Social Influence Theory explains how social interactions impact consumer behavior; and ECT helps assess trust's role in the purchase decision-making process.
e-WoM refers to the sharing of positive or negative statements about a product or company by potential, current, or former customers through digital platforms such as e-commerce, social media, blogs, or websites (Lee et al., 2022; Sulthana & Vasantha, 2019; Wu & Chiang, 2023). It has evolved significantly in shaping consumer purchasing processes, communication, and retention (Liu et al., 2019). e-WoM reviews are disseminated online and can substantially impact others' perceptions and purchasing decisions (Ali et al., 2022). The content and authenticity of e-WoM are crucial, as they represent spontaneous online sharing and influence consumer opinions (Ismagilova et al., 2017). Several indicators of e-WoM include intensity, positive valence, and content (Lee et al., 2022).
Customer reviews are pivotal in analyzing customer satisfaction with online experiences through e-commerce or other online platforms. Previous research indicates that customer reviews significantly influence decision-making for hesitant customers (Chen et al., 2019). Customers often rely on reviews to gather information and make efficient purchase decisions (Dwidienawati et al., 2020). Customer reviews on e-commerce platforms and social media provide valuable insights, reduce perceived risk, and enhance customer satisfaction (Kaur & Sharma, 2023). Critical indicators of customer reviews encompass perceived usefulness, source credibility, argument quality, valence, and evaluation value (Bondi, 2023). Through computerized text analysis, firms can quantify and predict customer evaluations based on unstructured data, with emotional tone and authenticity being key predictors of customer-firm interactions (Ferreira et al., 2023). Additionally, sentiment polarity, readability, and word length in customer textual reviews significantly impact overall customer satisfaction, highlighting the importance of analyzing these attributes to adjust strategies and increase financial benefits (Yang et al., 2023). By leveraging these indicators and insights from customer reviews, businesses can better understand consumer behavior, improve service quality, and effectively tailor their offerings to meet customer expectations.
Trust is fundamental in building brand relationships and influences customer purchase decisions (Cardoso et al., 2022). Research indicates that factors like service quality, satisfaction, and commitment positively impact customer lifetime value (CLV) in various industries, emphasizing the importance of trust in fostering long-term relationships with customers (Swe et al., 2022). Additionally, studies on trust in science and scientists reveal that trust levels can vary among different demographic groups, highlighting the significance of trust in influencing behaviors and decisions, such as vaccine acceptance and adherence to public health initiatives (Dandis et al., 2023). Therefore, establishing and maintaining customer trust is essential for businesses to enhance brand equity, drive purchase intentions, and cultivate loyal customer bases (Chan et al., 2020).
A purchase decision is the process by which a customer selects a particular product or service after considering various factors such as needs, preferences, budget, product information, reviews, recommendations, and prior experiences. It involves recognition of needs, information search, alternative comparison, final purchase, and post-purchase behavior (Prasad et al., 2019). Purchase decisions are complex processes influenced by many factors, such as intrinsic and extrinsic product characteristics, motivations, literacy levels, sustainability, and social influences (Marey & Purwanto, 2020). Studies highlight the significance of health, economic, emotional, and marketing motivations in guiding food choices (Zwierczyk et al., 2022).
Consumer engagement with e-WoM shapes trust toward e-commerce platforms (Gvili & Levy, 2023; Purwanto et al., 2020). The Dual Systems Theory approach suggests that consumer engagement with e-WoM leads to the development of trust, subsequently enhancing purchase intention (Wang et al., 2023). The Elaboration Likelihood Model (ELM) also supports this, suggesting that e-WoM, when perceived as credible and relevant, is processed through the central route, leading to more robust and more enduring trust (Petty & Cacioppo, 1986). Additionally, the study by Goraya et al. (2021) emphasizes the mediating role of trust in community and platform attributes on the relationship between social commerce attributes and behavioral outcomes, including e-WoM intentions (Rahaman et al., 2022). Furthermore, Rahaman et al. (2022) highlight the significance of e-WoM information quality, credibility, and usefulness in influencing online consumers' intention to adopt e-WoM and form purchase behavior on social media platforms (Goraya et al., 2021). Therefore, it can be theorized that positive e-WoM interactions build trust in e-commerce platforms, ultimately impacting consumer behavior and intentions, leading to the following hypothesis:
H1. e-WoM influences trust.
Research from various studies provides insights into the significant impact of customer reviews on trust. While some studies focus on the credibility of online reviews, such as the importance of argument quality and source credibility in evaluating review trustworthiness (Petrescu et al., 2022), others delve into the effects of review characteristics like valence and volume on consumer behavior, highlighting the influence of positive ratings on customer visits (Cheung et al., 2012). Attribution Theory helps explain how consumers attribute credibility to customer reviews based on perceived motives, such as whether the reviewer is seen as unbiased and knowledgeable (Kelley, 1973). Furthermore, the Social Judgment Theory posits that the valence and volume of customer reviews influence consumers' latitude of acceptance or rejection, ultimately shaping their trust in the reviewed product or service (Sherif & Hovland, 1961).
Another study by Martha et al. (2022) showed that customer reviews positively impact trust, with superior customer reviews indicating trust in e-commerce. This underscores the importance of customer reviews in customers' purchase decisions. The study of Venkatesakumar et al. (2021) reveals that customers consider both positive and negative feedback before making purchase decisions, with almost 90% relying on positive feedback and 86% on negative feedback. Additionally, research on identifying deception in consumer reviews emphasizes the role of suspicion in shaping consumer emotions, intentions, and brand trust after reading deceptive reviews, underscoring the central role of consumer suspicion in the deception process (Baek & Choe, 2020). These findings collectively suggest that customer reviews play a significant role in shaping trust and consumer behavior in various contexts, emphasizing the need for businesses to understand and leverage the power of online reviews in building trust with their audience. Thus, based on the theories and research findings above, the following hypothesis is formulated:
H2. Customer reviews influence trust.
The Information Processing Theory suggests that consumers actively seek and process information from e-WoM before making purchase decisions, which reduces the perceived risk associated with the purchase (Bettman, 1979). Social Influence Theory also supports the idea that e-WoM serves as a powerful social cue, guiding consumer behavior by reflecting the opinions and experiences of others (Kelman, 1958). The findings from Indrawati et al. (2023) and Kajtazi & Zeqiri (2020) further demonstrate the significant role of e-WoM in reducing uncertainty and aiding in purchase decisions. Moreover, the ECT explains how positive e-WoM can confirm consumers’ expectations, thereby influencing their purchase decisions (Oliver, 1980).
Information plays a crucial role in purchase decisions. Potential customers can gather and compare helpful information before making purchase decisions, and e-WoM is considered a good source of information (Dwidienawati et al., 2020). Indrawati et al. (2023) demonstrated that e-WoM has become a crucial consideration for customers in purchase decisions. e-WoM significantly influences customers' purchase decisions. According to the research findings of Kajtazi & Zeqiri (2020), a lack of adequate information to differentiate products increases the risk of purchase. This is also evident in the research findings of Kajtazi & Zeqiri (2020), where e-WoM influences new customers to make purchase decisions.
Other research studies have consistently shown the significant impact of e-WoM on consumer purchase decisions. Lee et al. (2022) emphasize the influence of e-WoM on post-purchase psychological perceptions and repurchase behavior, particularly in the healthcare sector. Flavián et al. (2023) further supported this by highlighting that voice-based recommendations, a form of e-WoM, are more effective in altering consumer behaviors than text-based reviews. Additionally, Aravindan et al. (2023) demonstrated the role of positive word-of-mouth in driving green purchase intentions. These findings collectively underscore the importance of e-WoM in shaping consumer decisions, indicating that favorable e-WoM significantly enhances purchase likelihood across various industries and contexts. Therefore, based on the theories and research findings above, the following hypothesis is formulated:
H3. e-WoM influences purchase decisions.
Customer reviews are critical in influencing purchase decisions, as highlighted by the Theory of Planned Behavior (TPB), which suggests that consumers’ attitudes towards products, shaped by customer reviews, significantly influence their intentions and behaviors (Ajzen, 1991). Heuristic-Systematic Model (HSM) explains how consumers may use customer reviews as heuristics to make quick purchase decisions, especially when cognitive resources are limited (Chaiken, 1980). The dynamic evaluation model proposed by Li et al. (2023) aligns with these theories, demonstrating how online customer reviews (OCRs) influence consumer decision-making processes.
Customer reviews play a crucial role in influencing purchase decisions, as indicated by various studies. Guo et al. (2020) highlighted that customer reviews significantly influence purchase decisions. Dwidienawati et al. (2020) emphasized the crucial role of customer reviews in e-commerce shopping decisions, with 91% of customers stating that they read reviews before making purchases. Customer reviews on e-commerce platforms, especially Shopee, are credible or convincing because their content aligns with users' experiences of the products or services used.
Li et al. (2023) proposed a dynamic product evaluation model based on OCRs to simulate potential consumers' cognitive processes. Bondi (2023) highlighted how consumer reviews on the Internet impact product evaluation and consumer decision-making. Additionally, Petrescu et al. (2022) emphasized the significance of consumer reviews in shaping purchase intentions and brand trust, especially in identifying deception in reviews. Al-Haddad et al. (2022) further supported this notion by demonstrating that consumer engagement with corporate social responsibility activities on social media positively influences purchase intentions. Furthermore, Ravula (2023) underscores that delivery performance, which influences customer reviews, significantly impacts review ratings and subsequent purchase decisions on e-commerce platforms. These studies affirm the strong relationship between customer reviews and purchase decisions, highlighting the critical role reviews play in shaping consumer behavior. Thus, based on the theories and research findings above, the following hypothesis is formulated:
H4. Customer reviews influence purchase decisions.
Trust is a critical determinant in the Technology Acceptance Model (TAM), where trust directly influences consumers' behavioral intentions to engage with technology or platforms (Davis, 1989). Commitment-Trust Theory also highlights the pivotal role of trust in fostering enduring relationships between consumers and brands, ultimately influencing purchase decisions (Morgan & Hunt, 1994).
The research indicates that customer trust influences purchase decisions, reflecting that higher trust leads to higher purchase decisions in e-commerce. The research findings from various studies provide valuable insights into the significant impact of trust on purchase decisions in different contexts (Chan et al., 2020). In e-commerce, customer trust is a crucial factor influencing purchase decisions, with higher levels of trust leading to increased purchase intentions (Qian et al., 2023). Additionally, trust in science has been highlighted as a fundamental element for accepting scientific information, showcasing how trust plays a pivotal role in decision-making processes (Radrizzani et al., 2023). Moreover, in buyer-supplier relationships, trust is a critical driver of cooperation and innovation performance, emphasizing the importance of trust in influencing business decisions and outcomes (Mynaříková & Pošta, 2023). Overall, these studies collectively underscore the essential role of trust in shaping purchase decisions across various domains, highlighting trust as a primary factor influencing consumer behavior and decision-making processes. Therefore, based on the theories and research findings above, the following hypothesis is formulated:
H5. Trust influences purchase decisions.
The Mediation Theory suggests that trust acts as a mediator between e-WoM and purchase decisions, where positive e-WoM builds trust, which in turn enhances the likelihood of a purchase (Baron & Kenny, 1986). Research by Koay et al. (2022) and Wu & Huang (2023) supports this mediation effect, demonstrating that trust developed from e-WoM significantly influences purchase decisions. This aligns with the Theory of Reasoned Action (TRA), which posits that trust, formed through positive e-WoM, leads to stronger intentions and behaviors, including purchase decisions (Fishbein & Ajzen, 1975).
Koay et al. (2022) demonstrated that e-WoM is highly beneficial for customers, with 70% of customers having high trust in e-WoM before making purchase decisions. Civemek in Sulthana & Vasantha (2019) found that e-WoM on social media (e-commerce) influences purchase decisions among customers, with many customers trusting and being influenced by information shared or posted by other customers before making purchase decisions. The research findings from Jéssica Müller-Pérez et al. (2023) support the significant impact of trust on the relationship between e-WoM and purchase decisions. Additionally, the study of Wu & Huang (2023) indicates that trust can mediate between e-WoM and purchase decisions, highlighting the crucial role of e-WoM in rapidly disseminating information in digital promotional activities. Trust, encompassing aspects like satisfaction, security, and assurance, indirectly positively influences purchase decisions (Handi et al., 2018). This underscores the importance of building and maintaining trust in online interactions to enhance consumer confidence and drive purchase behavior, especially in the context of e-commerce and digital marketing strategies. Therefore, based on the theories and research findings above, the following hypothesis is formulated:
H6. e-WoM influences purchase decisions through trust.
The interaction between customer reviews and trust in influencing purchase decisions can be explained by the ELM, where customer reviews processed through the central route lead to the development of trust, thereby influencing purchase decisions (Petty & Cacioppo, 1986). Additionally, Social Exchange Theory suggests that when perceived as genuine, positive customer reviews enhance trust, which mediates the relationship between reviews and purchase decisions (Blau, 1964).
The research findings by Pardede et al. (2023) suggest that the interactive relationship between customer reviews and trust plays a significant role in purchase decisions on e-commerce platforms, with trust mediating the influence of customer reviews on purchasing behavior. Additionally, Ferreira et al. (2023) demonstrated that the emotional tone and authenticity of OCRs are critical predictors of customer evaluations of service interactions, highlighting the impact of reviews on customer perceptions and decisions. Furthermore, Ibrahim (2023) emphasized the importance of considering the overall review platform context in predicting the helpfulness of reviews, indicating that trust and customer reviews collectively influence purchase decisions in online environments. These studies collectively suggest that when coupled with trust, customer reviews can significantly impact purchase decisions by enhancing the perceived trustworthiness of products and services, thereby influencing consumer choices in e-commerce settings. Therefore, based on the theories and research findings above, the following hypothesis is formulated:
H7. Customer reviews influence purchase decisions through trust.
Based on the above hypotheses, a model or conceptual framework was constructed and tested in this study, as shown in Figure 1.
3. Methodology
This study adopts a quantitative research approach, which involves systematically collecting, analyzing, and interpreting numerical data. The quantitative approach is suitable for testing hypotheses and examining relationships between variables, allowing the researchers to use statistical data analysis methods (Creswell, 2014). The research is explanatory in nature and aims at determining the causal relationships between e-WoM, customer reviews, trust, and purchase decisions.
This study was conducted between March and May 2024 in Tangerang, focusing on the Gen Z population who actively use marketplace platforms, particularly Shopee. The study location was selected due to the high engagement of Gen Z individuals with digital platforms and e-commerce in this region.
The population of this study consists of Gen Z individuals aged 15-25 in Tangerang. A purposive, non-probability sampling method was employed to select respondents who meet the inclusion criteria: regular users of Shopee and individuals exposed to e-WoM and customer reviews. The sample size of 127 respondents was determined based on the minimum requirement for SEM analysis, which generally suggests a sample size of 100-200 for stable results (Hair et al., 2011). The sample size is adequate for sufficient statistical power and reliable parameter estimates.
The research instrument utilized in this study is a questionnaire designed to measure the variables under investigation, namely e-WoM, customer reviews, trust, and purchase decisions. The measurement was conducted using a Likert scale with five points ranging from “strongly agree” to “strongly disagree.” The questionnaire framework was developed based on relevant literature to determine indicators relevant to the research variables.
Data analysis was performed using SEM with the assistance of SmartPLS software. SEM was employed to test and evaluate the relationships between variables within the research model. The steps for analysis included outer loadings, discriminant validity, composite reliability, average variance extracted (AVE), and Cronbach's alpha. This technique enables researchers to examine variables' direct and indirect impacts on each other (Hair et al., 2011).
By employing this methodology, the study aims to provide an in-depth understanding of the influence of e-WoM, customer reviews, and trust on purchase decisions among Gen Z individuals utilizing marketplace platforms, particularly Shopee.
4. Results
Outer model evaluation in SEM-Partial Least Squares (SEM-PLS) assesses the reliability and validity of latent variables and their indicators. This evaluation involves several steps, including examining outer loadings to ensure convergent validity, evaluating construct reliability and validity using measures like Cronbach's alpha and composite reliability, and assessing discriminant validity through various criteria such as the Fornell-Larcker criterion and the Heterotrait-Monotrait Ratio of Correlations (HTMT). Additionally, cross-loading analysis was conducted to confirm discriminant validity, while collinearity statistics like the Variance Inflation Factor (VIF) were examined to ensure no multicollinearity issues. R-squared values were also calculated to gauge the extent of determination of exogenous variables on their endogenous counterparts. Overall, outer model evaluation provides crucial insights into the quality and appropriateness of measurement models in SEM-PLS analyses.
In Table 1, all indicators meet the expected values for convergent validity, indicating a positive relationship among different measures of the same construct. The loading factor values for latent variables and their indicators demonstrate the integration of these measures into the same construct. Ideally, convergent validity requires that values should exceed 0.7 (Purwanto & Purwanto, 2020; Purwanto et al., 2018). All indicators meet the requirement, as shown in the table. Hence, all indicators are deemed valid.
Customer Review | e-WoM | Purchase Decision | Trust | |
CR1 | 0.890 | |||
CR2 | 0.889 | |||
CR3 | 0.899 | |||
CR4 | 0.866 | |||
CR5 | 0.864 | |||
EWM1 | 0.886 | |||
EWM2 | 0.897 | |||
EWM3 | 0.895 | |||
EWM4 | 0.864 | |||
EWM5 | 0.792 | |||
PD1 | 0.863 | |||
PD2 | 0.892 | |||
PD3 | 0.865 | |||
PD4 | 0.864 | |||
PD5 | 0.872 | |||
TR1 | 0.847 | |||
TR2 | 0.916 | |||
TR3 | 0.934 | |||
TR4 | 0.881 |
According to Hair et al. (2011), variables are considered valid if the composite reliability exceeds 0.70 (Purwanto & Mutahar, 2020). In Table 2, all variables in the study are deemed valid as they possess values exceeding 0.70. Additionally, each variable's AVE is more than 0.50, confirming their validity.
Cronbach's Alpha | Composite Reliability | AVE | |
Customer review | 0.928 | 0.946 | 0.777 |
e-WoM | 0.918 | 0.938 | 0.753 |
Purchase decision | 0.921 | 0.940 | 0.759 |
Trust | 0.917 | 0.942 | 0.801 |
The Fornell-Larcker criterion for discriminant validity suggests that a construct's associations should have higher correlations than correlations with different constructs. Table 3 shows that the correlations of associated constructs are higher, indicating good discriminant validity. Moreover, the AVE values, representing correlations with their indicators, are higher than correlations with other variables, meeting the criteria for adequate convergent validity.
Customer Review | e-WoM | Purchase Decision | Trust | |
Customer review | 0.882 | |||
e-WoM | 0.757 | 0.868 | ||
Purchase decision | 0.809 | 0.799 | 0.871 | |
Trust | 0.726 | 0.762 | 0.795 | 0.895 |
Henseler et al. (2015) proposed using the HTMT with a threshold of 0.85 or <0.90 to determine discriminant validity issues. In Table 4, all HTMT values are less than 0.90, indicating valid discriminant validity based on HTMT calculations.
Customer Review | e-WoM | Purchase Decision | Trust | |
Customer review | ||||
e-WoM | 0.817 | |||
Purchase decision | 0.875 | 0.865 | ||
Trust | 0.786 | 0.827 | 0.864 |
Table 5 indicates that the cross-loading values surpass those of other latent variables, confirming good discriminant validity for the latent variables.
Customer Review | e-WoM | Purchase Decision | Trust | |
CR1 | 0.890 | 0.685 | 0.747 | 0.625 |
CR2 | 0.889 | 0.630 | 0.728 | 0.639 |
CR3 | 0.899 | 0.714 | 0.746 | 0.657 |
CR4 | 0.866 | 0.605 | 0.700 | 0.619 |
CR5 | 0.864 | 0.701 | 0.644 | 0.663 |
EWM1 | 0.724 | 0.886 | 0.770 | 0.721 |
EWM2 | 0.696 | 0.897 | 0.714 | 0.657 |
EWM3 | 0.660 | 0.895 | 0.700 | 0.692 |
EWM4 | 0.613 | 0.864 | 0.668 | 0.620 |
EWM5 | 0.579 | 0.792 | 0.599 | 0.609 |
PD1 | 0.728 | 0.737 | 0.863 | 0.640 |
PD2 | 0.735 | 0.696 | 0.892 | 0.664 |
PD3 | 0.710 | 0.646 | 0.865 | 0.655 |
PD4 | 0.676 | 0.708 | 0.864 | 0.766 |
PD5 | 0.677 | 0.689 | 0.872 | 0.737 |
TR1 | 0.614 | 0.585 | 0.674 | 0.847 |
TR2 | 0.694 | 0.728 | 0.765 | 0.916 |
TR3 | 0.683 | 0.737 | 0.728 | 0.934 |
TR4 | 0.603 | 0.669 | 0.676 | 0.881 |
The VIF values in Table 6 are all less than 5, indicating no multicollinearity among the influencing variables.
Customer Review | e-WoM | Purchase Decision | Trust | |
Customer review | 2.674 | 2.342 | ||
e-WoM | 3.018 | 2.342 | ||
Purchase decision | ||||
Trust | 2.727 |
The R-square values in Table 7, ranging from 0.633 to 0.772, clearly show the level of determination of exogenous variables on their endogenous counterparts. These values, indicating moderate to strong determinations, are a testament to the model's reliability.
R-Square | R-Square Adjusted | |
Purchase decision | 0.772 | 0.767 |
Trust | 0.633 | 0.627 |
Inner model evaluation in SEM-PLS focuses on assessing the relationships between latent variables and testing the hypothesized paths or structural relationships. This evaluation involves examining path coefficients to determine the strength and significance of the relationships between constructs, typically using measures like t statistics and p values. Specific and total indirect effects were also analyzed to understand the mediation effects between constructs. By scrutinizing these aspects, inner model evaluation provides insights into the overall fit of the structural model and the validity of the proposed hypotheses in explaining the relationships between latent variables.
The results in Table 8 strongly validate the hypotheses of this study, showing positive effects for all tested, with statistically significant p-values (<0.05) and t-statistics exceeding the threshold of 1.96 (Liuspita & Purwanto, 2019). The original sample significance percentages, ranging from 27% to 49%, further underscore the strength of the model of this study.
Original Sample (O) | Sample Mean (M) | Standard Deviation (STDEV) | T-Statistics (|O/STDEV|) | P-Values | |
e-WoM → trust | 0.498 | 0.498 | 0.083 | 6.030 | 0.000 |
Customer review→ trust | 0.349 | 0.349 | 0.078 | 4.464 | 0.000 |
e-WoM → purchase decision | 0.279 | 0.279 | 0.085 | 3.294 | 0.001 |
Customer review → purchase decision | 0.371 | 0.369 | 0.090 | 4.120 | 0.000 |
Trust → purchase decision | 0.314 | 0.313 | 0.070 | 4.467 | 0.000 |
Table 9 demonstrates positive indirect effects for both hypotheses tested, with statistically significant p-values (<0.05) and t-statistics exceeding the threshold of 1.96, indicating significance.
Original Sample (O) | Sample Mean (M) | Standard Deviation (STDEV) | T-Statistics (|O/STDEV|) | P-Values | |
e-WoM -> trust → purchase decision | 0.156 | 0.156 | 0.043 | 3.642 | 0.000 |
Customer review-> trust → purchase decision | 0.110 | 0.110 | 0.036 | 3.009 | 0.003 |
The results in Table 10 show positive total indirect effects for both hypotheses tested, with statistically significant p-values (<0.05) and t-statistics exceeding the threshold of 1.96, signifying significance.
Original Sample (O) | Sample Mean (M) | Standard Deviation (STDEV) | T-Statistics (|O/STDEV|) | P-Values | |
e-WoM → purchase decision | 0.156 | 0.156 | 0.043 | 3.642 | 0.000 |
Customer review→ purchase decision | 0.110 | 0.110 | 0.036 | 3.009 | 0.003 |
5. Discussion
The findings of this study are of significant importance, demonstrating that e-WoM, customer reviews, and trust, acting as mediators, profoundly influence purchase decisions. The findings reveal the crucial impact of e-WoM on trust within contemporary consumer landscapes, emphasizing its significance in shaping consumer behavior (H1). The impact of e-WoM on trust (H1) is supported by Social Influence Theory, which posits that individuals’ attitudes and behaviors are significantly shaped by the opinions and behaviors of others within their social environment (Kelman, 1958). In the context of e-WoM, this theory explains how online interactions and shared experiences influence consumer trust, particularly on digital platforms where face-to-face interactions are absent. The ELM further supports this by suggesting that e-WoM, when perceived as credible and relevant, is processed through the central route, leading to a stronger and more lasting trust (Petty & Cacioppo, 1986). This underscores the importance of ensuring the authenticity of e-WoM channels to combat deceptive practices, thereby enhancing consumer trust in digital spaces. Practical implications include businesses engaging with online communities, collaborating with credible influencers, and leveraging monitoring tools to track and manage e-WoM sentiment effectively.
With the rise of online platforms and social media, e-WoM emerges as a powerful influencer, exerting a substantial positive effect on trust dynamics. This underscores the importance of regulatory measures to safeguard the authenticity of e-WoM channels, combat deceptive practices and enhance consumer trust in digital spaces. Moreover, educational initiatives to bolster consumer literacy regarding e-WoM can empower individuals to discern credible sources, contributing to a more discerning digital populace. Collaborative efforts among industry stakeholders to establish standardized practices for e-WoM dissemination are crucial, ensuring transparent disclosure and fostering trustworthiness within the digital marketplace. On a practical level, businesses can cultivate trust-based relationships by engaging with online communities, collaborating with credible influencers, and leveraging monitoring and analysis tools to track e-WoM sentiment effectively. By fostering an environment conducive to genuine, transparent, and influential e-WoM interactions, stakeholders can cultivate trust-based relationships and engender sustainable consumer loyalty in the digital era.
Customer reviews significantly influence trust (H2). The analysis of the impact of customer reviews on trust reveals a p-value of 0.000, a t-statistic greater than 4.464, and an original sample significance of 34%. This indicates that customer reviews have a significant positive influence. The significant influence of customer reviews on trust highlights their profound impact on consumer decision-making processes and brand perceptions. This emphasizes the importance of policies to ensure customer reviews' authenticity and transparency, including measures to combat fraudulent or manipulated reviews. Regulatory frameworks should be established to promote accountability and integrity in review platforms, fostering consumer trust. Additionally, practical implications entail businesses actively engaging with and responding to customer feedback, leveraging positive reviews to enhance brand credibility and loyalty. Implementing robust review monitoring systems and utilizing data analytics tools enable businesses to manage and capitalize on the influence of customer reviews effectively, ultimately fostering trust-based relationships with consumers.
Customer reviews significantly influence trust (H2), a finding grounded in Attribution Theory, which suggests that consumers assign credibility to reviews based on perceived motives and the reliability of the reviewer (Kelley, 1973). Additionally, the HSM explains how consumers use reviews as cognitive shortcuts (heuristics) to assess trustworthiness quickly, especially when they have limited information or cognitive resources (Chaiken, 1980). The study's significant p-value and t-statistic for this relationship underscore the critical role of customer reviews in shaping trust. Businesses are advised to prioritize the authenticity and transparency of customer reviews, implementing robust monitoring systems to manage and capitalize on their influence effectively.
The analysis highlights the significant influence of e-WoM on consumer purchase decisions, emphasizing the pivotal role of online interactions in shaping buying behavior (H3). This finding underscores the transformative impact of digital platforms on consumer decision-making processes. The analysis elucidates critical factors contributing to this influence, including the accessibility of authentic and real-time information, the interactive nature of online discussions, and the pervasive reach of e-WoM channels. Moreover, it underscores the importance of businesses adopting proactive strategies to manage and leverage online consumer interactions effectively, safeguarding their brand reputation and fostering consumer trust. By recognizing the power of e-WoM and its implications for marketing and consumer engagement, organizations can adapt their practices to capitalize on this influential phenomenon and drive positive outcomes in the digital marketplace.
The influence of e-WoM on purchase decisions (H3) is well-documented in Information Processing Theory, which highlights how consumers actively seek and process information from e-WoM to reduce perceived purchase risks (Bettman, 1979). Social Influence Theory also applies here, where e-WoM is a powerful social cue guiding consumer behavior by reflecting others’ opinions and experiences. The accessibility of real-time, authentic information through e-WoM significantly impacts purchase decisions, emphasizing the need for businesses to adopt proactive strategies to manage online consumer interactions and safeguard their brand reputation.
The research findings highlight the substantial impact of customer reviews on purchase decisions, elucidating their critical role in shaping consumer behavior (H4). The impact of customer reviews on purchase decisions (H4) is explained by the TPB, which suggests that attitudes shaped by customer reviews significantly influence consumers’ purchase intentions and behaviors (Ajzen, 1991). Social Judgment Theory further elaborates that the valence and volume of reviews impact consumers’ acceptance or rejection of products, influencing their purchase decisions (Sherif & Hovland, 1961). Given the strong relationship between customer reviews and purchase decisions, businesses should actively solicit and leverage customer feedback for product development and marketing strategies, ensuring prompt and transparent customer engagement.
The significant influence wielded by customer reviews underscores the importance of implementing policies to promote transparency and authenticity in online review platforms. Regulatory frameworks should be established to mitigate the proliferation of fake reviews and deceptive practices, safeguarding consumer trust in the digital marketplace. Moreover, practical implications necessitate businesses actively soliciting and leveraging customer feedback for product development and marketing strategies. Engaging with positive reviews and addressing negative feedback promptly and transparently can enhance brand credibility and foster long-term customer relationships. By harnessing the influence of customer reviews and prioritizing consumer trust, businesses can optimize their competitive advantage in an increasingly discerning market landscape.
The research findings elucidate the profound impact of trust on purchase decisions, underscoring its pivotal role in shaping consumer behavior (H5). Trust’s significant impact on purchase decisions (H5) aligns with the TAM, where perceived trust directly influences consumers’ behavioral intentions to engage with online platforms (Davis, 1989). The Commitment-Trust Theory supports this, emphasizing that trust is essential for fostering enduring consumer-brand relationships, which drive purchase decisions (Morgan & Hunt, 1994). The findings suggest that businesses must prioritize trust-building initiatives, such as transparent communication and reliable product quality, to enhance brand loyalty and customer satisfaction.
The discerned significant influence of trust highlights its critical importance as a determining factor in consumer choices within the marketplace. This emphasizes the necessity of implementing policies to foster and preserve trust within commercial transactions. Regulatory measures should be devised to uphold transparency, accountability, and ethical standards in business practices, bolstering consumer confidence and trust. Practical implications entail businesses prioritizing trust-building initiatives, such as transparent communication, reliable product quality, and exemplary customer service. By cultivating trust-based relationships with consumers, companies can enhance brand loyalty, increase customer satisfaction, and optimize their competitive advantage in the marketplace.
The research findings offer a compelling insight into the significant influence of e-WoM on purchase decisions, mainly when mediated by trust (H6). The influence of e-WoM on purchase decisions through trust (H6) is best understood through Mediation Theory, which highlights that trust acts as a mediator between e-WoM and purchase decisions (Baron & Kenny, 1986). The TRA complements this by indicating that trust, formed through positive e-WoM, leads to more robust consumer intentions and behaviors, ultimately influencing purchase decisions (Fishbein & Ajzen, 1975). This underscores the need for businesses to integrate trust-building strategies within their e-WoM efforts to drive positive consumer outcomes.
This highlights the interconnected nature of online communication and consumer trust within the digital marketplace. The identified mediation effect underscores the pivotal role of trust as a mechanism through which e-WoM shapes consumer behavior. In light of these findings, policymakers are urged to enact measures that promote transparency and authenticity in online communication channels, safeguarding consumer trust in e-WoM platforms. Regulatory frameworks should be established to combat fraudulent practices, ensuring the integrity of online reviews and recommendations. Moreover, practical implications entail businesses prioritizing trust-building initiatives in their e-WoM strategies, such as fostering genuine and credible consumer interactions and actively managing their online reputation. By leveraging the influence of e-WoM while nurturing consumer trust, businesses can enhance their competitive edge and foster long-term relationships with customers in the digital landscape.
Finally, customer reviews significantly influence purchase decisions through trust (H7), supported by the ELM (Petty & Cacioppo, 1986) and Social Exchange Theory (Blau, 1964). These theories explain how customer reviews build trust when processed via the central route, which mediates the relationship between reviews and purchase decisions. The findings suggest that businesses must actively foster trust through transparent review practices and leverage customer feedback to enhance their competitive edge in the digital marketplace. Customer reviews significantly influence purchase decisions with trust mediation (H7). The analysis shows a significant positive effect of customer reviews on purchase decisions with trust mediation. This indicates that the interaction between customer reviews and trust-based purchase decisions yields a significant positive value. The study unequivocally demonstrates the potent influence of customer reviews on purchase decisions, a power that is significantly amplified by trust. This revelation underscores the pressing need for businesses and regulatory bodies to understand and harness the impact of customer reviews on consumer behavior and decision-making processes. Trust, acting as a critical mediator, can dramatically increase the likelihood of a purchase, making the content and credibility of customer reviews a paramount concern in the digital marketplace.
From a policy perspective, consumer protection regulations should develop and enforce stricter guidelines to ensure the authenticity and reliability of customer reviews, including mechanisms to detect and eliminate fake reviews to enhance consumer trust and decision-making accuracy. Implementing standardized criteria for review platforms could help maintain the quality and credibility of customer feedback, such as verified purchases, review moderation policies, and transparent rating systems. Additionally, policies that incentivize genuine customer feedback can be beneficial, for instance, offering discounts or loyalty points to customers who provide verified reviews, encouraging more authentic and valuable feedback, and further fostering trust among potential buyers.
On a practical level, businesses bear a significant responsibility in fostering trust through transparent review practices. They should actively encourage and facilitate customer reviews, focusing on quality and authenticity. This can be achieved by providing easy-to-use review platforms and follow-up prompts post-purchase to gather valuable customer feedback. Businesses must prioritize building and maintaining trust, achieved by showcasing verified reviews prominently, responding to customer feedback, and addressing any issues raised in a timely and honest manner. Highlighting positive customer reviews in marketing campaigns can be an effective strategy, with trustworthy testimonials prominently featured on company websites, social media, and other marketing materials to leverage their positive impact on purchase decisions. Developing robust customer relationship management (CRM) systems that track and analyze customer feedback can provide valuable insights to guide improvements in products, services, and overall customer experience, thereby enhancing trust and increasing the likelihood of repeat purchases.
6. Conclusions
The comprehensive evaluation of the SEM through outer and inner model assessments yields insightful findings regarding the relationships between latent variables in the context of e-WoM, customer reviews, trust, and purchase decisions. The outer model evaluation ensures the reliability and validity of the measurement model, affirming the robustness of the constructs utilized. Convergent validity was established through satisfactory outer loadings, construct reliability, and validity measures, while discriminant validity was confirmed by both the Fornell-Larcker criterion and HTMT. Cross-loading analysis further substantiates discriminant validity, while collinearity statistics assure the absence of multicollinearity issues. The determination of exogenous variables on endogenous counterparts was delineated through R-squared values, elucidating the model's explanatory power.
The inner model evaluation scrutinizes the structural relationships between latent variables, elucidating their direct and indirect effects. Path coefficients exhibit significant positive effects, corroborating the hypotheses postulated. Specific and total indirect effects elucidate the mediation role of trust in the relationships between e-WoM, customer reviews, and purchase decisions, underscoring the nuanced dynamics within the model.
Despite the significant findings, this study has limitations. First, the sample representativeness may be constrained by the use of non-probability sampling methods, particularly purposive sampling, which may limit the generalizability of the results to the broader Gen Z population. Future research could address this limitation by employing probability sampling techniques to enhance the sample’s representativeness.
Second, the reliance on self-reported data via questionnaires introduces the possibility of common method bias, as respondents may consciously or unconsciously provide socially desirable responses. Future studies could consider incorporating objective measures or data triangulation to mitigate this potential bias.
Third, the study focuses primarily on a specific set of variables, i.e., e-WoM, customer reviews, trust, and purchase decisions, without exploring other potential moderating or mediating factors that could influence these relationships. For instance, variables such as consumer experience, brand loyalty, or cultural differences might provide deeper insights into the dynamics of consumer behavior in digital environments. Future research should consider expanding the model to include these additional factors, offering a more comprehensive understanding of the studied phenomena.
Finally, this study employs a cross-sectional design, which captures the relationships between variables at a single point in time. Longitudinal studies could provide more robust insights into the evolving nature of these relationships, especially as digital marketing strategies and consumer behavior continue to change. Tracking these variables over time would enhance the relevance and applicability of the findings in dynamic market environments.
The findings of this study make significant theoretical and practical contributions to the existing literature on e-WoM, customer reviews, trust, and purchase decisions. In theoretical contributions, this study extends Social Influence Theory by demonstrating the critical role of e-WoM in shaping consumer trust, particularly in digital environments where traditional face-to-face interactions are absent. Integrating the ELM further enriches the understanding of how consumers process and evaluate e-WoM information, leading to varying levels of trust based on the perceived credibility and relevance of the content. The findings related to customer reviews and trust contribute to Attribution Theory by emphasizing how consumers attribute credibility to reviews based on perceived motives and reviewer reliability. Furthermore, applying the HSM to understand how consumers use cognitive shortcuts when assessing trustworthiness provides new insights into the processes driving trust formation in online settings. The study also advances Mediation Theory by elucidating how trust is a crucial mediator in the relationships between e-WoM, customer reviews, and purchase decisions. The application of the TRA further deepens this understanding, highlighting the interconnectedness of trust, consumer intentions, and behaviors in the digital marketplace.
In practical implications, the research provides actionable insights for businesses and marketers on effectively leveraging e-WoM and customer reviews. By understanding the factors that enhance consumer trust, companies can develop strategies focusing on authenticity, transparency, and credibility in their online communications. Engaging with credible influencers, implementing robust review monitoring systems, and prioritizing genuine consumer interactions are key strategies that foster trust and drive positive purchase decisions. The findings underscore the need for robust regulatory frameworks to ensure the authenticity and reliability of e-WoM channels and customer reviews. Policies that address deceptive practices, enforce transparency, and promote accountability are essential for maintaining consumer trust in the digital marketplace. Standardized criteria for review platforms, such as verified purchases and transparent rating systems, can further enhance the credibility of online feedback, benefiting both consumers and businesses. Businesses are encouraged to adopt proactive trust-building initiatives, such as showcasing verified reviews, responding promptly to customer feedback, and maintaining consistent communication with consumers. Integrating CRM systems to track and analyze input can provide valuable insights for continuous improvement in products and services, ultimately leading to higher customer satisfaction and loyalty.
In conclusion, this study not only fills critical theoretical gaps in understanding e-WoM, customer reviews, and trust but also offers practical solutions for businesses aiming to navigate the complex dynamics of consumer behavior in the digital era. Future research could further explore additional moderating and mediating variables and conduct longitudinal studies to capture the evolving nature of these relationships over time, ensuring the ongoing relevance of these findings in a rapidly changing marketplace.
This study adheres to strict ethical guidelines, ensuring the rights and privacy of participants. Informed consent was obtained from all participants, and personal information was protected throughout the study. The methodology and procedures of this research have been approved by the appropriate ethics committee. Participants were informed of their rights, including the right to withdraw from the study at any time. All collected data is used solely for the purpose of this research and is stored and processed in a secure and confidential manner.
The data used to support the research findings are available from the corresponding author upon request.
The authors declare no conflict of interest.
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