Influences of External Incentives on Consumers’ Positive Electronic Word-of-Mouth Intention

Influences of External Incentives on Consumers’ Positive Electronic
Word-of-Mouth Intention
NIU Haipeng1, WANG Xiaofan2, SUN Naijuan1
1. School of Business, Renmin University of China, Beijing, P.R.China, 100872
2. School of Administration, Beijing University of Chinese Medicine, Beijing, P.R.China, 100029
Abstract: With a wide application of internet, more and more comments on brands, companies,
products and services by consumers appeared, which are academically called Electronic Word-of-Mouth
(EWOM). It is worth to analyze how to make use of EWOM as a rich resource both for practitioners and
scholars. This study focuses on positive EWOM intention by finding the influences of different
incentives including economy, return, social elements and self-enhancement incentives on customers’
response, as well as the influences of different tie strength. This study combines quantitative data
analysis methods to conduct descriptive statistics analysis, validity and reliability analysis, control test
and analysis of variance to verify the impact of incentive types and strength of relationship imposed on
will of positive word-of-mouth. The research results are as follows: Material incentive is the most
effective means to increase the customers’ will of WOM; Return incentive has a positive impact on
customers’ will of word-of-mouth; Enhancement of relationship intensity will promote consumers’ will
of EWOM; Consumers of different levels of involvement should be treated differently.
Keywords: Incentive Type, Tie Strength, Participation Level
Introduction
The latest report released by the American Pew internet survey agency and the American Life Project
indicated that when the users want to buy goods, they will usually check the internet information. An
consumer behavior survey of LCD TV which was made by China’s World Wide home appliances
network in July 2008 also showed that nearly 68% of consumers will search and gather relevant
information before they buy LCD TVs, among which 65.4% of consumers choose to search the relevant
information as well as other consumers’ evaluation via internet. Electronic Word-of-Mouth (EWOM)
has played an increasingly important role in consumers’ decision and related to the success in market
competition[1]. However, a comparative study about the behavior of Chinese and American consumers in
the forum to seek and release information indicated that Chinese consumers tend to search for the
relevant product information at the forum but few of them release personal experience. In contrast, the
American consumers are more willing to provide information. Thus in our country, despite the
information search of consumers has become a spontaneous act, but the initiative to spread
word-of-mouth has to be guided and inspired.
1 Literature
Word-of-mouth (WOM) is an informal interpersonal communication on a particular product, brand,
organization and service, which is made by a non-commercial disseminator and receiver with perceptive
informatics, it is a two-way communication behavior on a particular product, brand or organization,
which is initiated by individuals or groups[2]. Electronic Word-of-Mouth (EWOM) is a two-way
communication on enterprises, products and service, which is made by disseminator and receiver on the
network. Many scholars at home and abroad conducted studies on the motives of WOM, focusing on six
types of motivation, as shown in Table 1.
236
Table 1 The types of motives of WOM
motives of WOM
Social interaction
Scholars
（ ）
（ ） ; Lee（2006） ; Wasko
and Faraj（2005） ; Guo Zhao-yang and Lv Qiu-xia（2009） ; Li Yi-fan and Lu
Xiong-wen（2007）
Lee（2006） ; Ryu and Feick, 2007 ; Wasko and Faraj（2005） ; Wirtz & Chew,
Balasubramanian and Mahajan 2001
[3]
; Chiu 2006
[4]
[6]
[5]
[7]
[8]
Material Incentives
[5]
[9]
2002[10]
Altruism
（ ）
Balasubramanian and Mahajan 2001
（ ）
Chiu（2006） ; Lee（2006）
and Faraj 2005
Self-enhancement
Return Expectation
Interest to meet
（ ）
[3]
; Chiu 2006
[4]
（ ）
; Lee 2006
[5]
; Wasko
[6]
[4]
[6]
[6]
（ ）
[5]
; Norman & Russel, 2006; Wasko and Faraj 2005
[11]
; Wang Fei-rong, 2008
（
（ ） ; Wang Fei-rong, 2008
Balasubramanian and Mahajan（2001） ; Lee（2006） ; Wasko and Faraj（2005）
; Guo Zhao-yang and Lv Qiu-xia（2009） ; Li Yi-fan and Lu Xiong-wen（2007）
Lee 2006
）
[5]
; Guo Zhao-yang and Lu Qiu-xia 2009
[3]
[6]
[7]
[11]
[5]
[7]
[8]
In previous studies on WOM, the relationship intensity between sender and recipient is the element
concerned by the majority of scholars. Bristor（1990）[12] once pointed out that “WOM network is a
social network composed by a group of people who participate in the WOM spread.” The WOM took
place in the social network can be classified according to the extent of closeness between information
seeker and fountainhead. The closeness of this relationship is the relationship strength[12]. Wirtz and
Chew（2002）[10] supposed that the strength of relationship would affect the activities of WOM.
In addition, Kozinets（1999）[13] studied the relationship between the level of participation on the
network and the motivation of EWOM. He believed that there were great differences between those
contributors as well as viewers with a lower level of community participation and those insiders as well
as social person with a higher level of participation. Kozinets’（1999）[13] study showed that browser and
contributor are low participation members who mainly request for information, contribute little to the
community, rarely participate in community activities. Whereas, insiders and social person are members
of high involvement, they often provide help and support to community and other members.
2 Research design
2.1 Research framework and hypothesis
This article proposed research framework according to the existing literature and the characteristics of
the selected objects of study, shown in Chart1, among which, the independent variables include the
incentive types encouraging positive Electronic Word-of-Mouth (P-EWOM) and the relationship
strength between the transmitter and the receiver. The dependent variable is the will of satisfied
customer to disseminate positive WOM in the network environment. The conditioning variable is the
level of participation of customer behavior on the EWOM dissemination.
237
Independent variable 1
incentive types
：
：
：
：
Level 1 material incentive
Level 2 return incentive
Level3
social interaction
incentive
Level4
self-enhancement
incentive
×
Independent variable 2：
strength of relationship
：
：
：
conditioning variable level of
participation
：
：
：
Level 1 high involvement
Level 2 low involvement
③
④
①
：
dependent variable will
of P-WOM
：
：
Dimension1 intention of
WOM
Dimension 2 frequency of
VOM
Dimensio3:
depth
of
WOM
Dimension4 will of WOM
②
：
Level 1 strong links
Level 2 weak links
Chart 1: Schematic diagram of research framework
Description:
① main effect of incentive types on will of P-WOM
main effect of strength of relationship on will of P-WOM
interaction of incentive types and strength of relationship on will of P-WOM
moderating effect of level of participation on incentive types and will of P-WOM
From low levels of demand to high, Maslow classified the theory of demand into five types: physical
needs, security needs, social interaction needs, respect needs and the need of self-realization. The
incentive concluded by this study can correspond to different levels of Maslow need theory. Accordingly,
this study assumes that the lower the incentive level, the greater the incentive intensity. Thus proposed:
H1: Different incentive plays significantly different role on the will of P-WOM. With the increases
of incentive intensity, the will of P-WOM will increase.
According to the research of Wirtz and Chew 2002 [10], in the case of consumer satisfaction,
consumers are more willing to spread positive word-of-mouth to intimate person. Because of the risk of
false information dissemination existing in the process of the dissemination to the weak relationship
person, lack of familiarity with each other, little understanding of the preference of others,
recommended products and service may be difficult to make the recipient satisfaction. Thus proposed:
H2: The relationship strength will have a significant effect on the will of P-WOM. In the strong
links, people are more willing to spread the positive WOM.
Ryu and Feick 2007 [9] confirmed the interaction between the award and the relationship strength by
empirical research. In the strong links, the appearance and increase of the material incentives did not
change the consumers’ will to recommend. Whereas, in the weak links, the material incentives increase,
the will to recommend enhance. In the strong links relationship, consumers attach importance to
relations with the others. They are unwilling to bear the risk of unsuccessful recommendation, also
worried about the negative impact on the existing relationship caused by the recommendation. Whereas,
in the weak links, the communicators will suppose that their recommendation behavior is to help other
people or companies. The added value brought by external incentives will make the communicators to
feel it is worthy of the investment disseminating word-of-mouth. However, they do not care whether the
②
③
④
（
（ ）
238
）
relationship will be destroyed or not. This study attempts to examine whether the incentive and
relationship strength in the traditional word-of-mouth is also applicable in the network environment or
not. Thus proposed:
H3: Relationship strength interacts with the incentive type.
H3a: In the strong links, various incentives have no significant effect on the will of P-WOM
H3b: In the weak links, various incentives have significant effect on the will of P-WOM, with the
increases of incentive intensity, the will of P-WOM will increase.
According to Kozinets’ 1999 [13] research on the level and motive of participation, the lower the level
of participation, the more emphasis people imposed on the short-term indirect benefits, and they do not
care the relations with other members and the community. The higher the level of participation, the more
emphasis people imposed on long-term and immediate interests, and they paid more attention to
maintain the community relations. In addition, the research of Hall and Graham 2004 [14] also
considered that the first time virtual community members to join the virtual community is often out of
personal interest, Thus proposed:
H4: The level of participation has a regulating action on the relations between incentives and the
will of P-WOM.
H4a: For high-level participants, with the enhancement of incentive strength, the will of P-EWOM
will reduce.
H4b: For low-level participants, with the enhancement of incentive strength, the will of P-EWOM
will enhance.
（ ）
（ ）
2.2 Measurement of variables
For the incentive variables, in the six types of motivation discussed by scholars in the existing literature,
altruism and interest to meet, these two types of motive arises from individual itself, it is determined by
the individual s personality, habits and values, while the other four types of motivation can be inspired
by external incentives. Corresponding to the four types of motivation which can be stimulated by
external incentives, this study summarize the incentives as: material incentive, reward incentive, social
incentive and self-enhancement incentive. For the specific setting of different incentives, This study
carry out the design of incentives through the pre-research on part of the consumers, and with the
reference of some big networks, such as Baidu knows, the Public Comment Networks, Xiao Nei
networks and Tian-Ya community, etc. For the variables of relationship intensity and level of
participation, this study use the existing scales, making appropriate changes according to the specific
characteristics of Chinese language and the actual network usage. This study use Likert Scale7 to test
that to which extent does the item statements consist with the actual situation of the subjects.
’
2.3 Experiment design
2.3.1 Experimental groups design
In this paper, we test the hypothesis through the method of
between-subjects factorial design.
The manipulated variables are the incentive types (material incentive, return incentive, social incentive,
and self-enhancement incentive) and relationship intensity (strong links, weak links).Through
manipulation, it eventually formed eight different types of questionnaires, as shown in Table2:
4×2
Scenario groups
Table2: Design of experiment groups
Incentive types
Relationship strength
1
Material incentive
strong
2
Material incentive
weak
3
Return incentive
strong
4
Return incentive
weak
5
Social incentive
strong
239
6
Social incentive
weak
7
Self-enhancement incentive
strong
8
Self-enhancement incentive
weak
2.3.2 Sample selection and data collection
The author chose students of a Beijing university as experimental object in April, 2010. On the one hand,
students are the groups of high network utilization; they are familiar with EWOM behavior such as
online information search and dissemination, which has a strong correlation with the experiment content.
On the other hand, the group of college students has high homogeneity on the demographic
characteristics, which can better filter the interference which the demographic variables impose on the
experiment object using students as the experiment object. To ensure the subjects have certain network
experience, the samples of this study are all junior students.
In accordance with the requirements of sample size, taking into account the invalid questionnaires, this
study delivered 202questionnaires, within which 198questionnaires were returned, the recovery rate is as
high as 98%. Among the returned questionnaires, there are eight uncompleted ones, 27 subjects
appeared cognitive bias or clearly carelessness. Therefore, 33 questionnaires were not included in this
analysis, 167 questionnaires were eventually obtained. The number in each category was 20 or more,
meeting the requirements of experiment design.
3 Data analysis
3.1 Descriptive statistics
In the 167 valid questionnaires, there are 51.5% male and 48.5% female. The age of subject concentrates
between 18-30 years old; the monthly disposable income concentrates between 500-1200yuan. The
result of T test and ANOVA test showed that gender, age and disposable income did not have significant
impact on P-EWOM t=0.78, t=0.778, p>0.05; F=1.304, p>0.05; F=2.145, p>0.05 .We have achieved
the purpose of selecting the sample of university students to exclude the interference to results, which is
caused by demographic variables.
（
）
3.2 Validity analysis
Using LISREL 8.70 for confirmatory factor analysis, the factor loading standardized coefficient are all
above 0.59, indicating that the factors explain well. All items passed T test (t 1.96)and the residuals are
less than 0.7.From the indicators of model fitting degree,χ2/df=1.161< 2,the root mean square error of
approximation(RMSEA)is 0.0242 0.05,indicating that the model fitting degree is very good. In other
indicators of reflecting model fitting degree, NFI=0.946, RFI=0.929, IFI=0.992, CFI=0.992, GFI= 0.934,
they are all very close to 1, indicating that the fitting degree between data and model is good, there is
good discriminate validity.
＞
＜
3.3 Reliability analysis
Upon examination, the total Cronbach's α coefficient of the 15 major items in the questionnaire (not
including the demographic variables and situational possibility items) is 0.800,showing the reliability of
the questionnaire is very good. After removing any items, Cronbach's α coefficient does not increase, it
does not meet the deletion criteria, thus the test items are all maintained. The internal consistency
coefficient of each tested items exceeds the critical value of 0.7, “the general correlation coefficient of
correction terms” of 15 tested items are all greater than the critical value of 0.4. In addition, after
deleting each tested item, the figure of α does not significantly improve. Above all, the scale has good
reliability.
3.4 Control test
The purpose of control test is to investigate whether different level of independent variables in the
240
experiment design is significantly distinctive, and whether the relevant variables have achieved the
desired level. The results of T test show that the research is effective on the variable control, as shown in
Table3: Summary of control test results
Control level test group
Average value(standard deviation
Control variables
Relationship intensity
Satisfaction degree
Direction of WOM
Possibility of experiment
（
）
Strong links（N=83）
Weak links（N=84）
satisfaction（N=167）
positive WOM（N=167）
possibility （N=167）
（
）
2.9526（1.14309）
6.0079（0.91187）
5.6826（1.10905）
5.1976（1.63265）
4.3976 1.29473
）
T(p)
（0.000）
7.642（0.000）
28.456（0.000）
19.606（0.000）
9.478（0.000）
7.648
scene
3.5 Analysis of variance
This study adopts the average value of tested items indicating the level of factor. For the level of
participation, we use the average score of 306729 as demarcation point, then, it will be divided into high
participation and low participation, T tests showed that there was significantly difference between high
involvement groups and low involvement groups p<0.001,Mean 高=4.8378 Mean 低=2.5491 . The
type and intensity of independent variables are all category variables.
3.5.1 The results of variance analysis
The results of homogeneity of variance F=1.462 P>0.05
indicate that there is no significant
difference in the a =0.05 level of variance in each group, meeting the conditions of multivariate analysis
of variance.
The result of 3ANOVE analysis is shown in Table4. The main effect between incentive types of
independent variable and relationship intensity is remarkable; the interaction between the independent
variables is not remarkable, while the regulating action of level of participation is remarkable.
（
（
variables
，
，
）
）
Table 4 multivariate analysis of variance
Figure F
Probability figure P
Results
Corrected Model
13.786
.000
Intercept
4890.115
.000
Incentive types
26.650***
.000
Support H1
Relationship intensity
9.574**
.002
Support H2
Level of participation
8.477**
.004
Incentive types*relationship intensity
1.052
.371
Not support H3
Incentive types*level of participation
13.196***
.000
Support H4
＜
＜
＜
Remark: * indicates P 0.05, ** indicates p 0.01, *** indicates p 0.001,the same with the following
3.5.2 Main effect of incentive types
The main effect of incentive types is remarkable, the effect of different incentives is not entirely equal,
which verify the first half of hypothesis1.But this does not indicate the size order of the four incentives,
so we use LSD multiple comparison test to verify the second half of hypothesis1,as shown in Table5:
241
Table 5: The multiple comparisons of average incentive types figure
(I) types of incentive
(J) types of incentive
Mean
Probability
difference
interval
figure P
(I-J)
Material incentive
95%confidence
Lower
Upper
limit
limit
Social incentive
1.0915***
.000
.7228
1.4601
Return incentive
1.4633***
.000
1.0989
1.8276
Self-enhancement
1.4842***
.000
1.1177
1.8506
Material incentive
-1.0915***
.000
-1.4601
-.7228
Return incentive
.3718*
.046
.0075
.7361
Self-enhancement
.3927*
.036
.0263
.7592
Material incentive
-1.4633***
.000
-1.8276
-1.0989
Social incentive
-.3718*
.046
-.7361
-.0075
Self-enhancement
.0209
.909
-.3412
.3830
Material incentive
-1.4842***
.000
-1.8506
-1.1177
Return incentive
-.3927*
.036
-.7592
-.0263
Social incentive
-.0209
.909
-.3830
.3412
incentive
Social incentive
incentive
Return incentive
incentive
Self-enhancement
incentive
3.5.3 Main effect of relationship intensity
The main effect of relationship intensity is remarkable F=9.574, p<0.01 , and the impact of strong links
on the will of P-EWOM Mean=4.812 is greater than that of weak links Mean=4.406 .
3.5.4 The interaction between incentive type and relationship intensity
The result of 3 ANOVA analysis indicates that the interaction between incentive type and relationship
intensity will not significantly impact the will of P-EWOM F=1.052 p>0.05 .This shows that the
relationship intensity does not affect the excitation effect that incentive imposes on the will of P-EWOM,
hypothesis4 does not hold.
We analyzed the role of incentives under different relationship intensity, the results showed that in
strong links, the material incentive mean=5.775 influences the will of P-EWOM most, while there is no
significant difference between the other three incentives. Therefore, the hypothesis3a does not hold.
While in the weak links, except return incentive, the hypothesis which H3b imposed on the other three
incentives hold.
3.5.5 Regulation of the level of participation
According to the results of multivariate analysis of variance, the interaction between incentive types and
level of participation is extremely remarkable F=13.196, p<0.001 . Under high level of participation,
the impact of return incentive is significantly less than material incentive, but there is no remarkable
difference between self-enhancement incentive and social incentive. Under low level of participation,
the material incentive influence the will of P-EWOM most mean=5.688 ,followed by social incentive,
the difference between return incentive and self-enhancement incentive is not remarkable, but smaller
（
（
）
）
（
（
，
）
（
）
（
242
）
（
）
）
than the first two incentives.
4 Conclusion and outlook
4.1 Research implications
The significance of the results of this study is that when consumers have a satisfactory consumption
experience, enterprises should maximize the will of P-EWOM according to the relationship intensity on
website and choosing the most suitable type of incentives according to different level of consumers.
First, we should focus on the provision of material incentives. Providing material incentive is the most
effective means to increase the customers’ will of WOM. No matter what relationship intensity and level
of participation, material incentive always stimulate the will of P-EWOM most and the impact is very
significant. This shows that consumers focus most on practical economic interests when facing various
incentives.
Second, we should enhance the value of return incentives and provide more scarce resources. On the one
hand, make sure that return incentive have more contents of scarcity, not just so irreplaceable data such
as film songs .On the other hand, there should be more comprehensive mechanism to ensure that
consumers can be rewarded.
Third, we should pay more attention to the enhancement of relationship strength. The enhancement of
relationship intensity will promote consumers’ will of EWOM. With the rise of real name network
platforms such as Xiao Nei network, happy network and blog, a new type of relationship in the network
come into being. Although this kind of relationship is relationship in network, for the familiarity
between members offline, users are actually friends.
Fourth, we should pay more attention to the incentive design of different relationship intensity. In the
website on which the members know each other well, the strength of incentives must be large enough, or
the role of incentives will be offset because of the risk posed to the mutual relations. In the website of
weak relationship, consumers do not have to scruple relationship face friendship and other emotional
factors, they eventually become total egoists, we should take measures to provide virtual currency, to
give certain privilege and to gain qualifications to make friends.
The last, consumers of different levels of involvement should be treated differently. The community
members of lower level of participation pay more attention to realistic value of benefits, such as freely
browsing visitors and the ones who have gained information without disbursement. For the senior
members of deep level of participation and high level of contribution, we can take some online
incentives and the incentives which associate with community itself strongly.
、 、
4.2 Study limitations
Since the foreign researches on the incentives of EWOM are very limited, while the domestic researches
still remain at the level of fact induction, moreover, because of he human and financial constraint in
empirical researches, there are still many shortcomings and deficiencies in this article although we
sought to be vigorous. One shortcoming is about the integration degree of test scene, this study adopts
scenario description method, requiring subjects to read the questionnaire carefully, fully understand and
integrate into the virtual scene. There is inevitably misunderstanding because of the limitation caused by
subjective and objective conditions. Another shortcoming is the limitation of experimental methods,
although the experimental method could control the impact of independent variables with high internal
validity, external validity is relatively poor, the timing implementation and other variables of incentives
may affect the results.
、
4.3 Future research directions
As a relatively new field of study, this research could provide some ideas and preference for the future
researches. Future researches could concern the following aspects: First, we could make more detailed
classification of incentives and make further discussion to the form and quantity of single category on
the basis of incentives classification. Second, we could conduct researches about why consumers do not
disseminate information by WOM, because under many conditions, the individuals do not lack the
243
reasons for doing something, but there are reasons for not doing so. Third, we could verify the same
conclusion using different methods to increase the effectiveness and universality of the conclusions,
critical incident method and other methods can be used to confirm and extend the conclusion of this
study.
Acknowledgements:
This research was supported by the National Natural Science Foundation of China (70972133,
70522006). We are very grateful to Miss ZENG Yan for her important contribution to this paper.
References
[1]. Stauss, B. Global word of mouth. Service bashing on the internet is a thorny issue [J]. Marketing
Management, 1997, 6 (3): 28-30.
[2]. Guo Guo-qing and Yang Xue-cheng. Word of mouth marketing and its application strategy in
internet era[J] Finance and Trade Economics, 2006, 9 58-61. (in Chinese)
[3]. Balasubramanian, S. and Mahajan, V.. The economic leverage of the virtual community [J].
International Journal of Electronic Commerce, 2001, 5 (3): 103-138.
[4]. Chiu, C. M., Hsu, M. H. and Wang, T. G.. Understanding knowledge sharing in virtual
communities: An integration of social capital and social cognitive theories [J]. Decision Support
System, 2006, 42: 1872-1888.
[5]. Lee, K. O., Cheung, M. K., Lim, K. H. and Sia, C. L.. Understanding customer knowledge sharing
in web-based discussion boards: An exploratory study [J]. Internet Research, 2006, 16 (3):
289-303.
[6]. Wasko, M. and Faraj, S.. Why Should I Share? Examining Social Capital and Knowledge
Contribution in Electronic Networks of Practice [J]. MIS Quarterly, 2005, 29 (1): 35-57.
[7]. Guo Zhao-yang and Lv Qiu-xia. Effect of Members' Participation Motive on the Virtual
Community Business Model [J] China Industrial Economics 2009, 1 98-107. (in Chinese)
[8]. Li Yi-fan; Lu Xiong-wen. An Empirical Study of Online Games on the Motivation of Virtual
Community Members [J] Nankai Business Review. 2007, 5 : 55-60. (in Chinese)
[9]. Ryu, Gangseog and Feick, Lawrence. A Penny for Your Thoughts: Referral Reward Programs and
Referral Likelihood [J]. Journal of Marketing, 2007, 71 (1): 84.
[10]. Wirtz, Jochen and Chew, Patricia. The Effects of Incentives, Deal Proneness, Satisfaction and Tie
Strength on Word-of-Mouth Behavior [J]. International Journal of Service Industry Management,
2002, 13 (2): 141-162.
[11]. Wang Fei-rong, Chai Jin-ying and Gong Jian-li An Empirical Study on Knowledge Sharing in
Virtual Communities [J]. Journal of Zhejiang University of Technology (social science). 2008,
9 : 283-289. (in Chinese)
[12]. Bristor, Julia M.. Enhanced Explanations of Word of Mouth Communications The Power of
Relationships [J]. Research in Consumer Behavior, 1990, 4: 71.
[13]. Kozinets, Robert V.. E-tribal zed marketing: The strategic implications of virtual communities of
consumption [J]. European Management Journal, 1999, 17 (3): 252-264.
[14]. Hall, Hazel and Graham, Dianne. Creation and recreation: motivating collaboration to generate
knowledge capital in online communities [J]. International Journal of Information Management,
2004, 24 (3): 235.
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