8/12/2019 e-wom23.pdf
1/5
296
In-depth Study on the Influence of Internet Perceived Risk on the
E-WOM
GUO Guoqing, YAO Yanan,YU Lianzhao
Business School, Renmin University of China, Beijing, P.R.China, 100872
Abstract:This empirical study explores the relationship between internet perceived risk and E-WOM.In this study, internet perceive risk is divided into four dimensions based on exsited literrature which are
internet core-service risk, internet associated risk, internet privacy risk and internet fake risk, andE-WOM is studied from information releasing and opinion seeking perspective as an input variabe ofconsumer purchasing progress. Finally, the study found that all four internets perceived risks have
posive effect on E-WOM. Moreover, the high perceived risk will lead to frequent information releasing,information searching is still the most important measure for consumers to reduce their internet
perceived risks and consumers with high perceived risk are more prone to search for E-word-of-mouthinformation actively.Keywords:Internet, Perceived risk, E-WOM
1 Introduction
With the development of internet, E-WOM (Electronic Word-of-mouth) is becoming a universal
message when consumenrs make their purchase decisions. Consumers communicate with each other
online before making their decisions can reduce their perceived risk. This study will explore the
relationship model between internet perceived risk and E-WOM.
2 Theory Background
2.1Internet Perceived Risk
Perceived Risk was firstly originated from psychology research domain, which is defined as any
consumer action will lead to unexpected result which may be unpleasant, so consumer behavior is a kind
of risk bearing in itself. Forsyth and Boshi
2003
[1]defined perceived risk in the internet environment as
the consumer subjective expected lose when they experience online shopping. In this study, we define
the internet perceived risk consumer perceived loses before making purchase decision which are led
by product/service, internet and online shops during purchase and use process.
Information searching is the most effective method to reduce the perceived risk
Sheth and Venkatesan,
1968
[2], Boulding and Kirmani
1993
[3]thought that consumers will reduce their perceived risks by
searching for formal or informal information related to products, including brand reputation, free use,
buying products with high quality image or repeat purchase.
As for dimensions of internet perceived risk, Miyazaki 2001 [4]researched into the influence of privacyrisk and security risk on consumer behavior online. Forsyth and Boshi (2003)
[1] evaluated internet
perceived risk in terms of 4 dimensions: Financial risk, performance risk, psychology risk and time risk.
This study adopts the dimension of internet perceived risk developed by Chinese scholar Dong Dahai
2005
[5 ]which is composed of internet core-service risk, internet associated risk, internet privacy risk
and internet fake risk.
2.2 E-WOM
Word-of-mouth communication is an oral, person-to-person communication between a receiver and a
communicator whom the receiver perceives as non-commercial regarding a brand, a product, or a
8/12/2019 e-wom23.pdf
2/5
297
service (Arndt, 1967). [6]
However, with the development of internet, more and more consumers are
communicating with each other and sharing their opinions online, and E-WOM
Electronic Word of
Mouth
is emerging accordingly. On the basis of definition of Hennig-Thurau
2004
[7]
, we defineE-wom as the two-way communication related to products, enterprises and newsmakers online.
Compared to the information provided by enterprises, E-WOM on web forum has much more
significant impact on consumer behavior Bickart, Schindler 2001[8]
. This study takes E-WOM as
input variable, which refers to information searching online before making purchase decision including
information releasingand opinion seeking.
3 Hypotheses
The more frequent WOM behavior is, the higher perceived risk is
Arndt,1967
. Consumers with high
perceived risk will search for word-of-mouth information actively. A few scholars[4] [7] [8]
also found that
reducing perceived risk is the main reason for E-WOM communication. Moreover, consumers will also
release word-of-mouth information motivated by altruism and self-enhancement. Consumers willrelease information and share them with others while searching information. Therefore, internet
perceived risk has positive effect on information releasing. We suppose that:
H
Internet perceived risk has positive effect on E-WOM.
In order to explore the effects of 4 internet perceived risk dimensions on information releasing and
opinion seeking online, we make further hypotheses as follows:
H1: Internet core-service risk has positive effect on information releasing online.
H2: Internet core-service risk has positive effect on opinion seeking online
H3: Internet associated risk has positive effect on information releasing online.
H4: Internet associated risk has positive effect on opinion seeking online.
H5: Internet privacy risk has positive effect on information releasing online.
H6: Internet privacy risk has positive effect on opinion seeking online
H7: Internet fake risk has positive effect on information releasing online.
H8: Internet fake risk has positive effect on opinion seeking online
Figure 1. Research Model
4 Methodologies and Analysis
4.1 Sample
Information
releasing online(IR)
Opinion seeking
online(OS)
Internet fake
risk(FR)
Internet
privacy risk(PR)
Internetassociated risk(AR)
Internet core servicerisk (CR) H1 +
H2
+
H4
+
H5 +
H6
+
H7
+
H3
+
H8
+
8/12/2019 e-wom23.pdf
3/5
298
Data for this study are collected through online survey from consumers who bought their mobiles online.
318 questionnaires are handed out and 288 valid ones were received. The gender proportion is balanced
with 57.99% males and 42.01% females. 90.28% samples are below 35 years old, most of which arestudents with high education.
4.2 Latent variables and measurement
This study employes the scale of perceived risk posed by Chines scholar Da-hai Dong (2005) which is
composed of 19 items and measured in terms of Likert which rages from 1 (entirely disagree) to 7 (full
agree).
Table1 Latent variables, operational definations and scales
Concepts Dimensions Definitions Scales
Internet
core service
risk
Consumer
perceived risk
related to net
shops and web
sites.
The product information online are exaggeratedand even false
The refund of shopping online may beinconvenient.
The guarantee of shopping online may beinconvenient.
Maybe I cant receive the delivery. The net shop may be inexistent Maybe there is damage to goods during
delivery process.
I cant get enough product information due tothe lack of face-to-face interaction with
salesman.
There may be a big gap between the real goodsand expected goods.
Internet
associated
risk
Consumer
perceived possible
risk related
shopping online.
The payment failure online may lead to moneylost.
Searching for information online may betime-consuming due to the massive
information.
It may be a long time to receive the goods. The hacker maybe steal the credit card
information which lead to money lost
Taking the delivery by myself may betime-consuming.
Internet
privacy risk
Consumer
perceived risk
related to
personnel
information
leakage.
My shopping experience and habit may beanalyzed by online shop.
The net shop maybe connects with me withoutmy permission.
My personnel information may be leaked.
Internet perceived
risk(PR)
Internet
fake risk
Consumer
perceived possible
risk related to the
fake.
The return of goods may be time-consuming. The goods ordered online may be fake. There may be metal pressure when shopping
online
E-WOMInformation
releasing
Consumer sends
message or gives
I know mobiles very well; many people believethat I am the opinion leader.
8/12/2019 e-wom23.pdf
4/5
299
online advice to others
online
My friends think my opinion is the reliableinformation source when they decide to buy
mobiles online. I talked about mobiles with my friends in last 6
months.
Compared to others, many people are moreprone to my opinion when they ask for
suggestions about mobiles online.
I think that my friends rely on my opiniononline.
I like to talk about mobiles with my friendswhen I chat online.
I want to influence others view on mobilesthrough internet.
Opinion
seeking
online
Consumer
searches for
opinion or advice
from others.
Im prone to ask advices from others beforebuying mobiles
Ill search for the latest information aboutmobiles before buying mobiles.
Ill ask for suggestions about mobiles from myfriends online.
Ill ask for suggestions throng BBS, QQ, MSNand EMAIL before buying mobiles.
Ill be at ease if I ask for suggestions onlinebefore buying mobile
Ill ask others to provide information aboutmobiles for me.
I like to search for negative comment onmobiles before making purchasing decision.
I like to search for positive comment onmobiles before making purchasing decision.
Resource: summarized by authors
4.3 Reliability and validity
IPR and E-WOM scales have quite high reliabilities. The result of EFA shows that after deleting CR 4
and CR 6, the scale of perceived risk has high convergent validity and the 4 perceived risk factors
cumulative contribution of variance account to 87.313%. The resuls of CFA show that the scales of IPR
and E-WOM have high model fitting and validity.
Table 2 Reliability and vlidity of the variables
Variable Reliability RMSEA CFI NFIIPR =0.785 0.072 0.885 0.901
E-WOM =0.929 0.066 0.879 0.901
4.4 The effect of perceived risk online on E-WOM
We employ Amos to examine the relationship between internet perceived risk and E-WOM and the
result is as follow:Table 3 SEM result
Path coefficient Level of sig.
CR IR 0.27 0.012
AR
IR 0.32 0.010
8/12/2019 e-wom23.pdf
5/5
300
PR IR 0.36 0.000
FR
IR 0.45 0.000
CR
OS 0.36 0.000AR
OS 0.45 0.000
PR OS 0.25 0.014
FR
OS 0.39 0.000
We can see from Table 3 and Table 4 that RMSEA is 0.085>0.08, NFI, RFI, IFI, TLI and CFI are all
near to 1, so the fitting of model is well and all hypotheses are supported. Therefore, the perceived risk
online which is composed of internert core service risk, intenet associated risk, internet privacy risk and
internet fake risk has positive effect on E-WOM which is composed of information releasing online and
opinion seeking online.
Table 4 The path coefficient and fitting index of the model
df 2/df p-level RMSEA NFI RFI IFI TLI CFI
807.161 369 2.187 0.000 0.085 0.892 0.868 0.841 0.791 0.818
5 Conclusion
We can see from this study that internet perceived risk has positive effect on E-WOM.
As far as opinion leader is concerned, the high perceived risk will lead to frequent information releasing,
which is in accord with the study of Hennig-Thurau 2004 .[7]
However, the content of information
under the high perceived risk is still needed to a further research.
Information searching is the primary and important measure for consumers to reduce their perceived
risks and consumers with high perceived risk are more inclined to search for E-word-of-mouth
information actively.
Acknowledgments:Supported by projects of National Science Foundation of China (Grant No.70772090, 70972133)
References
[1]. Sandra M. Forsythe, Bo Shi. Consumer Patronage and Risk Perceptions in Internet Shopping.Journal of Business Research, 2003(56), 867-875.
[2]. Sheth J N, Venkatesan M. Risk-reduction Process in Repetitive Consumer Behavior. MarketingResearch, 1968 (5), 307-310
[3]. Boulding, William & Kirmani Amna. A consumer-side examination of signaling theory. Journal ofConsumer Research, 1993(20-1), 111-123.
[4]. Miyazaki, Anthony D, Fernandez, Ana. Consumer Perceptions of Privacy and Security Risksfor Online Shopping. Journal of Consumer Affairs, 2001 (35-1), 27-44.
[5]. Dong Dahai, Li Guanghui, Yang Yi. Research of the Perceived Risk Facets by Consumers inInternet Shopping. Chinese Journal of Management, 2005
1
, 55-60.
In Chinese
[6]. Arndt, J. Role of Product-related Conversations in the Diffusion of a New Product. Journal ofMarketing Research, 1967(4), 291-295.
[7]. Hennig-Thurau, Thorsten. Kevin P. Gwinner, Gianfranco Walsh, and Dwayne D. Gremler.Electronic Word-Of-Mouth Via Consumer-Opinion Platforms: What Motivates Consumers to
Articulate Themselves on the Internet? Journal of Interactive Marketing, 2004(18), 38-52.
[8]. Bickart, B., Schindler, R.M. Internet Forums as Influential Sources of Consumer Information.Journal of Interactive Marketing, 2001(15-3), 31-40.
Top Related