thesis on online reviews

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The Impact of Online Reviews on Consumers’ Purchasing Decisions: Evidence From an Eye-Tracking Study

1 School of Business, Ningbo University, Ningbo, China

Premaratne Samaranayake

2 School of Business, Western Sydney University, Penrith, NSW, Australia

XiongYing Cen

Yi-chen lan, associated data.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

This study investigated the impact of online product reviews on consumers purchasing decisions by using eye-tracking. The research methodology involved (i) development of a conceptual framework of online product review and purchasing intention through the moderation role of gender and visual attention in comments, and (ii) empirical investigation into the region of interest (ROI) analysis of consumers fixation during the purchase decision process and behavioral analysis. The results showed that consumers’ attention to negative comments was significantly greater than that to positive comments, especially for female consumers. Furthermore, the study identified a significant correlation between the visual browsing behavior of consumers and their purchase intention. It also found that consumers were not able to identify false comments. The current study provides a deep understanding of the underlying mechanism of how online reviews influence shopping behavior, reveals the effect of gender on this effect for the first time and explains it from the perspective of attentional bias, which is essential for the theory of online consumer behavior. Specifically, the different effects of consumers’ attention to negative comments seem to be moderated through gender with female consumers’ attention to negative comments being significantly greater than to positive ones. These findings suggest that practitioners need to pay particular attention to negative comments and resolve them promptly through the customization of product/service information, taking into consideration consumer characteristics, including gender.

Introduction

E-commerce has grown substantially over the past years and has become increasingly important in our daily life, especially under the influence of COVID-19 recently ( Hasanat et al., 2020 ). In terms of online shopping, consumers are increasingly inclined to obtain product information from reviews. Compared with the official product information provided by the sellers, reviews are provided by other consumers who have already purchased the product via online shopping websites ( Baek et al., 2012 ). Meanwhile, there is also an increasing trend for consumers to share their shopping experiences on the network platform ( Floh et al., 2013 ). In response to these trends, a large number of studies ( Floh et al., 2013 ; Lackermair et al., 2013 ; Kang et al., 2020 ; Chen and Ku, 2021 ) have investigated the effects of online reviews on purchasing intention. These studies have yielded strong evidence of the valence intensity of online reviews on purchasing intention. Lackermair et al. (2013) , for example, showed that reviews and ratings are an important source of information for consumers. Similarly, through investigating the effects of review source and product type, Bae and Lee (2011) concluded that a review from an online community is the most credible for consumers seeking information about an established product. Since reviews are comments from consumers’ perspectives and often describe their experience using the product, it is easier for other consumers to accept them, thus assisting their decision-making process ( Mudambi and Schuff, 2010 ).

A survey conducted by Zhong-Gang et al. (2015) reveals that nearly 60% of consumers browse online product reviews at least once a week and 93% of whom believe that these online reviews help them to improve the accuracy of purchase decisions, reduce the risk of loss and affect their shopping options. When it comes to e-consumers in commercial activities on B2B and B2C platforms, 82% of the consumers read product reviews before making shopping choices, and 60% of them refer to comments every week. Research shows that 93% of consumers say online reviews will affect shopping choices, indicating that most consumers have the habit of reading online reviews regularly and rely on the comments for their purchasing decisions ( Vimaladevi and Dhanabhakaym, 2012 ).

Consumer purchasing decision after reading online comments is a psychological process combining vision and information processing. As evident from the literature, much of the research has focused on the outcome and impact of online reviews affecting purchasing decisions but has shed less light on the underlying processes that influence customer perception ( Sen and Lerman, 2007 ; Zhang et al., 2010 ; Racherla and Friske, 2013 ). While some studies have attempted to investigate the underlying processes, including how people are influenced by information around the product/service using online reviews, there is limited research on the psychological process and information processing involved in purchasing decisions. The eye-tracking method has become popular in exploring and interpreting consumer decisions making behavior and cognitive processing ( Wang and Minor, 2008 ). However, there is very limited attention to how the emotional valence and the content of comments, especially those negative comments, influence consumers’ final decisions by adopting the eye-tracking method, including a gender comparison in consumption, and to whether consumers are suspicious of false comments.

Thus, the main purpose of this research is to investigate the impact of online reviews on consumers’ purchasing decisions, from the perspective of information processing by employing the eye-tracking method. A comprehensive literature review on key themes including online reviews, the impact of online reviews on purchasing decisions, and underlying processes including the level and credibility of product review information, and processing speed/effectiveness to drive customer perceptions on online reviews, was used to identify current research gaps and establish the rationale for this research. This study simulated a network shopping scenario and conducted an eye movement experiment to capture how product reviews affect consumers purchasing behavior by collecting eye movement indicators and their behavioral datum, in order to determine whether the value of the fixation dwell time and fixation count for negative comment areas is greater than that for positive comment area and to what extent the consumers are suspicious about false comments. Visual attention by both fixation dwell time and count is considered as part of moderating effect on the relationship between the valence of comment and purchase intention, and as the basis for accommodating underlying processes.

The paper is organized as follows. The next section presents literature reviews of relevant themes, including the role of online reviews and the application of eye movement experiments in online consumer decision research. Then, the hypotheses based on the relevant theories are presented. The research methodology including data collection methods is presented subsequently. This is followed by the presentation of data analysis, results, and discussion of key findings. Finally, the impact of academic practical research and the direction of future research are discussed, respectively.

Literature Review

Online product review.

Several studies have reported on the influence of online reviews, in particular on purchasing decisions in recent times ( Zhang et al., 2014 ; Zhong-Gang et al., 2015 ; Ruiz-Mafe et al., 2018 ; Von Helversen et al., 2018 ; Guo et al., 2020 ; Kang et al., 2020 ; Wu et al., 2021 ). These studies have reported on various aspects of online reviews on consumers’ behavior, including consideration of textual factors ( Ghose and Ipeirotiss, 2010 ), the effect of the level of detail in a product review, and the level of reviewer agreement with it on the credibility of a review, and consumers’ purchase intentions for search and experience products ( Jiménez and Mendoza, 2013 ). For example, by means of text mining, Ghose and Ipeirotiss (2010) concluded that the use of product reviews is influenced by textual features, such as subjectivity, informality, readability, and linguistic accuracy. Likewise, Boardman and Mccormick (2021) found that consumer attention and behavior differ across web pages throughout the shopping journey depending on its content, function, and consumer’s goal. Furthermore, Guo et al. (2020) showed that pleasant online customer reviews lead to a higher purchase likelihood compared to unpleasant ones. They also found that perceived credibility and perceived diagnosticity have a significant influence on purchase decisions, but only in the context of unpleasant online customer reviews. These studies suggest that online product reviews will influence consumer behavior but the overall effect will be influenced by many factors.

In addition, studies have considered broader online product information (OPI), comprising both online reviews and vendor-supplied product information (VSPI), and have reported on different attempts to understand the various ways in which OPI influences consumers. For example, Kang et al. (2020) showed that VSPI adoption affected online review adoption. Lately, Chen and Ku (2021) found a positive relationship between diversified online review websites as accelerators for online impulsive buying. Furthermore, some studies have reported on other aspects of online product reviews, including the impact of online reviews on product satisfaction ( Changchit and Klaus, 2020 ), relative effects of review credibility, and review relevance on overall online product review impact ( Mumuni et al., 2020 ), functions of reviewer’s gender, reputation and emotion on the credibility of negative online product reviews ( Craciun and Moore, 2019 ) and influence of vendor cues like the brand reputation on purchasing intention ( Kaur et al., 2017 ). Recently, an investigation into the impact of online review variance of new products on consumer adoption intentions showed that product newness and review variance interact to impinge on consumers’ adoption intentions ( Wu et al., 2021 ). In particular, indulgent consumers tend to prefer incrementally new products (INPs) with high variance reviews while restrained consumers are more likely to adopt new products (RNPs) with low variance.

Emotion Valence of Online Product Review and Purchase Intention

Although numerous studies have investigated factors that may influence the effects of online review on consumer behavior, few studies have focused on consumers’ perceptions, emotions, and cognition, such as perceived review helpfulness, ease of understanding, and perceived cognitive effort. This is because these studies are mainly based on traditional self-report-based methods, such as questionnaires, interviews, and so on, which are not well equipped to measure implicit emotion and cognitive factors objectively and accurately ( Plassmann et al., 2015 ). However, emotional factors are also recognized as important in purchase intention. For example, a study on the usefulness of online film reviews showed that positive emotional tendencies, longer sentences, the degree of a mix of the greater different emotional tendencies, and distinct expressions in critics had a significant positive effect on online comments ( Yuanyuan et al., 2009 ).

Yu et al. (2010) also demonstrated that the different emotional tendencies expressed in film reviews have a significant impact on the actual box office. This means that consumer reviews contain both positive and negative emotions. Generally, positive comments tend to prompt consumers to generate emotional trust, increase confidence and trust in the product and have a strong persuasive effect. On the contrary, negative comments can reduce the generation of emotional trust and hinder consumers’ buying intentions ( Archak et al., 2010 ). This can be explained by the rational behavior hypothesis, which holds that consumers will avoid risk in shopping as much as possible. Hence, when there is poor comment information presented, consumers tend to choose not to buy the product ( Mayzlin and Chevalier, 2003 ). Furthermore, consumers generally believe that negative information is more valuable than positive information when making a judgment ( Ahluwalia et al., 2000 ). For example, a single-star rating (criticism) tends to have a greater influence on consumers’ buying tendencies than that of a five-star rating (compliment), a phenomenon known as the negative deviation.

Since consumers can access and process information quickly through various means and consumers’ emotions influence product evaluation and purchasing intention, this research set out to investigate to what extent and how the emotional valence of online product review would influence their purchase intention. Therefore, the following hypothesis was proposed:

H1 : For hedonic products, consumer purchase intention after viewing positive emotion reviews is higher than that of negative emotion ones; On the other hand, for utilitarian products, it is believed that negative comments are more useful than positive ones and have a greater impact on consumers purchase intention by and large.

It is important to investigate Hypothesis one (H1) although it seems obvious. Many online merchants pay more attention to products with negative comments and make relevant improvements to them rather than those with positive comments. Goods with positive comments can promote online consumers’ purchase intention more than those with negative comments and will bring more profits to businesses.

Sen and Lerman (2007) found that compared with the utilitarian case, readers of negative hedonic product reviews are more likely to attribute the negative opinions expressed, to the reviewer’s internal (or non-product-related) reasons, and therefore, are less likely to find the negative reviews useful. However, in the utilitarian case, readers are more likely to attribute the reviewer’s negative opinions to external (or product-related) motivations, and therefore, find negative reviews more useful than positive reviews on average. Product type moderates the effect of review valence, Therefore, Hypothesis one is based on hedonic product types, such as fiction books.

Guo et al. (2020) found pleasant online customer reviews to lead to a higher purchase likelihood than unpleasant ones. This confirms hypothesis one from another side. The product selected in our experiment is a mobile phone, which is not only a utilitarian product but also a hedonic one. It can be used to make a phone call or watch videos, depending on the user’s demands.

Eye-Tracking, Online Product Review, and Purchase Intention

The eye-tracking method is commonly used in cognitive psychology research. Many researchers are calling for the use of neurobiological, neurocognitive, and physiological approaches to advance information system research ( Pavlou and Dimoka, 2010 ; Liu et al., 2011 ; Song et al., 2017 ). Several studies have been conducted to explore consumers’ online behavior by using eye-tracking. For example, using the eye-tracking method, Luan et al. (2016) found that when searching for products, customers’ attention to attribute-based evaluation is significantly longer than that of experience-based evaluation, while there is no significant difference for the experiential products. Moreover, their results indicated eye-tracking indexes, for example, fixation dwell time, could intuitively reflect consumers’ search behavior when they attend to the reviews. Also, Hong et al. (2017) confirmed that female consumers pay more attention to picture comments when they buy experience goods; when they buy searched products, they are more focused on the pure text comments. When the price and comment clues are consistent, consumers’ purchase rates significantly improve.

Eye-tracking method to explore and interpret consumers’ decision-making behavior and cognitive processing is primarily based on the eye-mind hypothesis proposed by Just and Carpenter (1992) . Just and Carpenter (1992) stated that when an individual is looking, he or she is currently perceiving, thinking about, or attending to something, and his or her cognitive processing can be identified by tracking eye movement. Several studies on consumers’ decision-making behavior have adopted the eye-tracking approach to quantify consumers’ visual attention, from various perspectives including determining how specific visual features of the shopping website influenced their attitudes and reflected their cognitive processes ( Renshaw et al., 2004 ), exploring gender differences in visual attention and shopping attitudes ( Hwang and Lee, 2018 ), investigating how employing human brands affects consumers decision quality ( Chae and Lee, 2013 ), consumer attention and different behavior depending on website content, functions and consumers goals ( Boardman and McCormick, 2019 ). Measuring the attention to the website and time spent on each purchasing task in different product categories shows that shoppers attend to more areas of the website for purposes of website exploration than for performing purchase tasks. The most complex and time-consuming task for shoppers is the assessment of purchase options ( Cortinas et al., 2019 ). Several studies have investigated fashion retail websites using the eye-tracking method and addressed various research questions, including how consumers interact with product presentation features and how consumers use smartphones for fashion shopping ( Tupikovskaja-Omovie and Tyler, 2021 ). Yet, these studies considered users without consideration of user categories, particularly gender. Since this research is to explore consumers’ decision-making behavior and the effects of gender on visual attention, the eye-tracking approach was employed as part of the overall approach of this research project. Based on existing studies, it could be that consumers may pay more attention to negative evaluations, will experience cognitive conflict when there are contradictory false comments presented, and will be unable to judge good or bad ( Cui et al., 2012 ). Therefore, the following hypothesis was proposed:

H2 : Consumers’ purchasing intention associated with online reviews is moderated/influenced by the level of visual attention.

To test the above hypothesis, the following two hypotheses were derived, taking into consideration positive and negative review comments from H1, and visual attention associated with fixation dwell time and fixation count.

H2a : When consumers intend to purchase a product, fixation dwell time and fixation count for negative comment areas are greater than those for positive comment areas.

Furthermore, when consumers browse fake comments, they are suspicious and actively seek out relevant information to identify the authenticity of the comments, which will result in more visual attention. Therefore, H2b was proposed:

H2b : Fixation dwell time and fixation count for fake comments are greater than those for authentic comments.

When considering the effect of gender on individual information processing, some differences were noted. For example, Meyers-Levy and Sternthal (1993) put forward the selectivity hypothesis, a theory of choice hypothesis, which implies that women gather all information possible, process it in an integrative manner, and make a comprehensive comparison before making a decision, while men tend to select only partial information to process and compare according to their existing knowledge—a heuristic and selective strategy. Furthermore, for an online product review, it was also reported that gender can easily lead consumers to different perceptions of the usefulness of online word-of-mouth. For example, Zhang et al. (2014) confirmed that a mixed comment has a mediating effect on the relationship between effective trust and purchasing decisions, which is stronger in women. This means that men and women may have different ways of processing information in the context of making purchasing decisions using online reviews. To test the above proposition, the following hypothesis was proposed:

H3 : Gender factors have a significant impact on the indicators of fixation dwell time and fixation count on the area of interest (AOI). Male purchasing practices differ from those of female consumers. Male consumers’ attention to positive comments is greater than that of female ones, they are more likely than female consumers to make purchase decisions easily.

Furthermore, according to the eye-mind hypothesis, eye movements can reflect people’s cognitive processes during their decision process ( Just and Carpenter, 1980 ). Moreover, neurocognitive studies have indicated that consumers’ cognitive processing can reflect the strategy of their purchase decision-making ( Rosa, 2015 ; Yang, 2015 ). Hence, the focus on the degree of attention to different polarities and the specific content of comments can lead consumers to make different purchasing decisions. Based on the key aspects outlined and discussed above, the following hypothesis was proposed:

H4 : Attention to consumers’ comments is positively correlated with consumers’ purchasing intentions: Consumers differ in the content of comments to which they gaze according to gender factors.

Thus, the framework of the current study is shown in Figure 1 .

Conceptual framework of the study.

Materials and Methods

The research adopted an experimental approach using simulated lab environmental settings for collecting experimental data from a selected set of participants who have experience with online shopping. The setting of the task was based on guidelines for shopping provided on Taobao.com , which is the most famous and frequently used C2C platform in China. Each experiment was set with the guidelines provided and carried out for a set time. Both behavioral and eye movement data were collected during the experiment.

Participants

A total of 40 healthy participants (20 males and 20 females) with online shopping experiences were selected to participate in the experiment. The participants were screened to ensure normal or correct-to-normal vision, no color blindness or poor color perception, or other eye diseases. All participants provided their written consent before the experiment started. The study was approved by the Internal Review Board of the Academy of Neuroeconomics and Neuromanagement at Ningbo University and by the Declaration of Helsinki ( World Medical Association, 2014 ).

With standardization and small selection differences among individuals, search products can be objectively evaluated and easily compared, to effectively control the influence of individual preferences on the experimental results ( Huang et al., 2009 ). Therefore, this research focused on consumer electronics products, essential products in our life, as the experiment stimulus material. To be specific, as shown in Figure 2 , a simulated shopping scenario was presented to participants, with a product presentation designed in a way that products are shown on Taobao.com . Figure 2 includes two segments: One shows mobile phone information ( Figure 2A ) and the other shows comments ( Figure 2B ). Commodity description information in Figure 2A was collected from product introductions on Taobao.com , mainly presenting some parameter information about the product, such as memory size, pixels, and screen size. There was little difference in these parameters, so quality was basically at the same level across smartphones. Prices and brand information were hidden to ensure that reviews were the sole factor influencing consumer decision-making. Product review areas in Figure 2B are the AOI, presented as a double-column layout. Each panel included 10 (positive or negative) reviews taken from real online shopping evaluations, amounting to a total of 20 reviews for each product. To eliminate the impact of different locations of comments on experimental results, the positions of the positive and negative comment areas were exchanged, namely, 50% of the subjects had positive comments presented on the left and negative comments on the right, with the remaining 50% of the participants receiving the opposite set up.

Commodity information and reviews. (A) Commodity information, (B) Commodity reviews. Screenshots of Alibaba shopfront reproduced with permission of Alibaba and Shenzhen Genuine Mobile Phone Store.

A total of 12,403 product reviews were crawled through and extracted from the two most popular online shopping platforms in China (e.g., Taobao.com and JD.com ) by using GooSeeker (2015) , a web crawler tool. The retrieved reviews were then further processed. At first, brand-related, price-related, transaction-related, and prestige-related contents were removed from comments. Then, the reviews were classified in terms of appearance, memory, running speed, logistics, and so on into two categories: positive reviews and negative reviews. Furthermore, the content of the reviews was refined to retain the original intention but to meet the requirements of the experiment. In short, reviews were modified to ensure brevity, comprehensibility, and equal length, so as to avoid causing cognitive difficulties or ambiguities in semantic understanding. In the end, 80 comments were selected for the experiment: 40 positive and 40 negative reviews (one of the negative comments was a fictitious comment, formulated for the needs of the experiment). To increase the number of experiments and the accuracy of the statistical results, four sets of mobile phone products were set up. There were eight pairs of pictures in total.

Before the experiment started, subjects were asked to read the experimental guide including an overview of the experiment, an introduction of the basic requirements and precautions in the test, and details of two practice trials that were conducted. When participants were cognizant of the experimental scenario, the formal experiment was ready to begin. Participants were required to adjust their bodies to a comfortable sitting position. The 9 points correction program was used for calibration before the experiment. Only those with a deviation angle of less than 1-degree angle could enter the formal eye movement experiment. In our eye-tracking experiment, whether the participant wears glasses or not was identified as a key issue. If the optical power of the participant’s glasses exceeds 200 degrees, due to the reflective effect of the lens, the eye movement instrument will cause great errors in the recording of eye movements. In order to ensure the accuracy of the data recorded by the eye tracker, the experimenter needs to test the power of each participant’s glasses and ensure that the degree of the participant’s glasses does not exceed 200 degrees before the experiment. After drift correction of eye movements, the formal experiment began. The following prompt was presented on the screen: “you will browse four similar mobile phone products; please make your purchase decision for each mobile phone.” Participants then had 8,000 ms to browse the product information. Next, they were allowed to look at the comments image as long as required, after which they were asked to press any key on the keyboard and answer the question “are you willing to buy this cell phone?.”

In this experiment, experimental materials were displayed on a 17-inch monitor with a resolution of 1,024 × 768 pixels. Participants’ eye movements were tracked and recorded by the Eyelink 1,000 desktop eye tracker which is a precise and accurate video-based eye tracker instrument, integrating with SR Research Experiment Builder, Data Viewer, and third-party software tools, with a sampling rate of 1,000 Hz. ( Hwang and Lee, 2018 ). Data processing was conducted by the matching Data Viewer analysis tool.

The experiment flow of each trial is shown in Figure 3 . Every subject was required to complete four trials, with mobile phone style information and comment content different and randomly presented in each trial. After the experiment, a brief interview was conducted to learn about participants’ browsing behavior when they purchased the phone and collected basic information via a matching questionnaire. The whole experiment took about 15 min.

Experimental flow diagram. Screenshots of Alibaba shopfront reproduced with permission of Alibaba and Shenzhen Genuine Mobile Phone Store.

Data Analysis

Key measures of data collected from the eye-tracking experiment included fixation dwell time and fixation count. AOI is a focus area constructed according to experimental purposes and needs, where pertinent eye movement indicators are extracted. It can guarantee the precision of eye movement data, and successfully eliminate interference from other visual factors in the image. Product review areas are our AOIs, with positive comments (IA1) and negative comments (IA2) divided into two equal-sized rectangular areas.

Fixation can indicate the information acquisition process. Tracking eye fixation is the most efficient way to capture individual information from the external environment ( Hwang and Lee, 2018 ). In this study, fixation dwell time and fixation count were used to indicate users’ cognitive activity and visual attention ( Jacob and Karn, 2003 ). It can reflect the degree of digging into information and engaging in a specific situation. Generally, a more frequent fixation frequency indicates that the individual is more interested in the target resulting in the distribution of fixation points. Valuable and interesting comments attract users to pay more attention throughout the browsing process and focus on the AOIs for much longer. Since these two dependent variables (fixation dwell time and fixation count) comprised our measurement of the browsing process, comprehensive analysis can effectively measure consumers’ reactions to different review contents.

The findings are presented in each section including descriptive statistical analysis, analysis from the perspective of gender and review type using ANOVA, correlation analysis of purchasing decisions, and qualitative analysis of observations.

Descriptive Statistical Analysis

Fixation dwell time and fixation count were extracted in this study for each record. In this case, 160 valid data records were recorded from 40 participants. Each participant generated four records which corresponded to four combinations of two conditions (positive and negative) and two eye-tracking indices (fixation dwell time and fixation count). Each record represented a review comment. Table 1 shows pertinent means and standard deviations.

Results of mean and standard deviations.

It can be noted from the descriptive statistics for both fixation dwell time and fixation count that the mean of positive reviews was less than that of negative ones, suggesting that subjects spent more time on and had more interest in negative reviews. This tendency was more obvious in female subjects, indicating a role of gender.

Fixation results can be reported using a heat mapping plot to provide a more intuitive understanding. In a heat mapping plot, fixation data are displayed as different colors, which can manifest the degree of user fixation ( Wang et al., 2014 ). Red represents the highest level of fixation, followed by yellow and then green, and areas without color represent no fixation count. Figure 4 implies that participants spent more time and cognitive effort on negative reviews than positive ones, as evidenced by the wider red areas in the negative reviews. However, in order to determine whether this difference is statistically significant or not, further inferential statistical analyses were required.

Heat map of review picture.

Repeated Measures From Gender and Review Type Perspectives—Analysis of Variance

The two independent variables for this experiment were the emotional tendency of the review and gender. A preliminary ANOVA analysis was performed, respectively, on fixation dwell time and fixation count values, with gender (man vs. woman) and review type (positive vs. negative) being the between-subjects independent variables in both cases.

A significant dominant effect of review type was found for both fixation dwell time ( p 1  < 0.001) and fixation count ( p 2  < 0.001; see Table 2 ). However, no significant dominant effect of gender was identified for either fixation dwell time ( p 1  = 0.234) or fixation count ( p 2  = 0.805). These results indicated that there were significant differences in eye movement indicators between positive and negative commentary areas, which confirms Hypothesis 2a. The interaction effect between gender and comment type was significant for both fixation dwell time ( p 1  = 0.002) and fixation count ( p 2  = 0.001). Therefore, a simple-effect analysis was carried out. The effects of different comment types with fixed gender factors and different gender with fixed comment type factors on those two dependent variables (fixation dwell time and fixation count) were investigated and the results are shown in Table 3 .

Results of ANOVA analysis.

Results of simple-effect analysis.

When the subject was female, comment type had a significant dominant effect for both fixation dwell time ( p 1  < 0.001) and fixation count ( p 2  < 0.001). This indicates that female users’ attention time and cognitive level on negative comments were greater than those on positive comments. However, the dominant effect of comment type was not significant ( p 1  = 0.336 > 0.05, p 2  = 0.43 > 0.05) for men, suggesting no difference in concern about the two types of comments for men.

Similarly, when scanning positive reviews, gender had a significant dominant effect ( p 1  = 0.003 < 0.05, p 2  = 0.025 < 0.05) on both fixation dwell time and fixation count, indicating that men exerted longer focus and deeper cognitive efforts to dig out positive reviews than women. In addition, the results for fixation count showed that gender had significant dominant effects ( p 1  = 0.18 > 0.05, p 2  = 0.01 < 0.05) when browsing negative reviews, suggesting that to some extent men pay significantly less cognitive attention to negative reviews than women, which is consistent with the conclusion that men’s attention to positive comments is greater than women’s. Although the dominant effect of gender was not significant ( p 1  = 0.234 > 0.05, p 2  = 0.805 > 0.05) in repeated measures ANOVA, there was an interaction effect with review type. For a specific type of comment, gender had significant influences, because the eye movement index between men and women was different. Thus, gender plays a moderating role in the impact of comments on consumers purchasing behavior.

Correlation Analysis of Purchase Decision

Integrating eye movement and behavioral data, whether participants’ focus on positive or negative reviews is linked to their final purchasing decisions were explored. Combined with the participants’ purchase decision results, the areas with large fixation dwell time and concerns of consumers in the picture were screened out. The frequency statistics are shown in Table 4 .

Frequency statistics of purchasing decisions.

The correlation analysis between the type of comment and the decision data shows that users’ attention level on positive and negative comments was significantly correlated with the purchase decision ( p  = 0.006 < 0.05). Thus, Hypothesis H4 is supported. As shown in Table 4 above, 114 records paid more attention to negative reviews, and 70% of the participants chose not to buy mobile phones. Also, in the 101 records of not buying, 80% of the subjects paid more attention to negative comments and chose not to buy mobile phones, while more than 50% of the subjects who were more interested in positive reviews chose to buy mobile phones. These experimental results are consistent with Hypothesis H1. They suggest that consumers purchasing decisions were based on the preliminary information they gathered and were concerned about, from which we can deduce customers’ final decision results from their visual behavior. Thus, the eye movement experiment analysis in this paper has practical significance.

Furthermore, a significant correlation ( p  = 0.007 < 0.05) was found between the comments area attracting more interest and purchase decisions for women, while no significant correlation was found for men ( p  = 0.195 > 0.05). This finding is consistent with the previous conclusion that men’s attention to positive and negative comments is not significantly different. Similarly, this also explains the moderating effect of gender. This result can be explained further by the subsequent interview of each participant after the experiment was completed. It was noted from the interviews that most of the male subjects claimed that they were more concerned about the hardware parameters of the phone provided in the product information picture. Depending on whether it met expectations, their purchasing decisions were formed, and mobile phone reviews were taken as secondary references that could not completely change their minds.

Figure 5 shows an example of the relationship between visual behavior randomly selected from female participants and the correlative decision-making behavior. The English translation of words that appeared in Figure 5 is shown in Figure 4 .

Fixation count distribution.

The subjects’ fixation dwell time and fixation count for negative reviews were significantly greater than those for positive ones. Focusing on the screen and running smoothly, the female participant decided not to purchase this product. This leads to the conclusion that this subject thought a lot about the phone screen quality and running speed while selecting a mobile phone. When other consumers expressed negative criticism about these features, the female participant tended to give up buying them.

Furthermore, combined with the result of each subject’s gaze distribution map and AOI heat map, it was found that different subjects paid attention to different features of mobile phones. Subjects all had clear concerns about some features of the product. The top five mobile phone features that subjects were concerned about are listed in Table 5 . Contrary to expectations, factors, such as appearance and logistics, were no longer a priority. Consequently, the reasons why participants chose to buy or not to buy mobile phones can be inferred from the gazing distribution map recorded in the product review picture. Therefore we can provide suggestions on how to improve the design of mobile phone products for businesses according to the features that users are more concerned about.

Top 5 features of mobile phones.

Fictitious Comments Recognition Analysis

The authenticity of reviews is an important factor affecting the helpfulness of online reviews. To enhance the reputation and ratings of online stores, in the Chinese e-commerce market, more and more sellers are employing a network “water army”—a group of people who praise the shop and add many fake comments without buying any goods from the store. Combined with online comments, eye movement fixation, and information extraction theory, Song et al. (2017) found that fake praise significantly affects consumers’ judgment of the authenticity of reviews, thereby affecting consumers’ purchase intention. These fictitious comments glutted in the purchasers’ real ones are easy to mislead customers. Hence, this experiment was designed to randomly insert a fictitious comment into the remaining 79 real comments without notifying the participants in advance, to test whether potential buyers could identify the false comments and find out their impact on consumers’ purchase decisions.

The analysis of the eye movement data from 40 product review pictures containing this false commentary found that only several subjects’ visual trajectories were back and forth in this comment, and most participants exhibited no differences relative to other comments, indicating that the vast majority of users did not identify the lack of authenticity of this comment. Moreover, when asked whether they had taken note of this hidden false comment in interviews, almost 96% of the participants answered they had not. Thus, Hypothesis H2b is not supported.

This result explains why network “water armies” are so popular in China, as the consumer cannot distinguish false comments. Thus, it is necessary to standardize the e-commerce market, establish an online comment authenticity automatic identification information system, and crack down on illegal acts of employing network troops to disseminate fraudulent information.

Discussion and Conclusion

In the e-commerce market, online comments facilitate online shopping for consumers; in turn, consumers are increasingly dependent on review information to judge the quality of products and make a buying decision. Consequently, studies on the influence of online reviews on consumers’ behavior have important theoretical significance and practical implications. Using traditional empirical methodologies, such as self-report surveys, it is difficult to elucidate the effects of some variables, such as review choosing preference because they are associated with automatic or subconscious cognitive processing. In this paper, the eye-tracking experiment as a methodology was employed to test congruity hypotheses of product reviews and explore consumers’ online review search behavior by incorporating the moderating effect of gender.

Hypotheses testing results indicate that the emotional valence of online reviews has a significant influence on fixation dwell time and fixation count of AOI, suggesting that consumers exert more cognitive attention and effort on negative reviews than on positive ones. This finding is consistent with Ahluwalia et al.’s (2000) observation that negative information is more valuable than positive information when making a judgment. Specifically, consumers use comments from other users to avoid possible risks from information asymmetry ( Hong et al., 2017 ) due to the untouchability of online shopping. These findings provide the information processing evidence that customers are inclined to acquire more information for deeper thinking and to make a comparison when negative comments appear which could more likely result in choosing not to buy the product to reduce their risk. In addition, in real online shopping, consumers are accustomed to giving positive reviews as long as any dissatisfaction in the shopping process is within their tolerance limits. Furthermore, some e-sellers may be forging fake praise ( Wu et al., 2020 ). The above two phenomena exaggerate the word-of-mouth effect of negative comments, resulting in their greater effect in contrast to positive reviews; hence, consumers pay more attention to negative reviews. Thus, Hypothesis H2a is supported. However, when limited fake criticism was mixed in with a large amount of normal commentary, the subject’s eye movements did not change significantly, indicating that little cognitive conflict was produced. Consumers could not identify fake comments. Therefore, H2b is not supported.

Although the dominant effect of gender was not significant on the indicators of the fixation dwell time and fixation count, a significant interaction effect between user gender and review polarity was observed, suggesting that consumers’ gender can regulate their comment-browsing behavior. Therefore, H3 is partly supported. For female consumers, attention to negative comments was significantly greater than positive ones. Men’s attention was more homogeneous, and men paid more attention to positive comments than women. This is attributed to the fact that men and women have different risk perceptions of online shopping ( Garbarino and Strahilevitz, 2004 ). As reported in previous studies, men tend to focus more on specific, concrete information, such as the technical features of mobile phones, as the basis for their purchase decision. They have a weaker perception of the risks of online shopping than women. Women would be worried more about the various shopping risks and be more easily affected by others’ evaluations. Specifically, women considered all aspects of the available information, including the attributes of the product itself and other post-use evaluations. They tended to believe that the more comprehensive the information they considered, the lower the risk they faced of a failed purchase ( Garbarino and Strahilevitz, 2004 ; Kanungo and Jain, 2012 ). Therefore, women hope to reduce the risk of loss by drawing on as much overall information as possible because they are more likely to focus on negative reviews.

The main finding from the fixation count distribution is that consumers’ visual attention is mainly focused on reviews containing the following five mobile phone characteristics: running smoothly, battery life, fever condition of phones, pixels, and after-sales service. Considering the behavior results, when they pay more attention to negative comments, consumers tend to give up buying mobile phones. When they pay more attention to positive comments, consumers often choose to buy. Consequently, there is a significant correlation between visual attention and behavioral decision results. Thus, H4 is supported. Consumers’ decision-making intention can be reflected in the visual browsing process. In brief, the results of the eye movement experiment can be used as a basis for sellers not only to formulate marketing strategies but also to prove the feasibility and strictness of applying the eye movement tracking method to the study of consumer decision-making behavior.

Theoretical Implications

This study has focused on how online reviews affect consumer purchasing decisions by employing eye-tracking. The results contribute to the literature on consumer behavior and provide practical implications for the development of e-business markets. This study has several theoretical contributions. Firstly, it contributes to the literature related to online review valence in online shopping by tracking the visual information acquisition process underlying consumers’ purchase decisions. Although several studies have been conducted to examine the effect of online review valence, very limited research has been conducted to investigate the underlying mechanisms. Our study advances this research area by proposing visual processing models of reviews information. The findings provide useful information and guidelines on the underlying mechanism of how online reviews influence consumers’ online shopping behavior, which is essential for the theory of online consumer behavior.

Secondly, the current study offers a deeper understanding of the relationships between online review valence and gender difference by uncovering the moderating role of gender. Although previous studies have found the effect of review valence on online consumer behavior, the current study first reveals the effect of gender on this effect and explains it from the perspective of attention bias.

Finally, the current study investigated the effect of online reviews on consumer behavior from both eye-tracking and behavioral self-reports, the results are consistent with each other, which increased the credibility of the current results and also provides strong evidence of whether and how online reviews influence consumer behavior.

Implications for Practice

This study also has implications for practice. According to the analysis of experimental results and findings presented above, it is recommended that online merchants should pay particular attention to negative comments and resolve them promptly through careful analysis of negative comments and customization of product information according to consumer characteristics including gender factors. Based on the findings that consumers cannot identify false comments, it is very important to establish an online review screening system that could automatically screen untrue content in product reviews, and create a safer, reliable, and better online shopping environment for consumers.

Limitations and Future Research

Although the research makes some contributions to both theoretical and empirical literature, it still has some limitations. In the case of experiments, the number of positive and negative reviews of each mobile phone was limited to 10 positive and 10 negative reviews (20 in total) due to the size restrictions on the product review picture. The number of comments could be considered relatively small. Efforts should be made in the future to develop a dynamic experimental design where participants can flip the page automatically to increase the number of comments. Also, the research was conducted to study the impact of reviews on consumers’ purchase decisions by hiding the brand of the products. The results would be different if the brand of the products is exposed since consumers might be moderated through brand preferences and brand loyalty, which could be taken into account in future research projects.

Data Availability Statement

Author contributions.

TC conceived and designed this study. TC, PS, and MQ wrote the first draft of the manuscript. TC, XC, and MQ designed and performed related experiments, material preparation, data collection, and analysis. TC, PS, XC, and Y-CL revised the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

The authors wish to thank the Editor-in-Chief, Associate Editor, reviewers and typesetters for their highly constructive comments. The authors would like to thank Jia Jin and Hao Ding for assistance in experimental data collection and Jun Lei for the text-polishing of this paper. The authors thank all the researchers who graciously shared their findings with us which allowed this eye-tracking study to be more comprehensive than it would have been without their help.

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What makes an online review credible? A systematic review of the literature and future research directions

• Open access
• Published: 05 December 2022
• Volume 74 , pages 627–659, ( 2024 )

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• K. Pooja   ORCID: orcid.org/0000-0001-7735-8308 1 &
• Pallavi Upadhyaya   ORCID: orcid.org/0000-0003-4523-2051 2  

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Online reviews of products and services are strategic tools for e-commerce platforms, as they aid in consumers’ pre-purchase decisions. Past research studies indicate online reviews impact brand image and consumer behaviour. With several instances of fake reviews and review manipulations, review credibility has become a concern for consumers and service providers. In recent years, due to growing webcare attitude among managers, the need for maintaining credible online reviews on the e-commerce platforms has gained attention. Though, there are several empirical studies on review credibility, the findings are diverse and contradicting. Therefore, in this paper, we systematically review the literature to provide a holistic view of antecedents of online review credibility. We examine variables, methods, and theoretical perspective of online review credibility research using 69 empirical research papers shortlisted through multi-stage selection process. We identify five broad groups of antecedents: source characteristics, review characteristics, consumer characteristics, interpersonal determinants in the social media platform and product type. Further, we identify research issues and propose directions for future research. This study contributes to existing knowledge in management research by providing the holistic understanding of the “online review credibility” construct and helps understand what factors lead to consumers’ belief in the credibility of online review. The insights gained would provide managers adequate cues to design effective online review systems.

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1 Introduction

Online reviews of products and services have become an integral component of product information on e-commerce platforms and are often used as strategic instrument to gain competitive advantage (Gutt et al. 2019 ). They are influential in marketing communications and help shoppers identify the products (Chen and Xie 2008 ) and make informed pre-purchase decisions (Hong and Pittman 2020 ; Eslami et al. 2018 ; Klaus and Changchit 2019 ; Reyes- Menendez et al. 2019 ). In the absence of physical interaction with the product, they aid consumers to take decisions based on experiences shared by previous users on the e-commerce platform (Klaus and Changchit 2019 ). Reviews facilitate the free flow of consumer-generated content that help managers promote their products or brand or company (Smith 2011 ). The products that get at least 5 reviews have a 270% higher conversion rate compared to the products with no reviews (Collinger et al. 2017 ).

With the growing popularity of online reviews, there is an overwhelming interest among researchers to understand the characteristics of reviews and reviewer that contribute to the credibility of online reviews (Cheung et al. 2009 ; Chih et al. 2020 ; Fang and Li 2016 ; Jimenez and Mendoza 2013 ; Liu and Ji 2018 ; Mumuni et al. 2019 ; Qiu et al. 2012 ; Tran and Can 2020 ; Yan et al. 2016 ). The credibility of online information and digital media is often contested, due to the lack of quality control standards and ambiguity concerning the ownership of the information with the convergence of information and media channels (Flanagin and Metzger 2007 ). As all online reviews cannot be trusted (Johnson and Kaye 2016 ) and when sources are uncertain (Lim and Van Der Heide 2015 ) consumers often use cues to assess review credibility. The credibility issue also arises due to review manipulation practices by asking the reviewers to write a positive review in favour of the brand and to write a negative review attacking the competitor's product, by incentivizing the reviewer (Wu et al. 2015 ).

Recent meta-analysis studies on electronic word of mouth (eWOM) communications have focused on factors impacting eWOM providing behaviour (Ismagilova et al. 2020a ), the effect of eWOM on intention to buy (Ismagilova et al. 2020b ), the effect of source credibility on consumer behaviour (Ismagilova et al. 2020c ), factors affecting adoption of eWOM message (Qahri-Saremi and Montazemi 2019 ) and eWOM elasticity (You et al. 2015 ). Moran and Muzellec ( 2017 ) and recently Verma and Dewani ( 2020 ) have proposed four-factor frameworks for eWOM Credibility. Zheng ( 2021 ) presented a systematic review of literature on the classification of online consumer reviews.

Even though there are literature reviews and meta-analysis on eWOM, they address different research questions or constructs in eWOM and no attempt to synthesise the antecedents of online review credibility, in the context of products and services has been made. Xia et al. ( 2009 ) posit that all eWOM are not formulated equally and classify eWOM as “many to one” (e.g., No of ratings, downloads calculated by computers), “many to many” (e.g., Discussion forums), “one to many” (e.g., Text-based product reviews), and “one to one” (instant messaging). Studies confirm that the effort to process and persuasiveness of different forms of eWOM vary (Weisfeld -Spolter et al. 2014 ). Senecal and Nantel ( 2004 ) argue that consumers spend significantly more time and effort to process online reviews than any other form of eWOM. Hence understanding credibility of the online reviews and the factors that influence credibility is important for managers of e-commerce platforms.

Our objective in this paper is three-fold: First, we revisit, review, and synthesize 69 empirical research on online review credibility that focuses on textual online reviews of products and services (“one to many” form of eWOM). Second, we identify the antecedents of review credibility. Finally, we identify gaps and propose future research directions in the area of online reviews and online review credibility. From theoretical perspective, this systematic review synthesises the antecedents of review credibility, in the context of online reviews of products and services. As in past literature, eWOM and online reviews are interchangeably used, we carefully analysed both the eWOM credibility and online review credibility and selected studies that focused on reviews of products and services. Studies on sponsored posts on social media, blogs, the brand initiated eWOM communication were excluded. From managerial perspective, this study would aid managers of e-commerce platforms, a holistic view of review credibility and aid in the design of online review systems.

1.1 Defining online review credibility

Mudambi and Schuff ( 2010 ) define online reviews as “peer-generated product evaluations, posted on company or third-party websites”. Person-to-person communication via the internet is eWOM. An online review is a form of eWOM. There are various channels of eWOM such as social media, opinion forums, review platforms, and blogs. Past literature posits that credible eWOM is one that is perceived as believable, true, or factual (Fogg et al. 2001 ; Tseng and Fogg. 1999 ).

The perception a consumer holds regarding the veracity of online review is considered as the review credibility (Erkan and Evans 2016 ). Several research studies (Cheung et al. 2009 ; Dong 2015 ) define credible online reviews as a review that the consumers perceive as truthful, logical, and believable. Past research defines credibility to be associated with consumers’ perception and evaluation and not as a direct measure of the reality of reviews (Chakraborty and Bhat 2018a ). The credibility of online reviews is described as consumers’ assessment of the accuracy (Zha et al. 2015 ) and validity of the reviews (Chakraborty and Bhat 2017 ).

2 Research methods

This paper uses the systematic literature review method (Linnenluecke et al. 2020 ; Moher et al. 2009 ; Neumann 2021 ; Okoli 2015 ; Snyder 2019 ) to synthesize the research findings. Liberati et al. ( 2009 ) explains systematic review as a process for identifying, critically appraising relevant research and analyzing data. Systematic reviews differ from meta-analysis with respect to methods of analysis used. While meta-analysis focuses primarily on quantitative and statistical analysis; systematic reviews use both quantitative and qualitative analysis and critical appraisal of the literature. In a systematic review, pre-specified protocols on inclusion and exclusion of the articles are used to identify the evidence that fits the criteria to answer the research question (Snyder 2019 ). In this paper, we follow the steps proposed by Okoli ( 2015 ) for conducting the systematic review process and the recommendations given by Fisch and Block ( 2018 ) to improve the quality of the review. The purpose of our systematic literature review is to identify and synthesize the antecedents of online review credibility.

The study uses journal articles from two popular research databases (Scopus and Web of Science) to conduct a systematic search of articles on review credibility/eWOM credibility. As online reviews are interchangeably used with other related concepts such as eWOM, user-generated content, and online recommendations in the literature, we used a diverse pool of sixteen keywords (refer Fig.  1 ) for the initial search. The keywords were identified through an initial review of literature and articles having these terms in the title, abstract, and keywords were chosen. Initial search and document retrieval were done in January 2022. Studies published till October 2022 were later updated in the paper. A set of filters using inclusion and exclusion criteria were applied to arrive at a focused set of relevant papers. The full-length empirical articles in English language, related to business management and allied areas were included for systematic review. Using multiple phases of filtering and reviewing (refer Fig.  1 ), we shortlisted the final list of 69 empirical papers that used either review credibility or eWOM credibility as a construct with a focus on reviews of products and services. In line with previous systematic reviews (Kuckertz and Brändle 2022 ; Nadkarni and Prügl 2021 ; Walter 2020) we excluded work in progress papers, conference papers, dissertations or books from the analysis.

Systematic review process

2.1 Descriptive analysis of empirical research on online review credibility

The 69 empirical research articles included 36 experimental design studies and 33 cross-sectional survey-based studies. Figure  2 summarises the review credibility publication trends in the last decade with their research design choices.

Research designs of Review credibility articles

Research on review credibility has used samples from diverse geographical regions, the highest number of studies being in the USA, China, and Taiwan (refer to Table 1 ). Table 2 and Table 3 summarizes the sample and analysis methods used in these studies. Even though online review is commonly used in tourism and hospitality, there are only six studies examining review credibility.

3 Theoretical perspectives in review credibility literature

Most of the empirical research (88 percent) on review credibility has used theories to explain the antecedents of review credibility. A total of 48 different theories have been invoked in explaining various dimensions of review credibility antecedents.

We observed five broad groups of theories from the underlying 48 theories that contribute to understanding the different aspects of online review credibility assessment by consumers. We discuss them in the following sections.

3.1 Information processing in online review

Several theories provide a lens to understand ways in which individual consumes or processes the information available in the online reviews. The popular theories discussed in the review credibility literature such as the elaboration likelihood model, heuristic—systematic model, accessibility—diagnosticity theory, and attribution theory describe how an individual processes information.

Building on the elaboration likelihood model (ELM) several studies have examined characteristics of online review content such as argument quality (Cheung et al. 2009 ; Hussain et al. 2018 ; Thomas et al. 2019 ), review sidedness (Cheung et al. 2012 ; Brand and Reith 2022 ), review consistency (Brand et al. 2022 ; Brand and Reith 2022 ; Cheung et al. 2012 ; Thomas et al. 2019 ), and source credibility (Cheung et al. 2012 ; Hussain et al. 2018 ; Reyes- Menendez et al. 2019 ). These dimensions are also examined using the heuristics-systematic model (HSM). These two theories are similar in their function as both ELM and HSM posit two routes (the central vs. peripheral route and the systematic vs. heuristic route) for judging the persuasiveness of messages (Chang and Wu 2014 ). In literature, the elaboration likelihood model has received more empirical support compared to the heuristics systematic model. The yale persuasive communication theory covers a wider array of factors that can affect the acceptance of the message (Chang and Wu 2014 ). This theory has been adopted by studies to evaluate the relationship between these factors with review credibility.

The psychological choice model posits that the effectiveness of online reviews gets influenced by environmental factors like product characteristics and consumer’s past experience. These factors influences the credibility assessment by the consumer and purchase decision based on their interaction with the online reviews.

Consumers’ use of information for judgment also depends upon the accessibility and diagnosticity of the input as proposed in accessibility-diagnosticity theory. This theory helps in understanding the utilization of information by individuals and posits that the information in hand has more value than information stored as a form of memory (Tsao and Hseih 2015 ; Chiou et al. 2018 ). The attribution theory helps in understanding the nature of the causal conclusion drawn by the consumers in the presence of negative and positive information (Chiou et al. 2018 ).

Overall, the theories related to information processing have contributed well to understanding the influence of strength of the message, argument, valence, source reputation, consistency, persuasiveness, and diagnosability.

Theories such as media richness theory (Tran and Can 2020 ) and language expectancy theory (Seghers et al. 2021 ) provided insights into the relevance of the quality of the information shared in online reviews. Several other theories focus on the information adoption process (ex. Information adoption mode, informational influence theory, dual-process theory). For example, cognitive cost theory has been used to explain review adoption due to the effect of different levels of cognitive involvement of the consumer when they are exposed to reviews from different platforms simultaneously (Yan et al. 2016 ).

The contribution of technology acceptance model (TAM) to the review credibility literature is operationalized in the study by Liu and Ji ( 2018 ). Hussain et al. ( 2018 ) uses TAM to complement ELM in the computer-mediated communication adoption process.

We observe that the theories in information processing in the online review have provided a theoretical lens to understand the role of the quality of the information in the online review credibility assessment.

3.2 Trust in online reviews

Studies have examined the trust formation and perception of the trustworthiness of the source of the information in online reviews using the theoretical lens of trust transfer theory and source credibility theory. Virtual communities do not support the face-to-face interaction between sender and receiver of the message. Therefore, the receiver has to rely on cues such as the reputation of the source, credibility of the source, and the reviewer profile. These cues are observed as some of the antecedents of review credibility. Trust transfer theory contributes to our understanding of how online reviews shared on a trusted e-commerce website makes the consumer consider that review is credible compared to the review shared on a website that is not trustworthy (Park and Lee 2011 ). Source credibility theory suggests trustworthiness and expertise of the source of the review have a positive relationship with review credibility (Mumuni et al. 2019 ; Shamhuyenhanzva et al. 2016 ). These theories note that when a person perceives the origin of online review as trustworthy, he would be more likely to consume the information.

3.3 Socio-cultural influence in online reviews

Individuals’ innate values or beliefs help shape their behaviour. As online reviews are more complex social conversations (Kozinets 2016 ) there is a need to gain perspectives on how these conversations differ in terms of country and culture (Bughin et al. 2010 ). The theories such as culture theory, and Hall’s categorization provide a lens to examine the influence of culture on online review consumption and assessment of review credibility (Brand and Reith 2022 ; Chiou et al. 2014 ; Luo et al. 2014 ).

In general, attention paid to understanding the influence of cultural factors on online reviews is very limited (Mariani et al. 2019 ; Gao et al. 2017 ). However, much attention has been given to understanding the role of social influence through the use of theories like social influence theory, role theory, social identity theory, social information processing theory, socio-cognitive systems theory, and value theory. The most prominent theory related to this theme is the social influence theory. Social influence theory emphasizes the social pressure faced by consumers to form a decision based on online reviews (Jha and Shah 2021 ). Social identity theory posits that an individual may reduce uncertainty by choosing to communicate with other people who share similar values and social identities (Kusumasondjaja et al. 2012 ).

Social information processing theory posits the importance of the closeness between review writer and reader on social networking as an alternative cue, in the absence of physical interaction (Lim and Van Der Heide 2015 ). The social standings of an individual in terms of the number of friends on social networks (Lim and Van Der Heide 2015 ), nonverbal cues such as profile photos (Xu 2014 ), and their impact on review credibility have been studied using this theory. In a nutshell, these theories explain individuals’ belief that gets shaped due to the influence of the social groups and how it impacts the credibility of the review.

3.4 Consumer attitude and behaviour towards online reviews

Consumers attitude towards computer-mediated communications and online reviews have been examined in past studies (Chakraborty and bhat 2017 ; Chih et al. 2020 ; Hussain et al. 2018 ; Isci and Kitapci 2020 ; Jha and Shah 2021 ) using several theoretical frameworks. Theories such as attitude—behaviour linkage, cognition-affection-behaviour (CAB) model, expectancy-disconfirmation theory (EDT), needs theory, regulatory focus theory, search and alignment theory, stimulus- organism-response model, theory of planned behaviour, yale attitude change model, associative learning theory were used in literature to examine the factors that influence the formation of the attitude and behaviour towards online reviews. These factors and their relationship with credibility evaluation have been studied by the yale attitude change model (Chakraborty and Bhat 2017 , 2018b ), and the stimulus-organism-response model (Chakraborty 2019 ). Jha and Shah ( 2021 ) adapted attitude-behavior linkage theory to study how the exposure to past reviews acts as an influence to write credible reviews.

The consumer’s expectation about product experience and credibility assessment is studied using theories like expectancy-disconfirmation theory (Jha and Shah 2021 ), needs theory (Anastasiei et al. 2021 ), and regulatory focus theory (Isci and Kitapci, 2020 ; Lee and Koo, 2012 ). Overall, these theories have contributed to the advancement of the understanding of the holistic process involved in consumer attitude formation and behaviour in online reviews.

3.5 Risk aversion

The theories such as category diagnosticity theory, prospect theory, uncertainty management theory, and uncertainty reduction theory provide a theoretical lens to examine how consumers rely on credible information to avoid uncertain outcomes. Hong and Pittman ( 2020 ) use category diagnosticity theory and prospect theory to hypothesize negative online reviews as more credible than positive reviews. An individual who focuses on reducing loss perceives negative online reviews as more diagnostic and credible. Kusumasondjaja et al. ( 2012 ) also argue that consumers try to avoid future losses by spending effort to find credible information before making a decision. With the help of these underlying assumptions, studies have used perspectives drawn from theories to understand the loss-aversion behaviour and higher perceived diagnostic value of negative information. Prospect theory suggests consumers attempt to avoid risks or loss and expect gain. Consumers avoid choosing the experience which has more negative online reviews because of the risk and loss associated with the negativity of the reviews (Floh et al. 2013 ). The risk aversion-related theories have contributed to understanding the consumers’ quest for credible information in negative reviews.

4 Antecedents of online review credibility

Literature on review credibility reveals varied nomenclature and operationalisation of antecedents of review credibility. However, we can broadly categorize review credibility antecedents into five broad groups: source characteristics, message characteristics, consumer characteristics, social/interpersonal influence, and product type (Refer to Fig.  3 ).

Anteeedents of review credibility

We discuss these antecedent themes along with the major constructs in each theme in the following sections. In the final section, we also summarise the theoretical perspectives in each antecedent themes.

4.1 Source characteristics

Literature reveals that several characteristics of the source influence the credibility perception and evaluation of review by consumers. Chakraborty and Bhat ( 2017 ) define a source as the person who writes online reviews. Researchers have operationalized the source characteristics primarily through reviewers’ knowledge and reliability (Chakraborty and Bhat 2017 ); reviewer characteristics such as identity disclosure, level of expertise, review experience, and total useful votes (Liu and Ji 2018 ). In several studies (Cheung et al. 2012 ; Chih et al. 2013 ; Mumuni et al. 2019 ; Newell and Goldsmith 2001 ; Reyes- Menendez et al. 2019 ; Yan et al. 2016 ), expertise and trustworthiness of the reviewer is one of the most common conceptualizations of source credibility. Cheung and Thadani ( 2012 ) define source credibility as the “message source’s perceived ability (expertise) or motivation to provide accurate and truthful (trustworthiness) information”.

Source credibility is used as a single construct in several studies (Abedin et al. 2021 ; Chih et al. 2013 ; Cheung et al. 2009 , 2012 ; Mumuni et al. 2019 ; Reyes-Menendez et al. 2019 ; Yan et al. 2016 ; Luo et al. 2014 ). Studies have also conceptualized its sub-dimensions such as source trustworthiness (Chih et al. 2020 ; Lo and Yao 2018 ; Shamhuyenhanzva et al. 2016 ; Siddiqui et al. 2021 ; Thomas et al. 2019 ; Tien et al. 2018 ); reviewer expertise (Anastasiei et al. 2021 ; Fang 2014 ; Fang and Li 2016 ; Jha and Shah 2021 ) and reviewers’ authority (Shamhuyenhanzva et al. 2016 ), as separate antecedents to review credibility. Mumuni et al. ( 2019 ) posited that reviewer expertise and reviewer trustworthiness as two distinct constructs. Chih et al. ( 2020 ) define source trustworthiness as the credibility of the information presented by the message sender. Thomas et al. ( 2019 ) operationalize reviewer expertise as a peripheral cue and found that the amount of knowledge that a reviewer has about a product or service is influential in consumer’s perception of review credibility. Information presented by professional commentators who are perceived as experts in the specific field was found to have a positive influence on credibility (Chiou et al. 2014 ).

Source cues help in assessing the credibility and usefulness of the information shared in product reviews (Liu and Ji 2018 ). Reviews written by the source whose identity is disclosed have higher credibility compared to the reviews written by unidentified sources (Kusumasondjaja et al. 2012 ). However, in case of positive reviews with disclosed identity of the sponsor the review, credibility is negatively affected (Wang et al. 2022 ). Zhang et al. ( 2020 ) found that suspicion about the identity of the message sender influences negatively on the message’s credibility. Past studies found that when the number of friends of a reviewer (Lim and Van Der Heide 2015 ) and a number of trusted members of the reviewer (Xu 2014 ) are high in the online review community, reviews of such reviewers are considered as more credible. If a reviewer involves very actively in writing the review, the number of reviews posted by the reviewer provides evidence to the reader that the reviews written by such reviewers are credible (Lim and Van Der Heide 2015 ). The consumer also believes online reviews to be credible when they perceive the reviewer as honest (Yan et al. 2021) and caring (Yan et al. 2021). The source characteristics as antecedents of review credibility are summarized in Table 4 .

Several studies also define the source with the characteristics of the platform where the review is published. Consumers’ trust on the website (Lee et al. 2011 ) and the reputation of the website (Chih et al. 2013 ) were found as antecedents of the review credibility. If a consumer perceives an online shopping mall as trustworthy, he would believe that reviews posted in shopping mall as credible (Lee et al. 2011 ). Chih et al. ( 2013 ) posit that in addition to the source credibility (reviewer expertise), consumers evaluate the quality of contents of a website based on website reputation, which in turn leads to higher trust on the website and higher perceived credibility of the review. Website reputation is defined as the extent to which consumers perceive the platform where the review is published to be believable and trustworthy (Chih et al. 2013 ; Thomas et al. 2019 ; Tran and Can 2020 ; Guzzo et al. 2022 ; Majali et al. 2022 ). Bae and Lee ( 2011 ) found that consumer-developed sites were perceived as more credible than marketer-developed sites. Similarly, Tsao and Hsieh ( 2015 ) found that review quality as perceived by consumers had a higher impact on review credibility on independent platforms than on corporate-run platforms. Ha and Lee ( 2018 ) found that for credence service (eg. Hospital), the provider-driven platform and reviews were more credible and for experience goods (eg. Restaurant), consumer-driven platforms were perceived as more credible.

4.2 Review characteristics

Several characteristics of the message or the review are found to influence the review credibility on online review platforms (presented in Table 5 ). A product with a large number of reviews provides evidence of higher sales and popularity of the product (Flanagin and Metzger 2013 ; Hong and Pittman 2020 ; Reyes- Menendez et al. 2019 ). When online review for a product or service is higher, it directly influences the review credibility (Hong and Pittman 2020 ; Reyes- Menendez et al. 2019 ; Thomas et al. 2019 ; Tran and Can 2020 ).

If the reviewer agrees with most of online reviews or recommendations of others those reviews are considered as consistent reviews (Chakraborty and Bhat 2017 , 2018b ; Chakraborty 2019 ). The consistent online reviews were found to have higher credibility (Abedin et al. 2021 ; Baharuddin and Yaacob 2020 ; Brand and Reith 2022 ; Chakraborty and Bhat 2017 , 2018b ; Chakraborty 2019 ; Cheung et al. 2009 , 2012 ; Luo et al. 2014 ; Tran and Can 2020 ). Fang and Li ( 2016 ) found out that receiver of the information actively monitors the consistency of the information while perceiving the credibility of review. The degree of agreement in aggregated review ratings on the review platform creates consensus among the reviewers (Qiu et al. 2012 ). Information evolved from such consensus is perceived as highly credible (Lo and Yao 2018 ; Qiu et al. 2012 ). However, a few studies (Cheung et al. 2012 ; Luo et al. 2015 ; Thomas et al. 2019 ) have reported contradicting findings and argue that when the involvement of consumers is low and consumers are knowledgeable, review consistency has an insignificant impact on the review credibility.

Past studies have found strong evidence on the impact of review argument quality (Anastasiei et al. 2021 ; Baharuddin and Yaacob 2020 ; Cheung et al. 2012 ; Thomas et al. 2019 ; Tran and Can 2020 ; Tsao and Hsieh 2015 ) and review quality (Bambauer-Sachse and Mangold 2010 ; Chakraborty and Bhat 2017 , 2018b ; Chakraborty 2019 ; Liu and Ji 2018 ) and argument strength (Cheung et al. 2009 ; Fang 2014 ; Fang and Li 2016 ; Luo et al. 2015 ) on review credibility. Concreteness in the argument also positively impacts the review credibility (Shukla and Mishra 2021 ).

According to Petty et al. ( 1983 ), the strength of the argument provided in the message represents the quality of the message. Cheung et al. ( 2009 ) define argument strength as the quality of the information in the online review. Chakraborty and Bhat ( 2017 ) present review quality as the logical and reliable argument in the online review. Recent studies (Thomas et al. 2019 ; Tran and Can 2020 ) considered accuracy and completeness as dimensions of argument quality.

Review attribute helps in classifying the review as an objective review or subjective review based on the information captured (Lee and Koo 2012 ). Jimenez and Mendoza (2013); Gvili and Levy ( 2016 ) operationalize the level of detail as the amount of information present in the review about a product or service. Past studies have found evidence for the positive relationship between different attributes of reviews such as review objectivity (Luo et al. 2015 ; Abedin et al. 2021 ), level of detail (Jimenez and Mendoza 2013 ), review attribute (Lee and Koo 2012 ), message readability (Guzzo et al. 2022 ), persuasiveness of eWOM messages (Tien et al. 2018 ), interestingness (Shamuyenhanzva et al. 2016 ), graphics (Fang and Li 2016 ) and suspicion of truthfulness (Zhang et al. 2020 ) with review credibility. Vendemia ( 2017 ) found that the emotional content of information in the review also influences the review credibility. While assessing the review credibility, the utilitarian function of the review (Ran et al. 2021 ) and message content (Siddiqui et al. 2021 ) play an important role.

Several studies confirm that review valence influences review credibility (Lee and Koo 2012 ; Hong and Pittman 2020 ; Lo and Yao 2018 ; Manganari and Dimara 2017 ; Pentina et al. 2018 ; Pentina et al. 2017 ; vanLohuizen and Trujillo-Barrera 2019 ; Kusumasondjaja et al. 2012 ; Lim and Van Der Heide 2015 ; Chiou et al. 2018 ). Chiou et al. ( 2018 ) explain review valence is negative or positive evaluation of the product or service in online reviews. Review valence is often operationalized in experimental research at two levels: positive reviews vs negative reviews. Several studies report that negative reviews are perceived to be more credible than positive reviews (Chiou et al. 2018 ; Kusumasondjaja et al. 2012 ; Lee and Koo 2012 ; Lo and Yao 2018 ; Manganari and Dimara 2017 ). Negative reviews present a consumer’s bad experience, service failure or low quality and they create a loss-framed argument. Tversky and Kahneman ( 1991 ) explain that loss-framed arguments have a greater impact on the behaviour of consumer than gain-framed arguments. Contradictory to these findings, a few studies found that positive reviews are more credible than negative reviews (Hong and Pittman 2020 ; Pentina et al. 2017 , 2018 ). Lim and Van Der Heide ( 2015 ) found that though negative reviews impact greatly on consumer behavior it is perceived to be less credible.

Several studies (Chakraborty 2019 ; Cheung et al. 2012 ; Luo et al. 2015 ) have observed the impact of review sidedness (positive, negative or two-sided reviews) on review credibility and found that two-sided reviews are perceived as more credible. Further, Cheung et al. ( 2012 ) found that when consumers’ expertise level was high and involvement level was low, review sidedness had a stronger impact on review credibility.

Star ratings are numerical evidence of product performance (Hong and Pittman 2020 ). Star rating represents the average rating of all the review ratings therefore it helps to assess the conclusions in general (Tran and Can 2020 ). Rating evaluation needs a low amount of cognitive effort while processing the review information (Thomas et al. 2019 ). Past studies have found star ratings (Hong and Pittman 2020 ), aggregated review scores (Camilleri 2017 ), product or service ratings (Thomas et al. 2019 ; Tran and Can 2020 ), review ratings (Luo et al. 2015 ), and recommendation or information rating (Cheung et al. 2009 ) act as peripheral cues influencing the review credibility.

4.3 Consumer characteristics

Receiver is the consumer of the review and consumer needs, traits, motivation, knowledge, and involvement have been found to influence the review credibility. Chih et al. ( 2013 ) posit that online community members have two types of needs: functional need (need to find useful product information) and social need (need to build social relationships with others). These needs motivate consumers to use online reviews and form perceptions of review credibility. Consumers refer to online reviews to understand the product's pros, cons, and costs (Hussain et al. 2018 ); reduce purchase risk, and information search time (Schiffman and Kanuk 2000 ).

Past research studies indicate consumer’s motivation to obtain more information on purchase context (Chih et al. 2013 ), self-worth reinforcement (Hussain et al. 2018 ), opinion seeking from other consumers (Hussain et al. 2018 ), and prior knowledge of the receiver on the product (Cheung and Thadani 2012 ; Wang et al. 2013 ), influences review credibility. When the online reviews are congruous to the consumer’s knowledge and experiences, the message is perceived to be credible (Chakraborty and Bhat 2017 , 2018b ; Chakraborty 2019 ; Cheung et al. 2009 ). Chiou et al. ( 2018 ) found that high-knowledge consumers find reviews less credible. Studies in the past have also used prior knowledge of consumers as a control variable (Bae and Lee 2011 ) and moderating variable (Doh and Hwang 2009 ) when studying other factors. Bambauer-Sachse and Mangold ( 2010 ) found that knowledge on manipulations on product reviews influenced consumers' product evaluations, negative reviews, in particular, and when they come from a highly credible source.

Lim and Van Der Heide ( 2015 ) observed differences in the perceived credibility of users and non-users of the review platform and found an interaction effect between users’ familiarity with the review platform and reviewer profile (number of friends and number of reviews) characteristics of review credibility. Consumer experience with online reviews affects their perception of review credibility (Guzzo et al 2022 ). Izogo et al ( 2022 ) posit that consumer experiences such as sensory, cognitive and behavioral experience also influences review credibility. Consumer motivation, beliefs, and knowledge, as antecedents in literature, are summarised in Table 6 .

Cheung et. al ( 2012 ) posited that the influence of source and message characteristics on review credibility depends on two characteristics of the consumer: involvement and expertise. The authors found that level of involvement and knowledge of consumers moderate the relationships between review characteristics (review consistency and review sidedness) source credibility, and review credibility. Consumers process the information through central route, when making high involvement decisions and carefully read the content (Lin et al. 2013 ; Park and Lee 2008 ). When consumers have low involvement decisions, they are more likely to use peripheral cues and pay lesser attention to the review content, resulting in low eWOM credibility. Xue and Zhou ( 2010 ) found that consumers with high involvement decisions trusted negative reviews. In a recent study, Zhang et al. ( 2020 ) found that personality traits such as dispositional trust can trigger suspicion about the truthfulness of the message and may in turn, impact review credibility.

4.4 Interpersonal influence in the social media

Earlier research shows that interpersonal influence (Chu and Kim 2011 ) and tie strength (Bansal and Voyer 2000 ) positively influences online reviews. Consumers perceive online reviews as more credible when social status and cognitive dissonance reduction can be achieved through online forums (Chih et al. 2013 ). The previous studies have considered these factors under the theme related to source or communicator of the message (Verma and Dewani 2020 )). However, the constructs tie strength and homophily represent an interpersonal relationship between the communicator and the reader. Therefore, we discuss them separately. Tie strength is considered to be higher in an online community when the members have close relationships with other members and frequently communicate with each other. Consumers who have similar tastes and preferences share information in brand communities and enjoy meeting other members in a meaningful way (Xiang et al. 2017 ). Reviews are found to be more credible when review writers get exposed to past reviews written by others (Jha and Shah 2021 ). The exposure to past reviews moderates the relationship between disconfirmation and perception of online review credibility (Jha and Shah 2021 ). The recommendations of the members on social networking sites have also been found to be influencing the credibility of online reviews (Siddiqui et al. 2021 ).

Consumers’ perceptions of their similarity to the source of message are believed to impact their credibility assessment (Gilly et al. 1998 ; Wangenheim and Bayon 2004). Brown and Reingen ( 1987 ) define similarity or homophily as the “degree to which individuals are similar to sources in terms of certain attributes”. Herrero and Martin ( 2015 ) found that hotel consumers would perceive reviews more credible when there is a similarity between users and content creators. Source homophily is found to have an impact on review credibility in the e-commerce context as well (Abedin et al. 2021 ). Similarity of the source is often described in terms of interests of consumers and content generators. Xu ( 2014 ) posits that when a greater number of trusted members for reviewers are present on the website, it increases trust, thereby impacting the perceived credibility of the review. (Table 7 ).

4.5 Product type

The type of the product (search or experience product) is found to impact user’s evaluation of review credibility (Bae and Lee 2011 ; Jimenez and Mendoza 2013 ) and review helpfulness (Mudambi and Schuff 2010 ). Experience products differ from search products. They require more effort in retrieving product’s attribute-related information online and often require direct experience to assess the product features accurately. Bae and Lee ( 2011 ) found that when review originates from the consumer-owned online community, consumers find review credible for experience products. Tsao and Hsieh ( 2015 ) found that the credibility of eWOM is stronger for credence products than search products. Credence goods are those whose qualities cannot be confirmed even after purchase, such as antivirus software and sellers often cheat consumers due to information asymmetry and charge higher prices for inferior goods.

Jimenez and Mendoza ( 2013 ) found differences in consumers’ evaluation of review credibility for search and experience products. The study found that for search products detailed reviews were considered more credible and for experience products, reviewer agreement impacted review credibility (Jimenez and Mendoza 2013 ). Chiou et al. ( 2014 ) found that the review credibility was perceived differently for elite (eg: Classical musical concerts) and mass (eg: movies) cultural offerings. The study posited that when consumers read reviews of elite cultural offerings, and it originates from professionals, it is perceived as more credible. (Table 8 ).

4.6 Summary of antecedent themes and theoretical perspectives

Review characteristics, followed by source characteristics, are the most researched themes in terms of the number of studies and theories used (refer to Fig.  4 ). It indicates the wide coverage of different theoretical perspectives examined in these two areas. Consumer characteristics, interpersonal determinants in social media, and product type were less researched antecedent themes and lesser examined through a theoretical lens.

Anteeedent themewise articles and theories

The most popular theories in review credibility literature are the elaboration likelihood model, social influence theory, accessibility- diagnosticity theory, attribution theory, and theory of reasoned action. Contribution from these theories was noted in at least four antecedent themes identified in our study. Table 9 summarizes the theories used in each antecedent theme identified in the current review.

5 Review credibility: future research directions

Though there is ample research on online review credibility, there are several gaps in understanding the aspects of consumer behavior in online review evaluation and mitigation of issues with credibility. We identify six research issues that need further investigation and empirical evidence.

5.1 Research issue 1: review credibility in a high-involvement decision-making context

Several studies have examined credibility of reviews in experience products such as movies (Chiou et al. 2014 ; Flanagin and Metzer 2013 ), restaurants (Ha and Lee 2018 ; Pentina et al. 2017 ; vanLohuizen and Trujillo-Barrera 2019 ), hotels (Lo and Yao 2018 ; Manganari and Dimara 2017 ), and search goods such as audiobooks (Camilleri 2017 ), consumer electronics (Bambauer-Sachse and Mangold 2010 ; Chiou et al. 2018 ; Lee et al. 2011 ; Lee and Koo 2012 ; Tsao and Hsieh 2015 ; Xu 2014 ), few studies (Jimenez and Mendoza 2013 ; Doh and Hwang 2009 ; Xue and Zhou 2010 ; Bae and Lee 2011 ) have examined both experience and search products.

However, most of the products involve low to medium involvement of consumers and there is a gap in understanding online review usage, credibility, and impact in the context of high involvement decisions. There are several online review platforms on high involvement goods and services such as cars (eg: carwale, auto-drive), and destination holiday planning (TripAdvisor). Consumers often use online reviews to reduce purchase risk. As purchase risks are higher in high involvement decisions, consumers would spend more time searching online to evaluate the product. It is also necessary to understand to what extent consumers trust online reviews in a high involvement decision context, which often combines online information, reviews, and offline experiences (eg: visit to a car dealership for a test drive). Previous studies on consumer involvement (Hussain et al. 2018 ; Lin et al. 2013 ; Park and Lee 2008 ; Reyes-Menendez et al. 2019 ; Xue and Zhou, 2010 ) have operationalized involvement as a multi-item construct that captures the level of involvement of consumers, using consumers’ response. Experimental design studies, using high involvement goods and their reviews would help to establish causal relationships, in high involvement goods context. As an exception, one of the recent studies by Isci and Kitapci ( 2020 ) uses experimental design using automobile products as the stimuli for the experiment. However, as observed in our analysis, there are scarce studies in high involvement decision making context.

5.2 Research issue 2: mitigation of low credibility of the online review

While extant literature is available on factors affecting review credibility and its impact on brand and consumer behavior, there is limited literature and discussion on how companies can mitigate the impact of low credibility of reviews and improve trust. More evidence and empirical research is required to demonstrate effectiveness of measures that firms can take to build credibility and improve trust. As reviews are an important component of product information in e-commerce websites and reviews are used to form pre-purchase decisions, research on mitigation of poor credibility would be useful. For example, while past research shows that reviews on marketer-developed sites are perceived less credible for experience products than consumer-developed sites (Bae and Lee 2011 ). There is a need to study strategies that marketers can use to gain the trust of consumers.

5.3 Research issue 3: mitigating impact of negative online reviews

Past studies have indicated that consumers pay more attention to negative reviews (Kusumasondjaja et al. 2012 ; Lee and Koo 2012 ; vanLohuizen and Barrera 2019 ; Yang and Mai 2010 ), and trust (Xue and Zhou 2010 ; Banerjee and Chua 2019 ) more than positive reviews. Negative reviews are found to be persuasive and have a higher impact on brand interest and purchase intention (Xue and Zhou 2010 ). There are also limited studies discussing the ways to mitigate the impact of negative reviews and strategies to deal with them in a wide variety of contexts. While extant literature is available on review characteristics such as review sidedness, review valence, and its impact on review credibility (Refer to Table 5 ), there is little empirical evidence on strategies to deal with negative reviews. An exception is a study by Pee ( 2016 ), that addressed this issue by focusing on marketing mix and suggested that managing the marketing mix can mitigate the impact of negative reviews. However, more research is needed to equip marketers with mitigation techniques and fair strategies to deal with negative reviews.

5.4 Research issue 4: credibility of brand initiated online reviews

Brand-initiated eWOM often incentivizes consumers to share the content with their friends and it is unclear whether such initiatives are perceived as less credible. Brands use a variety of strategies to promote products on social media and facilitate person-to-person communications of brand content such as referral rewards, coupons, and bonus points (Abu-El-Rub et al. 2017 ). Incentivized reviews can easily manipulate consumers as their motive is not to provide unbiased information to make an informed decision (Mayzlin et al. 2014 ).

These practices followed by the service providers, or the vendors could jeopardize the trust consumers have towards them. More research in this area would provide insights into the best social media marketing practices that are considered credible. Future research must focus on guiding marketers on ethical and credible practices in social media marketing and managing online reviews.

5.5 Research issue 5: presence of fake online reviews

Unlike incentivized reviews, deceptive opinion spams are written to sound real and to deceive the review readers (Ott, Cardie and Hancock 2013 ; Hernández Fusilier et al. 2015 ). Spammers use extreme language when it comes to praising or criticizing (Gao et al. 2021 ). These spammers are active on several social media and review platforms. As technology is continuously evolving deceptive opinion spam has found a way through the use of artificial intelligence. The social media platforms like Twitter and Facebook have experienced the rise of bot or automated accounts. This trend is even entering into online review systems and is a threat to the online review system Tousignant ( 2017 ). A study conducted by Yao et al. ( 2017 ) argues that the reviews generated by bots are not only undetectable but also scored as useful reviews. This is a serious issue as the whole purpose of online review platforms is to provide information that would lead an individual to make an informed decision, but these fake reviews severely damage the credibility of review site (Munzel 2016 ). In recent years, researchers started contributing to this area and have proposed models to detect fake reviews in different platforms such as app stores (Martens and Maalej 2019 ), online review platforms (Singh and Kumar 2017 ), and filtering fake reviews on TripAdvisor (Cardoso et al. 2018 ). However, presence of fake reviews can make the review users skeptical towards using the reviews. Future research must focus on the role of artificial intelligence in online review systems and its impact on consumers’ assessment of online review credibility. Research into tools to detect and curb the spread of fake reviews is needed to improve credibility of reviews.

5.6 Research issue 6: new forms of online reviews

Rapid technological developments have resulted in new digital formats of online reviews such as video and images. Past experimental design studies have primarily used stimuli in the form of textual reviews. As consumers use more and more multimedia data and engage in platforms such as Youtube.com or Instagram.com, research is required to examine the online review credibility and practices using new forms of reviews.

6 Theoretical contribution and managerial implications and conclusions

This paper makes three important theoretical contributions. First, it provides a consolidated account of antecedents, mediators and moderators of the construct online review credibility identifies five broad groups of antecedents. Second, this paper also makes a maiden attempt to map the antecedent themes to the theoretical frameworks in the literature. This mapping provides a holistic understanding of theories that examine various facets of online review credibility. In the process, we also identify theoretical lenses that are less investigated. Third we identify research gaps and issues that needs further investigation in the area of online review credibility. Some of the areas of future research include mitigation strategies for negative reviews and credibility of reviews in purchase of high-involvement product or service. Emergence of new forms of multimedia reviews, fake reviews and sponsored reviews have also triggered the need to push research beyond simple text reviews. Future research could use theoretical lens that have been less explored to investigate research issues in review credibility. There is a need to advance online review credibility research beyond the popular theoretical frameworks such as elaboration likelihood model, social influence theory, accessibility- diagnosticity theory, attribution theory, and theory of reasoned action.

The paper has several managerial implications. The lower credibility of reviews poses threat to its relevance in digital marketing and electronic commerce. Therefore, managers of electronic commerce must strive to adopt practices to preserve the trust and integrity of online reviews. Our review indicated five groups of antecedents of online review credibility: source characteristics, review characteristics, consumer characteristics, interpersonal characteristics in social media, and product type. Managers cannot control completely all the factors on the social media. However, by appropriately designing the e-commerce platform with the elements that influence credibility, managers will be able to improve their marketing communications. Awareness of review characteristics that impact review credibility would help managers to choose more appropriate measures to deal with negative and positive reviews. Managers must adopt a social media marketing strategy that is suitable to the context of the review and type of product.

Data availability

The dataset was generated by two licensed databases and thus cannot be made accessible.

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Pooja, K., Upadhyaya, P. What makes an online review credible? A systematic review of the literature and future research directions. Manag Rev Q 74 , 627–659 (2024). https://doi.org/10.1007/s11301-022-00312-6

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The study of the effect of online review on purchase behavior: Comparing the two research methods

International Journal of Crowd Science

ISSN : 2398-7294

Article publication date: 14 February 2020

Issue publication date: 3 March 2020

The purpose of this paper is to explain the difference and connection between the network big data analysis technology and the psychological empirical research method.

Design/methodology/approach

This study analyzed the data from laboratory setting first, then the online sales data from Taobao.com to explore how the influential factors, such as online reviews (positive vs negative mainly), risk perception (higher vs lower) and product types (experiencing vs searching), interacted on the online purchase intention or online purchase behavior.

Compared with traditional research methods, such as questionnaire and behavioral experiment, network big data analysis has significant advantages in terms of sample size, data objectivity, timeliness and ecological validity.

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Future study may consider the strategy of using complementary methods and combining both data-driven and theory-driven approaches in research design to provide suggestions for the development of e-commence in the era of big data.

• Crowd science
• Online purchase behavior
• Psychology method

Zhang, J. , Zheng, W. and Wang, S. (2020), "The study of the effect of online review on purchase behavior: Comparing the two research methods", International Journal of Crowd Science , Vol. 4 No. 1, pp. 73-86. https://doi.org/10.1108/IJCS-10-2019-0027

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Copyright © 2020, Jinghuan Zhang, Wenfeng Zheng and Shan Wang.

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1. Introduction

The development of e-commerce and the popularity of the internet, more and more people are accustomed to online shopping, they choose to buy commodities and services what they need on online. According to a report on January 2019, 74.8 per cent of netizens use online shopping. Online purchasing has become the main form of daily consumption. In this context, the study of online consumers’ purchase behavior has become the main field of consumer behavior. According to a survey report, 97.7 per cent of consumers refer to relevant reviews before online purchase. These reviews, as feed-backs of buyers, largely affect the purchase intention or purchase behavior of potential consumers. Thus, online reviews can serve as a promising data source to predict online purchase behavior. In addition, the risk perception of online purchase (when faced a buying situation, a consumer perceives a certain degree of risk involved in choice of a particular brand and how to buy it) also affects the purchase intention or decision ( Sun et al. , 2006 ). Therefore, risk perception is also a psychological variable that affects consumer purchase behavior ( Lawrence and O’Connor, 2000 ). Of course, the impact of this information on purchase intentions will be different which also depending on the type of commodities. Consumption of some commodities is common, while others have personal characteristics, making the impact of online reviews and perceived risk different.

Psychologists often use behavioral experiments in the laboratory setting to study the influential factors of consumers’ consumption decisions. Most of the methods adopted to first propose research hypotheses under the guidance of theories or based on existing studies, and then test these hypotheses under strictly controlled experimental conditions in the laboratory. For example, manipulate the proportion of positive online reviews, risk level and commodity types to explore the purchase intentions under these conditions, and then draw causal research conclusions. The biggest advantage of psychological behavioral research in the laboratory is repeatability, can withstand repeated tests and can get causal inferences.

this kind of studies can use people’s actual purchase rather than purchase intention; and

Researchers can obtain a large amount of consumption data, without having to collect it with great effort.

At the same time, these data are real, real-time, and can be verified repeatedly. However, the conclusion is based on correlation analysis and is about the correlation between the variables. The reasons behind the inference are not clear. Meanwhile, this kind of studies are the research about the commodity rather than the persons who do the purchase.

This study attempts to use two research methods and compare the differences between them from the perspective of methodology, and hope to put forward a new method to combine theory-driven with data-driven to study crowd science, with the aim of improving efficiency of the transaction, making all parties involved in the transaction taking full advantage of the online information to meet their needs.

1.1 Behavioral experiment method in psychology

Causality can be discussed. As the experimental method controls the influence of other irrelevant factors, it can be reasonably trusted to determine whether the difference in behavior results is caused by experimental conditions (i.e. independent variables), so as to make causal inference. In view of the importance of causality in research, experimental method also occupies an important position in scientific methodology,

Repeatability and verifiability. Experimental conditions of experimental method are designed by researchers in advance, so researchers have strong initiative and control. In particular, behavioral experiments have strict experimental design requirements and implementation procedures, and detailed disclosure is also made about the selection of experimental subjects, measurement tools and methods of all indicators or variables, and specific operational procedures. Therefore, the experimental method has good repeatability and testability.

1.2 Studies about online purchase behavior in psychology

An online review is a positive, neutral or negative statement, which is created by a future, actual or former consumer about a commodity or a company, and made available to the public through the internet. A growing number of researchers begin to focus on the relationship between quality of online reviews and the purchase intention. However, existing studies have found that the purchase intention of consumers is influenced by the online reviews’ quantity, which is positively correlated with the purchase intention ( Lawrence and O’Connor, 2000 ). Consumers tend to observe the proportion of positive and negative online reviews as well. The more positive reviews lead to the stronger purchase intention ( Zheng, 2008 ). However, consumers place greater emphasis on negative information in deciding to purchase ( Senecal and Nantel, 2004 ). Negative impulses attract more attention and act as stronger stimuli than positive ones. The work shows that consumers’ intention declines when the proportion of negative online reviews about a given commodity rises. When a potential consumer is exposed to a large number of negative online reviews, a negative expectation of the commodity is formed ( Chen et al. , 2012 ). Based on the existing studies, this work will further explore the impact of online reviews (positive/neutral/negative) on purchase behavior.

There is copious commodity classifications associated with online reviews. A frequently used classification is that of search and experience commodities, which is used by researchers to evaluate consumer purchase intention ( Nelson, 1974 ). A search commodity is one where information on commodity attributes is easily obtained by consumers without having to make a purchase in advance ( Hao et al. , 2009 ). Therefore, the information obtained in a search commodity is usually objective and easily compared with other similar commodities, cameras, cell phones and computers being common examples ( Li and Ren, 2017 ). On the other hand, an experience commodity is a commodity whose attributes are difficult to obtain. Consumers frequently want to feel and experience the commodity prior to any assessment. Thus, information pertaining to these commodities is mostly subjective, and evaluations conducted are based on previous experience ( Hao et al. , 2009 ). Typical examples of experience commodities are hotels, airlines, restaurants and other services ( Lim et al. , 2016 ). Consumers behave quite differently when looking for information on these two types of commodities: they tend to seek more information on other reviews concerning an experience commodity than on a search commodity ( Schlosser, 2011 ). However, some studies have pointed out that consumers are more dependent on the information provided by online reviews when purchasing search commodities ( Brodie et al. , 2013 ). The results of previous studies on the relationship between commodity types and purchase intention are not consistent. Therefore, this study would explore how commodity types affect purchase behavior in the real online shopping context.

perceived store-opportunism risk;

perceived commodity-performance risk;

perceived financial risk;

perceived delivery risk; and

perceived privacy risk ( Yu, 2016 ).

Online risk perception of consuming refers to consumers’ perception and judgment of possible adverse consequences brought by their shopping behaviors in the process of shopping ( Yu, 2016 ). Therefore, this study aims to explore how network risk perception influences purchase behavior in the network shopping context.

1.3 Big data analyze

More than ever before, the amount of data about consumers, suppliers and commodities has been exploding in today consumer world referred as “Big Data”. In addition, more data is available for the consumers from multiple sources including social network platforms. To deal with such amount of data, a new emerging technology “Big Data Analyze” is explored and employed for analyzing consumer behaviors and searching their information needs. Consumer behavior analysis is concerned with the study of inter actions among the consumers, commodities and operations such as purchasing, saving, brand choice, etc. Moreover, consumers are no longer what they used to be. Today’s consumers have evolved beyond being merely “buyers”. So, more insights information is necessary for analyzing a consumer behavior. In this aspect, Big Data has become a central role for making data driven decision making processes. However, there is no recognized concept to define the big data ( Dodds, 1991 ). Big data is usually considered as the data set that cannot be transmitted, accessed, processed and served in an endurable time period by existing communication and network systems ( Li et al. , 2018 ). Some researchers considered big data was generated by the interaction and integration of “human, machine and object”. The typical steps involved in studying big data sets: data preprocessing, dimensionality reduction and construction of predictive models.

There is an abundance of methods that can be used to build prediction models based on large data sets, ranging from relatively sophisticated approaches, such as deep learning, neural networks, probabilistic graphical models or support vector machines, to much simpler approaches, such as linear and logistic regressions. In the explanatory approach to science, the ultimate goal is to develop a mechanistic model of the data-generating process that gives rise to the observed data.

Then, combined with psychological empirical methods, how should we view psychological research based on big data analysis technology? Unfortunately, there is still very little systematic thinking on the methodology perspective of network big data psychology.

To explain the difference and connection between the network big data analysis technology and the psychological empirical research method, this study analyzed the data from laboratory setting first, then the online sales data from Taobao.com to explore how the influential factors, such as online reviews (positive vs negative mainly), risk perception (higher vs lower) and commodity types (experiencing vs searching), interacted on the online purchase intention or online purchase behavior.

2. Empirical study

2.1 study 1. the influence of consumer reviews and commodity types on online purchase intention, 2.1.1 purpose..

The purpose of this research is to analyze the role of consumer online reviews and commodity types on purchase intention by simulating online purchase behavior from the laboratory setting.

2.1.2 Methods.

2.1.2.1 participants..

We randomly sampled 120 students from Shandong Normal University and 76.7 per cent were females. The mean age of the participants was 22.03 years (SD = 1.65).

2.1.2.2 Design.

We used 2 (Online reviews: high ratio of positive reviews/high ratio of negative reviews) × 2 (commodity types: search commodity/experience commodity) in a between-subjects design. The dependent variable is consumer purchase intention.

2.1.2.3 Material.

Four psychological researchers selected USB flash disk, earphone and sound as search commodities, and clothing, facial cleanser and shoes as experience commodities. To avoid the influence of brand, price and other factors on subjects’ perception, the experimental materials only present the positive and negative proportion of commodity reviews. Among them, the material of high ratio of positive reviews’ group presented that: supposing you want to buy a commodity, 73 per cent of consumers gave the commodity positive reviews and 27 per cent gave negative reviews, and please make your decision according to the actual situation. The material of high ratio of negative online reviews’ group presented that: supposing you want to buy a commodity, 73 per cent of consumers gave the commodity negative reviews and 27 per cent gave the commodity positive reviews, and please make your decision according to the actual situation.

2.1.2.4 Research process.

This study was carried out in a quiet context. The subjects were asked to imagine themselves in the network shopping situation and assumed that they are going to buy a commodity. Then the subjects were presented the information of commodity pictures and online reviews. After they read the experimental materials, they were asked to fill in the purchase intention scale.

We adopted the purchase intention scale modified by Ma (2011) . Participants rated the way they felt on a seven-point Likert scale ranging from 1 = very little to 7 = a great extent. Cronbach’s alpha for this scale was 0.95.

2.1.3 Results.

We performed statistical analyses with online reviews and commodity types as the independent variables, the dependent variable as consumer purchase intention. The results are shown in Table I .

The results of non-repeated measures Anova ( Table II ) shows that the main effect of online reviews was significant ( F (1,116) = 238.14, p < 0.001, η p 2 = 0.67); and the main effect of commodity types is not significant, ( F (1,116) = 0.91, p >* 0.05, η p 2 = 0.01). The interaction between online reviews and commodity types is significant positively influence purchase intention. (F (1,116) = 5.93, p < 0.05, η p 2 = 0.05).

According to the results of simple effect analysis ( Figure 1 ), there is a significant difference between the online purchase intention of search commodities and experience commodities in the context of high ratio of positive online reviews ( p < 0.05), and the purchase intention of experience commodities is significantly higher than that of search commodities. No significant difference was found in purchase intention between search commodities and experience commodities ( p >* 0.05) in high ratio of negative online reviews.

Study 1 found that online reviews and commodity types provided a significant association with online purchase intention. In the context of high ratio of positive review, the online purchase intention of experience commodities is significantly higher than that of search commodities. There is no significant difference in purchase intention between search commodities and experience commodities in the context of high ratio of negative reviews. Studies have found that risk perception is negatively correlated with consumer online purchase intention, and the higher consumer risk perception is, the lower their purchase intention will be ( Chatterjee, 2001 ; Zheng, 2008 ). Risk perception as an important psychological variable that affects consumer purchase behavior, has been widely concerned by researchers ( Lawrence and O’Connor, 2000 ). Therefore, Study 2 will focus on the impact of risk perception on online purchase intention of experience commodities.

2.2 Study 2. The influence of risk perception on online purchase intention of experience commodities

2.2.1 purpose..

Firstly, the purpose of this research was to examine the influence of online reviews on purchase intention of experience commodities by simulating online purchase behavior in a laboratory setting. Secondly, this study investigated the influence of risk perception on the relationship between online reviews and purchase intention of experience commodities.

2.2.2 Methods.

2.2.2.1 participants..

The sample consisted of 120 unrelated healthy Chinese college students from Shandong Normal University, and 69.2 per cent were females. The mean age of the participants was 21.14 years (SD = 1.69).

2.2.2.2 Design.

We used 2 (Online reviews: high ratio of positive online reviews/high ratio of negative online reviews) × 2 (Risk perception: low risk perception level/high risk perception level) in a between-subjects design. The dependent variable is consumer purchase intention.

2.2.2.3 Material.

This study chose the same clothing, facial cleanser and shoes as experience commodities as in Study 1. Three decision-making tasks are used in this study. They are described in the following four different situations: high ratio of positive online reviews × high risk perception, high ratio of positive online reviews × low risk perception, high ratio of negative online reviews × high risk perception, and high ratio of negative online reviews × low risk perception. For example:

[…] high ratio of positive online reviews × low risk perception: assuming that you want to buy this kind of facial cleanser in Taobao.com, and 73 per cent of the consumers gave high ratio of positive online reviews to this commodity. Meanwhile, they think that this store provides a good service, clear logistics tracking, which are considered as a low risk perception. Please fill in the purchase intention scale according to your actual situation.

2.2.2.4 Research process.

This study was carried out in a quiet context. The participants were randomly assigned to four different situations. The subjects were asked to imagine themselves in the network shopping situation and assumed that they were going to buy a commodity. Then the subjects were presented the information. After they read the experimental materials, they were asked to fill in the purchase intention scale.

2.2.3 Results.

This paper conducted descriptive statistical analysis with online reviews and risk perception as the independent variables, and online purchase intention as the dependent variable. The results are shown in Table III .

The results of analysis of variance for non-repeated measures ( Table IV ) shows that the main effect of online reviews was significant (F (1,116) = 399.78, p < 0.001, η p 2 = 0.78). The online purchase intention of the subjects under the condition of high ratio of positive online reviews was significantly higher than that under the condition of high ratio of negative online reviews. Then, the main effect of risk perception is significant, (F (1,116) = 25.18, p <* 0.001, η p 2 = 0.18). The online purchase intention of subjects in the low risk perception group was significantly higher than that in the higher risk perception group.

According to the results of simple effect analysis, to investigate the influence of online reviews on the online purchase intention of experimental commodities under different risk perception situations. The result shows that ( Figure 2 ), under the high ratio of positive online reviews circumstances, the online purchase intention of subjects in the low risk perception context was significantly higher than that in the higher risk perception context ( p < 0.001). Under the situation of high ratio of negative online reviews, there is no significant difference between the online purchase intention of subjects under the low risk perception context and the purchase intention of subjects under the higher risk perception context ( p = 0.30).

The results of Study 2 show that the online purchase intention of subjects in the low risk perception context is significantly higher than that in the higher risk perception context. Compared with the high ratio of negative online reviews, the risk perception has a greater impact on the purchase intention of the subjects in the high ratio of positive online review situation. When faced with commodities with high ratio of positive online reviews, the lower risk perception level also Accompany by the stronger online purchase intention, which is consistent with the research hypothesis. With the increase of the risk perception level, the online purchase intention will decrease. At the same time, there is no significant difference in the influence of risk perception level on purchase intention in the high ratio of negative online review situation. This conclusion indicates that risk perception cannot adjust the relationship between the high ratio of negative online reviews and purchase intention. When the subjects are faced with the commodities of high ratio of negative online reviews, the purchase intention will be directly affected by the high ratio of negative online reviews, but not affected by the level of risk perception.

However, in network shopping context, a new risk perception is generated, which is not appearing in traditional shopping context. The perceived risk in traditional purchase context obviously is not exactly represent the perceived risk in network shopping context. Moreover, the anonymity of shopping online evaluation also makes consumers more authentic. Therefore, it is necessary to check whether the three variables have the same results in the actual online shopping situation.

2.3 Study 3. The influence of online reviews, risk perception and commodity types on purchase behavior

2.3.1 purpose..

This study explores the influence of online reviews on purchase behavior, and the role of risk perception in the real online shopping context. It intends to analyze the main factors that affect consumer purchase behavior to better improve the sales of online commodities.

2.3.2 Methods.

2.3.2.1 procedure..

In this study, Python language was used to grasp the monthly sales volume, total number of reviews, positive online reviews, neutral online reviews, negative online reviews, logistics scores and customer service scores. All data come from 300 search commodities and 300 experience commodities on Taobao.com in December 2018. The selection of commodity types and specific content is the same as Study 1. The collected data set was sorted out, and the incomplete feedback data were deleted to obtain the data collection of 590 commodities. After assigning values to online reviews, commodity sales volume and risk perception, SPSS and MPLUS were used to analyze the data.

2.3.2.2 Variable measurement.

Online reviews : we use the proportion of positive/neutral/negative reviews to analyze the relationship among purchase behavior and each kind of online reviews. The proportion of three kinds online reviews of 590 commodities was calculated, and the full distance of three types of online reviews of all commodities was obtained. Then, values were assigned to the three types of online reviews of each commodity. The proportion of positive online reviews was assigned with 92.55 per cent-94.04 per cent as 1, 94.04-95.53 per cent as 2, 95.53 per cent-97.02 per cent as 3, 97.02 per cent-98.51 per cent as 4 and 98.51 per cent-100 per cent as 5. The proportion of neutral online reviews was assigned with 0-0.692 per cent as 1, 0.692 per cent-1.384 per cent as 2, 1.384 per cent-2.076 per cent as 3, 2.076 per cent-2.768 per cent as 4, 2.768-3.46 per cent as 5. The proportion of negative online reviews was assigned with 0-0.914 per cent as 1, 0.914 per cent-1.828 per cent as 2, 1.828 per cent-2.742 per cent as 3, 2.742 per cent-3.656 per cent ass 4, 2.656 per cent-4.57 per cent as 5.

Risk perception : we use the star ratings about logistics and services as risk perception. Star rating range from one to five stars. Low to high values are assigned 1-5 points. The risk perception score of the commodity is the average of logistics and service score of each commodity. The higher score means the lower the risk perception of the consumer.

O nline purchase behavior : we use the monthly sales volume of Taobao.com at the end of December 2018 as the measurement of consumer online purchase behavior of the commodity. Then, the sales volume of the commodity is scored according to five points: assigning 1-700 to “1”, assigning 700-1400 to “2”, assigning 1400-2100 to “3”, assigning 2100-2800 to “4”, assigning 2800-3500 to “5”.

2.3.3 Result.

2.3.3.1 descriptive statistics and bivariate correlations.

The results are shown in Table V . The positive online review is not related to the purchase behavior and risk perception. The neutral online reviews had significant negative correlation with purchase behavior and risk perception. The negative online reviews were negatively correlated with purchase behavior and risk perception. As the positive online reviews are not related to purchase behavior and risk perception, the relationship between the positive online reviews and purchase behavior will not be discussed.

2.3.3.2 The relationship between the neutral online reviews, negative online reviews and purchase behavior: the moderating effect of risk perception and commodity type.

Firstly, MPLUS is used to analyze the moderating effect of risk perception and commodity type. The results ( Table VI ) showed that risk perception significantly negatively predict purchase behavior ( β = −1.08, SE = 0.10, p < 0.001). The neutral online reviews significantly negatively predict purchase behavior ( β = −0.76, SE = 0.35, p < 0.05). Our results did not show the significant relationship between the negative online reviews and purchase behavior ( β = −1.04, SE = 0.56, p >* 0.05), and the relationship between commodity type and purchase behavior was not significant ( β = −0.35, SE = 1.57, p > 0.05). The interaction of risk perception, the neutral online reviews and the negative online reviews significantly predict purchase behavior, that is, risk perception plays a positive moderating role in the relationship between the neutral online reviews, the negative online reviews and purchase behavior ( β = 0.22, SE = 0.08, p <* 0.01; β = 0.26, SE = 0.13, p < 0.05). However, the influence of interaction items of risk perception, commodity type and the negative online reviews, the neutral online reviews on purchase behavior is not significant, so the moderating variable of commodity type is no longer analyzed.

To investigate the influence of risk perception on the relationship between the neutral online reviews, the negative online reviews and purchase behavior, our study divide risk perception into high risk perception group and low risk perception group, according to the principle of average plus or minus one standard deviation. A simple slope test was carried out to investigate the influence of the neutral online reviews, the negative online reviews on purchase behavior at different levels of risk perception. The results show ( Figure 3 ) that in the case of high risk perception, the neutral online reviews and the negative online reviews has a significant predictive effect on the purchase behavior (β= −1.81, p (0.001;β= −1.77, p (0.01) in the case of low risk perception, we did not find the significantly effect of the neutral online reviews and the negative online reviews on the prediction of purchase behavior (β = 0.28, p >* 0.05;β = 0.30, p > 0.05).

The results of Study 3 show that the positive online reward was not significantly correlated with the purchase behavior, and the neutral and negative online reviews online negatively predicted the purchase behavior of consumers. It also found that risk perception plays a positive regulating role between neutral and negative online reviews and purchase behavior. In the case of higher risk perception, neutral and negative reviews had a significant effect on the prediction of buying behavior. In the case of low risk perception, neutral and negative online reviews had no significant effect on the prediction of purchase behavior.

3. Discussion

3.1 general discussion.

In the simulation of online purchase behavior, it is found that the reviews had significant impact on the purchase intention, and the purchase intention of commodities with high ratio of positive online reviews is significantly higher than that with high ratio of negative online rewards. What is inconsistent is that the analysis of real big data information found that the positive online reward was not significantly correlated with the purchase behavior, and the neutral and negative online reviews online negatively predicted the purchase behavior of consumers. Because the default set of good reviews on the website and some measures taken by merchants to get good reviews from buyers, which leads to the low reference value of favorable comments increasingly. So, consumers focus more on the relatively true descriptions of neutral and negative reviews in the purchase process. Meanwhile, in the process of shopping online, consumers will form a preliminary impression on the commodity based on the online reviews of buyers. In the process of impression formation and evaluation, more attention is paid to the negative side ( Jiang, 2015 ). Study indicates that negative ratings carry a much stronger effect than positive ones on a buyer’s trust level ( Sparks and Browning, 2011 ). Negative online reviews are viewed as an important source of information enabling online buyers to assess the quality of commodities/services. An important function of reviews is to reduce the risk and uncertainty that online buyers perceive relating to the commodity ( Ye and Zhou, 2014 ). Therefore, negative information is more likely to receive more attention and purchase behavior will be directly affected by the neutral and negative online reviews. In psychological simulated situations, the purchase intention often as a substitute for purchasing behavior also needs to be explored. Although intentions are presumed to be an indicator of to what extent people willing to approach certain behavior and how many attempt they are trying to perform certain behavior. However, there is a considerable distance between the laboratory situation and the real online shopping context, and the laboratory atmosphere also affect the psychological performance of the subjects. Although intention has been determined as a salient predictor of actual behavior to shop online, it should be acknowledged that purchase intention does not translate into purchase action ( Mo and Li, 2015 ). Researchers should explore the influencing factors of purchase behaviors in the real online context and provide reasonable suggestions for websites and sellers to generate more consumer purchase behaviors.

3.2 Crowd science

The results of behavioral research and network data are inconsistent, which causes us to rethink. Psychological research is based on theory. The fundamental hallmark of behavioral research is repeatable and can stand the test of time. Psychological research always find a causal relationship between variables. Network analysis based on big data tracks commodities rather than individuals and their psychological activities. It is based on the correlation between variables, and the underlying reasons are not clear. Both methods have their own advantages and disadvantages. So, we need to use the method of crowd science to analyze behavior.

Crowd science combines both substantive psychological science and relevant areas of the information and computer sciences. It is a complementary method and combines both data-driven and theory-driven approaches in research to provide suggestions for the development of e-commence in the era of big data. In addition to standard training in statistics and experimental design, such training programs would require coursework in software development, online data collection, machine learning and large-scale data analytics. Only when online merchants fully analyze the features of online consumers and master the consumer psychology can they be targeted to determine the business direction and business objectives according to their respective areas of expertise. They formulate commodity strategies, pricing strategies and promotional strategies for network marketing provide online services. They can better carry out network marketing activities so that it can achieve the desired purpose. It can comply with the development trend of the network economy, and make greater contributions to the development of the company. The development of crowd science really started. It can be said that all the original things may change dramatically in the context of crowd science. Similarly, the analysis of consumer buying behavior in the context of crowd science is only just beginning. Everything is still at an exploratory stage. It is still difficult to make a conclusion as to what the future looks like. A thousand people have a thousand Hamlets. Under the influence of crowd science, everyone’s feelings are different. This is precisely what crowd science wants to achieve: the precise positioning of each consumer.

The interaction among of online reviews and commodity types on consumer purchase intention

The interaction among of online reviews and risk perception on consumer purchase intention

The moderating effect of risk perception on the neutral online reviews, the negative online reviews and purchase behavior

Descriptive statistics (M±SD)

Analysis of variance of online reviews x commodity types on purchase intention

Analysis of variance of online reviews, risk perception on purchase intention

Descriptive statistics and bivariate correlations ( N = 590)

The moderating effect of risk perception, commodity types

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Sheridan is a writer from Hamilton, Ontario. She has a passion for writing about what she loves and learning new things along the way. Her topics of expertise include skincare and beauty, home decor, and DIYing.

Table of Contents

About Thesis Nootropics

Hands up if you guzzle five coffees a day to stay awake, have tried all the supplements in the book desperate to improve your headspace, and aren’t interested in prescribed medications. Designed to increase focus , Thesis nootropics might be for you. 

Thesis offers a customized blend of ingredients designed to optimize your cognitive function , with personalized details that tackle your specific needs. Nootropics boost brain performance in the same way a stimulant would, without the common negative effects. 

A study published in the Journal of Alzheimer’s Disease found that nootropics may help improve cognitive function in people with Alzheimer’s disease.

Interested in finding out more about the brand and how it works? Leaf through our Thesis Nootropics review. We’ll be your guide through the company and the process, as well as details on the treatments, highlights from customer reviews, answers to important FAQs, and more, to help you decide if it’s worth the try.

Pros and Cons

• Multiple cognitive benefits: Thesis Nootropics offers a variety of blends that cater to multiple aspects of cognitive function.
• Long-term effects: On top of short term benefits for daily life, Thesis nootropics ingredients are designed to impact the brain in the long-term.
• Personalized recommendations: Thesis Nootropics makes personalized recommendations based on your goals and unique brain chemistry.
• Potential side effects: The most common side effects to watch out for when you start taking Thesis Nootropics include heartburn, headaches, confusion, dizziness, loss of appetite, and digestive issues.
• Need to stop taking if issues arise: If you experience a headache or an upset stomach that won’t go away while taking their nootropics, Thesis recommends that you stop taking them.

What is Thesis Nootropics?

Nootropics are nutrient compounds and substances that are known to improve brain performance , such as caffeine and creatine. They help with issues that affect motivation, creativity, mood, memory, focus, and cognitive processing.

Nootropics are the ideal addition to an already healthy lifestyle that consists of exercise, proper nutrition, and enjoyable activities.  Thesis nootropics are carefully formulated to target specific needs, ranging from energy to creativity. The brand focuses on safety, ensuring that all supplements adhere to FDA guidelines and go through multiple clinical trials. 

How Thesis Nootropics Works

With all that being said, you may be wondering how Thesis provides users with an option that is specific to their needs. Fortunately, the process is simple and hassle free. Here’s how it works:

• Take the Thesis nootropics quiz
• Answer questions about your basic information
• Receive personalized recommendations 
• Get your starter kit for $120 , or $79 monthly when you subscribe 

After that, you’ll select one formula to take each week, taking one day off in between each different option. You’ll also track your results in the daily journal over the month to see how they affect your daily life. 

From there, it operates as a subscription service. Users will be able to optimize their next shipment by telling the brand which formulas worked best.

If you don’t like any of the blends in your box, let the company know and they’ll switch it for something that’s a better fit for your lifestyle, genetics, and goals.

Thesis Nootropics Ingredients

Thesis Nootropics is a brand that offers personalized nootropics designed to enhance cognitive function and overall brain health. Their blends contain a variety of ingredients that are carefully chosen for their cognitive-boosting properties. Here are some of the key ingredients in Thesis Nootropics:

• Cognizin (Citicoline) : Cognizin is a type of choline that is known for its ability to enhance cognitive function, including memory and focus.
• L-Theanine : L-Theanine is an amino acid that is found in green tea, and is known for its ability to promote relaxation and reduce stress and anxiety.
• Lion’s Mane Mushroom : Lion’s Mane Mushroom is a type of medicinal mushroom that is believed to have cognitive-boosting properties, including improved memory and focus.
• Rhodiola Rosea : Rhodiola Rosea is an adaptogenic herb that is known for its ability to reduce stress and fatigue, and improve mental clarity and cognitive function.
• Ashwagandha : Ashwagandha is an adaptogenic herb that is known for its ability to reduce stress and anxiety, and improve memory and cognitive function.
• Phosphatidylserine : Phosphatidylserine is a type of phospholipid that is found in high concentrations in the brain, and is believed to support cognitive function, including memory and focus³
• Alpha-GPC : Alpha-GPC is a type of choline that is known for its ability to enhance cognitive function, including memory and focus.
• TAU (uridine): TAU is a blend of uridine, choline, and DHA, which is believed to support brain health and cognitive function.
• Artichoke extract : Artichoke extract is believed to enhance cognitive function by increasing levels of acetylcholine, a neurotransmitter that is important for memory and learning.
• Dynamine : Dynamine is a type of alkaloid that is believed to enhance cognitive function by increasing levels of dopamine, a neurotransmitter that is important for mood and motivation.

Overall, the ingredients in Thesis Nootropics are carefully chosen for their cognitive-boosting properties, and are designed to work together to enhance overall brain health and cognitive function.

Thesis Nootropics Health Benefits

Thesis Nootropics is a brand that offers personalized nootropics designed to enhance cognitive function and overall brain health. Their blends contain a variety of ingredients that are carefully chosen for their cognitive-boosting properties, and offer numerous health benefits. Here are some of the health benefits of Thesis Nootropics:

• Increased cognitive energy : One of the key benefits of Thesis Nootropics is increased cognitive energy, which can help improve productivity, mental alertness, and motivation, as it contains cognizin .
• Enhanced mental clarity : Another benefit of Thesis Nootropics is enhanced mental clarity,given from Lion’s Mane Mushroom which can help reduce brain fog and improve focus.
• Improved memory and learning abilities : Thesis Nootropics contains ingredients that are believed to improve memory and learning abilities, like Phosphatidylserine , which can help users retain information more effectively.
• Elevated mood : Thesis Nootropics may help elevate mood and reduce symptoms of anxiety and depression, thanks to ingredients like L-Theanine and Ashwagandha .
• Lowered stress levels : The adaptogenic herbs in Thesis Nootropics, such as Rhodiola Rosea and Ashwagandha , are known for their ability to lower stress levels and promote relaxation.
• Boosted focus : Thesis Nootropics contains ingredients like Alpha-GPC and Artichoke extract , which are believed to boost focus and concentration.

While Thesis Nootropics offers numerous health benefits, it’s important to note that the long-term effects of nootropics are not yet fully understood and more research is needed.

3 Thesis Nootropics Bestsellers

Thesis energy review.

If you’re constantly struggling to keep up with the demands of your busy life, it might be time to try a natural energy booster like Thesis Energy. This powerful nootropic blend is specifically designed to increase energy, overcome fatigue, and build mental stamina.

Thesis Energy is caffeine-free, making it a great option for those who are sensitive to caffeine or looking for a natural alternative to traditional energy drinks. The Energy formulation is designed to help improve focus and mental clarity, increase cognitive energy, and reduce fatigue. Whether you’re facing a busy day at work, recovering after a night of poor sleep, or gearing up for an intense workout, Thesis Energy can help you power through.

Each ingredient in Thesis Energy is carefully chosen for its energy-boosting properties. The specific ingredients can vary depending on your needs, but they work together to help increase energy, improve mental clarity, and reduce fatigue.

To get the most out of Thesis Energy, take it every morning on an empty stomach. You can also take it again after lunch if you need an extra boost. It’s designed to help you tackle busy, hectic days, recover from poor sleep, and power through intense workouts.

If you’re tired of relying on coffee and energy drinks to get through the day, it might be time to give Thesis Energy a try. Check availability and start boosting your energy naturally today!

Thesis Creativity

If you’re someone who struggles with creativity or finds yourself feeling stuck in your creative endeavors, Thesis Creativity may be worth considering. This nootropic supplement is designed to help spark inspiration, enhance verbal fluency, and boost confidence in your own great ideas.

So what’s in Thesis Creativity? The ingredients may vary depending on your specific needs, but these ingredients work together to support stress management, memory function, mood regulation, and energy production.

By supporting stress management, memory function, and mood regulation, Thesis Creativity can help free up mental space for more creative thinking. Additionally, the caffeine and L-theanine combo can provide a boost of energy and focus without the jitters and crash that can come with caffeine alone.

To get the most out of Thesis Creativity, it is recommended to take it every morning on an empty stomach and again after lunch if you need an extra boost. This nootropic blend is particularly helpful for brainstorming and creative thinking, writing and creative projects, and public speaking and social situations.

As with any nootropic supplement, it’s important to note that the long-term effects of Thesis Creativity are not yet fully understood and more research is needed. It’s always a good idea to speak with a healthcare professional before adding any new supplements to your routine.

In summary, if you’re looking for a little extra help in the creativity department, Thesis Creativity may be a valuable addition to your nootropic lineup. Its unique blend of ingredients can help support mental clarity, mood regulation, and energy production, making it a valuable tool for any creative individual.

Thesis Logic

If you’ve been having trouble with your memory lately, such as forgetting what you had for lunch yesterday or struggling to recall common words, then Thesis Logic may be just what you need. This formula is designed to help enhance your processing speed, boost your memory, and deepen your thinking.

Thesis Logic is caffeine-free, making it a great option for those who are sensitive to caffeine. The formula is ideal for use during deep, focused work, complex problem-solving, research projects, and completing tedious tasks.

Taking Thesis Logic is easy – simply take it every morning on an empty stomach, and take it again after lunch if you need an extra boost. By incorporating Thesis Logic into your daily routine, you may notice improvements in your cognitive function and overall mental performance.

Who Is Thesis Nootropics For? 

Thesis nootropics are designed for a number of different specific needs, including anyone who wants to focus better, have more energy, and maintain mental clarity. All in all, the products are specifically formulated to improve day to day life and target your specific needs .

Thesis Nootropics Side Effects

While Thesis nootropics are designed to enhance cognitive performance and provide a range of benefits, it’s important to be aware of the potential side effects that can occur. As with any supplement, individual reactions can vary, and some people may experience side effects while others may not.

Some of the potential side effects of Thesis nootropics include:

• Insomnia : Some nootropics contain caffeine or other stimulants that can disrupt sleep patterns and lead to difficulty falling asleep or staying asleep.
• Blurry vision : Certain nootropics, such as those containing alpha GPC, have been linked to temporary blurry vision.
• High blood pressure : Stimulant-based nootropics can increase blood pressure, which can be dangerous for people with hypertension or other heart conditions.
• Fast heart rate : Similarly, stimulants can also increase heart rate, leading to palpitations or a rapid pulse.
• Circulation problem s: Certain nootropics, such as vinpocetine, can affect blood flow and circulation, leading to issues like dizziness, nausea, or headaches.
• Addiction : Some nootropics, such as those containing racetams, have been associated with the potential for addiction or dependence if used long-term.

It’s important to remember that not all nootropics will produce these side effects, and the severity of any reactions will depend on individual factors such as dosage, duration of use, and underlying health conditions. However, it’s always wise to discuss any potential risks with a healthcare professional before starting any new supplement regimen.

Additionally, it’s important to follow dosage instructions carefully and not to exceed recommended amounts, as this can increase the risk of side effects. By being mindful of potential risks and using nootropics responsibly, users can reap the benefits of these supplements without experiencing adverse effects.

Thesis Nootropics Reviews: What Do Customers Think?

At this point in our Thesis nootropics review, it’s time to turn to what customers are saying. So, we sourced testimonials from the brand’s website, Reddit, and ZenMasterWellness. And spoiler alert, the Thesis nootropics reviews we came across have nothing but good things to say.

On takethesis.com , the brand earns 4.4/5 stars out of 7,956 reviews. One patron describes their particular blend as the perfect alternative to prescription meds :

“ I have been off stimulants for months now and these formulas are far superior. My husband and daughter both noticed the change and said I have been more productive, focused, less anxious, and more “thinking outside the box”. I have tried for years to get off stims and nothing would work .”

On Reddit, many reviewers share similar sentiments about how effective the products are. One buyer shares that they tried tons of different nootropics on the market, and Thesis stands out amongst the crowd . 

On ZenMasterWellness, one reviewer states that their blend provided the exact results they were looking for :

“ They offer notable improvements to how well I’m able to focus, stay on task, and grind when it’s time to grind. In practice, this usually looks like a clearer mind and an improved ability to just… chill. With the Clarity and Creativity blends, in particular, I just feel leveled out .”

Backed by clinical trials and real customer experiences, Thesis stands out in the world of nootropics and supplements. The personalized selections prove effective, while the quality ingredients live up to expectations. 

Is Thesis Nootropics Legit?

If you’re wondering if this brand offers products that are too good to be true, this Thesis nootropics review is here to say that it is the real deal .

The brand is backed by numerous clinical trials, which highlight how 86% of customers reported improvements in a wide range of cognitive challenges, while 89% noticed an improvement in their ability to reduce stress and maintain energy.

Is Thesis Nootropics Worth It?

Thesis is an appealing choice in the world of nootropics because it provides a completely customized selection based on your needs and goals. Plus, the ingredients are potent and ensure the best effects—and you only end up paying for the benefits you actually need.

With that in mind, this Thesis nootropics review deems the brand worth the try.

Alternatives

Here are some alternatives to Thesis Nootropics that you might find interesting:

• Mind Lab Pro – This nootropic supplement is designed to improve cognitive function and mental performance. It contains 11 ingredients that work together to enhance memory, focus, and overall brain health.
• Thorne Supplements : If you’re looking for high-quality, science-based supplements, Thorne is a great choice. Their products are designed with the latest research in mind and are rigorously tested for quality and purity. Some of their popular offerings include multivitamins, protein powders, and omega-3 supplements.
• WeAreFeel Supplements : WeAreFeel is a supplement brand that offers a variety of products designed to support different aspects of your health. Their supplements are vegan-friendly and free from artificial colors, flavors, and preservatives. Some of their popular offerings include multivitamins, probiotics, and omega-3 supplements.
• Neuro Gum : If you’re looking for a quick and easy way to boost your focus and energy levels, Neuro Gum is a great option. This gum is infused with caffeine and other natural ingredients that can help improve mental clarity and alertness. Plus, it’s sugar-free and comes in a variety of delicious flavors.
• Neuriva Plus : Neuriva Plus is a brain supplement that’s designed to improve memory, focus, and cognitive performance. It contains a blend of natural ingredients, including coffee fruit extract and phosphatidylserine, that have been shown to support brain health. If you’re looking for a natural way to boost your cognitive function, Neuriva Plus is worth considering.

Thesis Nootropics Promotions & Discounts 

There aren’t currently any Thesis promos or discounts available. That being said, if you subscribe for recurring shipments of your recommended products, you’ll save $40 monthly .

Where to Buy Thesis Nootropics

At the time of this Thesis nootropics review, the products are exclusively available on the brand’s website, takethesis.com .

Is Thesis Nootropics vegan?  

Thesis nootropics are made with only vegan ingredients . That being said, while the brand has taken precautions to protect against cross contamination, the products are not certified vegan.

Is Thesis Nootropics gluten-free? 

On top of being vegan, Thesis products are made without gluten, eggs, or nuts . Again, while the brand strives to protect users against cross contamination, the products are not certified gluten free. 

What is Thesis Nootropics’ Shipping Policy?

If you’re anxiously awaiting your order from this Thesis nootropics review, you’ll be happy to hear that the company offers speedy shipping, sending orders out within 1 business day. After that, packages should arrive within only 1-3 business days . Costs are calculated at checkout.

At this time, Thesis is not able to offer international shipping. This Thesis nootropics review recommends following the brand on social media and signing up for the newsletter to stay up to date with shipping policies. 

What is Thesis Nootropics’ Return Policy?

If you find that your Thesis formula isn’t working out, the company requests that you contact them to make changes and adjustments to ensure you are able to receive the proper help.

If you would still like to make a return, follow these simple steps for a refund:

• Submit your refund request
• Ship the items back within 30 days of the original delivery
• Send an email with your tracking number to the brand
• Return any remaining product in their original packaging to: 

Thesis Returns 902 Broadway

6th Floor New York, NY 

Once your return has been received, a refund will be processed and email confirmation will be sent. It’s also important to note that the brand can only refund one month’s supply per customer and return shipping is the customer’s responsibility. 

How to Contact Thesis Nootropics

We hope you enjoyed this Thesis nootropics review! If you have any further questions about the brand or its products, you can contact them using the following methods:

• Call 1 (646) 647-3599
• Email [email protected]

902 Broadway Floor 6 New York, NY 10010

If you’re looking for other ways to boost your productivity via supplements, check out these other brands we’ve reviewed:

Thorne Supplements Review

WeAreFeel Supplements Review

Neuro Gum Review

Neuriva Plus Review

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Can You Trust Online Reviews? Apparently Not Much

Consumer advocate says there’s more deception in the world of online reviews than people realize. She recommends getting tips from friends and family instead.

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We use them all the time — Yelp, Tripadvisor, the BBB — websites that post reviews by customers, clients and patients of all sorts of companies and health care providers. But can we trust these reviews? Are the websites that post them taking steps to assure they are legit?

“No and no,” says Kay Dean of San Jose, Calif., a former criminal investigator in the U.S. Department of Education’s Office of Inspector General. Dean’s bad experience with a health care provider with glowing reviews led her on a journey into the expansive realm of fake online reviews. “I no longer put an ounce of trust in any online review site,” she says.

She is the founder of Fake Review Watch , which she says is on the side of consumers and honest businesses and attempts to show the issues that major review platforms have with fake reviews.

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Personal experience led to her investigation

About seven years ago, Dean used stellar reviews she saw on Yelp and Google to select a medical care provider. “The experience turned out to be the exact opposite of what was claimed on the platforms, leaving me suspicious about these reviews I had relied on. And so, drawing on my knowledge as an investigator, I began doing some digging and uncovered this medical practice was trading fake reviews with other businesses in Facebook groups.”

She discovered that “the online review world was saturated with so much deception — far more so than people realize.”

Frustrated by a lack of official action against this widespread fraud, Dean created YouTube videos with case studies as real examples, which she offers to major news outlets. “That’s been effective, but my larger goal is to highlight the culpability of tech companies and review sites that are not doing enough to protect the public. I try to educate people not to trust online reviews at all, and I attempt to rally public support for more enforcement and new legislation.”

Fake reviews are very convincing

I asked Dean to share the clues consumers should look for to alert them that they are reading a fake review.

“It is extremely difficult for the average consumer to discern which reviews are fake,” Dean notes, “as they can be very detailed and convincing, some written by the business itself. I’ve seen many contractor reviews with photos of work lifted off of a real estate listing in another state and thousands of Yelp reviews with content simply plagiarized from Tripadvisor written by other people, sometimes years earlier. Determining whether (a review is) real or fake often requires analyzing sets of reviewers and businesses together to see if suspicious patterns emerge indicating deception.”

Dean points out that even the Better Business Bureau website “has become polluted with review fraud, hosting plenty of fake BBB reviews. I’ve found that a robust black market exists for them, including several marketers in Facebook groups offering to sell BBB reviews. I reached out to one guy from Pakistan. He offered to sell them for $3 each!”

Furthermore, she notes, the BBB site lacks transparency. “Just click on a BBB review to find out something about the reviewer. Nothing comes up. There are no photos. No last names are used, nor is there any other way of finding out who or what else the person has reviewed, or if they even exist. So while the BBB says, ‘Trust us,’ you can’t.”

An industry of fake reviews

Online networks, many based in India, Pakistan and Bangladesh, sell fake reviews for the BBB, Yelp, Google, Angi and many more, charging as little as 50 cents per review. They have “programs” for movers, lawyers, doctors, dentists, you name it, and will create fake positive and negative reviews that appear to come from real people in cities all over America.

Sites such as Reviews That Stick offer reviews across multiple platforms to boost the reputation of a business.

“Much of the fraud, though, is organized on social media sites with impunity,” Dean says, adding, “Facebook does little to stop the marketing of fake reviews. There are scores of groups on its platform that openly facilitate buying and selling them. Under Section 230 of the Communications Decency Act , however, web-hosting platforms are not responsible for this kind of illegal activity conducted by third parties.”

Houston defamation attorney Paul Sternberg says, “But when the platform itself — such as the BBB — gives an A+ rating when they know or should know from hundreds of complaints the business is misleading its customers, I believe they have opened themselves up to being sued. Even if the platform says, ‘We do not endorse,’ the very fact of awarding that grade — which then is used by the business in its advertising — is an endorsement.”

If we can’t trust online reviews, then what?

Dean believes that until social media sites like Facebook and review platforms such as Google and Yelp can be held accountable for the rampant review fraud they allow to be foisted on the public, not much will change. This would require congressional action.

Until then, she recommends consumers use the old-fashioned method of choosing businesses — by talking to real relatives and friends about who they would recommend.

Dennis Beaver practices law in Bakersfield, Calif., and welcomes comments and questions from readers, which may be faxed to (661) 323-7993, or e-mailed to [email protected] . And be sure to visit dennisbeaver.com .

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After attending Loyola University School of Law, H. Dennis Beaver joined California's Kern County District Attorney's Office, where he established a Consumer Fraud section. He is in the general practice of law and writes a syndicated newspaper column, " You and the Law ." Through his column he offers readers in need of down-to-earth advice his help free of charge. "I know it sounds corny, but I just love to be able to use my education and experience to help, simply to help. When a reader contacts me, it is a gift." 

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Thesis Nootropics Review

Thesis has a range of targeted nootropics you can combine to optimize your results. our team will help you decide which ones are right for you..

Daniel is a senior editor and writer at Innerbody Research. After receiving his bachelor’s degree in writing, he attended post-graduate studies at George Mason University and pursued a career in nutritional science.

Dr. Segar is a cardiology fellow at the Texas Heart Institute and a member of Innerbody Research's Medical Review Board.

In this Review

Nootropics in general offer the potential to improve cognitive abilities and regulate mood without the need for a prescription. And while more research is necessary, current data suggests that they consist of ingredients that are generally safe and effective for healthy adults. 35 However, Thesis isn’t the only provider of high-quality nootropics, nor do they offer especially low prices. In this review, we'll compare and contrast Thesis’ six formulas and see how they stack up against a growing field of competitors.

Our Findings

• You can feel most results within an hour
• Products are third-party-tested for purity
• All options available without stimulants
• Outstanding phone support
• Subscriptions include complimentary wellness coaching
• Free shipping on all orders
• Use code INNERBODY for 10% off your first order
• Somewhat more expensive than competitors
• Up to four large pills per dose

Despite the somewhat high price, we recommend Thesis to anyone looking for a nootropic subscription that can be tailored to their specific needs. The formulas from Thesis provide tangible benefits with minimal ingredients, and each formula is available with or without caffeine. Thesis also offers stellar customer service and delivers their product in individually packed doses you can take just about anywhere.

Special Offer: Take 10% OFF with code INNERBODY

Why you should trust us

Over the past two decades, Innerbody Research has helped tens of millions of readers make more informed decisions about staying healthy and living healthier lifestyles. As nootropics have become more important players in the supplements landscape, we’ve taken a serious look at the key players to see which ones are worthwhile.

Thesis exists in a class of nootropics that combines multiple nootropic ingredients to achieve specific goals. We’ve spent hundreds of hours researching and testing various nootropics, including both individual ingredients and combinations like Thesis offers. In researching Thesis and their competitors, our team has read more than 100 clinical studies examining the efficacy and safety of nootropic ingredients, and we’ve combined all of that knowledge with our experiences to create this review.

If you're curious about our team's experience using Thesis nootropics and wondering how the products will arrive at your door, we made this handy, 5-minute video summarizing those details:

Additionally, like all health-related content on this website, this review was thoroughly vetted by one or more members of our Medical Review Board for accuracy.

How we evaluated Thesis

To evaluate Thesis, we examined the extensive research available on each ingredient the company uses and compared them to a growing marketplace of nootropics, many of which our testing team has tried over the past few years. Specifically, we assessed how effectively Thesis' formulas work, as well as their safety, cost, and the convenience of acquiring and taking them.

Ultimately, we found Thesis to be one of the more reliable companies in terms of product quality and customer care, even if they are among the more expensive nootropic brands. For any nootropic, you’re looking to create a noticeable effect in brain performance, and altering anything to do with that sensitive chemistry likely warrants a fair investment. The bargain bin is not typically where you want to shop for mind-enhancing substances.

We’ll get into a more direct comparison between Thesis and their competitors a little later, and you’ll see that the balance between their price and overall value is quite reasonable. For now, let’s look at each criterion in more detail.

Effectiveness

Nootropic companies have a plethora of ingredients at their fingertips when they formulate their products. Some companies take a modern approach, focusing on the latest research into established Western medicines. Others look to the past, where ancient Chinese and Ayurvedic practices employed various botanicals to achieve cognitive effects. The best companies combine these approaches, using potentially beneficial ingredients that science supports.

Thesis takes this combined approach, employing just under three dozen ingredients from amino acids to ancient herbs across their six products. The company scores highly in effectiveness thanks to the ingredients they choose and the doses they offer for each, making it likely that you can notice their combined effects.

Individual results will vary due to everything from sleep patterns to diet, but most people should find benefits in at least one of Thesis' six formulas. Caffeinated formulas generally have more pronounced effects than stimulant-free versions, but the value of Thesis offering every formula with or without stimulants cannot be overstated.

One minor knock against Thesis is that, unlike some of their competitors, Thesis does not have a nootropic blend designed for improved sleep. Better sleep supports cognition and mood, so some companies offer formulas designed specifically for sleep promotion with ingredients like melatonin. That said, some of Thesis’ formulas contain lion’s mane or Zembrin (a branded form of Sceletium tortuosum that’s been shown to reduce anxiety and promote sleep). 2 3 And the amount of Zembrin used in Thesis’ Creativity and Confidence blends is the exact same amount used in these successful studies — 25mg.

Good nootropics are, unfortunately, a bit expensive. You can find less expensive options than Thesis, but their $79 monthly rate is right in the middle of what the market demands. You could also argue that the ingredient quality, customization options, and overall efficacy Thesis offers make it a superior value to many less expensive alternatives. Still, the price remains a sticking point for some.

Let's compare the monthly and per-dose costs with some of Thesis' closest competition. The prices below reflect subscription savings where available.

Three of the seven competitors included in the chart above are more expensive than Thesis, and another three are no more than $15 less expensive, revealing their generally average cost. Focus Factor — consistently our top budget pick among nootropics — costs much less than others in the field and includes many ingredients with associated clinical research. The downside is that increasing the number of ingredients (even when they seem to work) increases the odds of an adverse reaction.

TruBrain is the only company that truly compares to Thesis from a quality and variety standpoint. Other companies offer only one or two formulas, whereas Thesis and TruBrain each offer several more targeted products. TruBrain allows you to spend just $69 on your first jar when you subscribe — $10 less than Thesis — but that price shoots up to $119 every month after that, making Thesis the superior value.

When we consider the safety of any supplement, we look at available research into individual ingredients and compare those dosages with what the supplement offers. Whenever possible, we also test the product ourselves to observe its effects on us. Additionally, we look for safety standards in manufacturing that can provide added peace of mind, like third-party testing and compliance with the FDA’s Good Manufacturing Practices (GMP).

Thesis manufactures their products in GMP-compliant facilities and has third-party testing performed to assess the purity of each ingredient and formula. And the clinical research involving the lion's share of their ingredients reveals minimal risk profiles with few to no adverse effects reported. That said, ashwagandha isn’t safe for pregnant or breastfeeding individuals, and it can stimulate thyroid activity, so anyone with thyroid concerns (hyper- or hypothyroidism) or on medication to regulate thyroid function should be careful. 36 37

Thesis also limits their formulas to a handful of ingredients, which reduces the likelihood that any one of them would cause an adverse reaction. This is pretty typical of nootropics in Thesis’ class, but less expensive nootropics might try to convince you of their value by stuffing a single blend with several dozen components. That might increase the chances you feel some positive effect, but the side effect risk goes up by the same token.

Convenience

Our convenience rating considers various aspects of a user's experience. It usually starts with the quality of a product's website design and whether or not its pages are easy to navigate. We also consider the presence of subscription systems that make reordering easier and money-back guarantees that protect your investment. A company's customer service is another vital aspect of convenience, especially if you need questions answered. The quality of an FAQ section, the availability of representatives via chat or phone call, and the responsiveness to email inquiries all play a part here.

Our convenience rating is also informed by the steps required to actually take the product. Nootropics often consist of large capsules, and doses can contain anywhere from 1-7 capsules, which is awful for anyone with difficulty taking pills. Smaller capsules, fewer capsules per dose, and simple dosing schedules are ideal. Thesis’ capsule count varies per formula, ranging from 2-4 mid-size capsules you can take 30 minutes before you might want or need their effects.

To summarize some important aspects of nootropic company convenience, let's look at which companies have large capsule counts, good money-back guarantees, and subscription systems.

Thesis also provides a service that few other companies offer: free consultations with in-house nootropic coaches. These experts can help you figure out the best time to take specific Thesis formulas and guide your experience so you can tell whether or not they're working for you. Follow-up consultations are also free as long as you subscribe to the product.

What are nootropics?

Nootropic is a term most people use to refer to any non-prescription supplement that can boost brainpower. 4 The technical definition is a little more nuanced — encompassing prescription medications like Ritalin and Adderall — but the supplement industry has largely co-opted it to categorize the new class of non-prescription products. The word loosely translates from its Greek origins to mean mind-changing, and the majority of ingredients in a given nootropic seek to alter the brain’s cognitive abilities, as well as its governance of mood and energy.

Most nootropic supplements contain botanical ingredients, vitamins, minerals, and amino acids that boast at least some clinical research connecting them with improvements in any of the following:

Compared to their prescription cousins, nootropic supplements aren't particularly strong. Still, limited clinical research indicates a tangible benefit to taking them.

What is Thesis?

Thesis is a supplement company with a focus on nootropics. Their founders each had experiences growing up with what would today be considered learning disabilities, and they credit nootropics for changing their lives. They make six distinct nootropic formulas, each with a specific ingredient profile.

Thesis differentiates themselves from their competitors in several critical ways:

• They offer a starter kit containing a personalized combination of four blends.
• You have the option to remove caffeine by request from any formula.
• They provide some of the best phone support we've ever experienced.
• Their targeted formulas conform to changing needs.

By providing you with a mix of formulas, Thesis gives you the ability to enhance the aspects of your cognitive and emotional life that need it the most on any given day. Maybe you know you have low energy levels on Mondays and Wednesdays, so you can take the Energy formula on those days. Maybe you want to devote your weekends to artistic pursuits. You can use the Creativity blend for that. Or you might find that one of their six blends works well for you in any situation. In that case, you can adjust your order to receive only that formula.

Thesis' customer service — particularly over the phone — is outstanding. While many customers might find chat support more convenient, our testers rarely waited more than a minute to speak to someone, and Thesis employs phone operators who are extraordinarily knowledgeable about the product and nootropics in general. Their email support is fine, and their chat support often redirects to an email inquiry. But that phone support is some of the best our testing team has experienced.

Is Thesis safe?

Most of the ingredients that Thesis uses in their nootropics exhibit minimal side effects in clinical research, so there’s a good chance that Thesis' various formulas will be safe for most people. But Thesis has nearly three dozen ingredients in their catalog, and not all of them will be safe for all users, including those who are pregnant or breastfeeding. Of course, the most important thing you can do is talk to your doctor before taking Thesis.

The most common side effects to watch out for when you start taking Thesis nootropics include:

• Loss of appetite
• Digestive issues

Thesis advises discontinuing their nootropics if you experience persistent headaches or an upset stomach.

Some Thesis products may present contraindications with certain prescription medicines. For example, ashwagandha has been shown to normalize thyroid hormone levels in people with hypothyroidism. 5 This has led some to believe that it could conversely cause thyrotoxicity in people with hyperthyroidism, though it’s worth noting that the study in question employed double the highest ashwagandha dose you’ll find in Thesis nootropics — the study used 600mg, and the ashwagandha dose in Thesis’ Creativity is 300mg.

Still, this should make abundantly clear the case for speaking with your doctor prior to taking Thesis. This is especially true considering the lack of research into the specific ingredient combinations you’ll find in Thesis products. There is also very little research looking into the risks of combining nootropic supplements with prescription stimulants such as Ritalin, Adderall, or Vyvanse.

Some side effects, such as jitteriness, can be attributed to the caffeine in Thesis formulas. The fact that you can elect to remove caffeine from any formula expands the company’s reach to anyone with caffeine sensitivities and those who really don’t want to give up their morning cup of coffee. If you want caffeine in your Thesis formula, we recommend trying it without having had any coffee first, so you can see how it affects you.

Insider Tip: If you’re not sure whether to get your formula with or without caffeine, we recommend getting it with caffeine. Thesis isolates the included caffeine in a single capsule separate from other ingredients. Caffeinated formulas cost the same as uncaffeinated ones, and you can always elect not to take the caffeine capsule (the smallest capsule in any formula, containing a white powder).

What are the ingredients in Thesis?

Thesis uses an impressive set of ingredients, many of which have been part of respectable clinical research. Not all of the effects they hope these ingredients provide have been proven with sufficient statistical significance or over multiple studies in different populations, but what we do know strongly suggests efficacy.

Here's a look at several Thesis ingredients that have encouraging research behind them:

Several studies on mice show that dihydrohonokiol-B (DHH-B) has potent anxiolytic effects. 6 That means it may be able to help combat anxiety. However, we can’t say this for sure since there haven’t been any studies conducted on humans yet, so any potential benefits are speculative at this time. 25 Converting the successful dose used in mice (1mg) to the equivalent human amount (4.86 mg) is about half the amount used in Thesis’ Confidence (10mg). 6

In numerous studies, ashwagandha has been shown to reduce stress and anxiety. 32 Thesis uses a branded KSM-66 ashwagandha, which has a high standardized count of withanolides — the component of ashwagandha responsible for its positive effects. 33 This ensures both efficacy and consistency from doses that align with those used in successful studies.

While every formula is different, you'll notice that each contains caffeine and L-theanine. The nootropic properties of caffeine are well established. 19 L-theanine — a non-stimulant derived from green tea — has been shown to smooth out the jittery effects of caffeine. You can easily have caffeine removed from any Thesis formula for no extra cost, which is unique in the nootropic market. The L-theanine will remain, as it has its own set of cognitive benefits in addition to its ability to tame caffeine. 20

Saffron offers multiple benefits, including increased levels of dopamine and glutamate, that are dose-dependent. Human studies have also shown positive effects on depression symptoms. Thesis’ Confidence uses 28mg, which is 2mg less than what was used in many of the studies on saffron’s antidepressant effects. However, one study did find success with as little as 15mg. 7

A review of more than 120 scientific articles looking into the cognitive effects of phosphatidylserine concluded that it “safely slows, halts, or reverses biochemical alterations and structural deterioration in nerve cells.” The study goes on to say that it “supports human cognitive functions, including the formation of short-term memory, the consolidation of long-term memory, the ability to create new memories, the ability to retrieve memories, the ability to learn and recall information, the ability to focus attention and concentrate, the ability to reason and solve problems, language skills, and the ability to communicate.” 34

Derived from a South African plant, Zembrin appears to provide cognitive and anti-anxiety effects as demonstrated in clinical studies on human participants that used the same 25mg dose found in Thesis Creativity and Confidence. 8

Synapsa is a patented form of Bacopa extract, a traditional Ayurvedic memory enhancer. Studies on humans resulted in statistically significant improvements in cognitive tests. The study used 150mg twice daily (300mg total), which is only 20mg less than the 320mg used in Thesis’ Logic. 9

7,8 DHF is a small molecular TrkB agonist that can easily cross the blood-brain barrier. It can increase brain-derived neurotrophic factor (BDNF), a protein that improves neuroplasticity, learning, and memory. BDNF deficiencies are connected to numerous cognitive ailments as well. However, no human studies have been conducted. 26 In mice, 7,8 DHF appears to enhance spatial memory. When converting the effective dose for mice to humans, Thesis’ Clarity offers roughly 6mg more (about 24mg compared to Thesis’ 30mg). 27

Choline is a precursor to acetylcholine, a powerful neurotransmitter in the peripheral, autonomic, and enteric nervous systems. 10 One study on older adult human participants found that taking 187-399mg per day of choline reduced the risk of low cognitive functioning by nearly 50% compared to an intake under 187mg per day. 28 The CDP choline content in Thesis’ Energy is 300mg.

A 2010 clinical study on 485 older adult (over 55 years old) subjects found that 900mg per day of DHA improved memory and learning in those with age-related cognitive decline. 11 And another study in healthy adults 18-90 years old found that 580mg per day helped improve memory. 29 Unfortunately, the amounts used in many studies to improve cognitive function are quite a bit more than the 200mg (which is DHA and L-lysine combined) found in Thesis’ Logic.

Like choline, Alpha-GPC acts as an effective acetylcholine precursor. Studies also show that supplementation with Alpha-GPC can stave off exercise-induced reductions in choline levels. The effective amount used in the mentioned study is 200mg, which is less than half of what you’ll find in Thesis’ Clarity (500mg). 12

In addition to being an effective treatment for neuropathic pain, agmatine appears to have potent effects as an antidepressant. A five-year safety case report study concluded that there are no long-term side effect risks. Thesis’ Creativity only contains 250mg, which is well below the amount tolerated by study participants (2.67g per day). 13

Research into epicatechin indicates that it can enhance cerebral blood flow, delivering more oxygen to the brain to ensure it operates at its highest efficiency. The most effective dose for cognitive benefits appears to be over 50mg per day, and Thesis’ Clarity contains 278mg. 14

Lion's mane has been shown to increase nerve growth factor and promote neurite outgrowth of specific neural cells. It's a safe and reliable neurotrophic, but studies have debunked claims of neuroprotective properties. 15 A very small study of only 41 participants found that 1.8g of Lion’s mane may reduce stress and improve cognitive performance. 30 Thesis’ Clarity contains 500mg of Lion’s mane.

Hyperphenylalaninemia, a severe deficiency in phenylalanine, results in reduced dopamine, serotonin, and noradrenaline levels in the brain. 16 It can also alter cerebral myelin and protein synthesis. Supplementing with phenylalanine may provide neuroprotective benefits.

In a 2020 study, phenylalanine was a large component in a mix of seven amino acids that appeared to improve cognitive, psychological, and social functioning in middle-aged and older adults. Effective doses ranged from 0.85g to 1.7g of phenylalanine. A serving of Thesis’ Motivation contains 500mg, a bit under half of the average amount. 31

Examining the six formulas

Thesis has six nootropic formulas in their lineup (even though you can only choose up to four of them per box). Several other nootropic companies like TruBrain and BrainMD boast targeted lineups, as well, but Thesis is the Goldilocks of the bunch. Where BrainMD’s hyper-specific formulas rely on perhaps too few ingredients to make them worthwhile, many of TruBrain’s complex blends lack real specificity. With Thesis, you get targeted effects from numerous ingredients in moderately complex and reasonably priced combinations.

Each Thesis formula has a blend of ingredients that addresses specific needs. Their names give you a pretty big clue as to what the company intends each to do, but a closer look at their ingredients will help you understand how they achieve this.

Their formulas are:

Interestingly, the company thinks of its formulas as working well in pairs. You don't have to utilize them as such, but it's helpful to know how they view their most effective combinations. The following list details their purported combined benefits.

Enhances focus, eliminates brain fog, and lets thoughts flow naturally

Gets you going, keeps you going, and never crashes

Sparks new ideas, inspires extroversion, and revels in openness

You'll usually only take one formula at a time, but these pairs may act synergistically for specific personality types or cognitive needs.

Note that your first shipment of Thesis will contain six individually packed doses for four of these six formulas. Thesis chooses these formulas for you based on the results of an intake questionnaire, but you can make adjustments to that shipment on the customer dashboard before the shipment leaves their warehouse.

Let's take a closer look at each formula as they would appear with caffeine included.

Thesis Clarity

Thesis Clarity relies on 7,8 DHF (dihydroxyflavone), Alpha GPC (glycerylphosphorylcholine), epicatechin, and lion's mane to increase blood flow to the brain and stimulate the production of acetylcholine, a powerful neurotransmitter associated with learning, memory, and attention. It's particularly adept at cutting through brain fog.

Here's a look at Clarity's full ingredients list:

• Alpha GPC: 500mg
• Lion's Mane Mushroom: 500mg
• Camellia sinensis tea leaf: 278mg
• Dihydroxyflavone: 30mg
• Caffeine: 100mg
• L-Theanine: 200mg

One dose of Clarity consists of four capsules for the caffeinated formula and three capsules for the stimulant-free formula.

Thesis Logic

Thesis Logic contains triacetyluridine (TAU), which caters to the health of the entire central nervous system. It also uses phosphatidylserine to help facilitate communication between and protection of brain cells. 17

This is Logic’s complete ingredients list:

• Ginkgo Biloba: 160mg
• Theobromine: 100mg
• Phosphatidylserine: 400mg
• High DHA Algae: 200mg
• Triacetyluridine: 30mg
• Bacopa Monnieri: 320mg

One dose of Logic consists of four capsules for the caffeinated formula and three capsules for the stimulant-free formula.

Thesis Energy

Thesis Energy uses cysteine and tyrosine alongside caffeine to deliver a steady energy supply. It also includes TeaCrine, a branded form of theacrine, which partners with caffeine to affect adenosine signaling and prevent fatigue.

Here’s a full list of Energy’s ingredients:

• Citicoline: 300mg
• Mango leaf: 300mg
• Theacrine: 100mg
• N-Acetyl cysteine: 500mg
• Indian trumpet tree: 100mg
• N-Acetyl L-tyrosine: 300mg

One dose of Energy consists of three capsules for the caffeinated formula and two capsules for the stimulant-free formula.

Thesis Motivation

Blood flow and cellular function are at the core of Thesis Motivation . It employs artichoke extract, forskolin, and B12 to achieve these goals, with a healthy dose of phenylalanine for added focus and motivation.

Here's Motivation's full ingredients list:

• L-Phenylalanine: 500mg
• Methylliberine: 100mg
• Vitamin B12: 1000mcg
• Forskolin: 250mg
• Artichoke: 450mg

One dose of Motivation consists of three capsules for the caffeinated formula and two capsules for the stimulant-free formula.

Thesis Creativity

Thesis Creativity aims to realign you with your inspiration by removing barriers caused by stress, anxiety, and depression. It contains ingredients with powerful anxiolytic properties and 5-HT reuptake inhibition.

Here's a look at Creativity’s ingredients list:

• Alpha GPC: 150mg
• Agmatine sulfate: 250mg
• Panax ginseng: 200mg
• Ashwagandha root: 300mg
• Sceletium tortuosum : 25mg

One dose of Creativity consists of three capsules for the caffeinated formula and two capsules for the stimulant-free formula.

Thesis Confidence

Confidence is designed to work hand-in-hand with Creativity, using saffron and DHH-B from magnolia bark to increase dopamine levels and decrease anxiety. One fascinating ingredient in this formula is sage extract, which one 2021 study showed can help with various memory tasks, including name and face recognition. 18 It’s worth noting, though, that this study employed a 600mg dose compared to Thesis’ 333mg dose.

Here is Confidence's complete ingredients list:

• Saffron: 28mg
• Magnesium bisglycinate: 500mg
• Sage: 333mg
• Magnolia Bark: 10mg
• Ashwagandha leaf & root: 120mg

One dose of Confidence consists of three capsules for the caffeinated formula and two capsules for the stimulant-free formula.

Our Thesis testing results

Our testing team has tried every Thesis formula (with and without caffeine) to determine their short- and long-term efficacy, at least at an anecdotal level. Here’s a quick summary of our experiences:

Clarity provided our testers with a combined sense of focus and mental ease, though we mostly found that it worked best from its second day forward. The very first dose is mildly effective, but it served us better as a loading dose. We had no crash from either caffeinated or uncaffeinated formulas.

Our testers found that Logic provided a similar experience as Clarity, increasing focus and mental acuity, but the caffeinated formula caused a crash in two of our testers. By excluding the caffeine, that crash can be avoided, though that comes at the expense of some efficacy.

We were very curious about how this formula would perform without the caffeine. Our testers had a noticeable increase in energy without jitteriness about one hour after taking Energy. The caffeinated version caused the worst crash of all the formulas, but we were pleased to find that the formula without caffeine still provided noticeable energy increases without a crash.

Our testers are generally a pretty motivated bunch, so we might not have been the best group to evaluate this particular formula. The testers who felt an uptick in a sense of motivation described it more like a feeling of being able to follow through on tasks with less distraction and completion anxiety.

Creativity, like Clarity, seemed to work better for our testers on its second and third days than on its first. Testers generally described a sensation similar to Motivation but without the feeling of being “on rails,” as one tester put it. It seems to allow for more curiosity and exploration, though not necessarily as much follow-through.

This is Thesis’ newest formula, so fewer of our testers have tried it. Among those who have, one tester with a mild case of social anxiety described feeling a bit more relaxed among groups of people. Testers preferred this formula without caffeine.

Thesis pricing, shipping, and returns

Thesis keeps their price structure decidedly simple. This is refreshing, considering the range of nootropics they offer. You don't have to worry about one formula costing you more than another. However, Thesis doesn't make a non-subscription approach economically feasible.

Every Thesis shipment — including the starter pack — consists of four small boxes, each containing six doses of a single formula. That’s 24 doses/month.

Here's how it works:

• Any one-time purchase of a one-month supply, including the starter kit, costs $119.
• When you subscribe, that monthly cost is only $79.
• You can take an extra 10% off your first order with the coupon code INNERBODY

Subscriptions require an account with Thesis, which gives you access to a well-designed customer dashboard. This is where you can easily make formula adjustments, alter your shipping schedule, or cancel your subscription entirely.

Shipping from Thesis is free in the U.S., and the company offers a 30-day money-back guarantee. In our testing experience, we attempted a return on a second shipment into the subscription. While it isn’t the company’s policy to do so, they refunded our money and let us keep the product. This is similar to some other “Keep it” guarantees we’ve seen from competitors, and we appreciated it.

Getting started with Thesis Nootropics

Thesis' website is easy to navigate, but it is inconvenient that you must complete the signup questionnaire before accessing formula-specific pages. There are ways around this — like direct searching or just knowing the formula URLs — but we think reviewing formulas should be a little easier when you first get to the site. And you won’t be able to place an order for anything until you complete the questionnaire.

The user interface for managing your subscription is exceptionally intuitive. You can quickly adjust your formula combinations, specifying whether or not you want specific formulas to contain caffeine.

Setting up a subscription with Thesis is a straightforward process. Here are the basic steps:

• Take the Thesis quiz . This will create a starter kit specific to your results. (You can also build a box from scratch if you know which formulas you want to try.)
• Order your starter kit. We recommend going with the kit Thesis creates after your quiz, but if you change your mind, you can use the customer portal after placing your order to make any changes to the formula combination before it ships.
• Set up a coaching consultation. This is an optional step, but we recommend it and encourage you to have your first consultation before your kit arrives.
• Take your nootropics as needed. Most people can experience some of Thesis nootropics' benefits within a few hours of ingestion. Some ingredients and formulas may take a few days to produce results.
• Refine your order. As you near the end of your first month, you can head over to the Thesis website and customize your next order to include the formula or formulas you like most.
• Set up follow-up consultations as needed. These will help you refine your future orders and maximize your results.

When you subscribe to the starter kit, you will continue receiving that kit every month until you customize your order. Thesis divides their boxes into four six-dose supplies, and you can mix and match those supplies to suit your needs. For example, you could boost energy on the weekdays and creativity on the weekends by getting a one-month supply with 18 servings of Energy in three packages and six servings of Creativity in a single package.

Personalized insights and coaching

When you take the quiz on the Thesis website, you'll get personalized insights comparing your results to other quiz-takers and a data set developed from nearly 500 scientific studies. The parameters in your results cover don’t completely line up with their formulas, but they include:

These results inform the system to make recommendations for your starter kit. After you order, you can set up a consultation with a Thesis coach. These consultations are free, and you can have as many follow-up sessions as you like. Other companies have apps or online resources like blogs or courses to help you on your nootropic journey, but Thesis’ personalized coaching offers a unique approach and execution.

Consultation calls last around 15 minutes, though some of our testers had their sessions go longer as their coaches' schedules allowed. We received best practices information about taking nootropics that covered dose timing, formula application, and more. Some of our testers also received diet and exercise advice that coincided with their formulas.

Alternatives to Thesis

There are generally two tiers of products in the nootropics landscape. The lower tier consists of products that cost between $20 and $40. Many of these nootropics contain proprietary blends that obscure the exact quantities of ingredients, presumably so companies can use more of the least expensive components. Some companies in this tier disclose their ingredient quantities but may not source them from the highest quality suppliers or perform third-party testing of any kind.

Top brands in this tier include:

• Onnit Alpha BRAIN
• Moon Juice Brain Dust
• Focus Factor

The second tier — where you'll find Thesis — consists of more expensive nootropics that spell their contents out clearly, use high-quality ingredients, and often perform third-party testing to ensure safety and potency. Top brands in this tier include:

• Qualia Mind

Hunter Focus

We have a comprehensive breakdown of our top nootropics , but here's a concise breakdown of Thesis' most comparable competition.

TruBrain offers one of the widest varieties of nootropics of any company — one of the few catalogs that rivals the variety Thesis offers. They also have some novel and beneficial delivery methods for their nootropic ingredients. Those include energy bars and liquid shots that are outstanding for anyone with difficulty swallowing pills.

TruBrain offers their nootropics in a targeted fashion, not unlike what you get from Thesis. They formerly offered their targeted blends in shot form only, but now you can get any of these targeted blends in capsule or liquid shot form. The shots come in small 1oz pouches that make them easy to take anywhere.

TruBrain's targeted blends include:

This is TruBrain's original blend. It contains seven nootropics, including Noopept, a branded form of N-phenylacetyl-L-prolylglycine ethyl ester. This blend is caffeine-free.

The Strong blend is identical to the Medium formulation in contents and doses, but it also contains 100mg of caffeine.

The Extra Strong formula builds on the Strong blend by adding 150mg of adrafinil (2-(diphenylmethyl)sulfinyl-N-hydroxyacetamide). 21 This wakefulness-promoting substance may also help with weight loss and athletic performance.

TruBrain's Sleep formula contains just four nootropic ingredients: GABA, melatonin, 5-HTP, and a blend that TruBrain calls "functional oils."

Mellow is identical to the medium strength formula, but it adds the functional oil combination used in Sleep.

This formula contains Lion's mane, a mushroom that may promote neural growth , though human studies are necessary to determine if this is true. 22 Its other nootropic ingredients are rhodiola, guayusa, and rosehips.

A 30-day supply of TruBrain nootropic shots costs $89. That's $10 more than the subscription cost for a one-month supply of Thesis. Some of their shots contain caffeine, and others don't. If it already contains caffeine, there's no way to alter a TruBrain formula to be stimulant-free.

The first month of TruBrain capsules costs a bit less, coming in at $69. After your first month, however, the price goes up to $119. That makes Thesis the better value, but if you want the best possible nootropics for sleep support, it might be worth the extra money to check out TruBrain.

Qualia Mind is a brand under the Neurohacker Collective, a company that offers several products to address things like sleep quality, skin health, and vision. They have three nootropics available:

• Qualia Mind Caffeine-Free
• Qualia Mind Focus

Their original blend is comprehensive, consisting of nearly 30 ingredients in high doses. That means it's liable to provide you with noticeable effects. It also means you might not know which of those effects are coming from which ingredients, and some of the less beneficial components in your body may also have side effects you'd rather avoid.

The caffeine-free version is identical to the original formula but leaves the caffeine out. Qualia Focus is a more streamlined offering with only seven nootropic ingredients, including caffeine, L-theanine, and L-ornithine. 23

Initial shipments from Qualia Mind are significantly discounted, but after the first month, the price makes theirs one of the most expensive nootropics we've tested. For example, the first month of a subscription to Qualia Mind costs just $39. After that, it costs $139/month. And a one-time purchase is $159.

One inconvenient aspect of Qualia Mind is that a single dose consists of seven capsules, which can get tiresome even for people who don't have trouble swallowing pills. On the bright side, Qualia's 100-day money-back guarantee allows you to try it for a little over three months to determine if you can handle that kind of daily dosing.

Hunter Focus is one of three supplements in the Hunter stack alongside the company's Test and Burn supplements. The stack is intended for male use — Test is a testosterone supplement — but Focus and Burn are suitable for men and women.

Like Qualia Mind, Focus has a long list of ingredients in generous doses. In fact, one serving of Hunter Focus is like taking all six of Thesis' formulas at once. That said, the serving itself is difficult to swallow, as it consists of six large pills.

Another knock on Hunter is that they don't offer a subscription system. That means you can't get an extra discount, and you must remember to reorder when you're running low (theoretically, a nootropic like this should boost your memory). There's also no money-back guarantee to speak of, only a return policy with a relatively short window that only applies to unopened products.

One bottle of Hunter Focus costs $90, and shipping is $8.95 unless you buy more than one bottle at a time. The company will throw a fourth in for free if you buy three bottles at once. That's the only way to get any savings through Hunter.

Individual nootropic components

Many companies offer combinations of nootropic ingredients to perform specific brain-related tasks or even provide globally positive cognitive benefits. However, the scientific research behind most of these ingredients almost always includes just one rather than a combination. Some people prefer to try one at a time to minimize the potential for side effects and determine if one particular ingredient works for them. A few companies offer single-ingredient nootropic supplements for this specific purpose.

Our favorite company dealing in individual nootropic components is Nootropics Depot. They offer a wide variety of single-ingredient supplements and a few targeted blends. The prices are generally fair, with an average range running from $16-$70. A 30-day money-back guarantee covers every purchase, and you get free shipping on orders over $50.

Nootropics FAQ

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Specific nootropics affect different parts of the brain in their own ways. Some — like caffeine — reduce fatigue by blocking adenosine receptors, while others act to protect neural connections that are already present while possibly contributing to new neural growth. 24 Some also mitigate depression and anxiety, which frees up the brain to perform at its best.

Are nootropics safe?

The safety of a nootropic depends on the specific ingredients involved. Many are perfectly safe in the doses commonly employed by nootropic companies, but some can cause reactions like increased heart rate, gastrointestinal discomfort, headache, and even tremors. The smartest thing to do is to talk to your doctor before introducing any new supplement to your regimen.

Do nootropics really work?

Many nootropic supplements are noticeably effective — caffeine is a great example. Efficacy varies depending on the specific component or combination. Fortunately, a lot of companies offer money-back guarantees, so you can try their products to see if they work for you without much financial risk.

Will nootropics make me smarter?

Nootropics won't necessarily make you smarter, but many can increase your alertness, improve short-term recall, and promote neural growth and protection. That creates a great environment for learning if you apply yourself while using nootropics, and many ingredients can help you with the motivation it takes to do so.

How do you pronounce nootropics?

The 'noo' in nootropics comes from the Greek nous , which philosophers use to mean mind or intelligence. The 'tropic' in nootropic comes from the Greek tropikos , which relates to turning or changing. So, nootropic roughly translates to mind-changing. You pronounce the 'noo' like 'new' and the 'tropic' with a long O sound, like 'toe pick.'

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Thesis Nootropic Review - Do Personalized Nootropics Work? I Found Out.

O dds are if you hadn’t heard about nootropics before the early 2010s, you’ve heard about them now. Nootropics burst onto the scene around that time, and they’ve been trending ever since. Why? Well, with bold claims of making you feel more focused, calmer, and even smarter , it’s no wonder that these unique supplements have been catching people’s attention. Especially after the toll of the pandemic on all of our mental wellbeing…

If you’re dealing with brain fog, fatigue, and poor productivity, nootropics probably sound enticing. But, finding natural, effective, no-nonsense nootropics in today’s crowded wellness market can seem like a steep order. 

That’s where Thesis comes in. Takethesis.com is an online brand that’s been a leader in personalized nootropics for years. With all-natural supplement blends that they claim are rooted in science, Thesis promises to bring a new meaning to the term “smart drugs”. 

But as someone who’s always reserved a healthy level of skepticism around the efficacy of supplements in general, I decided to try Thesis nootropics firsthand to see what the hype was all about. In this review, I’ll share my experience with Thesis, including my honest reaction after taking their formulas for greater focus, confidence, logic, and more.

Curious if Thesis can introduce you to the valuable world of nootropics, without the BS? Keep reading to learn what’s inside Thesis ‘ supplements and whether or not their nootropic blends had any effect on my brain.

What are nootropics?

Any natural or synthetic substance that can positively affect cognition, focus, memory, and other mental faculties, and sometimes your mood, is considered a nootropic.

Prescription stimulants like Adderall for ADHD are included as well. And while prescription drugs work for many, they typically exhibit a high instance of unwanted side effects. Natural remedies that boost mental performance, including organic supplements and dietary changes, are generally more sustainable over the long term. In fact, many ADHD patients first discover nootropics after seeking healthier alternatives to Adderall and other pharmaceuticals.

Read our full comparison of nootropics vs Adderall for more details on the key differences.

Source: Thesis

How long have nootropics been around?

The use of nootropics first became widespread in the 70s, when  Piracetam first became widely known as a treatment for motion sickness, then later was found to boost cognitive performance. This spurred more of an effort toward discovering and developing more nootropics . It’s since become a thriving market, especially after the global pandemic wreaked havoc on mental health and left many with persistent brain fog. Today, the internet is awash with countless brain-boosting products available to consumers without prescription, and most don’t have FDA approval or much clinical data to support their claims.

While we love having options, the wide range of (unproven) nootropic supplements available today makes it hard to know which could work for you. There are dozens of brands, each offering various different nootropic blends, all claiming to be the best in class. Should you really be expected to try them all?

Thesis is on a mission to solve this conundrum. The company emerged to not only offer great quality and transparency around their blends, but also to recognize patients’ need for personalized recommendations from experts.

Let’s dive in to see what nootropics Thesis offers, and how the support they offer differs from typical supplement companies.

What are Thesis nootropics?

Thesis (rebranded from FindMyFormula.com) is a longstanding nootropics company with an impressive customer base of over 500,000 users. Having been in the space for years, Thesis has developed a comprehensive data set of nootropics research that dwarfs those of their competitors. I found this data-driven pitch compelling, and thus decided that I’d give Thesis a shot as my first foray into the world of nootropics in general.

1. How Thesis works

To get started, complete Thesis’ online questionnaire . They only ask for basic info – you don’t have to share specific lab tests or detailed medical history. Next, the Thesis algorithm will process your answers to recommend one or more nootropic blends best suited to your needs, which will be shipped to your house within 1-3 business days. 

Thesis recommends you sample their nootropic blends for a month before selecting ones that you believe work the best for you. Of course, you don’t have to stick with just one – and many Thesis customers opt to continue taking two or more blends for varied nootropic benefits as desired. Customer’s purchase data then funnels back to bolster Thesis’s algorithm, further strengthening the reliability of its recommendation engine. Pretty cool, I must admit.

2. What makes Thesis unique

Thesis’ personalized nootropic recommendation algorithm, paired with the ability to try out four unique nootropic blends before selecting your go-to formula, is what defines the Thesis process. They spare you from the difficult, time-intensive testing of individual nootropics on your own, which could easily take months (and cost a serious amount of $). By first paring down your options to the supplements that are most likely to work for you, Thesis takes the legwork out of trying nootropics. 

Plus, when you become a Thesis customer, you’ll also get access to a nootropics expert. This coach is available for consultation at any time to help you optimize your nootropics routine so that you get the most out of these specialized supplements. This includes keeping track of your progress, as well as answering any and all questions you may have about the science supporting each ingredient.

What’s inside Thesis’s unique nootropic blends?

At this point, you’re probably wondering what nootropic blends Thesis has to offer, and what secret sauce ingredients lie within. Thesis currently has six different formulations, each designed to target specific needs:

After filling out Thesis’ online questionnaire, I was recommended all but their Creativity blend . Below, I’ll outline the key nootropic ingredients inside each, as well as review my own personal experience in experimenting with them for the first time.

Energy formula Ingedients

Thesis’ Energy formula is designed to boost energy, fight fatigue, and improve mental stamina. Its ingredients include:

• Choline, for learning and memory
• NAC, for detoxification
• NALT, to support nerve cell communication
• Sabroxy®, for a dopamine boost and heightened memory
• TeaCrine®, for improved motivation, energy, and cognitive function
• Zynamite®, for mental and physical energy
• Caffeine, for energy and alertness
• L-Theanine, for an improved stress response

Review of Thesis energy – did it work for me?

Keep in mind that the power of placebo is well documented, as is the tremendous bias in self-reporting of any kind. These two factors, in combination with the day-to-day choppiness of life in general, make it hard to objectively determine how well supplements of any kind work for a given individual, much less the general population at large. 

That said, putting those caveats aside for sec, I took Thesis’ energy blend for 6 days straight, and I definitely felt more ALERT. The results were noticeable and fairly instant – I felt more alive and energetic within the first hour of taking the four recommended pills , and the feeling generally continued late into the afternoon. 

Fearful that my morning cup of coffee might overshadow or confound the nootropic’s effects, my routine was to take Thesis’ energy formula first thing in the morning with just a glass of water. It could just be the pill’s healthy dose of caffeine (or again, perhaps just placebo?), but regardless, I no longer craved coffee. Thesis’ Energy nootropics jolted me to full attention and kept my energy high for hours. If you’re looking for a caffeine replacement, or perhaps just an extra boost after a night of poor sleep, I definitely recommend Thesis’ blend for higher energy. Here’s what they pills look like up close:

The one downside? I ended up trying Thesis Energy with coffee one morning and felt pretty jittery. Of course, caffeine (and nootropics!) affect everyone differently, so if you’re eager to give these a shot, try them with and without your normal dose of coffee or tea to see how you feel. For me, I only needed one, not both, but it’s worth testing to find out what works for you!

Clarity formula ingredients

Do you find yourself often feeling foggy or forgetful? If so, Thesis’s Clarity formula may be worth a try. Formulated for increased focus and attention span, the Clarity nootropics are designed to help you more easily enter a flow state. 

What ingredients are inside Thesis’ Clarity? Their unique formula contains:

• 7,8-DHF, for neural communication, neurogenesis, and neuroprotection
• Alpha GPC, for memory, neurogenesis, and neuroprotection
• Epicatechin, for improved mood, blood flow, and neuroprotection
• Lion’s Mane, for improved memory consolidation and neuroprotection
• L-Theanine, for a better response to stress

Review of Thesis clarity – my personal experience

In my next phase of experimentation with Thesis nootropics, I decided to sample the Clarity blend for 6 days straight. Note that these six days did not overlap with days I took other nootropics, as I wanted to document my reaction to their blends independently, rather than seeing how I felt taking all of them together at once.

Although the benefits of Thesis’ Clarity blend were admittedly less immediate and noticeable than those I experienced with their Energy blend, I can honestly report that on the days I took Clarity, I found it easy to maintain a state of mental flow for longer . I generally don’t struggle to enter flow and engage deeply with my work, and this remained true while taking Thesis Clarity. What was different for me, however, was the duration of my flow, and I did my best to document these benefits closely through journaling.

To try and make my process as scientific as possible, at lunch each day I recorded how long I was able to stay focused that AM, and then again at dinner, noting how long I had been able to focus in that afternoon. Upon comparing my notes from the week I took Clarity vs the week I didn’t take anything at all, some clear benefits emerged. Overall, I was able to stay in a state of flow for ~35% longer with Thesis Clarity , although I’d be careful not to assume similar results too broadly for a couple of key reasons.

For one, placebo could very much be to blame given that I wanted to be more focused, and thus that desire alone could be to blame for my positive results. There’s also a small sample bias. Having only taken Clarity for one week, my self-reported data is a long way from “scientific significance”. 

That said, nootropics and supplements are all about how you feel, and the end conclusion remains the same: I felt focused for longer when taking Thesis’ recommended blend for Clarity. If you find yourself being overly fidgety, forgetful, or disengaged at work, I recommend you give Thesis Clarity a shot.

Motivation formula ingredients

The Motivation formula is intended to boost willpower and productivity while reducing procrastination. This formula from Thesis includes the following nootropic ingredients:

• Artichoke extract, for stress management and circulation
• Dynamine®, for crash-free energy and a mood boost
• Forskolin, for improved cognitive function
• L-Phenylalanine, for mood, attention, and motivation
• B12, for energy and nerve wellness
• Theanine, for an improved stress response

Review of Thesis Motivation – does it actually work?

Although I consider myself highly motivated, we all have days when we feel kind of “meh”. Rather than sampling Thesis’ Motivation nootropic every day for six days in a row, as I had with other blends, I instead opted to only experiment with them on days I woke up feeling noticeably uninspired. Interestingly, but perhaps not so surprisingly, these mostly fell on Mondays, although I felt less inclined to face my responsibilities on other days as well.

So, on these days of lower motivation when I took Thesis’ recommended Motivation nootropics, how did they make me feel? Honestly, I’m not sure. When reviewing my journal entries, I don’t notice any strong signs that the Thesis’ Motivation nootropics helped me significantly. It’s possible they acted in more subtle or slower ways because, by the afternoon, my notes indicate that I always felt fully engaged and motivated with whatever I was doing. But I must admit, I felt no sudden rush of motivation or anything super perceptible about Thesis’ nootropics for Motivation.

This may be because I didn’t adequately measure my personal motivation level while journaling. It could also be that on cherry-picking days I felt less motivated and heavily on biased my experience. For instance, I wonder if my results would have been more pronounced if I took Motivation consistently every day? Ultimately, I should probably test Thesis’ Motivation blend more before drawing any hard conclusions. And again, it’s worth noting that everyone’s body is quite different. While I don’t struggle with day-to-day motivation, others clearly do, and thus might see more noticeable results than I did.

Creativity formula ingedients

Thesis’s Creativity formula is designed to spark inspiration, improve verbal fluency, and provide a boost of confidence. It contains:

• Agmatine, for stress management
• Alpha GPC, support for memory, neuroprotection, and neurogenesis
• Ginseng, for learning and memory
• Ashwagandha, to promote calm in stressful settings
• Zembrin®, for mood regulation and blood flow to the brain
• Caffeine, for energy

My review of thesis creativity

Unfortunately, Thesis didn’t recommend this formula to me, so I can’t comment on its efficacy. That said, it’s one of Thesis’ most popular formulations, and thus seems to work for thousands of happy customers. I’ll update this section when I have a chance to try it first-hand.

Confidence formula ingredients

Confidence is the newest nootropic blend from Thesis. It contains ingredients to target stress and insecurities while fostering a sense of self-assurance. The idea behind the Confidence blend is that it will help users to feel more sure of themselves and stay in the present.

The Confidence nootropic ingredients include:

• Magnesium L-threonate

Ashwagandha

Review of thesis confidence – does it work.

Even the most self-assured among us crave more confidence. That’s because it’s attractive and infectious. As Thesis’ newest nootropic blend, Confidence is recommended for “high-pressure situations” when you want to “expand your comfort zone”, so I decided to reserve mine for situations in which I was meeting new people, which often, for me, means anticipatory social anxiety.

Recording how I felt two hours before leaving to meet new folks (both for business and pleasure), and then comparing that to my notes from just one hour before each meeting, a clear pattern emerged. In all cases, I reported feeling more relaxed and ready for new encounters after taking Thesis nootropics .

Absent any supplements whatsoever, my typical levels of social anxiety generally increase steadily up until the moment I see people. Generally, I turn to meditation to try to remedy that in the short term. However, that didn’t appear to be the case the 6 times I sampled Thesis’ confidence formula, although it’s unclear why. Perhaps it’s a placebo effect. But in any event, I was encouraged to keep trying Thesis Confidence nootropics before performative moments of all kinds.

Do Thesis nootropics really work?

I didn’t expect any nootropics to have a significant perceptible impact on my mood or cognition, yet 3 of the 4 blends that I tried brought real benefits. In case you missed it, I chronicled my experience trying various nootropic blends from Thesis above. Overall, I have to say I was pretty impressed with their results. 

For me, Thesis’ Energy and Confidence blends worked the best. Clarity also helped me maintain flow for longer during the workday, but I didn’t notice any strong effects from their Motivation supplements. Of course, I don’t know for sure that the nootropics are directly responsible for the benefits I perceived after trialing each variety 6 times. It could have just been placebo effect or some other internal bias altering my perception of reality. But honestly, does it really matter? The effects were very positive, and for the most part, perceptible, too. That’s a win-win!

That said, everyone responds differently to nutrients, which explains why you should maintain a healthy dose of skepticism about how well nootropic blends might work for you. How can something as simple as an herb really make you feel happier, more focused, and more productive? You won’t know unless you try them for yourself and pay close attention to how you feel.

Since my initial exploration, several members of my team have tried Thesis nootropics as well. While we all agree that you likely won’t feel as stark of a mental difference from all natural nootropics as you would with synthetic prescription drugs, but we all experienced a noticeable, positive effect on mood, memory, energy, and focus. This corroborating evidence – albeit self-reported – reassured me that perhaps my experience wasn’t all placebo after all.

What’s it like to talk to a Thesis nootropic coach?

After trying Thesis supplements, I was eager to chat with their team of expert nootropic coaches to discuss my experience. Naturally, I wanted to know if what I felt was “normal”, as well as how to further optimize the benefits I felt by making adjustments. I know there are lots of telehealth platforms on the market and having a coach with the knowledge of something that I knew less about made me much more comfortable.

I was able to schedule a call within just a few days and chatted with someone named Cindy with a degree in neurobiology. She was able to explain how the various nootropics I had tried likely contributed to my experience and offered a few recommendations around what to try next given my individual results.

Ultimately, I not only enjoyed the conversation but felt like I had clear next steps. It was reassuring to know I could get advice again at any time in the future. This is an amazingly personal feature that makes Thesis stand out against other nootropic brands.

What active ingredients does Thesis include in their compounds?

Each ingredient included in Thesis’s formulations is backed by science, which you can find right on their website. There are ways to test for any deficiencies  that you might have, which can also help you decide which supplements would benefit you. Here’s an overview:

Synapsa® (Bacopa monnieri plant)

Bacopa has been shown to boost memory recall and be neuroprotective. 

TAU (uridine)

The body uses uridine to create choline (a cognitive enhancer), construct nerve cell membranes, and help prevent neuron damage. 

7,8-DHF (dihydroxyflavone)

Studies indicate that 7,8-DHF can help protect against brain damage and neurological decline. 

Choline supports nerve health, cerebral metabolism, and the function of neurotransmitters. It also has been shown to have neuroprotective benefits, preserving the health of your brain. 

When it’s taken regularly, DHA has been shown to boost memory and reaction time. 

Ashwagandha root helps regulate the body’s response to cortisol, the “ stress hormone”. 

The active components of GS15-4 Panax Ginseng have been found to boost memory formation and learning. 

NALT (N-Acetyl-L-Tyrosine)

NALT can increase alertness, energy, and cognitive function . 

Artichoke extract

Artichoke extract is rich in antioxidants that can boost your overall bodily function and offer protection against stress and toxins. 

NAC boosts levels of glutathione, which can reduce oxidative stress and help naturally detoxify the body. 

Methylcobalamin, a form of vitamin B12, is used in Thesis supplements to improve nerve health and energy levels. 

Lion’s Mane mushrooms

Lion’s Mane mushrooms can enhance your mood and quality of sleep while reducing stress levels.

There are a total of 28 ingredients found in Thesis nootropic blends . Others not listed above include alpha GPC, Zembrin®, phosphatidylserine, forskolin, Sabroxy®, TeaCrine®, agmatine, epicatechin, alpha GPC, Dynamine®, L-theanine, Zynamite®, L-Phenylalanine, theobromine, ginkgo Biloba, and caffeine. 

How much do Thesis nootropics cost?

For a one-time purchase, Thesis costs $119 for a one-month supply . This isn’t the most economical way to try their nootropics, though. Instead, we’d recommend signing up for a subscription , which costs $79 for a one-month supply, and will force you to properly test Thesis over a longer period for more credible results.

Thesis offers a 30-day money-back guarantee, which eliminates the risk of trying them out. If you’re not sold after a month, you can simply get your investment back – no questions asked. 

Thesis alternatives: How does Thesis compare to other nootropic brands?

Of course, Thesis is far from the only nootropic company in town. How does it stack up vs alternatives? Take a look for yourself:

Thesis Nootropic reviews: What are customers saying?

Before diving into nootropics with Thesis, we knew that you’d want to read what other customers are praising or complaining about in their reviews. Here’s what we found online:

Source: Facebook

Source: Reddit

The verdict: Are Thesis nootropics legit?

Armed with all of the information, including my own personal journey trying their nootropics for the first time, and a comparison of Thesis vs other popular alternatives… should you give Thesis a shot?

While Thesis is pricier than its competitors, we believe that their personalized approach is ultimately worth it for the value. For one, Thesis offers you access to an expert nootropics coach, who can seriously enhance your experience with the supplements and guide you on your journey to optimal mental performance.

Additionally, Thesis has done the heavy lifting of finding legitimate ingredients that are backed by reputable science and are more transparent with their ingredients and dosage than other brands. If we’re comparing to taking it upon yourself to test out individual nootropics on your own, Thesis will save you a ton of time.

Plus, the company’s unique blends pair ingredients that complement each other, and you won’t find these formulations anywhere else. They are custom formulas based on your individual needs, and you can try them for 30 days risk-free thanks to their money-back guarantee.

When push comes to shove, we’d recommend Thesis to anyone who’s interested in testing nootropics for the first time and doesn’t know where to start, as well as more experienced wellness enthusiasts looking to make nootropics a regular part of their self-care routine. For greater focus, energy, motivation, and a major mood boost, nootropics from Thesis worked for me, and with thousands of happy customers, it’s reasonable to assume their blends can work wonders for anyone willing to experiment under the guidance of one of their coaches. Of course, you’ll never know unless you try it out for yourself. Just don’t forget to use our promo code FINVSFIN for 10% off at checkout.

Remember to always consult with your doctor before starting a new supplement to ensure it’s right for you.

Have you tried out nootropics? Let us know about your experience and result in the comments below!

Frequently Asked Questions (FAQ)

For a one-time purchase, Thesis costs $119 for a  one-month supply . This isn’t the most economical way to try their nootropics, though. Instead, we’d recommend signing up for a  subscription , which costs $79 for a one-month supply, and will force you to properly test Thesis over a longer period for more credible results.

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Utilizing Creative Arts for HIV Treatment and Prevention Among Black Queer Youth: A Scoping Review Open Access

Henry, cody shymar (spring 2024).

The purpose of the following thesis project is to describe current practices of integrating creative art-based interventions as a tool to address HIV treatment and prevention among Black Queer Young People (BQYP) around the globe. Despite advancements in prevention and treatment of HIV, BQYP around the world continue to experience disappointingly high rates of HIV diagnosis and risk of contracting HIV throughout their lifetimes. Utilizing scoping review methodology this review yielded six types of creative art practices implemented across the globe that specifically address HIV treatment and prevention among various social and demographic populations including communities living with and without HIV. The scoping review identified a broad range of art forms that were categorized into groups including theater, poetry, photography, performance, sculpture and visual arts, and music and radio. Theater and theater camp programs can specifically work to promote community dialogue and to reduce HIV and anti-LGBTQ+ stigma. Poetry can promote education and shared learning related to HIV awareness. Photography and specifically the practice of photovoice can help to address both internal and structural related stigma. Participating in performance including Ballroom culture can improve self-expression and promote community dialogue related to HIV health messaging at the community level. The use of sculpture and visual arts allowed for participants to engage in community dialogue regarding HIV and helped to reduce individual and group stigmas related to HIV among women in Uganda. Music and Radio seem to be an acceptable and feasible tool within the HIV prevention and care continuum. Ultimately these art forms can be a specific and targeted approach to addressing high rates of HIV, reducing stigma related to HIV and anti-LQBTQ+, and promoting Pre-Exposure Prophylaxis (PrEP) uptake and awareness among BQYP.

Table of Contents

Chapter 1. INTRODUCTION pg. 1

Chapter 2. LITERATURE REVIEW pg. 5

Youth Health and HIV pg. 5

Black Communities and HIV pg. 8

HIV Treatment & Prevention: A Global Perspective pg. 8

Creative arts-based interventions in Health and Healing pg. 12

Creative Art as Therapy pg. 13

Arts Education and Creative Youth Development pg. 14

Chapter 3. METHODS pg. 15

Identifying the research question pg. 16

Identifying relevant studies pg. 16 

Study selection pg. 17

Data Sources pg. 17

Charting the data pg. 17

Collecting summarizing and reporting results pg. 18

Chapter 4. RESULTS pg. 18

Scoping review search and initial screening pg. 18

Description of papers included pg. 19

Photovoice pg. 19

Theater pg. 23

Performance pg. 26

Poetry pg. 29

Music and radio pg. 31

Sculpture and visual art pg. 33

Chapter 4. DISCUSSION and RECOMMENDATIONS pg. 38

Limitations pg. 42

Recommendations pg. 43

Public Health Implications pg. 44

References pg.45

About this Master's Thesis

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What’s So Good About On Running? The Sneaker Brand You See Everywhere Just Dropped a New Shoe for Summer

The Cloudrunner 2 amps up the performance features for better traction, cushioning and impact absorption.

By Tim Chan

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It seems like you can’t go anywhere these days without seeing a pair of On Running sneakers on the feet of people around you. Whether you’re at the airport, at the gym or even at the office , the Swiss running brand’s chunky kicks have become as much a style statement as they are an “if you know, you know” shoe for athletes.

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Designed for both hardcore running and casual wear alike, the Cloudrunner 2 starts with an upgraded “Helion superfoam” midsole designed for “higher energy return.” What that means: there’s better spring for your feet as you take a step and better cushioning as you land. Like a mattress for your feet , the Swiss-engineered material is soft and supportive, helping to cradle your feet without letting them sink in. Extra CloudTec cushioning helps to further absorb impact, while the wider fit is nice and roomy.

In addition to the increased support, the mesh upper keeps your feet cool and comfortable, with a breathable layer that won’t trap sweat. A durable heel clip helps to lock in stability and support.

Of course, the defining aesthetic characteristic of On Running sneakers are the chunky outsoles, and the Cloudrunner 2 features the same design. The brand does say the outsole has been upgraded so it “won’t trap stones as you run.” We like the sustainable aspect of these sneakers too: about 30% of the shoe is made from recycled materials, including the mesh upper, which is made from 100% recycled polyester.

On Cloudrunner

With the release of the new Cloudrunner shoes, the original On Cloudrunner is discounted 30% off right now online . Choose from six colorways in sizes 7-14 for men, and five colorways in sizes 5-11 for women.

Looks-wise, both pairs of On Running Cloudrunner shoes have become grail-worthy sneakers for fashion fans of all ages, thanks to their slightly oversized silhouette (which has drawn comparisons to Hoka sneakers ) and easy-to-pair colors. The sneakers go with everything from athleisure wear to a casual office attire of polo shirt and slacks. Shop the latest On Running releases here .

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All Thing Are Too Small: Essays in Praise of Excess - It all gets a bit too much in the end

Becca rothfeld’s collection is energetic and charmingly verbose, but her tendency to demystify everything wears thin.

Becca Rothfeld: Moments of clear insight and great beauty

Towards the end of All Things Are Too Small, Becca’s Rothfeld’s defence of maximalism, she reproduces a quotation that she has “so thoroughly digested and metabolised” that it is now an essential fixture of her “mental repertoire”.

“I love a demystified thing inordinately.”

Yes, I thought, that’s it. That’s the problem with this book: Rothfeld’s tendency towards such relentless demystification of her subjects that they’re pallid and lifeless by the time she’s through.

This is not true of all the essays in the collection. It opens promisingly and with astounding energy and vigour. Initially, one forgives Rothfeld’s immediately evident habit of making grand, inaccurate statements, such as: “Desire is as good a guide to truth as anything else.” If anything, her verbosity and inexactitude seem charming – she’s wrong because she’s passionate. Reading, I felt myself at a dinner table surrounded by voices stridently debating all manner of interesting things: literature, meaning, mindfulness, feminism, sex, sex and more sex (to give an idea of the topics of these essays).

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My God, though, did I want that dinner to end, so I could return somewhere peaceful and reflective, to cease the ringing in my ears of all this terribly intelligent demystifying. The humour, too, wears thin. Yes, it’s hilarious to mock the bourgeois aesthetic of Marie Kondo (I laughed aloud at “the declutterer dreams of a house without f**king or sh**ting”), but by the end of the collection, these knowing asides and the unremitting sarcasm made me feel like I was trying to converse with a surly, unimpressed teenager.

Also, Rothfeld’s attempts at love-writing made me physically cringe. At one point, she tells us that her husband loves reading so much, he does so in the shower. The impossible logistics of this image will never, I fear, cease to irritate me.

Yet, there are moments of clear insight, and of great beauty. Rothfeld’s capacious vocabulary left me stunned, and exquisite phrases such as “the gleaming purity of a history” almost made up for her agonising attempts at poeticism.

“The night was cool as mint. Behind him, the light from the streetlamp became butter melting. His voice was flat and nasal, mouthy as saltwater toffee.”

Ultimately, this collection’s great weakness is that these pieces have been gathered into a collection at all. I can see that, taken one at a time, Rothfeld’s tone would be pithy and gratifying, and these qualities would make up for her prolix, excessive demystification and broad, questionable statements. Alas, reading her thoughts over and over, all in a row, I grew frustrated, tired and harried. By the end, I wanted to leave the dinner party, to run out into the street, to regain the relief of a little mystery.

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ORIGINAL RESEARCH article

The impact of online reviews on consumers’ purchasing decisions: evidence from an eye-tracking study.

• 1 School of Business, Ningbo University, Ningbo, China
• 2 School of Business, Western Sydney University, Penrith, NSW, Australia

This study investigated the impact of online product reviews on consumers purchasing decisions by using eye-tracking. The research methodology involved (i) development of a conceptual framework of online product review and purchasing intention through the moderation role of gender and visual attention in comments, and (ii) empirical investigation into the region of interest (ROI) analysis of consumers fixation during the purchase decision process and behavioral analysis. The results showed that consumers’ attention to negative comments was significantly greater than that to positive comments, especially for female consumers. Furthermore, the study identified a significant correlation between the visual browsing behavior of consumers and their purchase intention. It also found that consumers were not able to identify false comments. The current study provides a deep understanding of the underlying mechanism of how online reviews influence shopping behavior, reveals the effect of gender on this effect for the first time and explains it from the perspective of attentional bias, which is essential for the theory of online consumer behavior. Specifically, the different effects of consumers’ attention to negative comments seem to be moderated through gender with female consumers’ attention to negative comments being significantly greater than to positive ones. These findings suggest that practitioners need to pay particular attention to negative comments and resolve them promptly through the customization of product/service information, taking into consideration consumer characteristics, including gender.

Introduction

E-commerce has grown substantially over the past years and has become increasingly important in our daily life, especially under the influence of COVID-19 recently ( Hasanat et al., 2020 ). In terms of online shopping, consumers are increasingly inclined to obtain product information from reviews. Compared with the official product information provided by the sellers, reviews are provided by other consumers who have already purchased the product via online shopping websites ( Baek et al., 2012 ). Meanwhile, there is also an increasing trend for consumers to share their shopping experiences on the network platform ( Floh et al., 2013 ). In response to these trends, a large number of studies ( Floh et al., 2013 ; Lackermair et al., 2013 ; Kang et al., 2020 ; Chen and Ku, 2021 ) have investigated the effects of online reviews on purchasing intention. These studies have yielded strong evidence of the valence intensity of online reviews on purchasing intention. Lackermair et al. (2013) , for example, showed that reviews and ratings are an important source of information for consumers. Similarly, through investigating the effects of review source and product type, Bae and Lee (2011) concluded that a review from an online community is the most credible for consumers seeking information about an established product. Since reviews are comments from consumers’ perspectives and often describe their experience using the product, it is easier for other consumers to accept them, thus assisting their decision-making process ( Mudambi and Schuff, 2010 ).

A survey conducted by Zhong-Gang et al. (2015) reveals that nearly 60% of consumers browse online product reviews at least once a week and 93% of whom believe that these online reviews help them to improve the accuracy of purchase decisions, reduce the risk of loss and affect their shopping options. When it comes to e-consumers in commercial activities on B2B and B2C platforms, 82% of the consumers read product reviews before making shopping choices, and 60% of them refer to comments every week. Research shows that 93% of consumers say online reviews will affect shopping choices, indicating that most consumers have the habit of reading online reviews regularly and rely on the comments for their purchasing decisions ( Vimaladevi and Dhanabhakaym, 2012 ).

Consumer purchasing decision after reading online comments is a psychological process combining vision and information processing. As evident from the literature, much of the research has focused on the outcome and impact of online reviews affecting purchasing decisions but has shed less light on the underlying processes that influence customer perception ( Sen and Lerman, 2007 ; Zhang et al., 2010 ; Racherla and Friske, 2013 ). While some studies have attempted to investigate the underlying processes, including how people are influenced by information around the product/service using online reviews, there is limited research on the psychological process and information processing involved in purchasing decisions. The eye-tracking method has become popular in exploring and interpreting consumer decisions making behavior and cognitive processing ( Wang and Minor, 2008 ). However, there is very limited attention to how the emotional valence and the content of comments, especially those negative comments, influence consumers’ final decisions by adopting the eye-tracking method, including a gender comparison in consumption, and to whether consumers are suspicious of false comments.

Thus, the main purpose of this research is to investigate the impact of online reviews on consumers’ purchasing decisions, from the perspective of information processing by employing the eye-tracking method. A comprehensive literature review on key themes including online reviews, the impact of online reviews on purchasing decisions, and underlying processes including the level and credibility of product review information, and processing speed/effectiveness to drive customer perceptions on online reviews, was used to identify current research gaps and establish the rationale for this research. This study simulated a network shopping scenario and conducted an eye movement experiment to capture how product reviews affect consumers purchasing behavior by collecting eye movement indicators and their behavioral datum, in order to determine whether the value of the fixation dwell time and fixation count for negative comment areas is greater than that for positive comment area and to what extent the consumers are suspicious about false comments. Visual attention by both fixation dwell time and count is considered as part of moderating effect on the relationship between the valence of comment and purchase intention, and as the basis for accommodating underlying processes.

The paper is organized as follows. The next section presents literature reviews of relevant themes, including the role of online reviews and the application of eye movement experiments in online consumer decision research. Then, the hypotheses based on the relevant theories are presented. The research methodology including data collection methods is presented subsequently. This is followed by the presentation of data analysis, results, and discussion of key findings. Finally, the impact of academic practical research and the direction of future research are discussed, respectively.

Literature Review

Online product review.

Several studies have reported on the influence of online reviews, in particular on purchasing decisions in recent times ( Zhang et al., 2014 ; Zhong-Gang et al., 2015 ; Ruiz-Mafe et al., 2018 ; Von Helversen et al., 2018 ; Guo et al., 2020 ; Kang et al., 2020 ; Wu et al., 2021 ). These studies have reported on various aspects of online reviews on consumers’ behavior, including consideration of textual factors ( Ghose and Ipeirotiss, 2010 ), the effect of the level of detail in a product review, and the level of reviewer agreement with it on the credibility of a review, and consumers’ purchase intentions for search and experience products ( Jiménez and Mendoza, 2013 ). For example, by means of text mining, Ghose and Ipeirotiss (2010) concluded that the use of product reviews is influenced by textual features, such as subjectivity, informality, readability, and linguistic accuracy. Likewise, Boardman and Mccormick (2021) found that consumer attention and behavior differ across web pages throughout the shopping journey depending on its content, function, and consumer’s goal. Furthermore, Guo et al. (2020) showed that pleasant online customer reviews lead to a higher purchase likelihood compared to unpleasant ones. They also found that perceived credibility and perceived diagnosticity have a significant influence on purchase decisions, but only in the context of unpleasant online customer reviews. These studies suggest that online product reviews will influence consumer behavior but the overall effect will be influenced by many factors.

In addition, studies have considered broader online product information (OPI), comprising both online reviews and vendor-supplied product information (VSPI), and have reported on different attempts to understand the various ways in which OPI influences consumers. For example, Kang et al. (2020) showed that VSPI adoption affected online review adoption. Lately, Chen and Ku (2021) found a positive relationship between diversified online review websites as accelerators for online impulsive buying. Furthermore, some studies have reported on other aspects of online product reviews, including the impact of online reviews on product satisfaction ( Changchit and Klaus, 2020 ), relative effects of review credibility, and review relevance on overall online product review impact ( Mumuni et al., 2020 ), functions of reviewer’s gender, reputation and emotion on the credibility of negative online product reviews ( Craciun and Moore, 2019 ) and influence of vendor cues like the brand reputation on purchasing intention ( Kaur et al., 2017 ). Recently, an investigation into the impact of online review variance of new products on consumer adoption intentions showed that product newness and review variance interact to impinge on consumers’ adoption intentions ( Wu et al., 2021 ). In particular, indulgent consumers tend to prefer incrementally new products (INPs) with high variance reviews while restrained consumers are more likely to adopt new products (RNPs) with low variance.

Emotion Valence of Online Product Review and Purchase Intention

Although numerous studies have investigated factors that may influence the effects of online review on consumer behavior, few studies have focused on consumers’ perceptions, emotions, and cognition, such as perceived review helpfulness, ease of understanding, and perceived cognitive effort. This is because these studies are mainly based on traditional self-report-based methods, such as questionnaires, interviews, and so on, which are not well equipped to measure implicit emotion and cognitive factors objectively and accurately ( Plassmann et al., 2015 ). However, emotional factors are also recognized as important in purchase intention. For example, a study on the usefulness of online film reviews showed that positive emotional tendencies, longer sentences, the degree of a mix of the greater different emotional tendencies, and distinct expressions in critics had a significant positive effect on online comments ( Yuanyuan et al., 2009 ).

Yu et al. (2010) also demonstrated that the different emotional tendencies expressed in film reviews have a significant impact on the actual box office. This means that consumer reviews contain both positive and negative emotions. Generally, positive comments tend to prompt consumers to generate emotional trust, increase confidence and trust in the product and have a strong persuasive effect. On the contrary, negative comments can reduce the generation of emotional trust and hinder consumers’ buying intentions ( Archak et al., 2010 ). This can be explained by the rational behavior hypothesis, which holds that consumers will avoid risk in shopping as much as possible. Hence, when there is poor comment information presented, consumers tend to choose not to buy the product ( Mayzlin and Chevalier, 2003 ). Furthermore, consumers generally believe that negative information is more valuable than positive information when making a judgment ( Ahluwalia et al., 2000 ). For example, a single-star rating (criticism) tends to have a greater influence on consumers’ buying tendencies than that of a five-star rating (compliment), a phenomenon known as the negative deviation.

Since consumers can access and process information quickly through various means and consumers’ emotions influence product evaluation and purchasing intention, this research set out to investigate to what extent and how the emotional valence of online product review would influence their purchase intention. Therefore, the following hypothesis was proposed:

H1 : For hedonic products, consumer purchase intention after viewing positive emotion reviews is higher than that of negative emotion ones; On the other hand, for utilitarian products, it is believed that negative comments are more useful than positive ones and have a greater impact on consumers purchase intention by and large.

It is important to investigate Hypothesis one (H1) although it seems obvious. Many online merchants pay more attention to products with negative comments and make relevant improvements to them rather than those with positive comments. Goods with positive comments can promote online consumers’ purchase intention more than those with negative comments and will bring more profits to businesses.

Sen and Lerman (2007) found that compared with the utilitarian case, readers of negative hedonic product reviews are more likely to attribute the negative opinions expressed, to the reviewer’s internal (or non-product-related) reasons, and therefore, are less likely to find the negative reviews useful. However, in the utilitarian case, readers are more likely to attribute the reviewer’s negative opinions to external (or product-related) motivations, and therefore, find negative reviews more useful than positive reviews on average. Product type moderates the effect of review valence, Therefore, Hypothesis one is based on hedonic product types, such as fiction books.

Guo et al. (2020) found pleasant online customer reviews to lead to a higher purchase likelihood than unpleasant ones. This confirms hypothesis one from another side. The product selected in our experiment is a mobile phone, which is not only a utilitarian product but also a hedonic one. It can be used to make a phone call or watch videos, depending on the user’s demands.

Eye-Tracking, Online Product Review, and Purchase Intention

The eye-tracking method is commonly used in cognitive psychology research. Many researchers are calling for the use of neurobiological, neurocognitive, and physiological approaches to advance information system research ( Pavlou and Dimoka, 2010 ; Liu et al., 2011 ; Song et al., 2017 ). Several studies have been conducted to explore consumers’ online behavior by using eye-tracking. For example, using the eye-tracking method, Luan et al. (2016) found that when searching for products, customers’ attention to attribute-based evaluation is significantly longer than that of experience-based evaluation, while there is no significant difference for the experiential products. Moreover, their results indicated eye-tracking indexes, for example, fixation dwell time, could intuitively reflect consumers’ search behavior when they attend to the reviews. Also, Hong et al. (2017) confirmed that female consumers pay more attention to picture comments when they buy experience goods; when they buy searched products, they are more focused on the pure text comments. When the price and comment clues are consistent, consumers’ purchase rates significantly improve.

Eye-tracking method to explore and interpret consumers’ decision-making behavior and cognitive processing is primarily based on the eye-mind hypothesis proposed by Just and Carpenter (1992) . Just and Carpenter (1992) stated that when an individual is looking, he or she is currently perceiving, thinking about, or attending to something, and his or her cognitive processing can be identified by tracking eye movement. Several studies on consumers’ decision-making behavior have adopted the eye-tracking approach to quantify consumers’ visual attention, from various perspectives including determining how specific visual features of the shopping website influenced their attitudes and reflected their cognitive processes ( Renshaw et al., 2004 ), exploring gender differences in visual attention and shopping attitudes ( Hwang and Lee, 2018 ), investigating how employing human brands affects consumers decision quality ( Chae and Lee, 2013 ), consumer attention and different behavior depending on website content, functions and consumers goals ( Boardman and McCormick, 2019 ). Measuring the attention to the website and time spent on each purchasing task in different product categories shows that shoppers attend to more areas of the website for purposes of website exploration than for performing purchase tasks. The most complex and time-consuming task for shoppers is the assessment of purchase options ( Cortinas et al., 2019 ). Several studies have investigated fashion retail websites using the eye-tracking method and addressed various research questions, including how consumers interact with product presentation features and how consumers use smartphones for fashion shopping ( Tupikovskaja-Omovie and Tyler, 2021 ). Yet, these studies considered users without consideration of user categories, particularly gender. Since this research is to explore consumers’ decision-making behavior and the effects of gender on visual attention, the eye-tracking approach was employed as part of the overall approach of this research project. Based on existing studies, it could be that consumers may pay more attention to negative evaluations, will experience cognitive conflict when there are contradictory false comments presented, and will be unable to judge good or bad ( Cui et al., 2012 ). Therefore, the following hypothesis was proposed:

H2 : Consumers’ purchasing intention associated with online reviews is moderated/influenced by the level of visual attention.

To test the above hypothesis, the following two hypotheses were derived, taking into consideration positive and negative review comments from H1, and visual attention associated with fixation dwell time and fixation count.

H2a : When consumers intend to purchase a product, fixation dwell time and fixation count for negative comment areas are greater than those for positive comment areas.

Furthermore, when consumers browse fake comments, they are suspicious and actively seek out relevant information to identify the authenticity of the comments, which will result in more visual attention. Therefore, H2b was proposed:

H2b : Fixation dwell time and fixation count for fake comments are greater than those for authentic comments.

When considering the effect of gender on individual information processing, some differences were noted. For example, Meyers-Levy and Sternthal (1993) put forward the selectivity hypothesis, a theory of choice hypothesis, which implies that women gather all information possible, process it in an integrative manner, and make a comprehensive comparison before making a decision, while men tend to select only partial information to process and compare according to their existing knowledge—a heuristic and selective strategy. Furthermore, for an online product review, it was also reported that gender can easily lead consumers to different perceptions of the usefulness of online word-of-mouth. For example, Zhang et al. (2014) confirmed that a mixed comment has a mediating effect on the relationship between effective trust and purchasing decisions, which is stronger in women. This means that men and women may have different ways of processing information in the context of making purchasing decisions using online reviews. To test the above proposition, the following hypothesis was proposed:

H3 : Gender factors have a significant impact on the indicators of fixation dwell time and fixation count on the area of interest (AOI). Male purchasing practices differ from those of female consumers. Male consumers’ attention to positive comments is greater than that of female ones, they are more likely than female consumers to make purchase decisions easily.

Furthermore, according to the eye-mind hypothesis, eye movements can reflect people’s cognitive processes during their decision process ( Just and Carpenter, 1980 ). Moreover, neurocognitive studies have indicated that consumers’ cognitive processing can reflect the strategy of their purchase decision-making ( Rosa, 2015 ; Yang, 2015 ). Hence, the focus on the degree of attention to different polarities and the specific content of comments can lead consumers to make different purchasing decisions. Based on the key aspects outlined and discussed above, the following hypothesis was proposed:

H4 : Attention to consumers’ comments is positively correlated with consumers’ purchasing intentions: Consumers differ in the content of comments to which they gaze according to gender factors.

Thus, the framework of the current study is shown in Figure 1 .

Figure 1 . Conceptual framework of the study.

Materials and Methods

The research adopted an experimental approach using simulated lab environmental settings for collecting experimental data from a selected set of participants who have experience with online shopping. The setting of the task was based on guidelines for shopping provided on Taobao.com , which is the most famous and frequently used C2C platform in China. Each experiment was set with the guidelines provided and carried out for a set time. Both behavioral and eye movement data were collected during the experiment.

Participants

A total of 40 healthy participants (20 males and 20 females) with online shopping experiences were selected to participate in the experiment. The participants were screened to ensure normal or correct-to-normal vision, no color blindness or poor color perception, or other eye diseases. All participants provided their written consent before the experiment started. The study was approved by the Internal Review Board of the Academy of Neuroeconomics and Neuromanagement at Ningbo University and by the Declaration of Helsinki ( World Medical Association, 2014 ).

With standardization and small selection differences among individuals, search products can be objectively evaluated and easily compared, to effectively control the influence of individual preferences on the experimental results ( Huang et al., 2009 ). Therefore, this research focused on consumer electronics products, essential products in our life, as the experiment stimulus material. To be specific, as shown in Figure 2 , a simulated shopping scenario was presented to participants, with a product presentation designed in a way that products are shown on Taobao.com . Figure 2 includes two segments: One shows mobile phone information ( Figure 2A ) and the other shows comments ( Figure 2B ). Commodity description information in Figure 2A was collected from product introductions on Taobao.com , mainly presenting some parameter information about the product, such as memory size, pixels, and screen size. There was little difference in these parameters, so quality was basically at the same level across smartphones. Prices and brand information were hidden to ensure that reviews were the sole factor influencing consumer decision-making. Product review areas in Figure 2B are the AOI, presented as a double-column layout. Each panel included 10 (positive or negative) reviews taken from real online shopping evaluations, amounting to a total of 20 reviews for each product. To eliminate the impact of different locations of comments on experimental results, the positions of the positive and negative comment areas were exchanged, namely, 50% of the subjects had positive comments presented on the left and negative comments on the right, with the remaining 50% of the participants receiving the opposite set up.

Figure 2 . Commodity information and reviews. (A) Commodity information, (B) Commodity reviews. Screenshots of Alibaba shopfront reproduced with permission of Alibaba and Shenzhen Genuine Mobile Phone Store.

A total of 12,403 product reviews were crawled through and extracted from the two most popular online shopping platforms in China (e.g., Taobao.com and JD.com ) by using GooSeeker (2015) , a web crawler tool. The retrieved reviews were then further processed. At first, brand-related, price-related, transaction-related, and prestige-related contents were removed from comments. Then, the reviews were classified in terms of appearance, memory, running speed, logistics, and so on into two categories: positive reviews and negative reviews. Furthermore, the content of the reviews was refined to retain the original intention but to meet the requirements of the experiment. In short, reviews were modified to ensure brevity, comprehensibility, and equal length, so as to avoid causing cognitive difficulties or ambiguities in semantic understanding. In the end, 80 comments were selected for the experiment: 40 positive and 40 negative reviews (one of the negative comments was a fictitious comment, formulated for the needs of the experiment). To increase the number of experiments and the accuracy of the statistical results, four sets of mobile phone products were set up. There were eight pairs of pictures in total.

Before the experiment started, subjects were asked to read the experimental guide including an overview of the experiment, an introduction of the basic requirements and precautions in the test, and details of two practice trials that were conducted. When participants were cognizant of the experimental scenario, the formal experiment was ready to begin. Participants were required to adjust their bodies to a comfortable sitting position. The 9 points correction program was used for calibration before the experiment. Only those with a deviation angle of less than 1-degree angle could enter the formal eye movement experiment. In our eye-tracking experiment, whether the participant wears glasses or not was identified as a key issue. If the optical power of the participant’s glasses exceeds 200 degrees, due to the reflective effect of the lens, the eye movement instrument will cause great errors in the recording of eye movements. In order to ensure the accuracy of the data recorded by the eye tracker, the experimenter needs to test the power of each participant’s glasses and ensure that the degree of the participant’s glasses does not exceed 200 degrees before the experiment. After drift correction of eye movements, the formal experiment began. The following prompt was presented on the screen: “you will browse four similar mobile phone products; please make your purchase decision for each mobile phone.” Participants then had 8,000 ms to browse the product information. Next, they were allowed to look at the comments image as long as required, after which they were asked to press any key on the keyboard and answer the question “are you willing to buy this cell phone?.”

In this experiment, experimental materials were displayed on a 17-inch monitor with a resolution of 1,024 × 768 pixels. Participants’ eye movements were tracked and recorded by the Eyelink 1,000 desktop eye tracker which is a precise and accurate video-based eye tracker instrument, integrating with SR Research Experiment Builder, Data Viewer, and third-party software tools, with a sampling rate of 1,000 Hz. ( Hwang and Lee, 2018 ). Data processing was conducted by the matching Data Viewer analysis tool.

The experiment flow of each trial is shown in Figure 3 . Every subject was required to complete four trials, with mobile phone style information and comment content different and randomly presented in each trial. After the experiment, a brief interview was conducted to learn about participants’ browsing behavior when they purchased the phone and collected basic information via a matching questionnaire. The whole experiment took about 15 min.

Figure 3 . Experimental flow diagram. Screenshots of Alibaba shopfront reproduced with permission of Alibaba and Shenzhen Genuine Mobile Phone Store.

Data Analysis

Key measures of data collected from the eye-tracking experiment included fixation dwell time and fixation count. AOI is a focus area constructed according to experimental purposes and needs, where pertinent eye movement indicators are extracted. It can guarantee the precision of eye movement data, and successfully eliminate interference from other visual factors in the image. Product review areas are our AOIs, with positive comments (IA1) and negative comments (IA2) divided into two equal-sized rectangular areas.

Fixation can indicate the information acquisition process. Tracking eye fixation is the most efficient way to capture individual information from the external environment ( Hwang and Lee, 2018 ). In this study, fixation dwell time and fixation count were used to indicate users’ cognitive activity and visual attention ( Jacob and Karn, 2003 ). It can reflect the degree of digging into information and engaging in a specific situation. Generally, a more frequent fixation frequency indicates that the individual is more interested in the target resulting in the distribution of fixation points. Valuable and interesting comments attract users to pay more attention throughout the browsing process and focus on the AOIs for much longer. Since these two dependent variables (fixation dwell time and fixation count) comprised our measurement of the browsing process, comprehensive analysis can effectively measure consumers’ reactions to different review contents.

The findings are presented in each section including descriptive statistical analysis, analysis from the perspective of gender and review type using ANOVA, correlation analysis of purchasing decisions, and qualitative analysis of observations.

Descriptive Statistical Analysis

Fixation dwell time and fixation count were extracted in this study for each record. In this case, 160 valid data records were recorded from 40 participants. Each participant generated four records which corresponded to four combinations of two conditions (positive and negative) and two eye-tracking indices (fixation dwell time and fixation count). Each record represented a review comment. Table 1 shows pertinent means and standard deviations.

Table 1 . Results of mean and standard deviations.

It can be noted from the descriptive statistics for both fixation dwell time and fixation count that the mean of positive reviews was less than that of negative ones, suggesting that subjects spent more time on and had more interest in negative reviews. This tendency was more obvious in female subjects, indicating a role of gender.

Fixation results can be reported using a heat mapping plot to provide a more intuitive understanding. In a heat mapping plot, fixation data are displayed as different colors, which can manifest the degree of user fixation ( Wang et al., 2014 ). Red represents the highest level of fixation, followed by yellow and then green, and areas without color represent no fixation count. Figure 4 implies that participants spent more time and cognitive effort on negative reviews than positive ones, as evidenced by the wider red areas in the negative reviews. However, in order to determine whether this difference is statistically significant or not, further inferential statistical analyses were required.

Figure 4 . Heat map of review picture.

Repeated Measures From Gender and Review Type Perspectives—Analysis of Variance

The two independent variables for this experiment were the emotional tendency of the review and gender. A preliminary ANOVA analysis was performed, respectively, on fixation dwell time and fixation count values, with gender (man vs. woman) and review type (positive vs. negative) being the between-subjects independent variables in both cases.

A significant dominant effect of review type was found for both fixation dwell time ( p 1  < 0.001) and fixation count ( p 2  < 0.001; see Table 2 ). However, no significant dominant effect of gender was identified for either fixation dwell time ( p 1  = 0.234) or fixation count ( p 2  = 0.805). These results indicated that there were significant differences in eye movement indicators between positive and negative commentary areas, which confirms Hypothesis 2a. The interaction effect between gender and comment type was significant for both fixation dwell time ( p 1  = 0.002) and fixation count ( p 2  = 0.001). Therefore, a simple-effect analysis was carried out. The effects of different comment types with fixed gender factors and different gender with fixed comment type factors on those two dependent variables (fixation dwell time and fixation count) were investigated and the results are shown in Table 3 .

Table 2 . Results of ANOVA analysis.

Table 3 . Results of simple-effect analysis.

When the subject was female, comment type had a significant dominant effect for both fixation dwell time ( p 1  < 0.001) and fixation count ( p 2  < 0.001). This indicates that female users’ attention time and cognitive level on negative comments were greater than those on positive comments. However, the dominant effect of comment type was not significant ( p 1  = 0.336 > 0.05, p 2  = 0.43 > 0.05) for men, suggesting no difference in concern about the two types of comments for men.

Similarly, when scanning positive reviews, gender had a significant dominant effect ( p 1  = 0.003 < 0.05, p 2  = 0.025 < 0.05) on both fixation dwell time and fixation count, indicating that men exerted longer focus and deeper cognitive efforts to dig out positive reviews than women. In addition, the results for fixation count showed that gender had significant dominant effects ( p 1  = 0.18 > 0.05, p 2  = 0.01 < 0.05) when browsing negative reviews, suggesting that to some extent men pay significantly less cognitive attention to negative reviews than women, which is consistent with the conclusion that men’s attention to positive comments is greater than women’s. Although the dominant effect of gender was not significant ( p 1  = 0.234 > 0.05, p 2  = 0.805 > 0.05) in repeated measures ANOVA, there was an interaction effect with review type. For a specific type of comment, gender had significant influences, because the eye movement index between men and women was different. Thus, gender plays a moderating role in the impact of comments on consumers purchasing behavior.

Correlation Analysis of Purchase Decision

Integrating eye movement and behavioral data, whether participants’ focus on positive or negative reviews is linked to their final purchasing decisions were explored. Combined with the participants’ purchase decision results, the areas with large fixation dwell time and concerns of consumers in the picture were screened out. The frequency statistics are shown in Table 4 .

Table 4 . Frequency statistics of purchasing decisions.

The correlation analysis between the type of comment and the decision data shows that users’ attention level on positive and negative comments was significantly correlated with the purchase decision ( p  = 0.006 < 0.05). Thus, Hypothesis H4 is supported. As shown in Table 4 above, 114 records paid more attention to negative reviews, and 70% of the participants chose not to buy mobile phones. Also, in the 101 records of not buying, 80% of the subjects paid more attention to negative comments and chose not to buy mobile phones, while more than 50% of the subjects who were more interested in positive reviews chose to buy mobile phones. These experimental results are consistent with Hypothesis H1. They suggest that consumers purchasing decisions were based on the preliminary information they gathered and were concerned about, from which we can deduce customers’ final decision results from their visual behavior. Thus, the eye movement experiment analysis in this paper has practical significance.

Furthermore, a significant correlation ( p  = 0.007 < 0.05) was found between the comments area attracting more interest and purchase decisions for women, while no significant correlation was found for men ( p  = 0.195 > 0.05). This finding is consistent with the previous conclusion that men’s attention to positive and negative comments is not significantly different. Similarly, this also explains the moderating effect of gender. This result can be explained further by the subsequent interview of each participant after the experiment was completed. It was noted from the interviews that most of the male subjects claimed that they were more concerned about the hardware parameters of the phone provided in the product information picture. Depending on whether it met expectations, their purchasing decisions were formed, and mobile phone reviews were taken as secondary references that could not completely change their minds.

Figure 5 shows an example of the relationship between visual behavior randomly selected from female participants and the correlative decision-making behavior. The English translation of words that appeared in Figure 5 is shown in Figure 4 .

Figure 5 . Fixation count distribution.

The subjects’ fixation dwell time and fixation count for negative reviews were significantly greater than those for positive ones. Focusing on the screen and running smoothly, the female participant decided not to purchase this product. This leads to the conclusion that this subject thought a lot about the phone screen quality and running speed while selecting a mobile phone. When other consumers expressed negative criticism about these features, the female participant tended to give up buying them.

Furthermore, combined with the result of each subject’s gaze distribution map and AOI heat map, it was found that different subjects paid attention to different features of mobile phones. Subjects all had clear concerns about some features of the product. The top five mobile phone features that subjects were concerned about are listed in Table 5 . Contrary to expectations, factors, such as appearance and logistics, were no longer a priority. Consequently, the reasons why participants chose to buy or not to buy mobile phones can be inferred from the gazing distribution map recorded in the product review picture. Therefore we can provide suggestions on how to improve the design of mobile phone products for businesses according to the features that users are more concerned about.

Table 5 . Top 5 features of mobile phones.

Fictitious Comments Recognition Analysis

The authenticity of reviews is an important factor affecting the helpfulness of online reviews. To enhance the reputation and ratings of online stores, in the Chinese e-commerce market, more and more sellers are employing a network “water army”—a group of people who praise the shop and add many fake comments without buying any goods from the store. Combined with online comments, eye movement fixation, and information extraction theory, Song et al. (2017) found that fake praise significantly affects consumers’ judgment of the authenticity of reviews, thereby affecting consumers’ purchase intention. These fictitious comments glutted in the purchasers’ real ones are easy to mislead customers. Hence, this experiment was designed to randomly insert a fictitious comment into the remaining 79 real comments without notifying the participants in advance, to test whether potential buyers could identify the false comments and find out their impact on consumers’ purchase decisions.

The analysis of the eye movement data from 40 product review pictures containing this false commentary found that only several subjects’ visual trajectories were back and forth in this comment, and most participants exhibited no differences relative to other comments, indicating that the vast majority of users did not identify the lack of authenticity of this comment. Moreover, when asked whether they had taken note of this hidden false comment in interviews, almost 96% of the participants answered they had not. Thus, Hypothesis H2b is not supported.

This result explains why network “water armies” are so popular in China, as the consumer cannot distinguish false comments. Thus, it is necessary to standardize the e-commerce market, establish an online comment authenticity automatic identification information system, and crack down on illegal acts of employing network troops to disseminate fraudulent information.

Discussion and Conclusion

In the e-commerce market, online comments facilitate online shopping for consumers; in turn, consumers are increasingly dependent on review information to judge the quality of products and make a buying decision. Consequently, studies on the influence of online reviews on consumers’ behavior have important theoretical significance and practical implications. Using traditional empirical methodologies, such as self-report surveys, it is difficult to elucidate the effects of some variables, such as review choosing preference because they are associated with automatic or subconscious cognitive processing. In this paper, the eye-tracking experiment as a methodology was employed to test congruity hypotheses of product reviews and explore consumers’ online review search behavior by incorporating the moderating effect of gender.

Hypotheses testing results indicate that the emotional valence of online reviews has a significant influence on fixation dwell time and fixation count of AOI, suggesting that consumers exert more cognitive attention and effort on negative reviews than on positive ones. This finding is consistent with Ahluwalia et al.’s (2000) observation that negative information is more valuable than positive information when making a judgment. Specifically, consumers use comments from other users to avoid possible risks from information asymmetry ( Hong et al., 2017 ) due to the untouchability of online shopping. These findings provide the information processing evidence that customers are inclined to acquire more information for deeper thinking and to make a comparison when negative comments appear which could more likely result in choosing not to buy the product to reduce their risk. In addition, in real online shopping, consumers are accustomed to giving positive reviews as long as any dissatisfaction in the shopping process is within their tolerance limits. Furthermore, some e-sellers may be forging fake praise ( Wu et al., 2020 ). The above two phenomena exaggerate the word-of-mouth effect of negative comments, resulting in their greater effect in contrast to positive reviews; hence, consumers pay more attention to negative reviews. Thus, Hypothesis H2a is supported. However, when limited fake criticism was mixed in with a large amount of normal commentary, the subject’s eye movements did not change significantly, indicating that little cognitive conflict was produced. Consumers could not identify fake comments. Therefore, H2b is not supported.

Although the dominant effect of gender was not significant on the indicators of the fixation dwell time and fixation count, a significant interaction effect between user gender and review polarity was observed, suggesting that consumers’ gender can regulate their comment-browsing behavior. Therefore, H3 is partly supported. For female consumers, attention to negative comments was significantly greater than positive ones. Men’s attention was more homogeneous, and men paid more attention to positive comments than women. This is attributed to the fact that men and women have different risk perceptions of online shopping ( Garbarino and Strahilevitz, 2004 ). As reported in previous studies, men tend to focus more on specific, concrete information, such as the technical features of mobile phones, as the basis for their purchase decision. They have a weaker perception of the risks of online shopping than women. Women would be worried more about the various shopping risks and be more easily affected by others’ evaluations. Specifically, women considered all aspects of the available information, including the attributes of the product itself and other post-use evaluations. They tended to believe that the more comprehensive the information they considered, the lower the risk they faced of a failed purchase ( Garbarino and Strahilevitz, 2004 ; Kanungo and Jain, 2012 ). Therefore, women hope to reduce the risk of loss by drawing on as much overall information as possible because they are more likely to focus on negative reviews.

The main finding from the fixation count distribution is that consumers’ visual attention is mainly focused on reviews containing the following five mobile phone characteristics: running smoothly, battery life, fever condition of phones, pixels, and after-sales service. Considering the behavior results, when they pay more attention to negative comments, consumers tend to give up buying mobile phones. When they pay more attention to positive comments, consumers often choose to buy. Consequently, there is a significant correlation between visual attention and behavioral decision results. Thus, H4 is supported. Consumers’ decision-making intention can be reflected in the visual browsing process. In brief, the results of the eye movement experiment can be used as a basis for sellers not only to formulate marketing strategies but also to prove the feasibility and strictness of applying the eye movement tracking method to the study of consumer decision-making behavior.

Theoretical Implications

This study has focused on how online reviews affect consumer purchasing decisions by employing eye-tracking. The results contribute to the literature on consumer behavior and provide practical implications for the development of e-business markets. This study has several theoretical contributions. Firstly, it contributes to the literature related to online review valence in online shopping by tracking the visual information acquisition process underlying consumers’ purchase decisions. Although several studies have been conducted to examine the effect of online review valence, very limited research has been conducted to investigate the underlying mechanisms. Our study advances this research area by proposing visual processing models of reviews information. The findings provide useful information and guidelines on the underlying mechanism of how online reviews influence consumers’ online shopping behavior, which is essential for the theory of online consumer behavior.

Secondly, the current study offers a deeper understanding of the relationships between online review valence and gender difference by uncovering the moderating role of gender. Although previous studies have found the effect of review valence on online consumer behavior, the current study first reveals the effect of gender on this effect and explains it from the perspective of attention bias.

Finally, the current study investigated the effect of online reviews on consumer behavior from both eye-tracking and behavioral self-reports, the results are consistent with each other, which increased the credibility of the current results and also provides strong evidence of whether and how online reviews influence consumer behavior.

Implications for Practice

This study also has implications for practice. According to the analysis of experimental results and findings presented above, it is recommended that online merchants should pay particular attention to negative comments and resolve them promptly through careful analysis of negative comments and customization of product information according to consumer characteristics including gender factors. Based on the findings that consumers cannot identify false comments, it is very important to establish an online review screening system that could automatically screen untrue content in product reviews, and create a safer, reliable, and better online shopping environment for consumers.

Limitations and Future Research

Although the research makes some contributions to both theoretical and empirical literature, it still has some limitations. In the case of experiments, the number of positive and negative reviews of each mobile phone was limited to 10 positive and 10 negative reviews (20 in total) due to the size restrictions on the product review picture. The number of comments could be considered relatively small. Efforts should be made in the future to develop a dynamic experimental design where participants can flip the page automatically to increase the number of comments. Also, the research was conducted to study the impact of reviews on consumers’ purchase decisions by hiding the brand of the products. The results would be different if the brand of the products is exposed since consumers might be moderated through brand preferences and brand loyalty, which could be taken into account in future research projects.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author Contributions

TC conceived and designed this study. TC, PS, and MQ wrote the first draft of the manuscript. TC, XC, and MQ designed and performed related experiments, material preparation, data collection, and analysis. TC, PS, XC, and Y-CL revised the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

The authors wish to thank the Editor-in-Chief, Associate Editor, reviewers and typesetters for their highly constructive comments. The authors would like to thank Jia Jin and Hao Ding for assistance in experimental data collection and Jun Lei for the text-polishing of this paper. The authors thank all the researchers who graciously shared their findings with us which allowed this eye-tracking study to be more comprehensive than it would have been without their help.

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Keywords: online reviews, eye-tracking, consumers purchasing decisions, emotion valence, gender

Citation: Chen T, Samaranayake P, Cen X, Qi M and Lan Y-C (2022) The Impact of Online Reviews on Consumers’ Purchasing Decisions: Evidence From an Eye-Tracking Study. Front. Psychol . 13:865702. doi: 10.3389/fpsyg.2022.865702

Received: 30 January 2022; Accepted: 02 May 2022; Published: 08 June 2022.

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Copyright © 2022 Chen, Samaranayake, Cen, Qi and Lan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: XiongYing Cen, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

The New ChatGPT Offers a Lesson in A.I. Hype

OpenAI released GPT-4o, its latest chatbot technology, in a partly finished state. It has much to prove.

ChatGPT-4o trying to solve a geometry problem Credit... Arsenii Vaselenko for The New York Times

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By Brian X. Chen

Brian X. Chen is the author of Tech Fix , a weekly column about the societal implications of the tech we use.

• May 31, 2024

When OpenAI unveiled the latest version of its immensely popular ChatGPT chatbot this month, it had a new voice possessing humanlike inflections and emotions. The online demonstration also featured the bot tutoring a child on solving a geometry problem.

To my chagrin, the demo turned out to be essentially a bait and switch. The new ChatGPT was released without most of its new features, including the improved voice (which the company told me it postponed to make fixes). The ability to use a phone’s video camera to get real-time analysis of something like a math problem isn’t available yet, either.

Amid the delay, the company also deactivated the ChatGPT voice that some said sounded like the actress Scarlett Johansson, after she threatened legal action , replacing it with a different female voice.

For now, what has actually been rolled out in the new ChatGPT is the ability to upload photos for the bot to analyze. Users can generally expect quicker, more lucid responses. The bot can also do real-time language translations, but ChatGPT will respond in its older, machine-like voice.

Nonetheless, this is the leading chatbot that upended the tech industry , so it was worth reviewing. After trying the sped-up chatbot for two weeks, I had mixed feelings. It excelled at language translations, but it struggled with math and physics. All told, I didn’t see a meaningful improvement from the last version, ChatGPT-4. I definitely wouldn’t let it tutor my child.

This tactic, in which A.I. companies promise wild new features and deliver a half-baked product, is becoming a trend that is bound to confuse and frustrate people. The $700 Ai Pin , a talking lapel pin from the start-up Humane, which is funded by OpenAI’s chief executive, Sam Altman, was universally panned because it overheated and spat out nonsense. Meta also recently added to its apps an A.I. chatbot that did a poor job at most of its advertised tasks , like web searches for plane tickets.

Companies are releasing A.I. products in a premature state partly because they want people to use the technology to help them learn how to improve it. In the past, when companies unveiled new tech products like phones, what we were shown — features like new cameras and brighter screens — was what we were getting. With artificial intelligence, companies are giving a preview of a potential future, demonstrating technologies that are being developed and working only in limited, controlled conditions. A mature, reliable product might arrive — or might not.

The lesson to learn from all this is that we, as consumers, should resist the hype and take a slow, cautious approach to A.I. We shouldn’t be spending much cash on any underbaked tech until we see proof that the tools work as advertised.

The new version of ChatGPT, called GPT-4o (“o” as in “omni”), is now free to try on OpenAI’s website and app . Nonpaying users can make a few requests before hitting a timeout, and those who have a $20 monthly subscription can ask the bot a larger number of questions.

OpenAI said its iterative approach to updating ChatGPT allowed it to gather feedback to make improvements.

“We believe it’s important to preview our advanced models to give people a glimpse of their capabilities and to help us understand their real-world applications,” the company said in a statement.

(The New York Times sued OpenAI and its partner, Microsoft , last year for using copyrighted news articles without permission to train chatbots.)

Here’s what to know about the latest version of ChatGPT.

Geometry and Physics

To show off ChatGPT-4o’s new tricks, OpenAI published a video featuring Sal Khan, the chief executive of the Khan Academy, the education nonprofit, and his son, Imran. With a video camera pointed at a geometry problem, ChatGPT was able to talk Imran through solving it step by step.

Even though ChatGPT’s video-analysis feature has yet to be released, I was able to upload photos of geometry problems. ChatGPT solved some of the easier ones correctly, but it tripped up on more challenging problems.

For one problem involving intersecting triangles, which I dug up on an SAT preparation website , the bot understood the question but gave the wrong answer.

Taylor Nguyen, a high school physics teacher in Orange County, Calif., uploaded a physics problem involving a man on a swing that is commonly included on Advanced Placement Calculus tests. ChatGPT made several logical mistakes to give the wrong answer, but it was able to correct itself with feedback from Mr. Nguyen.

“I was able to coach it, but I’m a teacher,” he said. “How is a student supposed to pick out those mistakes? They’re making this assumption that the chatbot is right.”

I did notice that ChatGPT-4o succeeded at some division calculations that its predecessors did incorrectly, so there are signs of slow improvement. But it also failed at a basic math task that past versions and other chatbots, including Meta AI and Google’s Gemini, have flunked at: the ability to count. When I asked ChatGPT-4o for a four-syllable word starting with the letter “W,” it responded, “Wonderful.”

OpenAI said it was constantly working to improve its systems’ responses to complex math problems.

Mr. Khan, whose company uses OpenAI’s technology in its tutoring software Khanmigo, did not respond to a request for comment on whether he would leave ChatGPT the tutor alone with his son.

OpenAI also highlighted that the new ChatGPT was better at reasoning, or using logic to come up with responses. So I ran it through one of my favorite tests: I asked it to generate a Where’s Waldo? puzzle. When it showed an image of a giant Waldo standing in a crowd, I said that the point is that he’s supposed to be hard to find.

The bot then generated an even larger Waldo.

Subbarao Kambhampati, a professor and researcher of artificial intelligence at Arizona State University, also put the chatbot through some tests and said he saw no noticeable improvement in reasoning compared with the last version.

He presented ChatGPT a puzzle involving blocks:

If block C is on top of block A, and block B is separately on the table, can you tell me how I can make a stack of blocks with block A on top of block B and block B on top of block C, but without moving block C?

The answer is that it’s impossible to arrange the blocks under these conditions, but, just as with past versions, ChatGPT-4o consistently came up with a solution that involved moving block C. With this and other reasoning tests, ChatGPT was occasionally able to take feedback to get the correct answer, which is antithetical to how artificial intelligence is supposed to work, Mr. Kambhampati said.

“You can correct it, but when you do that you’re using your own intelligence,” he said.

OpenAI pointed to test results that showed GPT-4o scored about two percentage points higher at answering general knowledge questions than previous versions of ChatGPT, illustrating that its reasoning skills had slightly improved.

OpenAI also said the new ChatGPT could do real-time language translation, which could help you converse with someone speaking a foreign language.

I tested ChatGPT with Mandarin and Cantonese and confirmed that it was OK at translating phrases, such as “I’d like to book a hotel room for next Thursday” and “I want a king-size bed.” But the accents were slightly off. (To be fair, my broken Chinese is not much better.) OpenAI said it was still working to improve accents.

ChatGPT-4o also excelled as an editor. When I fed it paragraphs that I wrote, it was fast and effective at removing excessive words and jargon. ChatGPT’s decent performance with language translation gives me confidence that this will soon become a more useful feature.

Bottom Line

A major thing OpenAI got right with ChatGPT-4o is making the technology free for people to try. Free is the right price: Since we are helping to train these A.I. systems with our data to improve, we shouldn’t be paying for them.

The best of A.I. has yet to come, and it might one day be a good math tutor that we want to talk to. But we should believe it when we see it — and hear it.

Brian X. Chen is the lead consumer technology writer for The Times. He reviews products and writes Tech Fix , a column about the social implications of the tech we use. More about Brian X. Chen

Explore Our Coverage of Artificial Intelligence

News  and Analysis

Google appears to have rolled back its new A.I. Overviews  after the technology produced a litany of untruths and errors.

OpenAI said that it has begun training a new flagship A.I. model  that would succeed the GPT-4 technology that drives its popular online chatbot, ChatGPT.

Elon Musk’s A.I. company, xAI, said that it had raised $6 billion , helping to close the funding gap with OpenAI, Anthropic and other rivals.

The Age of A.I.

After some trying years during which Mark Zuckerberg could do little right, many developers and technologists have embraced the Meta chief  as their champion of “open-source” A.I.

D’Youville University in Buffalo had an A.I. robot speak at its commencement . Not everyone was happy about it.

A new program, backed by Cornell Tech, M.I.T. and U.C.L.A., helps prepare lower-income, Latina and Black female computing majors  for A.I. careers.

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