WHAT COGNITIVE BIASES ATTACK POTENTIAL CUSTOMERS IN USER REVIEWS THE MOST?

Full text

2022 Volume XXII(1): 5-21
Acta academica karviniensia DOI: 10.25142/aak.2022.001
5
WHAT COGNITIVE BIASES ATTACK POTENTIAL CUSTOMERS IN
USER REVIEWS THE MOST?
[Jaká kognitivní zkreslení nejvíce útočí na potenciální zákazníky v
uživatelských recenzích?]
Radka Bauerová1, Tereza Ikášová2, Veronika Kopřivová3, Tomáš Pražák4, Michal
Stoklasa5
1 Silesian University, School of Business Administration, Univerzitní nám. 1934/3,733 40 Karviná
Email:bauerova@opf.slu.cz
2 Silesian University, School of Business Administration, Univerzitní nám. 1934/3,733 40 Karviná
Email:ikasova@opf.slu.cz
3 Silesian University, School of Business Administration, Univerzitní nám. 1934/3,733 40 Karviná
Email:koprivova@opf.slu.cz
4 Silesian University, School of Business Administration, Univerzitní nám. 1934/3,733 40 Karviná
Email:prazak@opf.slu.cz
5 Silesian University, School of Business Administration, Univerzitní nám. 1934/3,733 40 Karviná
Email:stoklasa@opf.slu.cz
Abstract: Reading reviews is a common activity for many potential customers when deciding to buy
a product from a particular retailer. It is such a common activity that many of them may be unaware
that they are influenced not only by the content of the review itself, but also by its style, display,
length, and distinctiveness, with a particular cognitive bias behind each of these elements. This has an
impact on their decision-making, which may ultimately be illogical. In reality, however, we are
affected by hundreds of confirmed distortions that force us to think and act irrationally. If people are
not always able to make rational decisions, then many of the economic assumptions need to be
reviewed. The aim of this paper is therefore to uncover the cognitive biases that attack potential
customers in user reviews and to determine their influence on e-shop popularity ratings. In order to
accomplish the objective, a survey was conducted among the TOP 100 e-shops on the Czech market,
from which were selected 70 e-shops to identify the most frequently occurring cognitive biases. In the
first step, the heuristic method of observing e-shop websites was used. In the second step, a chi-square
two-sample test was used to obtain results due to the nominal nature of the data under study. It was
found that in terms of the user interface, the most emerging biases are bandwagon effect, apophenia,
authority bias and social proof. Then, in the case of examining the reviews themselves, it was found
that availability bias, story bias, processing difficulty effect, negativity effect and authority bias were
determined to be the most likely to influence potential customers. Some of these biases were also
found to affect the popularity ratings of the e-shop, which marketing managers should pay attention to
because of the link between popularity and loyalty.
Keywords: apophenia, authority bias, bandwagon effect, e-shops, negativity effect, online reviews,
processing difficulty effect, story bias.
JEL classification: M30, M31, C12
Received: 19.11.2021; Reviewed: 6.12.2021; 19.1.2022; Accepted: 18.5.2022
Introduction
In economics theory, the standard model is that everybody is rational, self-interested,
calculating and have all the available information, in contrast, psychologists' research often
suggests a much more skeptical view of ours cognitive abilities. Kahneman (2011) shows the
importance to identify and understand mistakes in judgments and decisions of others and over

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time of themselves, as well as efforts to limit bad judgments and decisions. If people are not
always capable of making rational decisions, then a lot of what economists had inferred on the
basis of those assumptions really needed to be re-examined. For these reasons, it is important
to monitor the psychological factors that affect a person in decision-making. At this time,
purchasing decisions are very often moved to the online space, where consumers are affected
by various cognitive biases.
From an evolutionary perspective, cognitive biases seem somewhat mysterious because they
deviate from standards of logic and accuracy (Haselton, Nettl and Andrews 2015). Cognitive
biases refer to cases in which human cognition produces representations that are
systematically distorted relative to some aspect of objective reality. The concept of cognitive
biases has been explored in the literature from many different perspectives, ranging from their
effect on decision making by mitigating more costly errors (Johnson, Blumstein, Fowler and
Haselton 2013) and optimizing behaviour (Marshall, Trimmer, Houston and McNamara
2013), to their use in a specific domain. Studies dealing with the effect and use of cognitive
biases in online marketing communication, specifically in the context of reviews, are relevant
to this paper. Bandwagon effect (Wu and Lin 2017), analysis paralysis (Houdek et al. 2018),
authority bias (Sundar, Xu and Oeldorf-Hirsch 2008), and negative bias (Yang and Unnava
2016) can be considered the most important cognitive biases for reviews in the web
environment framework. Overall, however, consumers in the study setting are also influenced
by many other biases such as story bias, availability bias, social proof, apophenia effect, Von
Restorff effect, humour effect and processing difficulty effect confirmation bias, loss
aversion, blind spot bias, anchoring bias, social influence, the effects and synergistic effect of
which are worthy of inclusion in the study. However, according to Haselton, Nettle, and
Andrews (2015), the idea that human judgment is flawed is itself flawed. Indeed, the
evolution of cognitive biases suggests that humans are precisely through them adapting to the
environment in which they live and may be functional traits designed by the wisdom of
natural selection.
Cognitive biases are naturally part of everyone's life and have a significant impact on society-
wide behaviour as well. It is a very broad topic covering a myriad of errors that can be
committed not only by consumers when making purchasing decisions, but by anyone
confronted with a situation in which they have to make a specific decision. Given the fact that
nowadays internet users are influenced by various fraudulent messages or fake product
reviews, it is more important than ever before to identify ways to avoid falling prey to these
fraudulent practices. At the same time, in the growth of consumer trust in online product
reviews, i.e. in the opinions of other entirely unknown people, it is also important to formulate
the ways in which the company can influence the decision-making of the consumer.
Therefore, the purpose of this study is to uncover the cognitive biases that attack potential
customers in user reviews and to determine their influence on e-shop popularity ratings. The
observating sample is Top 100 largest e-shops in Czechia, from which were closely monitored
70 e-shops. In order to fulfil the aim of the paper, a heuristic method of analysing e-shop
websites and the types of cognitive bias is used. The impact of cognitive biases on the
popularity rating is analysed by Pearson Chi-square test. This paper first introduces the
cognitive biases that have been found to affect review readers. Subsequently, the methods
section mainly presents how the data was collected and analysed. The results chapter first
presents general findings on the proportion of e-shops allowing their customers to post
reviews. Subsequently, attention is paid to the results already focusing on the specific
cognitive biases that were revealed in our investigation and their possible influence on the

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popularity ratings of the e-shops under study. The paper concludes with a summary of the
most important findings and their scientific and managerial implications.
1 Cognitive biases in the domain of user reviews
Although consumers typically seek both positive and negative reviews to evaluate products
(You et al. 2015), it is not only the negativity and positivity of reviews that influence their
final purchase decision, but many other cognitive biases. Already when viewing a review
page, analysis paralysis can begin to affect the consumer. This bias consists in displaying a
certain number of reviews per page. Therefore, analysis paralysis causes consumers to feel
that if consumers have too many choices, they tend not to choose any (Houdek et al. 2018).
This is consistent with the finding that those consumers who face too many choices, even if
they are pleasant choices, suffer from decision fatigue, which causes them to be less focused
and more likely to give up more quickly when trying to complete the task (Worth 2009).
Consumers postpone their purchasing decisions when they are "spoilt" for choice, whereas
they buy faster when they have fewer options to choose from (Iyengar 2010). More options
have been found to lead to greater dissatisfaction because customer expectations are increased
(Kurien et al. 2014). Consumers may experience choice paralysis when it is difficult to find
all relevant options and effectively check available feedback such as reviews (Basuroy,
Chatterjee and Ravid 2003; Breugelmans, Kohler, Dellaert, and de Ruyter 2012; Khare,
Labrecque and Asare 2011).
Reading the reviews then the bandwagon effect starts to have an effect. The assumption of the
bandwagon effect is that the probability of adopting a viewpoint increases with the number of
people who hold that viewpoint (Muchnik et al. 2013; Vosoughi, Roy and Aral 2018; Sundar,
Oeldorf-Hirsch and Xu 2008; Xu et al. 2012). For online consumer reviews to serve as
decision-making guides, consumers must first trust the reviewer. However, unlike in-person
communication where trust develops overtime, consumers must rely on personal information
to establish trust in the reviewer in the context of online shopping. The results of a study
examining reviewer trust showed that the cues of the reputation and profile picture
differentially contributed to users' affective trust and the cognitive trust toward the reviewer
(Xu 2014). Kim and Gambino (2016) focused on personalization features and herding effect
stimuli (star ratings and specific reviews) in the case of a restaurant website. Their research
showed that personalization features and herding effect stimuli increased positive perceptions
and their behavioral intentions toward the website and the recommended restaurant. Another
experiment that examined web users revealed that online ratings are highly sensitive to
irrational herding behavior and that herding can be manipulated (Bohannon 2013). This effect
is also associated with the authority effect in many papers. The creation of more positive
attitudes toward a product review website was found to be related to the source of
information, where if an expert was cited as the source of information for a product review,
such a product review elicited more favorable attitudes toward the website (Kim et al. 2015).
This study also revealed that perceived authority and herding heuristics mediated the
relationship between the presence of social plugins and favorable attitudes toward a website
through perceived trustworthiness. The findings not only highlighted the strength of authority
and herding stimuli in the rapid appraisal of a product review site, but also discovered a
theoretical pathway that explained the role of social plugins on e-shops websites. Research
suggests that new media features such as large numbers of "likes", shares,comments, or high
ratings can induce a herding effect that positively influences the effectiveness of online word-
of-mouth (e-WOM) messages (Sundar, Oeldorf-Hirsch and Xu 2008; Xu et al. 2012). In
studies examining e-WOM in the form of online reviews in conjunction with the herding
effect, positive reviews have been found to influence both perceptions of the review itself and

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perceptions about the product (Sundar, Oeldorf-Hirsch and Xu 2008; Xu et al. 2012; Wu and
Lin 2017). Within the online shopping environment, the herding effect influences reviews and
sales rankings, which in turn affects the perceived popularity and customer's intention to
purchase the product (Sundar, Oeldorf-Hirsch and Xu 2008). Comment ratings also positively
affect the perceived credibility of reviews, which influences the perceived usefulness of
reviews, product attitude, and purchase intention (Sundar, Oeldorf-Hirsch Xu 2008; Wu and
Lin 2017). Therefore, from the group of user interface (UI) elements, the next focus will be on
authority bias.
Based on the theory of authority bias, consumers trust authority more. Therefore, mentioning
phrases such as ‘verified customer’, ‘registered customer’ and ‘expert’ for specific reviews
can influence consumers' judgement (Kreimer 2016; Ngo-Ye and Sinha 2014; Liu and Du
2020). Authority bias occurs when the opinions and instructions of authority figures are
unquestionably accepted and followed. Research in this area has found that statements
attributed to prestigious persons scored higher in agreement with the rater's opinion than
anonymous statements (Kreimer 2016). Furthermore, reviewer characteristics and the
authority of the member in a given community have been found to help predict the usefulness
of reviews (Ngo-Ye and Sinha 2014). Research focusing on the influence of product
photography in reviews has found that reviews using an image can directly indicate the
socioeconomic status of reviewers, which is quite different from text-based reviews (Liu and
Du 2020). The publication of these images was found to have a significant effect on consumer
purchase intentions, suggesting that consumers have higher purchase intentions when they
feel that products are recommended by reviewers with high socioeconomic status. Other
research has focused on how the verified purchase label of reviewers influences consumers'
product purchase decisions (He et al. 2020). Such reviewer labeling evokes consumers'
perception that the reviewer has experience with the product and maximizes the utility of his
or her review. Thus, research by He et al. (2020) confirmed that reviews by verified reviewers
are directly related to obtaining higher sales for products reviewed by those reviewers.
Related to the strength of authority is the credibility of the source. As part of research
focusing on this credibility before and after making a purchase, it has been found that if
customers purchase a product based on credibility and are subsequently dissatisfied with it,
they will reconsider their judgement of the credibility of the entire website (Hsieh and Li
2020). Therefore, credibility in online reviews is not only a short-term influence when
purchasing products, but also a long-term influence, as it can affect future purchases. As part
of the power of authority, this bias has been found to be significantly enhanced when all
information is consistent across the Internet (Lankes 2008).
The value of an online review, whether anonymous or supported by authority bias, can be
enhanced by social proof bias. Hilverda, Kuttschreuter and Giebels (2018) analysed the social
proof bias which affects the perceived number of interactions for reviews. Thus, a review with
more "likes" may be perceived as more valuable. However, the diversity of text within the
story bias can also contribute significantly to the perception of a review as valuable. Story
bias is associated with the conjunction fallacy, whereby consumers believe the review more if
there is a story with more details (Fico, Richardson, and Edwards 2004). Story bias is
connected with the Von Restorff effect. This effect represents the tendency to remember what
stands out in some way (Chee and Goh, 2018). In reviews, this can include using emojis,
writing the review in capital letters only, using bullets, and other symbols. However, attention
must be paid to the length of the text itself. Chevalier and Mayzlin (2006) found that the
processing difficulty effect played an important role in reviews. The authors suggested that
longer reviews decrease the relative share. We can also judge the value of a review by

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whether we are familiar with the reviewer's style of expression. In this case, availability bias
plays a role. Availability bias makes familiar things seem good (Dimara, Dragicevic, and
Bezerianos 2016). This bias is very difficult to study because it is based on the individuality
of the consumer. Nevertheless, there are commonly known phrases that we can include and
examine here, such as "I recommend" or "Super". Related to this is also apophenia bias,
which is based on people's tendency to identify meaningful patterns where none actually exist.
As a result of Jones and Martin (2021) study, people tend to prefer positive results over
negative ones. The final choice of the customer can also be affected by confirmation bias.
Confirmation bias describes a condition in which consumers tend to favour information and
interpretations that support their view while ignoring or undervaluing those that contradict
their beliefs or interpreting ambiguous information to be consistent with their own view (Del
Vicario et al. 2017).
Another important element is emotions. Emotions can significantly influence the way reviews
are processed. For this reason, the humour effect described by positive emotions in reviews
will be analysed. The empirical evaluation by Garcia and Schweitzer (2011) or Malik and
Hussain (2017) found that trust, joy, and anticipation have a greater impact on perceived
helpfulness. On the other hand, negativity effect means a tendency to place more emphasis on
negative experiences rather than positive ones. Consumers suffering from this bias feel that
"negative is stronger than positive" and will perceive threats rather than positives in a given
situation (Kim and Hwang 2020). A study using eye tracking and self-reporting showed that
consumers spend more time on negative reviews and orient themselves more by the number
of positive and negative reviews than by the quantity of product sold (Shi et al. 2020). Many
studies confirm that negative reviews were perceived as more useful (Chen and Lurie 2013;
East, Uncles, Romaniuka Lomax 2016; Yang and Unnava 2016; Kim and Hwang 2020).
However, another study, also using the eye tracking method, found that although consumers
underestimate the ratings of high-volume products compared to low-volume products due to
negativity effect (Shi et al. 2020), presenting a percentage of positive reviews can eliminate
the rating difference. In addition, when both the percentage of positive reviews and the sales
volume are high, consumers prefer products with lower sales volume but a higher percentage
of positive reviews over products with higher sales volume but a lower percentage of positive
reviews. However, when evaluating the usefulness of a review, there was a relationship
between the usefulness rating and its negative content, the more negative the review was, the
more useful it was rated, which also confirms the effectiveness of negativity effect in the
study area (Cui et al. 2012). The findings of these studies highlighted the importance of
emotions in online reviews and the significant implications for consumers and e-commerce
retailers.
Based on the literature review, it is evident that there are many cognitive biases in user
reviews. Therefore, the following research question was formulated to uncover which biases
have the greatest impact on an e-shop popularity rank. The research question is ‘Which
cognitive biases found in user reviews can affect the popularity of an e-shop?’.
2 Methods
We applied the mentioned cognitive biases to the top 100 largest e-shops according to a study
on the českýkošíkroku.cz website. In order to fulfil the aim of the paper, a heuristic method of
observing e-shop websites and analysing the types of cognitive bias on the evaluation of the
offered products is used. The main object of research is the reviews of products sold.

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Heuristic analysis is a basic method of examining websites. It is an expert analysis performed
on the basis of already known and practically verified knowledge concerning the selected
qualitative characteristics of the web presentation. This knowledge can take the form of a list
of points that need to be checked on the website, or the analysis is based only on the
theoretical knowledge and practical experience of person processing it. The main advantages
of heuristic analysis are the relative ease of implementation, lower time requirements and the
possibility to apply both theoretical knowledge and practical experience in research.
Data collection
As part of the observation of the researched websites, two main categories of services
provided at the e-shop were selected. The choice of these main categories was based on the
focus of the e-shop. Consequently, two subcategories of the main products were identified.
These subcategories included mainly the most popular, best-selling or most expensive
products. Thus, 4 significant products were selected for each e-shop, for which it was possible
to assume the highest number of reviews. If product did not have any reviews, no distortion
was examined. In the case of 30 e-shops, it was not possible to perform analyses. The author
collective carried out a total of 280 observations according to precisely defined criteria and
metrics (70 e-shops and 4 products for each of e-shop). Subsequently, cognitive biases and
their metrics were defined for analysis. For the purpose of this paper, we analysed a total of
seven user interface elements and eleven specific elements that may be present in the reviews.
These elements are part of the tables in results. All available reviews were taken into account
for each product. Totally more than 10 000 reviews were analysed. The individual
observations were carried out in the period of October 2021. The list of TOP 100 e-shops,
selected categories and products and the total number of reviews is available in the appendix.
Data analysis
Firstly, frequency analysis was conducted focusing on the number of e-shops that allow the
inclusion of reviews on their websites. Subsequently, only those e-shops that allow their
customers to post reviews were examined. The results of the popularity of the examined
e-shops were taken from the study on the českýkošíkroku.cz website. The popularity scores
were divided into four categories. The less popular category, where e-shops achieved between
51% and 60% popularity; the popular category, where e-shops achieved between 61% and
70% popularity; the more popular category, where e-shops achieved between 71% and 80%
popularity; and the most popular category, where e-shops achieved between 81% and 90%
popularity. None of the e-shops studied achieved less than 51% popularity and none achieved
more than 90% popularity. During data cleaning, e-shops that do not allow their customers to
post reviews of their products were removed from the dataset. There was a total of 30 such e-
shops in the study. This step resulted in the category of less popular e-shops disappearing
from the dataset. The analysis further investigated the cognitive biases of the website users in
terms of UI elements and the element in reviews. Subsequently, attention was paid to
investigating the possible influence of cognitive biases from the perspective of UI and reviews
themselves on the level of popularity of e-shops. In this step, a chi-square two-sample test was
used to obtain results due to the nominal nature of the data under study.
This method gives us the basic characteristics of the relationship between the observed
variables. Due to the high number of monitored variables, this method selects important
elements to which it will be possible to pay more attention in further research. The Pearson
chi-square tests the match of expected and actual frequencies in parts of the range of possible
values. A test of independence assesses whether observations consisting of measures on two
variables, expressed in a contingency table, are independent of each other. The aim is to

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calculate Pearson's cumulative test statistic, which asymptotically approaches. Pearson's chi
square test is calculated by means of a nonparametric test in the statistical program SPSS. The
results are discussed in relation to the chosen null hypothesis about the independence of the
observed traits.
3 Results
Based on an analysis of the total number of e-shops surveyed, according to the TOP 100
metric, it was found that 58% of e-shops allow their customers to post text reviews of the
products they have purchased. Almost one-third of e-shops do not allow to post reviews of
purchased products at all. As shown in Figure 1, other e-shops, although not allowing text
reviews, allow customers to rate products with stars or allow potential customers to ask
questions.
Figure 1: Usage of reviews on e-shops
Source: websites of the analysed e-shops; own illustration
An examination of specific elements within the user interface (UI) revealed that users are
most often shown the overall percentage of customers recommending a product. In this case,
there may be a bandwagon effect, whereby when a higher percentage of recommending
customers is reached, this may have a positive effect on the perception of the appropriateness
of purchasing product. Furthermore, very often the date of the review is indicated next to the
review. In this case, the apophenia effect may act on customers, where they may
unconsciously give more weight to more recent reviews. Up to 66% of e-shops that allow the
insertion of reviews show a certain number of reviews per page, which may mitigate the
effect of analysis paralysis. Since this is an effect where a potential customer browsing
reviews may be paralyzed and not complete their intended purchase due to this bias, all
e-shops should pay attention to sorting options within their UI to avoid this situation. The
following table shows the specific values of the use of elements within UI and their
assignment to specific cognitive biases.

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Table 1: Percentage of used UI elements
Cognitive biases
Web elements examined
Yes
No
Not possible
to determine
Analysis paralysis
Showing a certain number of reviews per page
66.04%
18.87%
15.09%
Bandwagon effect
Indication of the total percentage of customers recommending
the product/Indicated average star rating
92.45%
5.66%
1.89%
The overall position of the product in the category/e-shop
24.53%
75.47%
0.00%
Authority bias
Reviewers' photos
3.77%
92.45%
3.77%
Verified customer/professional review
35.85%
60.38%
3.77%
Evaluation by the e-shop itself
13.21%
86.79%
0.00%
Negativity effect
Number of negative reviews listed
43.40%
52.83%
3.77%
Social proof
Option to like/dislike a specific review or yes/no to a question
about the usefulness of a review
33.96%
62.26%
3.77%
Option to add questions to the product
33.96%
(+1.89% non-
public)
60.38%
0.00%
Apophenia
The date the review was posted appears
84.91%
11.32%
3.77%
Bandwagon and
negativity effect
The positives and negatives of the purchased product are
highlighted
45.28%
50.94%
3.77%
Source: websites of the analysed e-shops; own calculation
In terms of the content of the user reviews themselves, the focus was on eleven specific
elements (Table 2) that may be present in the reviews. Very often, reviewers rated the product
using familiar phrases (up to 73% of reviewers), where the use of these phrases may have a
positive/negative impact on the reader of the review in terms of availability bias. Often
reviews are also written in the form of storytelling (up to 71% of reviewers), where story bias
may influence the reader.
Table 2: Proportion of specific elements in reviews
Cognitive biases
Specific elements examined in the review
Yes
No
Story bias
Stories in reviews
71.13%
28.87%
Von Restorff effect
Visually different reviews
38.66%
61.34%
Availability bias
Familiar phrases in reviews
73.20%
26.80%
Negativity effect
Spelling mistakes
41.54%
58.46%
Negative emotions in reviews
13.85%
86.15%
Negative content reviews
42.05%
57.95%
Humour effect
Positive emotions in reviews
41.54%
58.46%
Processing difficulty
effect
Long reviews (two or more lines)
67.01%
32.99%
Authority bias
Name and surname of the author of the review
20.51%
79.49%
Only the name of the reviewer
43.88% (+2.04%
occasionally)
54.08%
Negativity effect
Unreliable reviews
12.24%
87.76%
Source: websites of the analysed e-shops; own calculation
Our research found that several different cognitive biases affect the reader of a review, both
from the position of the e-shop itself (the possibilities within the UI) and from the position of
the customers who created the review. Realistically, there are certainly many more cognitive
biases within review affecting the reader, but in our research, we have uncovered the possible
effects of analysis paralysis, bandwagon effect, authority bias, negativity effect, social proof,
apophenia, story bias, Von Restorff effect, Availability bias.
Furthermore, the possible influence of cognitive biases in terms of UI and reviews themselves
on the level of popularity of e-shops was investigated. The null hypotheses are formulated as
follows: “Cognitive biases (examined) within UI do not affect the popularity of e-shops”. The
following table presents the results of the investigation.

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Table 3: The effect of cognitive biases in UI on e-shop popularity
Cognitive biases
Web elements examined
Pearson Chi-Square
Value
df
Asymp.Sig.
Analysis paralysis
Showing a certain number of reviews per page
1.598
4
0.809
Bandwagon effect
Indication of the total percentage of customers
recommending the product/Indicated average star rating
4.740
4
0.315
The overall position of the product in the category/e-shop
1.968
2
0.374
Authority bias
Reviewers' photos
4.332
4
0.363
Verified customer/professional review
2.809
4
0.590
Evaluation by the e-shop itself
2.660
2
0.264
Negativity effect
Number of negative reviews listed
1.620
4
0.805
Social proof
Option to like/dislike a specific review or yes/no to a
question about the usefulness of a review
1.510
4
0.825
Option to add questions to the product
5.045
2
0.080
Apophenia
The date the review was posted appears
1.423
4
0.840
Bandwagon and
negativity effect
The positives and negatives of the purchased product are
highlighted
1.873
4
0.759
Source: websites of the analysed e-shops; popularity study on českýkošíkroku.cz; own calculation
Null hypotheses cannot be rejected based on test results. The results show that cognitive bias
within the user interface did not affect the popularity of the e-shops studied. For this reason,
the value of the contingency coefficients is not shown in the table.
The same procedure was also applied to examine the effect of cognitive biases within the user
reviews on the level of e-shops´ popularity. The results (Tab. 4.) show different findings.
Table 4: The effect of cognitive biases in user reviews on e-shop popularity
Cognitive biases
Specific elements examined in the
review
Pearson Chi-Square
Value
df
Asymp.Sig.
Contingency
Coefficient Value
Story bias
Stories in reviews
12.995
2
0.002*
0.251
Von Restorff effect
Visually different reviews
7.344
2
0.025*
0.191
Availability bias
Familiar phrases in reviews
5.383
2
0.068
0.165
Negativity effect
Spelling mistakes
14.685
2
0.001*
0.266
Negative emotions in reviews
4.943
4
0.293
0.158
Negative content reviews
2.968
2
0.227
0.123
Humour effect
Positive emotions in reviews
9.306
2
0.010*
0.214
Processing difficulty effect
Long reviews (two or more lines)
9.938
2
0.007*
0.221
Authority bias
Name and surname of the author of the
review
20.062
4
0.000*
0.307
Only the name of the reviewer
19.841
12
0.070
0.305
Negativity effect
Unreliable reviews
3.071
4
0.546
0.125
Source: websites of the analysed e-shops; popularity study on českýkošíkroku.cz; own calculation
The investigation confirmed the possible influence of cognitive biases in user reviews on e-
shop popularity ratings. It was found that story bias, Von Restorff effect, Negativity effect,
Humour effect, processing difficulty effect and authority bias are the biases that can influence
the perception of popularity. In the case of story bias and processing difficulty effect, these
are also biases that appear very frequently in user reviews. On the other hand, the remaining
mentioned biases affecting the popularity of the e-shop (Von Restorff effect, negativity effect,
Humour effect and authority bias) do not occur in almost every second review, yet they also
influence the popularity rating of the e-shop.
4 Discussion
Interestingly, the results show that many cognitive biases affect consumers, and the less
frequent ones have not been shown to have less of an effect on popularity ratings of the e-
shop, as might be expected. The results confirm previous findings that analysis paralysis has a
significant effect on consumers (Iyengar 2010; Basuroy, Chatterjee and Ravid 2003;
Breugelmans et al. 2012; Chevalier and Mayzlin 2006; Khare, Labrecque and Asare 2011)

2022 Volume XXII(1): 5-21
Acta academica karviniensia DOI: 10.25142/aak.2022.001
14
specifically in our research, it shows a strong effect on e-shop popularity ratings. Companies
appear to be aware of the importance of the brandwagon effect, which was found in more than
90% of the e-shops surveyed, but this effect was found to have only a weak to moderate effect
on e-shop popularity ratings. This may be due to the fact that while this effect is one of the
most important for purchase decisions, within the e-shop popularity it is possible that
consumers perceive it as already standard. Thus, especially in the elements examined, which
were indication of the total percentage of customers recommending the product, indicated
average star rating or information about the overall position of the product in the category/e-
shop. Within authority bias, the mention of verified customer or professional review was
found to be the most significant element. These findings confirm the results of previous
studies (Kreimer 2016; Ngo-Ye and Sinha 2014; Liu and Du 2020) that mentioned that
mentioning ‘verified customer’ or “expert” can influence consumers´ judgement. The results
of the social proof bias show that this effect does not only operate in terms of the number of
interactions received by the reviews (Hilverda, Kuttschreuter and Giebels 2018), but also
significantly influences the opinion on the popularity of the e-shop. The apophenia bias
examined whether the date the review was published appears to have an effect on the
popularity of the e-shop. The assumption was, in line with Jones and Martin (2021) findings
on this bias that people may tend to perceive more recent reviews as better, which may
influence them. This assumption was confirmed as the effect of the date the review was added
on the popularity of the e-shop. An interesting finding is that the negativity effect has a much
greater effect on the popularity rating of an e-shop when it is present in the AI (as the number
of negative reviews listed), whereas within user reviews alone the negativity effect is not
significantly associated with the popularity rating of an e-shop. Perhaps only in the case of
spelling mistakes appearing in reviews can a stronger effect be observed, which shows that
even here negative review sentiment can negatively affect the overall popularity rating of the
e-shop, confirming previous findings on the significance of this cognitive bias (Chen and
Lurie 2013; East et al. 2016; Yang and Unnava 2016; Kim and Hwang 2020). Overall, the
results show that cognitive biases in user reviews have a very weak effect on e-shop
popularity ratings compared to cognitive biases that appear in the UI.
These results need to be interpreted with caution, because this study has its limitations. One of
the limitations of the study is the method used to obtain secondary data. The results of the
heuristic analysis are only partial in nature, typical of basic research. Thus, it is likely that
there are also additional cognitive biases in the text reviews, but these may not have been
present in the given sample of secondary data. Intuition is used in the heuristic analysis, which
could influence the attribution of specific biases for a particular review. Therefore, the authors
of this paper attempted to mitigate this bias problem by creating a set of specific variables that
were assigned to each bias. If these variables were present in a given review, a team member
followed this formula to assign the appropriate type(s) of cognitive bias to that review.
Another limitation is the selection of monitored research items and the research sample. In
this research, 70 e-stores were analyzed after the data cleaning process and reviews were
conducted for 4 selected products each time. The selection of the research sample was not
random as the TOP 100 e-shops on the Czech market were included in the research. For
further research, it would be advisable to examine e-shops also in terms of the product range
sold and expand the sample. This might have revealed the connection between the product
category and the cognitive biases used in it. However, this was not the aim of this research.
The authors of the paper aimed primarily to uncover the cognitive biases that appear in
reviews because in future research they want to focus on the already specific biases that
actually occur and determine their weight in product purchase decisions. To do this, however,

2022 Volume XXII(1): 5-21
Acta academica karviniensia DOI: 10.25142/aak.2022.001
15
the authors of the paper will need to use a different research method that is able to examine
the influence of each bias on consumer behaviour in more depth.
Conclusion
The aim of the paper was to uncover the cognitive biases that attack potential customers in
user reviews and to determine their influence on e-shop popularity ratings. First, various
cognitive biases were described. Then a heuristic method of observing e-shop websites and
analysing the types of cognitive biases was used. The sample consists of the top 100 largest
Czech e-shops. The main object of the research was the product reviews. Two product
categories were chosen on each website. These included mainly the most popular, best-
selling, or most expensive products. Analysed were a total of seven user interface elements
and eleven specific cognitive bias elements that may be present in the reviews.
Only 58 % of TOP 100 Czech e-shops allow their customers to post product reviews. Almost
one third of e-shops does not allow their customers to post product reviews at all, the rest
allows only to rate products with stars or ask questions. The research uncovered which
cognitive biases influence review readers the most and which the least. In terms of the UI, the
most used are bandwagon effect with 92.45 %, apophenia with 84.91 %, and avoidance to
analysis paralysis with 66.04 %. The least used are authority bias (measured by three elements
ranging from 60.38 % to 92.45 %) and social proof (measured by two elements, 30.38 % and
62.26 %). In terms of review´ texts the most used availability bias with 73.2 %, story bias
with 71.13 %, and processing difficulty effect with 67 %. The least used were negativity
effect bias (measured by three elements ranging from 67.95 % to 86.15 %) and authority bias
(measured by two elements, 54.08 % and 79.49 %). Surely, other cognitive biases can also
play a role in customer decision making while reading product reviews in the biggest Czech e-
shops, but this research gives a solid conclusion on which ones are currently used and should
be considered by the consumers.
Moreover, based on the results of our research, we can say that companies cannot influence
the popularity of their e-shop through UI variation, i.e. how they display reviews. This is
because only cognitive biases appearing in the customer reviews themselves can affect the
popularity ratings of an e-shop. Since popularity is an important predictor of customer loyalty,
we recommend that companies focus on promoting specific elements that influence the
popularity of their e-shop with their reviewers. Thus, the answer to the research question is
that the cognitive biases in user reviews that may affect the popularity of an e-shop include in
particular the use of stories in reviews, visually different reviews, removing spelling mistakes,
hinting at positive emotions in the text, longer reviews and inserting first and last names.
Acknowledgement
This paper was supported by the Ministry of Education, Youth and Sports Czech Republic
within the Institutional Support for Long-term Development of a Research Organization in
2021.
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Annex 1 Specifics of the examined e-shops and selected product categories
The name of the
e-shop
Selected subcategories
Selected product
reviews on
the web
The name of the
e-shop
Selected
subcategories
Selected product
reviews on the
web
Astratex
Brassieres
Podprsenka Angelia New
YES
Lidl
Hits of the Week
PARKSIDE® Invertorová svářečka
PISG 120 B3
YES
Podprsenka Maia 4D Soft Control Deluxe
LIVARNOLIVING® Otočný stojan
na boty
Underpants
Brazilky Carole
Fashion
LUPILU® Dívčí softshellová bunda
Brazilky Ester
PEPPERTS® Chlapecké tepláky
Footshop
Sneakers
Raf Simons
YES
Mall
Mobile phone
Xiaomi Redmi 9A, 2GB/32GB,
Global Version, Granite Gray
YES
Adidas ZX
Xiaomi Redmi 9A, 2GB/32GB,
Global Version, Sky Blue
Boots
Filling Pieces
Hobby and garden
Kärcher SE 4001
Timberland
Kärcher Zametací stroj S 4 Twin
(1.766-360.0)
Alza.cz
Mobile phone
IPhone 11 64GB
YES
Marimex
NO, only the
questions section
(public)
Xiaomi Redmi Note 10S
Max-Shop
Mobile phone
Apple iPhone 11 Pro 64GB Midnight
Green
YES
Notebooks
Macbook Air 13 M1
Samsung G525F Galaxy XCover 5
HP Pavilion Gaming 15ec-1900nc
Smart watches
Garmin (010-02174-03) Vivoactive 4
4Home
Bed linen
Bavlněné povlečení Nordic Friends
YES
Apple Watch (MYYH2HC/A) SE
44mm
Krepové povlečení Podzim
Mega Knihy
Fiction
Šikmý kostel
YES
Sheets
Jersey
Má cesta za štěstím - Karel Gott
Jersey Podzim
Listopád
AB-COM.cz
NO
Zuzanin dech
AboutYou
NO
Megapixel
Lens
Nikon 70-300 mm f/4,5–6,3 G AF-P
DX ED VR
YES
akoupelnyatopeni.c
z
Electric Boilers
Protherm kotel RAY 12 KE
YES
Sony FE 85 mm f/1,8
Protherm kotel RAY 9 KE
Camera
Sony Alpha A7 III tělo
Combination toilet bowls
Aqualine JALTA RIMLESS WC kombi
CYESn EOS R6 tělo
-
Megatel
NO
Alfa.cz
NO
Mironet
NO
Answear
NO
Mojekolo
NO, only the
questions section
(public)
Asko Nabytek
NO
Mobil
Pohotovost
NO
Benu
Over-the-counter
medicines
OLYNTH HA 1MG/ML nosní podání
YES
Muziker
Guitar
Elektrická kytara
YES
IBALGIN 400MG potahované tablety
Klasická kytara
Vitamins
MedPharma Vitamín C 1000mg s šípky
studiová beyerdynamic
Preventan Akut
studiová lewitz
Bonami
Seating furniture
Sada 2 koženkových židlí Actona Batilda
YES
NOSICE-
STRESNI.cz
NO
Černá jídelní židle s prvky v dekoru
dubového dřeva Actona Roxby
Notino
Women's perfume
Dior
YES
Sofas and couches
Variabilní pohovka Karup Design Roots
Raw/Light Grey
Lancome
Variabilní pohovka Karup Design Fresh
Natural Clear/Dark Grey
shampoos
Kerastase Paris
Bonprix
Pullovers and sweaters
Bavlněný svetr se stojáčkem
YES
Loreal professionel
vetr z jemného úpletu s výstřihem do V
Obchody 24
Washing machine
LG F4WT
YES
T-shirts and tops
Triko s dlouhým rukávem Rainbow
Bosh Serie 6
Dlouhé boxy triko s krátkými rukávy bpc
Coffee maker
Espresso Krups Esential
Conrad
Acoustic components
Visaton 2913 miniaturní reproduktor
YES
Espresso Bosch Tassimo
Visaton 2912 miniaturní reproduktor
OBI
Building material
Beton Hobby
YES
Smoke detectors
Cordes Haussicherheit CC-80-1
bezdrátový detektor kouře
Portlandský směsný cement
v dané podkategorii už není žádná recenze
Garden furniture
Ochranný obal na stůl a židle
Cycology
Bowden, ropes
Alu koncovka na lanko - 2mm Alligator
LY-IPA03
YES
Box na polstry
Alu koncovka lanka - 1,6mm Alligator
LY-IPA01
Ok Hračky
NO, only the
questions section
(public)
Handles
Kliky ShimYES DEORE FC-M6100
Okay
Mobile phone
iPhone SE 2020
YES
KLIKY SHIMYES ULTEGRA FC-
R8000 2X11SP
Samsung Galaxy A12
CZC.cz
Mobile phone
Samsung Galaxy A52s
YES
Television
Philips 43PUS
Apple iPhone SE 2020, 64GB
Hisense 65U8QF
Tablets
Apple iPad Air 2020 (4. gen.), 10,9",
64GB
Online-sport.cz
Option to add a
review exists, but
no review is on the
site
Samsung Galaxy Tab A7 T500N,
3GB/32GB
Onlinekoupelny
NO
Datart
Television
Televize LG OLED65CX
YES
ONLINESHOP
Washing machines
AEG ProSteam
YES
Televize Samsung QE55Q77TA
Beko HDF7 Slim
Video equipment
Set-top box GoGEN DVB 272 T2 PVR
černý
Food processor
Eta Gratussino Bravo
Set-top box Tesla TEH-500 PLUS
Bosh Mum
Decathlon
Women's T-Shirts
DÁMSKÉ BĚŽECKÉ TRIČKO RUN
DRY RŮŽOVÉ KALENJI
YES
Originalky
NO
DÁMSKÉ FITNESS TRIČKO ZE 100%
BAVLNY BÍLÉ NYAMBA
Elnino
Women's perfume
Enrique Iglesias Deeply Yours
YES
Women's hoodies and
sweaters
DÁMSKÝ TURISTICKÝ HYBRIDNÍ
SVETR NH 100 ŠEDÝ QUECHUA
Guess Seductive
DÁMSKÁ TURISTICKÁ FLEECOVÁ
MIKINA MH 520
Aftershave
Hugo Boss Boss Bottled
Decodoma
Linen
Ložní rodinná souprava z mikrovlákna
HILDY
YES
Giorgio Armani Acqua
Ložní rodinná souprava z mikrovlákna
MEADOW
Peddy
NO, only the
questions section
(public)
Tension covers
Antibakteriální bielastické potahy
SANITIZED
Pekro
NO, only the
questions section
(public)
Bielastické potahy BRILLANTE
Penzo
NO
Detske Kocarky
Option to add
a review
exists, but no
review is on
the site
Pilulka
Over-the-counter
drugs
Paralen 500
YES
Dobreelektro
Pre-filled washing
machines
Pračka Beko WRE6612CSBSW
YES
Wobenzym
Pračka Beko WRE6511BWW
Drugstores
Perlan 45g
Tumble dryers
Sušička Beko EDS7434CSRX
Batist vložky porodnické

2022 Volume XXII(1): 5-21
Acta academica karviniensia DOI: 10.25142/aak.2022.001
20
Sušička Beko DPS7405GB5
PNEUMATIKY
winter tyres
Barum Polaris 5
YES
DOMACITECHNI
KA.cz
NO, only the
questions
section
(public)
Continental Winter Contact TS 860
Dr.Max
NO
summer van tyres
Continental Van Contact
Eberry
NO, only
questions
section (non-
public)
Nokian cLien Van
Electronic Star
Fryers
AeroVital Deluxe horkovzdušná fritéza
YES
Profizoo
Dogs
PROFIZOO Ucho vepřové sušené
volně 1ks
YES
VitAir Turbo horkovzdušná fritéza
BRIT Premium Dog Adult L 15 kg
Coffee Machines
Espressionata Gusto espresso kávovar
Cats
Bayer Foresto obojek pro malé psy do
8kg 38cm
Passionata 20 kávovar
WHISKAS s hovězím masem 14kg
Electroworld
Laptops
Apple MacBook Air 13" M1 256 GB
(2020) MGN63CZ/A
YES
Prozdravi
Detoxification of the
organism
Aloe Vera gel 1000 ml
YES
ASUS VivoBook 14 M415DA-EK341T
stříbrný
MycoBaby dračí sirup 200 ml +
pastelky ZDARMA
Monitors
Philips 243V7QDSB
Acidification of the
organism
pH Mineral Balance 60 tablet
LG 24TN510S-PZ
pH Minerals na odkyselení organismu
320 g
Elektrocz
Washing machines and
dryers
AEG L8WBE68SI
YES
Kola Šilhavý -
RAMALA
NO
Electrolux EW7W368SI
roboticky-
vysavac.cz
Robotic vacuum
cleaners
iRobot Roomba 975 WiFi
YES
Refrigerators
Bosch KGN39XIDQ
iRobot Roomba 676 WiFi
Bosch KGE36AWCA
Stick vacuums
BOSCH BBH32551
Elektrospecialista
NO, only
questions
section (non-
public)
BOSCH BBHF214G
Eobuv
Women's Running Shoes
Boty NIKE - Revolution 5 BQ3207 002
Black/White/Anthracite
YES
Siko
Shower Panels
panel SIKO na stěnu černá/chrom
ALUSHOWERC
YES
Boty MERRELL - Vapor Glove 3 Luna
Ltr J003422 Black/Charcoal
SIKO Bamboo Shower
BAMBOOSHOWER
Women's Fitness Shoes
Boty PUMA - St Activate 369122 20
Castlerock/Puma White
Faucets
S-Line Pro termostatická 150 mm
chrom SIKOBSLPRO268T
Boty SKECHERS - Graceful Moves
128258/BKW Black/White
S-line Pro termostatická 150 mm
chrom SIKOBSLPRO222T
Eoshop
NO, only
questions
section (non-
public)
Smartronix
NO
EUC Lékárná
NO
Smarty
Apple products
Apple AirPods bezdrátová sluchátka
(2019) bílá
YES
Euronics
Front-loading washing
machines
Pračka AEG ProSteam® L7FEE48SC
bílá
YES
Apple MacBook Pro 13,3" / M1 / 8GB
/ 256GB / vesmírně šedý
Pračka AEG ProSteam® L7FBE69SCA s
funkcí AutoDose bílá
Mobile phone
Xiaomi Redmi Note 10 Pro
6GB/128GB Onyx Gray
Top-loading washing
machines
Pračka AEG ÖKOMix® LTX8C373C
bílá
Realme 7i DualSIM 4/64GB Glory
Silver
Pračka AEG ProSteam® LTX7E272C bíl
SpokojenýPes.cz
Dog food
Marp Holistic Lamb Grain Free 2 kg
YES
EUROPARFÉMY
Perfumed lotions
Lanvin Éclat D´Arpege
YES
Marp Natural Green Mountains Lamb
12 kg
Karl Lagerfeld Karl Lagerfeld For Her
Granules for cats
Marp Holistic Chicken Cat 2 kg
Eau de Toilette
Calvin Klein CK One
Essential Foods Jaguar 3 kg
HUGO BOSS Boss Bottled
Sportisimo
T-Shirts
Lotto CHRENIA
YES
Eva.cz
NO
Puma INDIVIDUAL RISE JERSEY
ExaSoft
NO
Shoes
adidas GRAND COURT
Expert
NO
(individual
reviews
cannot be
displayed,
only the
overall star
rating)
Lotto SET MATCH AMF INF SL
Fepro
NO
(individual
reviews
cannot be
displayed,
only the
overall star
rating)
SportObchod
Cycling
Střešní nosič kol Thule FreeRide 532
YES
Fitham
NO, only the
questions
section
(public)
Střešní nosič kol Thule ProRide 598
Hornbach
Washbasins
Umyvadlo Cersanit MITO 60x45 cm
YES
Tennis
Tenisové míče Head Tour (4 ks)
Umývátko Tarn přírodní kámen 40x23x11
cm
Tenisové míče Wilson US Open (4ks)
TOILETS
WC kombi Grand s úspornou armaturou
Suntech
NO
WC kombi Grand MK43894
Svářečky-
Obchod.cz
CO2 WELDERS
(MIG-MAG)
KOWAX GENIMIG 220
MIG/MAG,MMA + HOŘÁK +
KABELY + VENTIL + KUKLA
YES
Imobily
Option to add
a review
exists, but no
review is on
the site
KOWAX GENIMIG 220 + HOŘÁK
4M, KABELY 3M, VENTIL,
KUKLA, SVAŘOVACÍ DRÁT,
SPREJ, PODVOZEK, LÁHEV CO2
PLNÁ
Insportline
NO
Plasma cutters
SCHEPPACH PLC 40 PLAZMOVÁ
ŘEZAČKA
iStage
NO
VECTOR PARIS 700 PLASMA
PILOT + HOŘÁK PLASMA
Jysk
Bedrooms - wardrobes
Skříň DAMHUS 60x150 tmavě šedá
YES
Tchibo
NO
Skříň HAGENDRUP 96x176 kombi buk
Tescoma
Home food
preparation
Souprava pro kvašení TESCOMA
DELLA CASA 5000 ml
YES
Bathroom - bathroom
equipment
Dávkovač mýdla ROSENLUND
Závaží pro kvašení TESCOMA
DELLA CASA, 3 ks
Miska na mýdlo MALA šedá plast
Knives
Nůž univerzální AZZA 13 cm
K24
NO
Nůž univerzální AZZA 9 cm
Kamody
Top Selling Products
2020 by Consumer
VILEDA TURBO mop 151153
YES
Teshop
NO
GARDENA Pipeline vodní zásuvka, 3/4"
8250-20
Tipa
NO
Den Braven Mamut Glue, High Tack
lepidlo 290 ml, bílá, 0411RL 1173
T.S.Bohemia
NO
Fiskars X25 - XL Sekera štípací 72 cm,
2400 g (122483) 1015643
Velko Pneu
NO

2022 Volume XXII(1): 5-21
Acta academica karviniensia DOI: 10.25142/aak.2022.001
21
Kasa
Large household
appliances
Sušička prádla Bosch WTW87467CS bílá
YES
Vestavné
spotřebiče.cz
Built-in ovens
WHIRLPOOL AKP 244/IX
YES
Pračka AEG ProSteam® L7FEE48SC
bílá
WHIRLPOOL AKP 449/IX
Small Home Appliances
Espresso Krups Arabica EA811010 černé
SIEMENS EH645FFB1E
Tyčový vysavač Rowenta DUAL FORCE
2 V 1 RH6751WO modrý
SIEMENS EH651FFC1E
Knihy Dobrovský
Bestsellers
Má cesta za štěstím - Karel Gott
YES
Zoot
NO
Šikmý kostel
Kytary
Option to add a
review exists, but
no review is on the
site
Pozvaní
L-E
Option to add a
review exists, but
no review is on the
site
Listopád
Lekarna
(Lékárna.cz)
Dietary supplements
and vitamins
GS Vitamin C 1000 se šípky 120
tablet
YES
Kobras
NO
GS Vápník Hořčík Zinek PREMIUM
s vitaminem D 100+30 tablet
Kosmas
Readers recommend
Zuzanin dech
YES
Over-the-counter
medicines
PARALEN 500 mg 24 tablet
0 Tu, svazek první
IBALGIN 400 mg 100 potahovaných
tablet
Dlouhá trať
Kuma
NO
Šikmý kostel