Journal of Information Technology Applications and Management

Korea Data Strategy Society (한국데이터전략학회)
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Analyzing the Effect of Trust in Reviews on Trust in a Product and a Company: Using the Trust Transfer Theory

  • Namjae Cho (School of Business, Hanyang University) ;
  • Xiaochen Li (School of Business, Hanyang University) ;
  • Giseob Yu (School of Business, Kyungpook National University)
  • Received : 2024.02.15
  • Accepted : 2024.02.25
  • Published : 2024.02.29
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Abstract

The aim of this research is to examine the impact of trust in reviews. Expertise, enjoyment, recency, and usefulness-four aspects of reviews-are designated as independent variables, and trust in reviews has been chosen as the mediating variable. The dependent variables are trust in firms and trust in products. For explaining the flow of trust, this study uses the theory of Trust Transfer. The study's findings demonstrated that customer trust in a product leads to consumer trust in a company, which is derived from trust in reviews. Reviews were found to be important from a practical standpoint. Furthermore, it was discovered that a product's category or features would have an impact on how reviews are trusted.

Keywords

1. Introduction

Word-of-mouth (WOM) refers to the exchange of opinions regarding specific products or experiences between individuals [Westbrook, 1987]. With the advent and advancement of the internet, WOM has transformed into online word-of-mouth (e-WOM), which signifies the communication of product information on the online platform [Gelb and Johnson, 1995]. This transformation has brought about changes in consumer behavior. Consumers, when making purchasing decisions, seek online consumer reviews to gather essential information about products [Zhu and Xiaoquan, 2010], and they rely on such reviews as references before making a purchase [Chevalier and Mayzlin, 2006]. Technological progress has facilitated the emergence of a new form of product purchasing, wherein consumers assess and share product information online [Avery et al., 1999].

Due to the significance of reviews in influencing consumer purchases, they have become a crucial resource for consumer marketing and corporate activities [Mayzlin et al., 2014; Chevalier and Mayzlin, 2006]. Successful consumer marketing strategies utilizing reviews, pioneered by Amazon [New York Times, 2004], have been adopted by various online platforms such as internet retailers and search engine sites [Chen and Zie, 2008; Lantz, 2019]. Unlike recommendation systems managed by companies, reviews are generated based on consumer experiences [Jabr and Zheng, 2014], making them valuable for establishing customer trust in products offered by businesses [Nielsen Online Global Consumer Study, 2009] and potentially influencing product purchases.

The influence of reviews on consumers has been the subject of various studies examining the relationship between reviews and consumers. Research has been conducted from diverse perspectives, such as analyzing the relationship between product evaluations and consumers’ purchase intentions and payments [Sridhar and Srinivasan, 2012; Cheung and Thadani, 2012], investigating how reviews assist consumers’ purchase decision-making process on specific websites [Mudambi and Schuff, 2010], exploring the effects of reviews on product and consumer characteristics and purchase intentions [Zhu and Xiaoquan, 2010], and studying fake reviews [Luca and Zervas, 2015].

Because consumers’ trust in reviews was formed, consumers’ purchases were made with reference to reviews [Li et al., 2006; Quershi et al., 2009]. Consumers strive to reduce risks through relationships with trusted third parties [Mayer et al., 1995], and online reviews serve as a means of communication or a source of trust-building with these third parties. This trust is considered a crucial factor and strategy that can even influence consumers' repurchasing behavior [Flavian et al., 2006; Gefen, 2002]. Consequently, the trust formed through reviews is highly important, which is regarded as a manageable aspect from a corporate perspective.

Research on reviews has predominantly focused on whether they impact product or service purchases. Studies on the credibility of reviews have also been actively conducted. However, there is a need for research investigating the process by which trust in reviews transitions. Thus, this study aims to analyze how trust in reviews influences trust in products and companies through a particular flow. In this study, the Trust Transfer Theory (hereafter TTT) is adopted as the background theory to analyze the flow of trust. TTT refers to the cognitive process in which trust in one specific entity can be transferred to other related entities [Stewart, 2003]. That is, TTT is a valuable theory for understanding the essence of trust. This theory has been predominantly applied and utilized in e-commerce and mobile commerce contexts [Cheng et al., 2019; Lu et al., 2010]. However, the aim of our research is to investigate whether the trust formed through reviews can be transferred to the trust in related products and companies based on the prior studies that demonstrated the transfer of trust between related entities such as companies and their employees [Doney and Cannon, 1997].

In this study, the five key characteristics of reviews, namely expertise, empathy, recency, and usefulness are set as independent variables, while the trust in reviews is set as the mediating variable. The dependent variables are set as trust in products and trust in companies. The research questions for this study are as follows:

Q1: Which factors of reviews influence the formation of trust?

Q2: Does the trust formed through reviews transfer to trust in products and companies?

2. Theoretical Background

2.1 Characteristics of Reviews

As the importance of online reviews has increased, various forms of review platforms have emerged. Yelp.com is a platform where users can share reviews of various restaurants, while STEAM has grown as a platform for consumers to write reviews about games they have played. These online reviews, also known as Electronic Word of Mouth (e-WOM), differ from traditional face-to-face communication in that they occur on the internet, where consumers share information and experiences about products [Schindler and Bickart, 2002]. The e-WOM differs from traditional word-of-mouth in terms of speed, convenience, and the number of people reached [Sun et al., 2006; Cantallops and Salvi, 2014].

The significance of online reviews lies in the fact that these are not information conveyed by companies but rather information generated and transmitted directly by consumers who have used the product or service. As a result, other consumers perceive such information to be highly trustworthy and relevant [Bickart, 2002; Harrison-Walker, 2001]. In other words, online reviews serve as a channel for consumers to obtain objective information when they cannot directly examine the product [Dabholkar, 2006].

Online reviews have more purpose than merely disseminating information. They can also provide enjoyment in the process of information exploration for consumers [Mathwick and Ridgon, 2004] and facilitate extended engagement on review platforms [Kumar and Benbasat, 2006]. According to a survey conducted in Korea in 2017, 87 percent of consumers check reviews when making online purchases and approve of the reviews' significance and necessity [TrendMonitor, 2017]. Previous research results suggest that online reviews play various roles. From a business perspective, reviews also hold significant importance due to their substantial impact on various aspects of corporate activities. They play a crucial role in formulating detailed marketing strategies, enhancing customer interactions and loyalty, and facilitating communication with the target market [Cantallops and Salvi, 2014]. Therefore, reviews are significant in the realm of corporate activities. The unique online environment accentuates the importance of online reviews [Elliott, 2002].

Online reviews can generally be categorized into positive and negative reviews [Sparks and Browning, 2011]. Positive reviews share favorable experiences and recommendations with potential consumers, while negative reviews discourage potential consumers from making purchases based on unfavorable experiences [Hu et al., 2009; Litwin et al., 2008; Mauri and Minazzi, 2013]. Some studies have shown that information contained in negative reviews is perceived as more valuable and helpful to potential consumers due to its rarity and unpredictability [Yin, Bond, and Zhang, 2014]. Therefore, review management is essential in business [Lee and Yang, 2015] because reviews can impact not only product or company image but trust [Mauri and Minazzi, 2013]. Online reviews have evolved beyond being a form of word-of-mouth and can influence both product and company trust.

2.2 Trust Transfer Theory (TTT)

Trust has been extensively studied and discussed in various academic fields, including management, as one of the fundamental factors influencing human interactions [Gambetta, 1988; Rousseau et al., 1998; Oh and Cho, 2016]. It is defined as a psychological state that involves accepting risks based on positive expectations or behaviors, and as a belief that others will not engage in malicious actions [Eddleston et al., 2012; Dyer, 2012; Robinson, 1996].

Trust tends to shift from well-known targets to unfamiliar ones [Uzzi, 1996], and in the online context, this characteristic of trust can even facilitate purchase decisions [Quelch and Klein, 1996]. This process of trust transfer, based on persuasion theory, can influence consumer behavior in online marketing [Funkhouser, 1984; Milliman and Fugate, 1988; Stewart, 2003]. Due to these traits of trust, trust transfer is considered an important and long-term issue in online marketing [Keen, 1997]. Trust transfer can be observed in both online and offline contexts. For example, higher trust in courier services can lead to increased trust in the online sites where orders are placed, which can influence customer satisfaction through the online word-of-mouth effect [Sirdeshmukh et al., 2002]. The formation of trust in the online context is attributed to the existence of multiple communities where evaluations are conducted [Bakos and Dellarocas, 2002].

Research on trust transfer in the online context has been conducted in various topics. The earlier studies focused on inter-organizational trust transfer through web pages of two online platforms [Stewart, 2003], and dominated online purchases [Fang et al., 2014]. Previous studies have explored diverse topics, including the impact of reviewer characteristics on consumers’ positive behavioral intentions [Xu, 2014], the formation of trust relationships between platforms [McKnight et al., 1998], and the trust formation and transfer processes in shared accommodation platform companies [Gutiérrez et al., 2017]. Several studies have demonstrated the essential and significant nature of trust formation and transfer in the process of online transactions transitioning to offline products and services, concerning consumers’ perceptions of products and companies [Ert et al., 2016; Zamani et al., 2019]. Trust, which is an effective and indispensable factor in enhancing long-term relationships between businesses and consumers [Agag and El-Masry, 2016], plays a crucial role.

In this study, we utilize the trust transfer theory to investigate the process by which trust in reviews transfers to trust in products and companies. We set reviews as the starting point for trust formation and measured the trust in reviews through their characteristics. Using that, this study elucidates the aforementioned trust transfer process.

3. Research Methodology

To answer the research questions of this study, the analysis was conducted using the research model. The independent variables are set as the expertise, enjoyment, time-liness, and usefulness of the review to explore their impact on the formation of review trust. Also, product and corporate trust are set as mediating and dependent variables, respectively, to investigate whether the trust in reviews is transferred. Research Point 1 is a point to find the answer to research question 1, and Research Point 2 is an analysis path to explore the process of trust transfer in reviews, which is one of the core questions of this study. In this study, the analysis was conducted using the SPSS 21 and Amos 21 programs. The study participants consisted of Chinese consumers who had recently made purchases based on reviews. The survey was distributed and collected both online and offline. The questionnaire was structured with a Likert 5-point scale (1 for ‘Not at all’ ~ 5 for ‘Very much so’).

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<Figure 1> Research Model

3.1 Hypothesis Development

3.1.1 Expertise in Reviews

Expertise refers to the ability of an information provider to objectively evaluate the characteristics or performance of a product [McGuire, 1968]. In the past, expertise was measured using factors such as specialized knowledge, experience, and qualifications related to the information source [Ohanian, 1990]. However, in recent online review research, reviewer expertise has been analyzed by measuring factors such as the number of followers, rankings, and social status within a specific site [Yin et al., 2014; Cheng and Ho, 2015; Craciun and Moore, 2019].

If there are characteristics within online reviews that indicate reviewer expertise, consumers can easily recognize and find more useful reviews [Mackiewicz, 2010]. Moreover, as these characteristics increase, reviewers can gain more trust from consumers [Banerjee et al., 2017; Willemsen et al., 2011]. Indeed, reviewer expertise has been found to directly influence the trust in reviews [Willemsen et al., 2011].

In this study, expertise is defined based on McGuire’s [1968] definition as the ability of experienced consumers to provide valid evaluations of product characteristics or performance. Building on prior research, we hypothesize the following relationship between reviewer expertise and trust in reviews:

H1-1: Reviewer expertise will be positively associated with trust in reviews.

3.1.2 Enjoyment in Reviews

Enjoyment can be defined as a pleasurable characteristic that meets the information satisfaction needs of users on the Internet [Hwang, 2010]. Enjoyment itself is an immediate experience felt by consumers and is also defined as high satisfaction [Webster and Martocchio, 1992]. Enjoyment is mainly dealt with as an important variable among the characteristics of information that online reviews have [Haley, 1996; Elliot, 2002; Shindler and Bickart, 2002]. In previous studies, the enjoyment of reviews was shown to affect the trust of the information provided by the review [Eom, 2013]. That is, the trust in the information in the review means that the consumer trusts the review, and it can be seen that there is a causal relationship.

In this study, the enjoyment of the review was defined as a pleasurable characteristic that meets the information satisfaction needs [Hwang, 2010]. The hypothesis setting to see the relationship between the enjoyment of the review and the trust of the review is as follows.

H1-2: Enjoyment in review will be positively associated with trust in reviews.

3.1.3 Recency in Reviews

Considering the fundamental purpose of websites as information dissemination platforms, the presence of up-to-date and high-quality information can lead to positive user attitudes toward websites [DeLone and McLean, 1992; Tandon et al., 2020]. The recency of information provided online is one of the crucial indicators for consumers to judge whether it is useful [Madu, 2002]. In fact, consumers tend to assess businesses based on the recency of reviews rather than their quantity, with reviews older than three months being considered irrelevant to product-related information [BrightLocal, 2019].

When making decisions, consumers tend to focus more on the most recent information than outdated information [Xie et al., 2016]. In other words, through reviews containing the latest information, consumers make purchase decisions for products [Wulff et al., 2015]. The location of links within a website has been found to be a significant factor influencing consumers’ clicking behavior, with links placed at the top of a page being more likely to be clicked by users [Murphy et al., 2006; Ansari and Mela, 2003]. Therefore, the most recent reviews can instill the trust in consumers and influence their purchase decisions for products or services.

In this study, the recency of reviews is defined as the most recent experiences written by consumers that are associated with the post-date of the review [Tandon et al., 2020; Xie et al., 2016]. Based on this, the following hypothesis is formulated:

H1-3: Recency in review will be positively associated with trust in reviews.

3.1.4 Usefulness in Review

Review usefulness refers to the perception of consumers that online reviews written by others will be beneficial and helpful to them [Schuckert et al., 2015]. The usefulness of reviews is largely influenced by the characteristics of both the product and the review itself [Mudambi and Schuff, 2010]. Factors such as the review’s rating and length can have an impact, and the usefulness may vary depending on whether the product is an experiential or search good [Liu and Park, 2015].

The significance of review usefulness lies in its role as a criterion for potential consumers to judge the quality of reviews, ultimately influencing their behaviors [Filieri et al., 2018; Li et al., 2019; Salehan and Kim, 2016; Zhao et al., 2019]. Some researchers argue that review usefulness represents the most efficient characteristic among a plethora of review information, enabling consumers to save time and effort [Filieri et al., 2018]. In other words, higher review usefulness can induce product purchases or certain behaviors, and this process can be interpreted as part of the trust-building process.

In this study, review usefulness is defined as the perception that reviews are beneficial and helpful to consumers [Schuckert et al., 2015]. Based on previous research, the following hypothesis is formulated:

H1-4: Usefulness in review will be positively associated with trust in reviews.

<Table 1> Measurement Items and Quotation

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3.1.5 Trust in Reviews and Trust in a Product and a Company

Trust in reviews on online platforms is of great importance as consumers base their product and service purchases on these reviews, even though they do not represent direct transactions between providers and buyers [Cheung et al., 2012]. Considering that the trust in online reviews is influenced by the reviewers and objectivity, rather than by the platform or content type [Banerjee et al., 2017], it can be explained that online reviews with higher consumer involvement are more trustworthy compared to less involved reviews [Reyes-Menende et al., 2019]. In other words, trusting reviews [Oliveira et al., 2017] imply that they play a significant role in consumer decision-making for product and service purchases [Shan, 2016].

In this study, we consider trust in online reviews as an important factor and hypothesize that it will mediate the relationship between the characteristics of reviews and reliability in products and companies. The hypotheses are as follows:

H2-1: Trust in reviews will be positively associated with trust in a product.

H2-2: Trust in reviews will be positively associated with trust in a company.

H3: Trust in a product will be positively associated with trust in a company

H4: Trust in a product will mediate the relationship between trust in reviews and trust in a company.

4. Research Results

4.1 Demographic Characteristics

A total of 302 respondents participated in this study. Among the respondents, 81 were male and 221 were female, with a majority of female participants. In terms of age distribution, the largest group consisted of individuals aged 20 to 25, 164 respondents, while there were also 74 respondents aged 40 above. A significant portion of the participants had made purchases of household goods and food products, with the primary platform used being Taobao. Detailed demographic characteristics are presented in <Table 2>.

<Table 2> Demographic Characteristics of Survey Respondents

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4.2 Results

Before the research analysis, it was found that there was a gender difference among the respondents, and it was checked whether there was a difference according to gender. A t-test analysis was conducted by dividing the gender into two groups. The analysis results showed that there was no difference according to gender in the remaining variables except for corporate trust (<Table 3>).

<Table 3> T-test Analysis Results According to Gender

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**p < .01.

4.2.1 Correlation, Mean and Standard Deviation Result

The correlation analysis among variables along with the mean and standard deviation analysis are as follows. For the means, values ranged from 3.3045 to 3.8598, while for the standard deviations, values ranged from 0.7014 to 0.7913. The correlation analysis revealed significant correlations among all included variables, with a notable strong correlation observed between product trust and company trust variables (<Table 4>).

<Table 4> Correlation, Mean and Standard Deviation Result

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**p < .01.

4.2.2 Exploratory Factor Analysis and Reliability Result

The results of the exploratory factor analysis are presented in <Table 5> and <Table 6>. To facilitate factor analysis, the variables were distinguished and analyzed twice. The four independent variables showed a total of 13 items (excluding Exp2 and Use2, which fell below the standard) that were suitable for raising the standard. The trust in reviews and the trust in products and companies were analyzed for a total of 11 items (excluding Ptrust4, which fell below the standard).

<Table 5> Exploratory Factor Analysis and Reliability Result (Independent Variables)

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Kaiser-Mayer-Olkin: .923,

Battlett’s chi-squared: 2060.567, df: 120, sig: .000

<Table 6> Exploratory Factor Analysis and Reliability Result (Dependent and Mediating Variables)

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4.2.3 Exploratory Factor Analysis and Reliability Result

A confirmatory factor analysis was conducted using the AMOS program based on the results of the exploratory factor analysis. Absolute fit indices and incremental fit indices, among others, were used to evaluate the model’s fit. The construct reliability and the average variance extracted (AVE) values were derived to measure internal consistency. The results of the model fit are as follows: CMIN: 496.864, DF: 231, p: .000, CMIN/DF: 2.151, RMR: .030, RMSEA: .062, GFI: .876, PGFI: .674, NFI: .915, IFI: .953, TLI: .943, CFI: .952. Overall, values that meet the criteria were derived, and there appeared to be no major problems with the model fit for the research. The construct reliability (> 0.7) and AVE values (> 0.5) showed that all values meet the criteria (<Table 7>).

<Table 7> Confirmatory Factor Analysis Results

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4.2.4 Hypothesis Testing Results

The results of the hypothesis tests H1-1~H1-4, H2-1~H2-2, H3 are as follows. The result of verifying the impact of the expertise of online reviews on review trust showed that the path coefficient (Estimate) was .327 (t=4.389, p<0.01), which was significant. As the expertise increases, users’ trust in online reviews increases, and among the three variables, expertise had the greatest impact on the formation of review trust. The result of verifying the impact of the enjoyment of online reviews on online review trust showed that the path coefficient (Estimate) was .350 (t=3.092, p<0.05), which was significant. It can be interpreted that if consumers feel that the content of the review is enjoyable for themselves, positive emotions influence the formation of review trust. The result of verifying the impact of the timeliness of online reviews on review trust showed that the path coefficient (Estimate) was .090 (t=.702, p>0.05), which was not significant, so the hypothesis was rejected. The result of verifying the impact of the usefulness of online reviews on review trust showed that the path coefficient was .229 (t-value=2.316, p<0.05), which was significant. In other words, it was analyzed that if one judges that the content of the review they have checked can be usefully utilized for themselves, trust in the review is formed.

Hypothesis H2-1, which states that online review trust has a positive impact on product trust, showed that the path coefficient was .566 (t-value=7.655, p-value<0.01), which was significant. Considering the environment where reviews are frequently used as reference materials before purchasing a product, this is an analysis result that can confirm the importance of reviews. Hypothesis H2-2, which states that product trust has a positive impact on corporate trust, showed that the path coefficient was .825 (t-value=8.462, p<0.01), which was significant. In other words, it can be confirmed that trusting a product translates into trust in the company that manufactures or provides the product. However, the result of verifying the impact of review trust on corporate trust showed that the path coefficient was .146 (t-value=1.760, p>0.05), which was not significant. The detailed results of the hypothesis tests are as follows (<Table 8>).

<Table 8> Analysis Results of Hypothesis (H1-1 ~ H1-4, H2-1 ~ H2-2, H3)

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The bootstrap method was used to verify the mediation effect (Bootstrap = 1,000 / Percentile Confidence Intervals = 95 / Bias-corrected Confidence Intervals = 95 set), and the significance of the mediation effect is determined by checking whether ‘0’ is included in the given confidence interval [Lee, 2014]. If ‘0’ is not included in the confidence interval, it is considered significant at the p < .05 (or .01) level [Lee, 2014]. The results of the mediation effect hypothesis (H4) are as follows (<Table 9>).

<Table 9> Analysis Results of Hypothesis (H4)

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5. Conclusion

This study aimed to examine the factors influencing trust in reviews, trust in a product and trust in a company, based on the characteristics of online reviews, targeting Chinese consumers who have experienced products online. Also, using the Trust Transfer Theory (TTT), we verified the relationship between trust in review, trust in a product, and trust in a company. The main results of this study are as follows.

First, among the characteristics of online reviews, expertise, enjoyment, and usefulness had a positive impact on trust in review. It was found that if professional terms and knowledge are included in reviews, or if potential consumers feel joy while reading reviews, consumers form trust in reviews. Also, if they judge that the review contains information necessary for purchasing a product or service, consumers are also likely to trust the review. However, recency did not affect trust inreview. This result is contrary to many previous studies, and it was found that respondents who responded to the survey value the content more than the time the review was written. Considering that the product that the respondent mainly purchased is daily necessities or food, it is judged that the category of the product to be purchased has affected the result. In other words, categories with less product change and high purchase frequency are likely to be less affected by the time of writing than products that change over a certain period of time, such as electronic devices and clothes.

Second, looking at the relationship between trust in reviews and trust in a product and a company, it was found that trust in review has a positive impact on trust in product and trust in product has a positive impact on trust in a company. The result that the trust in reviews affects trust in a product is consistent with the research results of standard previous studies, and in the research of Zhang and Fu [2019], it was found that trust formed online in the game market has a significant impact on consumer trust formation for major sellers. In the research of Belanche et al. [2014], it was found that user trust in public administration formed offline plays an important role in promoting trust in electronic services. Similarly, the result that trust in a product affects trust in a company is also the same as previous research. In the research of Sirdeshmukh et al. [2002], it was found that as trust in courier service increases, trust in the online site where orders are made increases, which is consistent with the research result of this study that trust in a product affects trust in a company. The result of this study showed that trust in review did not directly affect trust in a company, but it had a full-mediation effect through trust in a product. This confirmed statistically the phenomenon that online trust in reviews is transferred to trust in a company through trust in a product. It was confirmed that the trust formed in online reviews is transferred to trust in a product. Therefore, from a corporate perspective, because online reviews affect the company, a strategic approach is needed to enhance the trust in reviews that consumers feel.

5.1 Implication and Limitation

This study has the following practical implications for companies selling products and services using online reviews. As shown in the research results, when online reviews on online shopping platforms are professionally described, funnily expressed, and include the latest information with real-time characteristics, consumers can ultimately increase their trust in the company mentioned in the review. The transfer of trust was statistically confirmed to ultimately affect the trust of the company. These results suggest that companies need to manage online reviews and explain their importance. Therefore, companies need to develop and provide products in the direction consumers want by understanding consumer reactions through online reviews, not only the quality and diversity of products. Especially, online reviews with enjoyment have a strong impact on corporate trust, so companies should pay more attention to how to satisfy this characteristic and manage it well.

The limitations and future research of this study are as follows. First, this study confirmed the significance of how the trust of online reviews is transferred using quantitative methodology. Due to the limitations of the methodology, it did not analyze how and why trust is transferred, but future research on this question is expected to be needed. Also, the recency of online reviews, a characteristic of online reviews, did not affect review trust but did affect product trust. No specific analysis has been made on how this influence crosses layers, and a more in-depth analysis of this is needed. Second, the respondents who participated in this study showed a concentration phenomenon in specific genders, ages, and product categories. For the generalization of the results, it is judged that analysis of various genders, ages, and product categories reflecting the limitations of this study is needed. In this study, most of the respondents were women, so a t-test was conducted, but if it is considered that gender can still affect the response results, future research reflecting this limitation is needed. Therefore, in future research, it is necessary to balance gender by participating in similar responses for men and women, analyze separately according to gender, and compare differences. Also, this study did not classify age and the category of purchased goods, but if future research reflecting this area is conducted for the generalization of the results of this study, meaningful results are expected to be derived.

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