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Which kinds of online reviews predict the online purchase
behavior？
Jinghuan Zhang†
Shandong Normal
University
Jinan, China
zhangjinghuan@126.com
Wenfeng Zheng
Shandong Normal
University
Jinan, China
zwf19_94@163.com
Yukang Su
Shandong Normal
University
Jinan, China
113673610@qq.com
Xiaoye Xu
Shandong Normal
University
Jinan, China
136325344@qq.com
ABSTRACT
As the continuous growth of online shopping, the massive data
behind this are valuable sources for website to study and adjust
marketing strategies. Therefore, it is of great significance to
scrutinize the consumers ’purchase behaviours and the related
factors that have major effects on purchase intention or behaviour.
This study analysed 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 behaviour. The results showed that: (1) in the laboratory
setting, the online purchase intention was greatly affected by the
online reviews and the interaction between the reviews and the
product types. In particular, the purchase intention was higher
presented with positive reviews than negative ones, especially for
experiencing products. Furthermore, stronger purchase intention
was found for experiencing goods with lower risk perception and
positive reviews. (2) For the real online transaction data,
interestingly, the positive reviews had no effects on purchase, but
the neural/negative reviews may negatively affect the purchase
behaviour for products with higher risk perception. In addition,
these findings were discussed from theories and practice
perspectives respectively.
CCS CONCEPTS
• Social and Professional topics • Professional
topics • Computing and business
KEYWORDS
Online reviews, Product types, Risk perception, Online purchase
behavior
ACM Reference format:
Jinghuan Zhang, Wenfeng Zheng, Yukang Su and Xiaoye Xu.
2019.Which kinds of online reviews predict the online purchase behavior?
The 4th International Conference on Crowd Science and
Engineering(ICCSE’19), ICCSE’19, Jinan, China, 8 pages.
1 Introduction
China has witnessed the extraordinarily rapid development of
Internet since the 21st century. Retail network emerged and
developed in such a context, which has an important impact on the
future of e-commerce business models. For consumers, shopping
on the Internet this new shopping channels have increasingly
reflected the concern and interest in expanding online shopping.
Because it will give consumers a tremendous advantage to: break
time and space constraints, shopping convenience, and so on,
which in turn contributes to the rapid development of online
shopping. The transformation of consumption mode from
traditional to online and offline integration. And online purchase
behavior becomes one of the important research topics.
In the era of Web 2.0, customers increasingly post online reviews
of products or services on the Internet. These online reviews
contain a wealth of information, such as customers’ concerns and
opinions, which are valuable for managers and researchers to
understand customer purchase behavior. The number of online
reviews is very large and these reviews are contributed by
hundreds of thousands of customers. Thus, online reviews can
serve as a promising data source to predict online purchase
behavior. As the consumers cannot feel the commodities and get
the purchased commodities as offline shopping does when
conducting shopping online, they will feel the higher risks of
purchase commodities more than offline shopping[8]. Therefore,
the researchers noted that risk perception is also a psychological
variable that affects consumer purchase behavior[6]. A related
question is different types of goods have different attribute,
whether it will influence consumer purchase behavior together
with risk perception？
The study has attempted to explicitly or implicitly understand
customer purchase behavior from online reviews. The majority of
these studies can be divided into two categories, using
This material is based upon work supported by, or in part by, China’s National Key
Research and Development Project 2017YFB1400102.
†Correspondence should be sent to Jinghuan Zhang, Department of Psychology,
Shandong Normal University, No.88 East Wenhua Road, Jinan, 250014, China.
E-mail: zhangjinghuan@126.com
Permission to make digital or hard copies of part or all of this work for personal or
classroom use is granted without fee provided that copies are not made or
distributed for profit or commercial advantage and that copies bear this notice and
the full citation on the first page. Copyrights for third-party components of this
work must be honored. For all other uses, contact the authors.
ICCSE'19, October, 2019, Jinan, China
© 2019 Copyright held by the owner/author(s).978-1-450 3-7640-2/19/10...$15.00
140
DOI: 10.1145/3371238.3371260
ICCSE'19, October, 2019, Jinan, China
J. Zhang et al.
questionnaires and basing on big data. Questionnaires were used
to explore the mechanism of the usefulness, credibility and risk
perception of online reviews on their purchase behaviors.
However, due to the subjective limitations of the respondents on
comments and risk perception, the data and analysis results
obtained by this method are deviation from the real experience.
Therefore, it is worthwhile to consider using the big data to
understand customer purchase behavior. 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 behaviour.
1.1 Purchase behavior
Purchase intention is the subjective probability or possibility that
a consumer will buy a particular product or brand, and has been
proposed as a predictor of subsequent purchasing [7]. And
intention has been determined as a salient predictor of actual
behavior to shop online.Under online shopping context,
quantitative study on how online reviews affect consumer
purchase behavior can be transformed into research on how online
reviews affect the commodity volume and sales [5]. A study about
online reviews of the movie industry found that it is feasible to
measure total consumer purchase by the movie's box office
revenue [6]. Therefore, product sales are used to measure the
purchase behavior of the overall consumer group in this paper.
1.2 Online reviews
An online review is a positive, neutral or negative statement,
which is created by a future, actual, or former consumer about a
product 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. But 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[6]. Consumers tend to observe the proportion
of positive and negative online reviews as well. The more positive
reviews lead to the stronger purchase intention [32]. However,
consumers place greater emphasis on negative information in
deciding to purchase [13]. 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 product rises. When a
potential consumer is exposed to a large number of negative
online reviews, a negative expectation of the product is formed
[16]. Based on the existing studies, this work will further explore
the impact of online reviews (positive/neutral/negative) on
purchase behavior.
1.3 Products types
There are copious product classifications associated with online
reviews. A frequently used classification is that of search and
experience products, which is used by researchers to evaluate
consumer purchase intention [9]. A search product is one where
information on product attributes is easily obtained by consumers
without having to make a purchase in advance [17]. Therefore, the
information obtained in a search product is usually objective and
easily compared with other similar products, cameras, cell phones,
and computers being common examples [20]. On the other hand,
an experience product is a product whose attributes are difficult to
obtain. Consumers frequently want to feel and experience the
product prior to any assessment. Thus, information pertaining to
these products is mostly subjective, and evaluations conducted are
based on previous experience [17]. Typical examples of
experience products are hotels, airlines, restaurants, and other
services [21]. Consumers behave quite differently when looking
for information on these two types of products: they tend to seek
more information on other reviews concerning an experience
product than on a search product [14]. However, some studies
have pointed out that consumers are more dependent on the
information provided by online reviews when purchasing search
products [2]. The results of previous studies on the relationship
between product types and purchase intention are not consistent.
Therefore, this study would explore how product types affect
purchase behavior in the real online shopping context.
1.4 Risk perception
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. Bauer first introduced the perceived risk concept to
consumer behavior research in order to explain such phenomena
as information seeking, brand loyalty, opinion leaders, reference
groups and pre-purchase deliberations [1]. Perceived risk is a
fundamental concept in consumer behavior that implies that
consumers experience pre-purchase uncertainty as to the type and
degree of expected loss resulting from the purchase and use of a
product [23]. According to the S-O-R theory, consumers will be
stimulated externally when they shop on the Internet, which will
change consumers' psychology and perception and then affect
their purchase behavior. Among them, risk perception is the most
influential factor. Perceived risk determined the consumer ’s
attitude toward online purchase, which subsequently affected
willingness to purchase and actual purchase behavior [30].
Previous studies have found that risk perception is negatively
correlated with purchase intention [30]. The traditional inventory
used to measure perceived risk will not be applicable to measuring
Internet consumer's perceived risk. Studies have pointed out that
shopping risk perception of consumer network refers to
consumers' perception and judgment of possible adverse
consequences brought by their shopping behaviors in the process
of shopping network. Online shopping consumer's perceived risks
consist of five dimensions: perceived store-opportunism risk,
perceived product-performance risk, perceived financial risk,
perceived delivery risk, and perceived privacy risk [29]. 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 [29]. Therefore,
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J. Zhang et al.
this study aims to explore how network risk perception influences
purchase behavior in the network shopping context.
2 Empirical study
2.1 Study 1 The influence of consumer reviews and
product types on online purchase intention
2.1.1 Purpose
The purpose of this research is to analyze the role of consumer
online reviews and product 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% 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 (Product types: search
product/experience product) 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 audio as search products, and clothing,
facial cleanser and shoes as experience products. In order to avoid
the influence of brand, price and other factors on subjects'
perception, the experimental materials only present the positive
and negative proportion of product reviews. Among them, the
material of high ratio of positive reviews’ group presented that:
Supposing you want to buy a product, 73% of consumers gave the
product positive reviews, and 27% 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 product, 73% of consumers
gave the product negative reviews, and 27% gave the product
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 product. Then the subjects were presented the information
of product 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 (2012).
Participants rated the way they felt on a 7-point Likert scale
ranging from 1 = very little to 7 = a great extent. Cronbach's alpha
for this scale was .95.
2.1.3 Results
We performed statistical analyses with online reviews and product
types as the independent variables, the dependent variable as
consumer purchase intention. The results are shown in Table 1.
Table 1. Descriptive Statistics (M±SD).
SP
EP
Total
PR
3.53±0.6（n=30）
4.01±0.74（n=30）
60
NR
1.72±0.8（n=30）
1.51±0.79（n=30）
60
Total
60
60
120
Note. PR means high ratio of positive online reviews; NR means high ratio
negative online reviews; SP means search product; EP means experience
product.
The results of non-repeated measures Anova ( table 2) shows that,
the main effect of online reviews was significant ( F(1,116) =
238.14, p< 0.001, ηp²= 0.67); and the main effect of product
types is not significant,( F(1,116) = 0.91, p> 0.05, ηp²= 0.01).
The integration between online reviews and product types is
significant positively influence purchase intention. (F (1,116)
=5.93，p<0.05，ηp²=0.05).
Table 2. Analysis of variance of online reviews x product types
on purchase intention.
Source of variation
III Sum of square
df
MS
F
Correction Model
143.91
3
47.97
81.66***
Interception
869.57
1
869.57
1480.27***
OR
139.89
1
139.89
238.14***
PT
0.53
1
0.53
0.91
OR×PT
3.48
1
3.48
5.93*
Error
68.14
116
0.58
Total
1081.62
120
Adjusted total
212.05
119
Note. OR means online reviews; PT means product types.
According to the results of simple effect analysis (Fig. 1),
there is a significant difference between the online purchase
intention of search products and experience products in the
context of high ratio of positive online reviews (p<0.05), and the
purchase intention of experience products is significantly higher
than that of search products. No significant difference was
found in purchase intention between search products and
experience products (p>0.05) in high ratio of negative online
reviews.
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J. Zhang et al.
Fig.1. The interaction among of online reviews and product types
on consumer purchase intention.
Study 1 found that online reviews and product types provided a
significant association with online purchase intention. In the
context of high ratio of positive review, the online purchase
intention of experience products is significantly higher than that
of search products. There is no significant difference in purchase
intention between search products and experience products 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 [3][31]. Risk perception as
an important psychological variable that affects consumer
purchase behavior, has been widely concerned by researchers [6].
Therefore, study 2 will focus on the impact of risk perception on
online purchase intention of experience products.
2.2 Study 2 The influence of risk perception on
online purchase intention of experience products
2.2.1 Purpose
Firstly, the purpose of this research was to examine the influence
of online reviews on purchase intention of experience products 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 products.
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% 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 products as study 1. Three
decision-making tasks are used in this study. They are described
in 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% of the consumers gave
high ratio of positive online reviews to this product. 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 product. 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 3.
Table 3. Descriptive Statistics (M±SD).
LP
HP
Total
PR
4.80±0.59（n=30）
3.76±0.44（n=30）
60
NR
1.94±0.87（n=30）
1.76±0.67（n=30）
60
Total
60
60
120
Note. PR means high ratio of positive online reviews；NR means high ratio of
negative online reviews; LP means low risk perception ；HP means high risk
perception.
The results of analysis of variance for non-repeated measures
(table 4) shows that, the main effect of online reviews was
significant (F (1,116) = 399.78，p<0.001，ηp²=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. And
the main effect of risk perception is significant, (F (1,116) =25.18
，p<0.001，ηp² = 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.
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J. Zhang et al.
Table 4. Analysis of variance of online reviews, risk perception
on purchase intention.
Source of variation
III Sum of square
df
MS
F
Correction Model
193.54
3
64.51
145.86***
Interception
1127.85
1
1127.85
2549.94***
OR
176.82
1
176.82
399.78***
RP
11.13
1
11.14
25.18***
OR×RP
5.585
1
5.58
12.63**
Error
51.31
116
0.44
Total
1372.70
120
Adjusted total
244.85
119
Note. RP means risk perception ; OR means Online reviews.
According to the results of simple effect analysis, to investigate
the influence of online reviews on the online purchase intention of
experimental products under different risk perception situations.
The result shows that (Fig. 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).
Fig.2. The interaction among of online reviews and risk
perception on consumer purchase intention.
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
products 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 products
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 shopping network context, a new risk perception is
generated which is not available in traditional shopping context.
The perceived risk in traditional purchase context obviously
cannot 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
explore the influence of the relationship between product types,
risk perception, online reviews and online purchase behavior in
the online shopping context.
2.3 The influence of reviews, risk perception and
product types on purchase behavior in online
shopping context
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
products.
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 products and 300 experience products on Taobao.com
in December 2018. The selection of product types and specific
content is 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 products. After assigning values to online
reviews, product sales volume and risk perception, SPSS and
MPLUS were used to analyze the data.
2.3.2.2 Variable measurement:
Online reviews: The present study separately calculated the
proportion of the positive online reviews, neutral online reviews,
and negative online reviews of 590 products in the total. Among
them, the proportion of positive online reviews is 92.55%-100%,
the proportion of neutral online reviews is 0-3.46%, and the
proportion of negative online reviews is 0-4.57%. Then five
points are scored for each product's three types of online reviews,
and the relationship between online reviews and purchase
behavior is analyzed.
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J. Zhang et al.
6
Online purchase behavior: The monthly sales volume of
Taobao.com at the end of December 2018 was taken as the
measurement of consumer online purchase behavior of the
product. Then, the sales volume of the product 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’.
Risk perception: After buying each product, customers need to
give star ratings about logistics and services. Star rating range
from one to five stars. Five stars are the best and one star is the
worst. The risk perception score of the product is the average of
logistics and service score of each product. The higher score
means the lower the risk perception of the consumer.
2.3.3 Result
2.3.3.1 Descriptive Statistics and bivariate correlations
Table5. Descriptive Statistics and bivariate correlations (N=590).
Variable
1
2
3
4
5
6
1 PT
—
2 PR
-0.06
3 NOR
-0.25**
-0.06
4 NR
-0.20**
-0.08
0.78***
5 PB
-0.23**
-0.07
-0.13**
-0.12**
6 RP
-0.11**
-0.01
0.22***
0.21***
-0.74***
1
M
—
3.94
1.14
1.07
1.92
3.11
SD
—
1.14
0.51
0.34
1.03
0.96
Note. PT means product types; PR means positive online reviews; NOR means
neutral online reviews; NR means negative online reviews; PB means online
purchase behavior; RP means risk perception.
The results are shown in Table 5. 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. Since 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 product type.
Firstly, MPLUS is used to analyze the moderating effect of risk
perception and product type. The results (Table 6) showed that
risk perception significantly negatively predict purchase behavior
(B=-1.08, SE=0.10, p<0.001). The neutral online reviews
significantly negatively predict purchase behavior (B=-0.76,
SE=0.35, p<0.05). Our results didn’t show the significant
relationship between the negative online reviews and purchase
behavior (B=-1.04, SE=0.56, p>0.05),and the relationship
between product type and purchase behavior was not significant
(B=-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 (B=0.22, SE=0.08, p<0.01;B=0.26, SE=0.13, p<0.05).
However, the influence of interaction items of risk perception,
product type and the negative online reviews, the neutral online
reviews on purchase behavior is not significant, so the moderating
variable of product type is no longer analyzed.
Table 6. The moderating effect of risk perception, product types.
PB
B
SE
P
NOR Model
RP
-1.08
0.10
<0.001
PT
-0.35
1.57
>0.05
NOR
-0.76
0.35
<0.05
NOR×RP
0.22
0.08
<0.01
NOR×PT
0.33
1.55
>0.05
NOR×RP×PT
0.04
0.48
>0.05
NR Model
RP
-1.07
0.13
<0.001
PT
-0.02
3.92
>0.05
NR
-1.04
0.56
>0.05
RP×NR
0.26
0.13
<0.05
PT×NR
0.02
3.92
>0.05
RP × PT×NR
0.04
1.18
>0.05
Note. NOR means neutral online reviews; NR means negative online reviews;
RP means risk perception; PT means product types; NR means negative online
reviews; PB means online purchase behavior.
In order 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 (Fig. 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 didn't 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).
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J. Zhang et al.
Fig.3. The moderating effect of risk perception on the neutral
online reviews, the negative online reviews and purchase
behavior.
3. Discussion
3.1 The relationship between online reviews and
purchase behavior
In the online shopping context, it is found that the reviews had
significant impact on the purchase intention, and the purchase
intention of products with high ratio of positive online reviews is
significantly higher than that with high ratio of negative online
rewards, which is consistent with the previous research conclusion
[15][29][32].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 product based on the online
reviews of buyers. In the process of impression formation and
evaluation, more attention is paid to the negative side [19]. Study
indicates that negative ratings carry a much stronger effect than
positive ones on a buyer's trust level [25]. Negative online reviews
are viewed as an important source of information enabling online
buyers to assess the quality of products/services. An important
function of reviews is to reduce the risk and uncertainty that
online buyers perceive relating to the product [28]. 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 attempts they are trying in order 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 [22]. 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 Relationship between product types, risk
perception and online purchase behavior
In the simulation of online purchase behavior, it is found that the
main effect of product type is not significant, the interaction
between online reviews and product type is significant, and the
purchase intention of experience products is significantly higher
than that of search products in the situation of high ratio of
positive online rewards. Under the situation of high ratio of
negative online rewards, there is no significant difference in
purchase intention between search products and experience
products. Researchers believe that in terms of product attributes,
the description of search products is clearer, and consumers less
rely on the reviews from buyers. Experience products require
consumers to perceive the attributes of products in the process of
use, so consumers are more likely to expect recommendations and
suggestions from others and rely more on the reviews of buyers
when buying experience products [11]. In addition, the interaction
between risk perception and online reviews will affect the
purchase intention of the subjects. Under the circumstance of high
ratio of positive online rewards, the purchase intention under low
risk perception is significantly higher than that under high risk
perception. In the high ratio of negative online review situation,
there is no significant difference in the influence of risk
perception level on purchase intention. This study comes to the
conclusion that risk perception cannot affect the relationship
between negative online reviews and purchase intention. When
subjects are faced with products with high ratio of positive online
rewards, their purchase intention will be directly affected by the
negative online rewards, but not by the level of risk perception.
In the real shopping network context, it is 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.
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J. Zhang et al.
According to Prospect Theory [24], when consumers are faced
with risks and uncertainties, they will reduce shopping risks
through a series of information search behaviors. When
consumers see the neutral and negative online reviews of products,
they will selectively pay attention to them, while they are more
sensitive to neutral and the negative online rewards. The more
negative online reviews that customs receive, the greater the
perceived risk of consumers will be, and the greater the impact on
purchase behavior [25].
3.3 Practical significance and deficiencies
The conclusion of this paper can help sellers to grasp the
importance of online reviews, correct deficiencies timely and it
provides a reference for the adjustment of marketing strategy. At
the same time, sellers can generate more consumer purchase
behaviors by improving the speed of logistics, improving service
attitudes, and solving consumer concerns about products.
There are limitations in this study. First, as this was a
cross-sectional survey, the ability to determine causal
relationships among the study variables is limited. Future
researchers could use a longitudinal design to examine the validity
of these relationships. Second, consumer's age, income and other
information have not been further analyzed, which made the
generalizability of our results to other segments of the population
is limited. Future researchers could explore more details based on
big data.
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