This document analyzes the dimensions of consumers' perceived risk and how they influence online purchasing behavior. It discusses previous research on perceived risk dimensions. The study aims to identify the key dimensions of perceived risk for the overall B2C e-commerce process, and examine how these dimensions impact online purchasing behavior. The study develops hypotheses about 8 dimensions of perceived risk and their influence on purchasing behavior. It presents a research model and methodology using a survey to collect data from 388 online consumers in China. Exploratory factor analysis identified 8 dimensions of perceived risk from the survey data that could analyze types of perceived risk for the overall B2C process. These dimensions and their impact on purchasing behavior are empirically tested.

1. Communications in Information Science and Management Engineering CISME
Dimensions of Consumers’ Perceived Risk and Their
Influences on Online Consumers’ Purchasing
Behavior
Lingying Zhang1, 2, Wojie Tan3, Yingcong Xu1, Genlue Tan1
1
College of Management, Shenzhen University, Shenzhen 518060, China
2
Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518000, China
3
Normal School, Shenzhen University, Shenzhen 518060, China
1
zly2009@gmail.com; 3tanwj2011@163.com
Abstract-Consumers’ perceived risk is an important factor that In this paper, firstly, we discussed the perceived risk
affects online consumers’ purchasing behavior. In this paper, the dimensions impact on consumer online shopping
first empirical research was about the dimension structure of decision-making and analyzed the composition of online
consumers’ perceived risk (CPR) for the overall process of B2C shopping consumer perceived risk. Based on investigation
E-Commerce, and eight dimensions of consumers’ perceived risk
were ascertained by confirmatory factor analysis, i.e. perceived data, eight perceived risk dimensions which have significant
health risk, perceived quality risk, perceived privacy risk, impact on consumer online shopping decision-making are
perceived economic risk, perceived time risk, perceived social verified and proposed. Secondly, we empirically tested what
risk, perceived delivery risk and perceived after-sale risk. Then, risk factors from the overall process of B2C may really cause
perceived risk dimensions affecting consumers’ purchasing consumers’ perceived risks and examined what dimensions of
behavior and their structural relationships were investigated perceived risks significantly influenced consumers’
through a consumer survey and statistical analysis using the purchasing behavior in the overall process of B2C.
methods of confirmatory factor analysis and structural equation
model. The results of empirical testing demonstrate that there II. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT
are five independent dimensions, perceived health risk, perceived
quality risk, perceived time risk, perceived delivery risk and The original concept of perceived risk is extending out
perceived after-sale risk which affect significantly online from the psychology by Harvard University Raymond A.
consumers’ purchasing behavior. The results also show that the Bauer [7]. The dimensions of perceived risk are the specific
other three dimensions, perceived privacy risk, perceived social contents or types of perceived risk. Bauer [7] held that the
risk and perceived economic risk are the less relevant factors. perceived risk will affect the consumer’s purchase decision,
Ke ywords- Risk Dimensions; Perceived Risk; Shopping Online; but he didn’t analyze the perceived risk’s specific types.
Consumers’ Purchasing Behavior; Overall Process of B2C Followed Bauer’s theory, Cox and Rich [8] gave the specific
explanation of perceived risk. He believed that the perceived
I. INTRODUCTION risk included at least two factors, uncertainty and adverse
The analysis for dimensions of consumer perceived risk in consequences. Following the theory of consumers’ perceived
online shopping is a necessary step to know the contents and risk, consumers will perceive risk when they face uncertainty
types of consumer perceived risk, which is considered to be and potentially undesirable consequences as a result of
one of the important factors that impact on consumer online purchase [9, 10].The more risk consumers perceived, the less
shopping decision-making, and it is also one of the important likely it is that they will make a purchase. Therefore,
research theme for the online shopping risk [1][2]. Previous Perceived risk is powerful at explaining consumers’ behavior
researchers focused on the risks in the phase of online because “consumers are more often motivated to avoid
transactions, some of them put forward the structure of risk mistakes than to maximize utility in purchasing” (Mitchell
dimensions in different perspectives such as the lack of security, [11]).
privacy risk, the credibility of online retailers or reliability risk
[3][4], functional risk, shopping risk, time risk, social risk, A. Dimensions of Consumers’ Perceived Risk and Their
psychological risk and so on [5][6]. Influences
The overall process of B2C includes three phases such as Previous researchers have proposed many dimensions of
information searching before buying, the choosing of products perceived risk from different perspectives. Mitchell [11,12]
showed that consumer perceived different levels of risk at
and the service after purchasing. Therefore, the consumer’s
every stage in the shopping process and proposed the five
perception of risk in every phase of the overall process should
evaluation criteria for the model of perceived risk:
be considered, and so does the influence.
understandability, predictability, reliability and effectiveness,
In this context, taking into consideration the different risk practicality and availability. Anne-Sophie [13] studied the
facets in every phase of the overall process of B2C, the four sources of risk such as product, remote transaction, the
present study attempts to analyze the perceived risk in the Internet and website risks, proposed eighteen strategies about
overall process of B2C and their influence on online how to reduce the perceived risk, and his empirical results
consumers’ purchasing behavior. This study seeks to showed that secure payment, money-back guarantee and
incorporate these dimensions of perceived risk into a research product replacement are the top three risks which will affect
model, identify their impact on online consumers’ purchasing the consumer decision-making. After qualitative exploration,
behavior, and test the relationships between constructs in the Dong, Li, and Yang [14] proposed four dimensions of
overall process of B2C. perceived risk. Sun, Zhang, and You [15] proposed the
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sources of risk which had larger impact on consumer online shopping. Chen and Li[26] built four structural
perceived risk, and verified there were seven dimensions of equation models to measure six dimensions of perceived risk
perceived risk. Based on the traditional six dimensions, Yu, and their influences on consumer purchase intention. Herrero
Dong, and Liu [16] added another four dimensions such as Crespo, Rodrı´guez del, Bosque, and Garcı´a de los Salmones
services, payment, delivery, and privacy risk. Sa´nchez [5] studied the perceived risk that would influence
In E-commerce, perceived risk is often considered as a consumer’s attitudes and willingness for online purchasing.
perception for a natural characteristic of B2C by many Before our exploring tests for the structure of dimensions
consumers [17, 18]. Greater perception of risk on the part of of perceived risks in the overall process of B2C and their
consumers acts as a deterrent to their purchase intentions. influences on consumer purchasing behavior in our following
Several authors have observed that the perceived risk in studies, we analyzed all the risk variables related to the
e-commerce has a negative effect on shopping behavior on overall process of B2C E-Commerce, especially in the phases
the Internet [19], attitude toward usage behavior [20, 21, 22] of searching information before purchasing and after-sale
and intention to adopt E-commerce [23]. services considering the risk source from the overall process
Diverse studies have also obtained empirical evidence that of B2C and our current research purposes. Nine important
supports the effect of perceived risk on consumer purchasing variables such as social risk, economic risk, privacy risk, time
behavior. Cunningham et al. [24] proposed that private risk, risk, quality risk, health risk, delivery risk, after-sale risk,
product risk and the risk of unknown origin would impact on purchasing behavior were chosen in our research model
the online shopping. Based on the investigation for perceived according to traditional literature on them and the empirical
risk and online purchasing behavior, Forsythe and Shi[25] evidence obtained from E-commerce context. They were
found that perceived risk significantly related to online defined in Table 1.
purchasing behavior, which could explain the barriers of
TABLEⅠDEFINITION OF VARIABLES IN LITERATURE AND PROPOSED IN THIS STUDY
Related Literature
Variable Definition
and Our Research
Social Potential loss of status in one’s social group as a result of adopting a product or service, looking foolish or
[5,24,27]
risk unpopular.
Economic The potential monetary outlay associated with the initial purchase price as well as the subsequent
[5,24,27]
risk maintenance cost of the product, and the potential financial loss due to fraud
Privacy
Potential loss of control over personal information, when the information is used without permission. [5,23,27]
risk
Time Potential loss of time associated with making a bad purchasing decision by wasting time researching,
[5,24,27]
risk shopping, or have to replace the unexpected goods.
Quality The possibility of the product malfunctioning and not performing as it was designed and advertised and
[6,24,27]
risk therefore failing to deliver the desired benefits
Health Potential loss of health because of prolonged use of computer will cause fatigue or visually impaired, [23]
risk pressure on one’s heart, or buying counterfeit products which is harmful to one’s health. This study
Delivery Potential loss of delivery associated with goods lost, goods damaged and sent to the wrong place after [16]
risk shopping. This study
After-sale [16]
Potential loss of after-sales associated with products problems, commercial disputes, and service guarantee.
risk This study
Purchasing The possibility of consumer behavior to doubt, give up, cut down spending, cut down frequency, and to put
Behavior off one’s purchasing because of perceived risks. This study
From above discussion, the following research hypotheses H6: The perceived quality risk has a negative influence on
are proposed: consumers’ purchasing behavior.
H1: The perceived risk in the overall process of B2C H7: The perceived health risk has a negative influence on
E-commerce is constructed by eight dimensions. consumers’ purchasing behavior.
H2: The perceived social risk has a negative influence on H8: The perceived delivery risk has a negative influence on
consumers’ purchasing behavior. consumers’ purchasing behavior.
H3: The perceived economic risk has a negative influence on H9: The perceived after-sale risk has a negative influence on
consumers’ purchasing behavior. consumers’ purchasing behavior.
H4: The perceived privacy risk has a negative influence on B. Research Model
consumers’ purchasing behavior.
As the hypotheses proposed above, firstly, there are eight
H5: The perceived time risk has a negative influence on dimensions which construct the perceived risk in the overall
consumers’ purchasing behavior. process of B2C E-commerce and they will have different
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impacts on consumers' perceived risk. The research model of China. They were randomly selected as our respondents. We
this paper is presented as Fig. 1. received 427 respondents in which information was missing
on key variables for some of the respondents and finally we
H1 were only able to use the data of 388 cases. The number of our
samples is more than ten times of 37 items, so we can use
Dimensions of Perceived Risk them for the further analysis.
From the demographic variables and the percentage
Perceived Social Risk
number listed in Table 2 we know that all of them have
experience of online purchasing, 54.1% of them are male, and
Perceived Economy Risk
most of our respondents are young people with age between
H2 18 to 34 years old. Age, gender and online shopping times
Perceived Privacy Risk H3 represent the socio-demographic background of the
respondents.
Perceived Time Risk H4
H5 Perceived TABLEⅡDEMOGRAPHIC VARIABLES
Purchasing
Behavior Demographic variables Percentage number
Perceived Quality Risk H6 of respondents
H7
Age: Age of the respondent
Perceived Health Risk 18~24 67.5
H8 25~30 19.3
H9 31~34 8.0
Perceived Delivery Risk  35 5.2
Gender of the respondent
Perceived After-sale Risk Male 54.1
Times of online shopping
Fig. 1 The Research Model  3 32.5
4~8 28.6
9~15 21.9
III. RESEARCH METHODOLOGY
 16 17
A. Formation of Questionnaire
In order to acknowledge what kind perceived risk factors
Based on the related literatures and our previous studies,
have important influence on the overall process of B2C, we
we designed a questionnaire. Firstly, we summarized all the
applied exploratory factor analysis to the 32 items to explore
items about perceived risks and consumer purchasing behavior
the constructs of consumers’ perceived risk, reliability and
in the previous studies. Then, after pre-investigating to our
validity for the measures are tested, and the verification results
colleagues and college students, some items were adjusted. At
are proposed in the next paragraph.
last, we got our final questionnaire, in which there are 32
measurement items listed for part 1 used to measure the risk IV. DATA ANALYSIS AND RESULTS
dimensions in the overall process of B2C, and the other 5
items for part 2 used to measure the consumers’ purchasing A. Measurement Model Analysis
behavior. We used Likert scale of 1-5 with end points of We use exploratory factor analysis to extract a number of
“strongly disagree” and “strongly agree” to measure these common factors which may explain most information of the
items. Especially in part 1, after summarizing all the items measures. From part 1, these factors are constructs of the
about perceived risks in the previous studies, we added some perceived risk online shopping, but from part 2, the factor
items in each of the three phases for the overall process of describes consumer purchasing behavior. Firstly, SPSS17 was
B2C. For example, in the phase of searching information used to test the KMO and Bartlett’s test of sphericity. The
before buying, considering that it would cause their health risk KMO about dimensions of perceived risk in part 1 is 0.836, its
for consumers to spend much long time on information Bartlett’s test p value is 0.000. The KMO about perceived
searching, we added five items to measure this risk. Another 5 purchasing behavior in part 2 is 0.882, its Bartlett’s test p
items were added to measure customers’ perceived risk from
value is 0.000. The test values indicate that the data from our
worrying about the quality of products in the phase of
questionnaire are acceptable to perform further factor analysis.
transaction. In the phase of after transaction, considering the
risk factors such as long time waiting, the possible accidents Then, for part 1, two items T31 and T32 are deleted
by delivery, the evaluation by some others and the service of because their rotated factor loadings are less than 0.4 by using
after-sales, 10 items were added to measure these risks. All the principal component analysis method and variance
items used to measure the variables proposed in Table 1 are maximization rotation, and we got 30 items kept in and their
presented in Table 2. factor loadings are shown in Fig. 1. Table 3 shows that there
are eight common factors extracted from the remaining 30
B. Data Collection
items and variance contribution rates. Considering the
The data collection was conducted through a personal cumulative variance contribution rate is 88.627%, these eight
survey aimed at online shopping consumers in China by using variables could be used to analyze the contents and types of
interview, investigating online and in business streets from perceived risk for the overall process of B2C.
October, 2010 to January, 2011. The three main kinds of
people in our samples were white-collar from company, From part 2, we also got one common factor and the
blue-workers from factory, and college students from cumulative variance contribution rate is 90.38% as shown in
university, more than half of them came from Shenzhen, Table 3.
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TABLEⅢ MEASUREMENT ITEMS AND THE COMMON FACTOR AND THE VARIANCE CONTRIBUTION
Factor Variance
Variable Item Measurement Factor name
loading Contribution
T2 Prolonged use of computers may cause adverse effects for health. 0.932
T1 Prolonged online shopping may lead to fatigue or visually impaired 0.894 Perceived
Health
T4 The loss of online shopping happens will be pressure on my heart. 0.882 17.245% Health Risk
Risk
T3 Buying counterfeit products can damage my health. 0.864 (PHR)
T11 It would make me irritable to the process to return or repair products 0.818
T25 Online shopping may buy counterfeit products. 0.931
T24 The actual quality of the goods does not match its description. 0.902 Perceived
Quality
T26 I bought the product may not meet my needs. 0.892 27.059% Quality
Risk
T23 Online shopping is not a good judge of product quality. 0.869 Risk(PQR)
T27 Goods ordered online can’t personally try and expectations very different. 0.780
T15 Online shopping E-mail address may be abused by others. 0.960
Perceived
Privacy T17 Online shopping the phone number may be abused by others. 0.945
8.129% Privacy
Risk T16 Online shopping the bank card may be stolen by others. 0.928
Risk(PPR)
T22 The personal information may be disclosed to others companies 0.829
T13 Use the online payment services will charge an additional fee. 0.915 Perceived
Economic
T14 Delivery service will be charged with additional fee. 0.900 7.896% Economic
Risk
T12 Online shopping may cost more than the store. 0.899 Risk(PER)
T30 If the products have problem the communicating with the seller and 0.901
the service may require a lot of time. Perceived
Time
T28 Sellers may not be timely delivery, reception have to wait long. 0.896 13.079% Time Risk
Risk
T21 Courier services of varying quality, delivery time may be too long. 0.868 (PTR)
T29 The goods returned may be waiting a long time. 0.868
T6 Online shopping may affect the image of people around me. 0.948 Perceived
Social
T7 Online products may not be recognized by relatives or friends. 0.931 7.116% Social Risk
Risk
T5 Online shopping may make others reduce your evaluation. 0.923 (PSR)
T18 Express Delivery after shopping areas easily lost goods. 0.916 Perceived
Delivery
T20 Express Delivery after shopping areas easily damaged goods. 0.908 4.554% Delivery
Risk
T19 Express Delivery may be sent to the wrong place. 0.855 Risk(PDR)
T10 If the products have problem, hard to find the seller interference. 0.915 Perceived
After-sale
T8 difficult to solve commercial disputes in online shopping. 0.897 3.509% After-sale
Risk
T9 Products purchased online may miss after-sales service guarantee. 0.866 Risk(PAR)
I doubt whether to do my purchasing online because of the perceived risk
J1 0.975
I give up my purchasing online because of the perceived risk Perceived
J2 0.970
Purchasing I cut down my spending on purchasing online because of the perceived risk Purchasing
J3 0.964 90.380%
Behavior I cut down my frequency on purchasing online because of the perceived Behavior
J4 0.962
risk (PPB)
J5 0.879
I decided to put off my purchasing online because of the perceived risk
The eight common factors are the eight dimensions of which, construct validity is definitely important validity that
perceived risk we seek for and named as follows: perceived should be tested. Construct validity includes convergent
health risk(PHR), perceived quality risk(PQR), perceived validity and discriminate validity. In this paper, we used
privacy risk(PPR), perceived economic risk(PER), perceived average variance extracted (AVE) values to test the
time risk(PTR), perceived social risk(PSR), perceived delivery convergent validity and confirmatory factor analysis for
risk(PDR) and perceived after-sale risk(PAR). For the one testing discriminate validity. Table 4 shows that the AVE of
common factor from part 2, we named it as perceived each dimension is greater than 0.7, therefore, the survey data
purchasing behavior (PPB). in our research have a good convergent validity.
Reliability refers to the reliability of the investigation, TABLE Ⅳ  ,CR AND AVE VALUE OF DIMENSIONS
which shows consistency, reproducibility and stability of the
results. Cronbach’s  coefficient is used to conduct Dimension Item  CR AVE
reliability analysis. If cronbach’s  coefficient is greater than PHR T2,T1,T4,T3,T11 0.923 0.944 0.772
0.8, it is generally believed that the investigation has a fairly
good reliability. Table 4 shows that  value of each
PQ R T25,T24,T26,T23,T27 0.914 0.940 0.768
dimension is greater than 0.8 and indicates that the survey data PPR T15,T17,T16,T22 0.875 0.954 0.841
in our research are true and reliable. The composite reliability PER T13,T14,T12 0.886 0.930 0.819
value CR of each dimension is greater than 0.9 and implies PT R T30,T28,T21,T29 0.905 0.934 0.780
that our survey data have a high reliability.
PSR T6,T7,T5 0.843 0.954 0.872
Validity analysis is used to analyze the effectiveness of the
P DR T18,T20,T19 0.907 0.922 0.798
survey results. Validity refers to the degree to which evidence
and theory support the interpretations of test scores entailed by PAR T10,T8,T9 0.858 0.921 0.797
proposed uses of tests. It is divided into various validities such PPB J1,J2,J3,J4,J5 0.873 0.913 0.9035
as content validity, criterion validity and construct validity. In
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B. Structural Model Analysis dimensions showed no-cross construct loadings above 0.5,
A Confirmatory Factor Analysis (CFA) is performed to indicating good discriminate validity. The hypothesis H1 is
evaluate the validity of the measurement scales of all variables verified.
included in the proposed model. Once the measurement model For the purchasing behavior model, which is used to verify
is validated, the risk dimensions model and purchasing the hypotheses H2-9, the indexes show that there is a good
behavior model are performed. The goodness-of-fit indices goodness-of-fit between the model and the survey data and the
indicate that there are appropriate specifications of the two model is available to be used to test the relationship between
models (Table 5), these indexes of both models are above the risk dimensions and consumer purchasing behavior. The test
recommended levels and the test results indicate that the outputs about the path coefficients and significant levels of the
survey data in this paper are real and reliable. The values of purchasing behavior model are given in Fig. 2. The results
 2 /df for the two models are not more than 3. The values of indicate that there are five hypotheses, i.e. H5-9, are supported
NFI, IFI, CFI, GFI, and AGFI for the two models are more but there are the other three hypotheses, i.e. H2-4, are rejected.
than 0.9, and both RMSEA below 0.08, which means the two There are some differences about the results obtained in our
models are acceptable and available. study with the dedications of previous studies. It is worth for
us to do further discussions and find whether there are any
The results support the first hypothis H1, confirming that new implications for the results, especially in the application
the perceived risk of the overall process of B2C includes the on the research for online purchasing behavior of consumers
eight dimensions proposed in the risk dimension model. These coming from different cultures and countries.
TABLEⅤ GOODNESS-OF-FIT INDEXES OF THE RESEARCH MODEL
Indexes 2 df  2 /df NFI IFI CFI GFI AGFI RMSEA
recommended levels - - <3 >0.9 >0.9 >0.9 >0.9 >0.8 <0.08
the risk dimensions model 658.43 372 1.77 0.951 0.981 0.981 0.923 0.916 0.046
the online purchasing behavior model 941.257 519 1.81 0.947 0.971 0.971 0.913 0.906 0.055
Fig. 2 The research model with path coefficient
Significant relationship Non significant relationship
of B2C, and the impacts for each of them on consumers’
V. DISCUSSIONS
purchasing behavior.
There are abundant researches on the effect of perceived
The results obtained confirm that the composition of
risk toward the purchasing decision and the determinants of
online shopping consumer perceived risk and some
buying intention in online context. To date, however,
dimensions of perceived risks from the two phases before
attempts to study both risk dimensions and consumers’
buying and after purchasing of B2C have significantly
purchasing behavior jointly have proved insufficient and
influenced online consumers’ purchasing behavior. From the
lacked depth. Thus, we have examined such important
supported hypotheses H5, H6, H7, H8, and H9, we can know
variables as perceived risk dimensions in the overall process
what risk dimensions have significant influence on
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