The Word of Mouth Dynamic: How Positive (and
Negative) WOM Drives Purchase Probability
An Analysis of Interpersonal and
Non-Interpersonal Factors
Rodolfo Vázquez-
This study has two main objectives: (a) to examine the relative impacts of positive and
Casielles
negative word of mouth (PWOM and NWOM) on the shift in the receiver’s brand purchase
University of Oviedo, Spain
[email protected]
Leticia Suárez-
probability; and (b) to analyze the effect, direct or indirect, of a number of interpersonal
and non-interpersonal factors on the relation between PWOM or NWOM and the shift
Álvarez
in the receiver’s purchase probability. The data were collected from a sample of 1,035
University of Oviedo, Spain
consumers in four product/service categories. The results suggest that firms should
[email protected]
develop a proactive management of WOM communications that takes into account
Ana-Belén
aspects of both the sender and receiver.
del Río‑Lanza
University of Oviedo, Spain
[email protected]
INTRODUCTION
During the past decade, advances in electronic
In the fields of social psychology and consumer
communications technology have led to considera-
behavior, marketing researchers have produced
ble expansion in the number and types of informal
a considerable amount of theoretical work on the
communications channels. Electronic newsgroups,
effect of interpersonal communication. Such inter-
blogs, virtual communities, instant messaging, cell
personal communication has become known as a
phones, and Personal Digital Assistants (PDAs),
process of word of mouth (WOM) communication,
among other options, offer consumers instantane-
which now is regarded as one of the most impor-
ous interactions with advertisers, fellow consum-
tant and effective communications channels (Kel-
ers, and other market players (Allsop, Bassett, and
ler, 2007). Firms such as Nestlé, Procter & Gamble,
Hoskins, 2007; Hung and Li, 2007; Smith, Coyle,
L’Oréal, Bosch, Microsoft, GlaxoSmithKline, and
Lightfoot, and Scott, 2007).
Johnson & Johnson, to name just a few, increas-
This uptick in activity has helped make WOM
ingly recognize that WOM is an extremely credible,
a powerful communications channel that has an
persuasive, and highly effective tool of informal
important influence in the formation of consumer
means of creating consumer engagement (Nielsen,
opinions and in their purchase decisions. More-
2009). Another example of the popularity of WOM
over, this type of communication among con-
is the appearance of consultancies specializing
sumers is particularly interesting for advertising
in this area (e.g., gaspedal.com and trnd [http://
practitioners, for two reasons:
company.trnd.com/en]). Such companies build
WOM campaigns as part of integrated marketing
communication. Likewise, the official trade association for the WOM marketing industry (Word
of Mouth Marketing Association, or WOMMA),
founded in 2005, promotes and advances WOM by
offering educational programs, ethical guidelines,
• Research suggests that WOM can complement
and extend the effects of advertising (Bayus,
1985; Hogan, Lemon, and Libal, 2004), and
• Research shows that companies can stimulate
WOM through advertising (Graham and Havlena, 2007).
a standardized language, as well as pursuing a
Although previously many advertisers tradition-
research agenda and developing WOM metrics.
ally have considered WOM as an alternative to
DOI: 10.2501/JAR-53-1-043-060
March 2013 JOURNAL
OF ADVERTISING RESEARCH 43
the word of mouth dynamic
advertising, WOM and advertising now
purchase probability. For this purpose, the
negative, about a brand, product, service,
are regarded as two important communi-
authors have grouped the variables into
or organization, in which the receiver
cations channels that interrelate and complement each other.
of the message perceives the sender to
• interpersonal
factors
(how
actively
have a non-commercial intention (Arndt,
The main objective of the current arti-
WOM is sought, strength of tie between
cle is to analyze how WOM communica-
sender and receiver, and sender’s expe-
These definitions are consistent with
tion increases (or decreases) the receiver’s
rience and strength of expression),
other WOM studies (Gruen, Osmonbekov,
and
Czaple, 2006; Harrison-Walker, 2001; Wan-
brand-purchase probability.
WOM communication can be said to
have two dimensions (Harrison-Walker,
• non-interpersonal
factors
(receiver’s
loyalty, experience, and perceived risk).
1967).
genheim, 2005; Wangenheim and Bayon,
2007), and share two characteristics:
2001):
In the current study, the authors’ research
• “WOM activity” includes such aspects
has
• The receiver of the message must perceive the sender to be unconnected with
as
any commercial organization. In other
–– how often WOM takes place,
–– the number of people with whom the
WOM sender communicates, and
–– the quantity of information provided.
• “WOM valence” can be positive, negative, or neutral.
• embraced the perspective of the WOM
receiver,
words, for it to be credible, a WOM
recommendation must spring from a
• compared the impacts of positive and
negative WOM, and
natural dialogue between the two people, and it should be the product of the
• determined the direct and indirect
effects of the different interpersonal and
sender’s knowledge and the receiver’s
need to know.
non-interpersonal factors on the shift in
• WOM can be either positive or negative.
Although the content and strength of both
the purchase probability of the receiver
Positive WOM encourages purchase,
dimensions of the WOM condition affect
of positive (or negative) WOM.
whereas negative WOM discourages
the probability of a consumer’s choosing
a particular brand, few studies have ana-
purchase.
The balance of this research
lyzed the impact of both dimensions.
The WOM literature has three lines of
The majority of studies in the WOM lit-
• presents the authors’ conceptual defin-
erature have focused on the WOM activ-
ition of WOM and the lines of research
ity dimension. And, in fact, there is little
examining how WOM works,
research.
• The first focuses on the perspective
empirical evidence that helps explain how
• describes a conceptual model, and
of the WOM sender and analyzes the
positive and negative WOM contributes to
• presents
reasons why people make positive (or
the shift in the probability of choosing a
the
authors’
proposed
hypotheses.
brand (Assael, 2004; East, Hammond, and
Lomax, 2008).
negative) recommendations on the basis
of their experiences with a product.
Explanations of research design, meth-
These studies conclude that a number
Moreover, these studies primarily have
odology, and results follow. The work
of forces (non-interpersonal factors)
focused on positive WOM and its influ-
concludes with a discussion of the main
exist and give rise to recommendations.
ence on which product is purchased. It also
findings of the analysis and then offers
These forces include
is necessary to examine negative WOM,
managerial implications.
–– satisfaction or dissatisfaction (Ander-
which discourages purchase (Bruyn and
son, 1998; Bowman and Narayandas,
Lilien, 2008). To that end, this research
LITERATURE REVIEW
2001; Brown, Barry, Dacin, and Gunst,
analyzes the WOM valence dimension
The literature defines WOM as “all infor-
2005;
and the impact of positive and negative
mal communications directed at other
Hermann, 2007; Maxham and Nete-
WOM on the shift in the receiver’s pur-
consumers about the ownership, usage,
meyer, 2002), loyalty (Gounaris and
chase probability.
or characteristics of particular goods and
Heitmann,
Lehmann,
and
Stathakopoulus, 2004);
Finally, this study also examines the
services or their sellers” (Westbrook, 1987,
–– commitment to the firm (Brown
variables that explain—directly or indi-
p. 261). Additionally, WOM can be any oral
et al., 2005; Dick and Basu, 1994;
rectly—the shift in the WOM receivers’
and personal communication, positive or
Henning-Thurau,
44 JOURNAL
OF ADVERTISING RESEARCH March 2013
Gwinter,
Walsh,
the word of mouth dynamic
and Gremler, 2002; Lacey, Suh, and
CONCEPTUAL MODEL AND HYPOTHESES
positive (or negative) about the object of
Morgan, 2007);
In line with the aforementioned literature
advice (East et al., 2008).
–– trust (Ranaweera and Prabhu, 2003;
Sichtmann, 2007);
on WOM, the authors have developed a
conceptual framework (See Figure 1) that
(Wangenheim
and
Bayon,
• adopts the perspective of the WOM
2004a
2004b); and
the opposite response among receivers
(Fitzsimons and Lehmann, 2004): people
–– service quality (Harrison-Walker, 2001);
–– length of relationship with the firm
Some studies, however, have observed
• describes the relations between the type
–– perceived value (Matos and Vargas,
of WOM (positive or negative) and the
2008).
sometimes react against negative comments and became even more committed
receiver;
to the brand. Such contrary responses can
occur when
shift in the brand-purchase probability;
• analyzes which type of WOM has the
• The second line of research aims to
most impact on the shift in the brand-
understand WOM receivers’ informa-
• people are directed to do things that
they do not want to do,
• the WOM receiver disagrees with the
purchase probability; and
values of the advisor, or
tion search behaviors or, more spe-
• investigates the effect—direct or indi-
cifically, under what circumstances
rect—on the shift in the WOM receiver’s
• when prior commitment to a brand may
(non-interpersonal factors) consumers
brand-purchase probability of different
prevent consumers from fully accepting
resort to WOM rather than other infor-
interpersonal (how actively WOM is
useful negative information about that
mation sources before making their pur-
sought, strength of tie between sender
brand.
chase decisions.
and receiver, and sender’s experience
Researchers have found that con-
and strength of expression) and non-
Assuming that contrary responses are not
sumers are more likely to seek other
interpersonal factors (receiver’s loyalty,
common, then conceivably positive WOM
people’s opinions before purchasing
experience and perceived risk).
has a positive impact—and negative
1
WOM a negative impact—on the brand’s
when they have less experience and a
stronger involvement in the purchase
IMPACT OF POSITIVE AND NEGATIVE WOM
of the product category (Gilly, Graham,
ON SHIFT IN RECEIVER’S PURCHASE
Wolfinbarger, and Yale, 1998) or when
PROBABILITY
they perceive greater risk in the decision
In general, positive (or negative) WOM
making (Bansal and Voyer, 2000).
is assumed to make the receiver more
purchase.
The authors thus offer their first
hypothesis:
H1:
Positive (negative) WOM has a
positive (negative) impact on the
• The third line of research also adopts
the perspective of the WOM receiver
and examines why some personal
information sources (positive and negative WOM) exert a stronger influence.
Researchers
have
identified
forces
(interpersonal factors) that influence the
receiver’s behavior, such as
–– the WOM sender’s experience and
strength of expression (Bansal and
Voyer, 2000; Gilly et al., 1998);
–– the strength of the personal tie
between WOM sender and receiver
(Frenzen and Nakamoto, 1993);
–– the demographic similarity (Brown
and Reingen, 1987); and
–– the perceptual affinity (Gilly et al.,
1998).
The model hypothesised in this study is based on the theory
of planned behaviour (Ajzen, 1991). In line with this theory,
the authors postulate three conceptually independent determinants of behavioral intention (shift in the WOM receiver’s brand-purchase probability). The first is the attitude
toward WOM. Attitude toward WOM is measured here
by estimating the impact of positive and negative WOM on
the shift in the receiver’s purchase probability. The second
predictor is the subjective norm, which is concerned with
judgments of the effects—direct or indirect—on the shift in
the WOM receiver’s brand-purchase probability of different
social influences (how actively WOM is sought, strength of
tie between sender and receiver, and sender’s experience and
strength of expression). The third antecedent is the degree
of perceived behavioral control, which is concerned with
perceptions of the effects, on the shift in the WOM receiver’s
brand-purchase probability, of people’s confidence in their
ability to deal with purchase situations (receiver’s experience and perceived risk). The authors argue, however, that
these three variables from the theory of planned behavior are
insufficient to permit prediction of the shift in the WOM
receiver’s brand-purchase probability. Anther variable—
past behavior (receiver’s loyalty)—could further enhance
the shift in the WOM receiver’s brand-purchase probability.
1
shift in the receiver’s purchase
probability.
It is also interesting to analyze which
type of WOM (positive or negative) has
the most impact. The literature offers little
evidence on this question.
Some studies have found that negative WOM has more impact than positive
WOM. For example, one field study found
that negative WOM has twice as much
impact on judgment or attitudes as positive WOM (Arndt, 1967). The author of
that report studied only one brand, however, and systematic research should be
based on all the brands in a category and
should include a range of categories. This
author also used a new brand about which
March 2013 JOURNAL
OF ADVERTISING RESEARCH 45
the word of mouth dynamic
2002). According to this research, when the
brand is unfamiliar, the negative informaTie strength
Sender’s
experience
Sender’s strength of
expression
tion is perceived to have more diagnosticity, but when the brand is familiar, no
significant differences exist in the impacts
of positive (or negative) information.
How actively WOM
is sought
That study argued that brand familiarity
attenuates the perception of the greater
diagnostic value of negative information
WOM COMMUNICATION
BETWEEN SENDER
AND RECEIVER
SHIFT IN RECEIVER’S
PURCHASE PROBABILITY
Positive WOM
Negative WOM
and suggested that, under these circumstances, positive information may be perceived to be more diagnostic than negative
information.
Such studies as those referenced here
How actively
WOM is sought
Receiver’s loyalty
typically measure how advice changes
judgment and/or attitude. In research on
the purchase of brands, it is more relevant
Receiver’s
experience
Receiver’s
perceived risk
to measure the change in the purchase
probability brought about by WOM type.
From this perspective, using both role-play
INTERPERSONAL
FACTORS
NON-INTERPERSONAL
FACTORS
experiments and surveys further measured WOM’s impact on choice as a shift
in the stated purchase probability, from
Figure 1 Factors Associated with Impact of Positive and
Negative WOM on Shift in Receiver’s Purchase Probability
pre-WOM purchase probability to postWOM purchase probability (East et al.,
2008). These authors contended that, if
the pre-WOM purchase probability is
there could be few established beliefs.
position implied by the WOM message
below 0.5, there is more room for change
Nevertheless, a later study confirmed the
and the receiver’s position.
in response to positive WOM than in
previous results and observes that nega-
This gap has diagnostic value: informa-
tive WOM is more influential than positive
tion that restates what the receiver believes
For example, if the pre-WOM pur-
WOM (Assael, 2004).
response to negative WOM.
may increase certainty but is unlikely to
chase probability is 0.3, positive WOM
There is some theoretical justification for
change other aspects of a receiver’s judg-
can have a maximum effect of 0.7 (up to
the idea that negative information usually
ment (e.g., purchase probability). In many
unity), whereas negative WOM can have
has more impact on judgment than posi-
markets, the greater amount of positive
a maximum effect of only 0.3 (down to 0).
tive information. Indeed, one study found
information about the different brands
That study also sought to obtain a mean
that negative information usually was
ensures that the position of most WOM
pre-WOM purchase probability of 0.4, so
rarer than positive information because
receivers is positive, so negative informa-
the authors argued that positive WOM
the latter can often be presumed (Fiske,
tion will have more impact.
usually had more effect than negative
1980). In such instances, the relative rar-
In any case, the impact of positive (or
ity of negative information surprises con-
negative) WOM may differ when the
In short, room for change in the brand-
sumers and, consequently, they pay more
brands are familiar. For example, one
purchase probability is limited by the pre-
attention to it.
study analyzed the response of consum-
WOM purchase probability, which could
WOM.
This is the so-called negativity effect,
ers receiving positive and negative infor-
favor the impact of either positive (or
which has been observed in other studies
mation about brands and compared the
negative) WOM, depending on the mean
(Chevalier and Mayzilin, 2006) and can be
results when the consumers are familiar
pre-WOM purchase probability.
expressed in terms of the gap between the
or unfamiliar with the brand (Ahluwalia,
46 JOURNAL
OF ADVERTISING RESEARCH March 2013
Thus, conceivably:
the word of mouth dynamic
H2:
Positive WOM has more impact
than negative WOM on the shift
Tie strength
Closeness, Intimacy,
Support, Association
in the receiver’s brand-purchase
probability when the pre-WOM
purchase probability is low.
WOM TYPE
Sender’s experience
Knowledge, Competence,
Education, Experience
in the product category
INTERPERSONAL FACTORS ASSOCIATED
WITH IMPACT OF POSITIVE AND NEGATIVE
WOM ON SHIFT IN RECEIVER’S PURCHASE
PROBABILITY
Positive WOM
Figure 2 summarizes the characteristics
WOM is sought; strength of tie between
and strength of expression), the relation
H5 (+)
H4 (+)
How actively WOM is sought
Selective exposure to WOM
Predisposition towards WOM
of the interpersonal factors (how actively
sender and receiver; sender’s experience
Sender’s strength of expression
Convincing arguments
H6 (+)
Negative WOM
between them, and their impact on the
H3 (+)
SHIFT IN RECEIVER’S PURCHASE PROBABILITY
shift in the receiver’s purchase probability.
HOW MARKETERS ACTIVELY SEEK WOM
The active search for information through
WOM is defined as “the process of seeking and paying attention to personal
Figure 2 Interpersonal Factors: Impact on Shift in Receiver’s
Purchase Probability
communications.”
Associated with the process of active
of the relationship between the WOM
and receiver will be more familiar with
search for information through WOM is
receiver who must make the decision and
each other, and the receiver will attribute
the selective exposure to the messages
the WOM sender (Duhan, Johnson, Wilcox,
greater credibility to the sender. Moreover,
deriving from WOM communication,
and Harell, 1997): in other words, in func-
the receiver will be more likely to initiate
which, in turn, implies that the consumer
tion of their tie strength. The tie strength
an active search for information.
has a greater predisposition toward the
of a relationship is considered to be high
WOM message (Arndt, 1967).
when the sender knows the receiver per-
Thus, a message that is sought actively
sonally. Moreover, the tie strength contains
will have a greater impact on the shift in
the following interpersonal dimensions
the WOM receiver’s purchase probability
(Frenzen and Davis, 1990):
than one that is received passively and is
moreover unsought and unrequested.
The authors’ third hypothesis follows:
H3: The more intense the WOM
In light of the preceding, the fourth
hypothesis is as follows:
H4:
The stronger the tie between
the sender and the receiver, the
more actively the receiver will
• closeness,
seek information through the
• intimacy,
two types of WOM (positive or
• support, and
negative).
• association.
SENDER’S EXPERIENCE AND STRENGTH
(positive or negative) receiver’s
active search for information,
Tie strength, therefore, reflects the relation
OF EXPRESSION
the greater the shift in the receiv-
and the type of tie existing between two
The WOM sender’s experience conceiv-
er’s purchase probability.
people.
ably will affect the way the WOM is
A later work suggested that a high tie
perceived.
TIE STRENGTH
strength will have a stronger influence
Specifically, the receiver will seek infor-
Sources of WOM recommendation can
on the receiver’s behavior than a weak tie
mation more actively from a sender seen as
be classified according to the similarity of
strength (Frenzen and Nakamoto, 1993).
expert: in other words, someone who has
the parties and the proximity or closeness
When the tie is strong, the WOM sender
a high level of knowledge, competence,
March 2013 JOURNAL
OF ADVERTISING RESEARCH 47
the word of mouth dynamic
education, and experience in the product
category (Netemeyer and Bearden, 1992).
By contrast, if the receiver perceives the
sender’s knowledge, competence, education, and experience in the product cat-
SHIFT IN RECEIVER’S PURCHASE PROBABILITY
WOM TYPE
H7 (–)
H3 (+)
egory is low, the receiver is likely to be less
Receiver’s loyalty
Motivation for processing positive WOM
Resistance to being persuaded by negative WOM
predisposed to seek or request information from the sender to form an intention
or make a purchase decision.
The fifth hypothesis of the current study
Positive WOM
is as follows:
H5:
How actively WOM is sought
Selective exposure to WOM
Predisposition towards WOM
H8 (–)
The greater the receiver’s perception of the sender’s expe-
H10 (+)
Negative WOM
rience, the more actively the
Receiver’s experience
Receiver’s perceived risk
H9 (–)
Confidence about ability to
Subjective expectation of losses
make an appropriate decision
Individual characteristic
receiver will seek information
through the two types of WOM
(positive or negative).
Conversely, the WOM sender’s strength
of expression can be defined as the WOM
receiver’s perception of the extent to which
Figure 3 Non-Interpersonal Factors: Impact on Shift in
Receiver’s Purchase Probability
the sender uses convincing arguments in
their positive (or negative) WOM.
with an interpersonal factor (how actively
market experience (Matos and Vargas,
sender’s
WOM is sought), and their impact on the
2008; Sweeney, Soutar, and Mazzarol, 2008).
strength of expression will directly affect
shift in the receiver’s purchase probability.
Conceivably,
the
WOM
the impacts of the positive and negative
Thus,
the
conceptual
framework
proposes
WOM communication on the shift in the
Receiver’s Loyalty
receiver’s future purchase probability
The loyalty of the receiver of the positive
(East et al., 2008).
(or negative) WOM communication about
prior brand loyalty, the weaker
a brand can conceivably help explain the
the impact of positive and nega-
shift in their future purchase probability.
tive WOM about the brand on
This leads to the following hypothesis:
H6:
H7:
The greater the WOM receiver’s
The greater the WOM send-
Loyal receivers have a stronger moti-
er’s strength of expression, the
vation for processing new positive infor-
greater the shift in the purchase
mation (positive WOM) about the brand
probability of the consumer who
they purchase habitually to reduce their
Receiver’s Experience
has received positive (or nega-
cognitive
(Wangenheim,
Various studies have suggested that a
tive) WOM.
2005) and reinforce their future purchase
negative relation exists between the con-
behavior.
sumer’s experience and the active search
NON-INTERPERSONAL FACTORS
dissonance
the shift in the receiver’s purchase probability.
Furthermore, loyal receivers will have
for external information before making
ASSOCIATED WITH IMPACT OF POSITIVE
a strong resistance to being persuaded
a purchase decision (Bansal and Voyer,
AND NEGATIVE WOM ON SHIFT IN
by negative information (negative WOM)
2000; Mishra, Umesh, and Stern, 1993).
RECEIVER’S PURCHASE PROBABILITY
about the brand they purchase habitu-
This is because the expert receiver already
Figure 3 summarizes the characteristics of
ally and will try to convince themselves
possesses sufficient knowledge about the
the non-interpersonal factors (receiver’s
that their previous decisions were right
product category and has no need to con-
loyalty, experience, and perceived risk),
and that the negative recommendation is
sult with other people before making a
the relation between them, their relation
the result of the WOM senders’ one-off
decision.
48 JOURNAL
OF ADVERTISING RESEARCH March 2013
the word of mouth dynamic
By contrast, WOM receivers with little
experience or knowledge about the product category are likely to lack confidence
about their ability to make an appropriate,
satisfying decision. Thus, they will feel the
need to consult with other consumers.
A relation conceivably exists between WOM
receivers’ experience in the product category
and their perceived risk in its purchase.
Hypothesis 8 of this work follows:
information about the product. WOM is
H8:
The greater the WOM receiver’s
one of the most effective sources of infor-
experience, the less actively they
mation for reducing the risk associated
will seek information through
with the purchase of a particular product
the two types of WOM (positive
(Guo, 2001).
or negative).
• their use and consumption is very widespread, and
• consumers are likely to perceive risk in
the purchase decision.
People who perceive more risk in a pur-
The nature of the choices helped ensure
chase situation tend to seek information
that the authors could gather a sample
Receiver’s Perceived Risk
through WOM more actively than those
of subjects that had received positive (or
A perceived risk is defined as a “subjec-
who perceive a lower risk (Arndt, 1967).
negative) WOM communications from
tive expectation of losses” (Dholakia, 1997,
WOM, in fact, may be the most import-
people unconnected to the different mar-
p. 161). The perceived risk variable is tied
ant information source for reducing risk
ket players.
to each product category, so the purchase
(Bansal and Voyer, 2000). It also has the
The study participants were recruited
of different product categories is associ-
strongest impact on the receiver of the
randomly in various shopping centers in
ated with different levels of perceived risk.
communication, mainly because it permits
northern Spain. To ensure familiarity, the
Perceived risk also is an individual char-
clarification of any doubts and offers the
consumers interviewed had to own and
acteristic, as different people can perceive
chance of leaving feedback (Murray and
use a mobile telephone or laptop com-
different levels of risk when purchasing
Schlacter, 1990).
puter or use the services of a mobile-phone
the same product.
The final hypothesis of the current
A relation conceivably exists between
study:
company or travel agency. They also had
to have received, in the past 3 months,
WOM receivers’ experience in the prod-
positive (or negative) WOM for different
uct category and their perceived risk in
H10: The greater the receiver’s per-
its purchase. Consumers who are less
ceived risk in relation to the pur-
experienced in a particular product cat-
chase of the product, the more
After this random sampling system, the
egory probably will perceive more risk
actively they will seek informa-
authors obtained information from a sam-
in that purchase and, from the informa-
tion through the two types of
ple of 1,100 individuals. They excluded
tion economics perspective, they will
WOM (positive or negative).
65 questionnaires due to incomplete data,
gain more from the information that the
brands of the aforementioned products or
services.
which resulted in a net sample size of
WOM sender provides (Gilly et al., 1998).
METHODOLOGY
The penultimate hypothesis of this work
Sample and Data Collection
follows:
To test the 10 hypotheses, the authors
product or service. The sample, therefore,
1,035.
Each subject was asked about only one
chose two consumer durables product
consisted of 1,035 different individuals.
the
markets: mobile phones and laptop com-
Furthermore, the sample consisted of
receiver of the two types of
puters; and two services: mobile-phone
actual consumers of the products or ser-
WOM (positive or negative), the
companies and travel agencies.
vices analyzed, not of students.
H9: The
more
experienced
lower the perceived risk associated with the purchase of the
These products and services were cho-
The distribution of the subjects by prod-
sen because
ucts/services was as follows (Table 1):
• consumers need to make evaluations
• 258 subjects owned and used a mobile
product/service.
In an effort to reduce the risk associated
and comparisons when purchasing
with a purchase decision, consumers seek
them (high involvement),
phone,
• 253 owned and used a laptop,
March 2013 JOURNAL
OF ADVERTISING RESEARCH 49
the word of mouth dynamic
Table 1
Sample Characteristics
for each construct. They also consulted
five practitioners and academic experts.
Any problematic items were either deleted
Product – Service
or appropriately modified.
Mobile
Mobile-phone
phone Laptop services
Travel agency
services
Total
items to 20 consumers of the products
SUBJECTS
258
253
268
256
1,035
and services analyzed in this research in
Male (%)
46.8
53.8
44.6
46.2
47.7
face-to-face meetings to ensure that the
Female (%)
53.2
46.2
55.4
53.8
52.3
questions were worded with appropri-
Between 18 and 34 (%)
49.4
47.8
44.5
40.1
45.4
Between 35 and 54 (%)
38.3
43.5
42.2
38.6
40.5
Over 54
12.3
8.7
13.3
21.3
14.1
Positive WOM (%)
52.4
54.2
50.8
53.1
52.6
Negative WOM (%)
47.6
45.8
49.2
46.9
47.4
The authors presented the resulting
ate consistency. They then revised several
items on the basis of the feedback. Finally,
to measure each of the constructs of interest, they adopted single-item and multiitem scales (Appendix).
The authors used three single-item
measures to capture information about
brand-purchase probability before receiv-
• 268 used the services of a mobile-phone
company, and
• 256 used a travel agency.
The distribution by gender was 47.7 percent male and 52.3 percent female. A total
of 45.4 percent of the respondents were
If they had received a number of
ing the WOM recommendation (receiver’s
WOM communications, they were asked
loyalty), brand-purchase probability after
to consider the single communication
receiving the WOM recommendation, and
they felt had had the most impact on their
sender’s strength of expression.
decision.
The questionnaire then asked survey
participants about the following:
between ages 18 and 34 years, 40.5 percent
A single-item measure is sufficient if
the construct is such that in the mind of
“raters” (e.g., respondents in a survey),
the object or attribute of the construct is
between 35 and 54 years, and 14.1 percent
• the brand that was the subject of the
“concrete,” meaning that it consists of one
older than 54 years. Finally, 52.6 percent
positive (or negative) recommendation;
object or attribute that is easily and uni-
of the respondents had received positive
WOM, whereas 47.4 percent had received
negative WOM.
The authors collected the information
they required using structured questionnaires presented in the course of personal
interviews. The first part of the ques-
formly imagined (Bergkvist and Rossiter
• a number of points relating to the WOM
sender:
or the attribute (how convincing/cred-
–– experience in the product/service cat-
ible were the explanations of the person
egory, and
–– credibility of arguments used; and
• the probability of choosing the brand
category, their current brand, their ten-
before and after the positive (or nega-
dency to ask for advice before making the
tive) recommendation.
purchase, and their perception of the risk
focused on the WOM received by the
who sent the WOM) is concrete, so the
authors used single-item measures to capture information about brand-purchase
receivers) about their experience with the
The second part of the questionnaire
In the current study, the object (brand)
–– strength of relationship with them,
tionnaire asked the respondents (WOM
in the purchase.
2007, 2009).
probability (a 10-point scale) and sender’s
strength of expression (7-point scale).
The shift in the receiver’s brandpurchase probability was calculated as
The questionnaire concluded with ques-
the difference between the probability of
tions about the age and gender of the
choosing the brand after and before the
respondents.
recommendation.
individuals. The interviewees were asked
The authors also use multi-item meas-
whether they had received many or only
Variable Measures
ures to capture information about five
a few positive (or negative) WOM com-
Using construct definitions and pre-
constructs linked to interpersonal and
munications about a particular product or
existing measures available from the liter-
non-interpersonal factors of the WOM
service in recent months.
ature, the authors generated a set of items
communication:
50 JOURNAL
OF ADVERTISING RESEARCH March 2013
the word of mouth dynamic
• how actively WOM is sought,
• tie strength,
• sender’s experience,
• receiver’s experience, and
• receiver’s perceived risk.
Another problem that the authors considered was
common-method bias, which occurs when the
correlation between two or more constructs is high.
To evaluate each of these measures, the
authors used 7-point scales. The principal
The results obtained allowed the authors
examined. Together, these tests provide
theoretical argument for using a multi-
to identify five factors corresponding to
evidence of reliability and validity. See
item measure of a construct is that a multi-
interpersonal and non-interpersonal con-
Appendix for a summary of the scales’
item measure captures more information
structs of the WOM communication. The
psychometric
and is more likely to tap all facets of the
factor loadings were high in each of the
obtained from the measurement model.3
construct of interest (Bergkvist and Ros-
five dimensions identified, and the factors
siter, 2007, 2009). Another argument for
together explained 85 percent of the vari-
RESULTS
multiple items is that it increases reliabil-
ance (KMO = 0.897).
Descriptive Analysis: Impact of WOM
properties,
which
were
Communications on Purchase Probability
ity by allowing the calculation of the coef-
As a result, the common-method bias
ficient alpha, which indicates the “internal
was not a problem for the current analysis,
Descriptive analysis (using SPSS) was
consistency” of all the items that represent
so multi-item measures could be used in
employed to test the hypothesized rela-
the presumed underlying construct.
subsequent analyses to obtain information
tions H1 and H2 in the four product/ser-
This “reliability” argument, however,
about the constructs linked to interper-
vice categories. Table 2 (col. 1) shows the
needs to be qualified. The coefficient alpha
sonal and non-interpersonal factors of the
categories. Columns 2 and 3 are the pur-
never should be used without first estab-
WOM communication.
chase probabilities prior to positive and
negative WOM, respectively, and columns
lishing the unidimensionality of the scales;
this can be investigated by factor analysis.
Data Analysis: The Measurement Model
4 and 5 are the mean shifts in the purchase
Thus, the authors ran five exploratory fac-
The data analysis employed a two-step
probability produced by positive and neg-
tor analyses for the constructs linked to
procedure. The measurement model was
ative WOM, respectively.
interpersonal and non-interpersonal fac-
estimated for the entire sample (positive
According to these results, positive
tors of the WOM communication. These
and negative WOM receivers) prior to the
WOM has a positive impact, and negative
tests confirmed the unidimensionality of
analysis of the structural model.2 All vari-
WOM has a negative impact on the shift in
each of the five scales, which means the
ables of interest were conceptualized as
the receiver’s brand-purchase probability.
coefficient alpha can be used.
reflective first-order constructs. A meas-
H1 is supported.
The resulting coefficient alphas were
urement model including how actively
Furthermore, when the mean impacts of
high, indicating “internal consistency”
WOM is sought, tie strength, sender’s
positive and negative WOM are measured
and supporting the use of multi-item
experience, receiver’s experience and per-
as the shift in purchase probability, posi-
measures to capture information about
ceived risk was subjected to confirmatory
tive WOM produces a mean shift of 1.8542,
the constructs linked to interpersonal and
factor analysis using structural equation
and negative WOM produces a mean shift
non-interpersonal factors of the WOM
modeling (with EQS).
As a result, a 22-item, five-factor covari-
communication (See Appendix).
Another problem that the authors con-
ance structure measurement model was
sidered was common-method bias, which
estimated to assess the fit, reliability, and
occurs when the correlation between two
validity of the measurement scales of the
or more constructs is high. To analyze
model constructs. In addition, the average
common-method bias, the authors ran
variance extracted (AVE), the composite
an exploratory factor analysis with all
reliability coefficient (CR), and the stand-
the attributes linked to interpersonal and
ardized lambda parameters also were
non-interpersonal factors of the WOM
2
communication.
The results of the structural model (causal analysis) can be
seen in the Results section.
The measurement model fits the data well. Regarding
reliability, each construct has a composite reliability and
AVE greater than the recommended threshold values of 0.5
and 0.6, respectively. In addition, for all constructs, the
Cronbach alpha coefficient exceeds 0.9. Convergent validity
is supported as all lambda parameters are significant and
greater than 0.5. Discriminant validity is supported, as
the confidence intervals of the correlations between all the
variables do not include 1.0 and the squared correlations
do not exceed the AVE. Finally, the fit statistics indicate a
good model fit (Root Mean Square Error of Approximation
= 0.065; Bentler-Bonett Non-Normed Fit Index = 0.955;
General Fit Index = 0.966; robust Comparative Fit Index
= 0.961).
3
March 2013 JOURNAL
OF ADVERTISING RESEARCH 51
the word of mouth dynamic
Table 2
Impact of Positive and Negative WOM on Shift in Receivers’
Purchase Probability
hypotheses in the two subsamples: consumers who had received positive WOM
or negative WOM (Table 4).�
Most of the proposed relations are
Purchase probability
Shift in purchase probability
Product/Service
Category
Prior to
positive WOM
Prior to
negative WOM
Shift after
positive WOM
Shift after
negative WOM
Mobile phone
4.4336
4.5245
1.7310
−1.4951
Laptop
4.4389
4.6631
1.9005
−1.6631
Mobile-phone services
3.6892
3.7330
1.7149
−1.5519
Travel agency
4.6347
4.9896
1.8767
−1.7187
TOTAL
4.2984
4.4721
1.8542
−1.6261
supported in both subsamples: consumers who had received positive (or negative) WOM. Thus, the more intense the
receiver’s active search for information
and sender’s strength of expression, the
greater the shift in the brand-purchase
probability (See Table 4).
Thus, H3 and H6 are supported.
The results also confirm the influence
of sender’s experience, receiver’s experience, and receiver’s perceived risk on how
Descriptive analysis: impact of receivers’ loyalty on purchase probability
actively WOM is sought, and H5, H8, and
of –1.6261, which means positive WOM is
impact of positive and negative WOM on
14 percent more influential than negative
the brand-purchase probability.
H10 are supported.
The results also show that H9 is sup-
WOM. When absolute numbers are tested,
ported in both subsamples: the greater the
positive WOM has significantly more
Causal Analysis: Structural Model
experience of the receiver of the positive
impact than negative WOM in the means
Evaluation
(or negative) WOM communication, the
data and across categories of products
The authors used structural-equation
lower the risk perceived in the purchase of
(p < 0.001 one-tailed exact tests).
modeling (with EQS) to test the remaining
the product/service.
Thus, analyzing the shifts in purchase
probability, H2 is supported. Overall, positive WOM has more impact that negative
Table 3
Mean Shift in Brand Purchase Probability as Function of Loyalty
WOM.
The authors also used descriptive analysis (with SPSS) to test the hypothesized
relation H7 in the four product/service
categories. The results do show that the
Purchase probability prior to
WOM (receiver’s loyalty)
Mean shift in purchase
probability after positive
WOM
Mean shift in purchase
probability after negative
WOM
X-axis
Y-axis
Y-axis
greater the WOM receiver’s previous loy-
0
1.2206
0.0000
alty, the weaker the impact of both posi-
1
1.5778
−0.3846
tive and negative WOM communications
2
1.9029
−0.9526
3
2.2857
−1.2806
tion between previous brand loyalty and
4
2.4240
−1.6907
shift in the brand purchase probability in
5
2.5563
a more accessible form. For both positive
−2.1852
6
1.9337
−2.5957
7
1.3508
−2.5222
then deflects toward the x-axis. These
8
0.7143
−1.6870
deflections can be attributed to the effect
9
0.6471
of brand commitment and show how this
−0.7143
10
0.0000
−0.4667
16.6132
−14.4796
on the shift in the brand-purchase probability. Table 3 and Figure 4 present the rela-
and negative WOM, a relatively straight
section on each plot is evident, which
factor constrains the impact.
Thus, this work provides support for
H7: the receiver’s loyalty reduces the
52 JOURNAL
OF ADVERTISING RESEARCH March 2013
TOTALS
The relation between previous brand loyalty and shift in the brand purchase
the word of mouth dynamic
3,0000
2,8750
Negative WOM
Positive WOM
2,7500
Mean shift in purchase probability after positive and negative WOM
2,6250
2,5000
2,3750
2,2500
2,1250
2,0000
1,8750
1,7500
1,6250
1,5000
1,3750
1,2500
1,1250
1,0000
0,8750
0,7500
0,6250
0,5000
0,3750
0,2500
0,1250
0,0000
0
1
2
3
4
5
6
7
8
9
10
Purchase probability prior to WOM (receiver’s loyalty)
Figure 4 Mean Shift in Purchase Probability after Positive and Negative WOM
The results, however, only partially
DISCUSSION AND CONCLUSIONS
Furthermore, this work differs from
support the influence of the strength of
WOM long has been recognized as a pow-
most earlier studies on WOM in that the
the tie between sender and receiver on
erful force affecting consumers’ attitude
authors investigated various brands in a
how actively WOM is sought. The param-
and choice. The results of the current study
range of categories of products (mobile
eters obtained are significant for the
enhance current understanding of how
phones and laptops) and services (mobile-
subsample of consumers who received
WOM influences the receiver’s choice.
phone
companies
and
travel
agen-
positive WOM but non-significant for the
This article, unlike previous studies,
cies). From this perspective, this study
subsample of consumers who received
represents an attempt to explicitly test the
makes various contributions to the lit-
negative WOM.
differential impact of positive and nega-
erature on WOM communications in
tive WOM on the mean shift in the brand-
marketing.
H4 is supported for positive WOM but
not for negative WOM.
purchase probability.
Specifically:
March 2013 JOURNAL
OF ADVERTISING RESEARCH 53
the word of mouth dynamic
Table 4
Structural Models: Parameter Estimates
Positive WOM
subsample
Hypothesised paths
Supported
Negative WOM
subsample
Supported
H3: How actively WOM is sought → Shift in brand purchase probability
0.226**
YES
−0.065*
YES
H4: Tie strength → How actively WOM is sought
0.096**
YES
0.015
NO
H5: Sender’s experience → How actively WOM is sought
0.155**
YES
0.135**
YES
H6: Sender’s strength of expression → Shift in brand purchase probability
0.489**
YES
−0.440**
YES
H7: Receiver’s loyalty → Shift in brand purchase probability
−0.325**
YES
−0.426**
YES
H8: Receiver’s experience → How actively WOM is sought
−0.159**
YES
−0.126
YES
H9: Receiver’s experience → Receiver’s perceived risk
−0.218**
YES
−0.219**
YES
H10: Receiver’s perceived risk → How actively WOM is sought
0.646**
YES
0.659**
YES
Bentler-Bonett Non-normed Fit Index (BBNNFI)
0.910
0.915
Comparative Fit Index (CFI)
0.919
0.923
General Fit Index (GFI)
0.924
0.928
Root Mean Square Error of Approximation (RMSEA)
0.075
0.080
1231.1561
(0.000)
Satorra-Bentler Scaled Chi Square S-Bχ2
(probability value)
1279.0923
(0.000)
Standardised parameters are shown (**p < 0.01)
• The empirical analysis shows that positive (negative) WOM has a positive
positive WOM having more impact than
and be more efficient if they are directed
negative WOM.
at senders with strength of expression
(negative) impact on the shift in the
receiver’s
brand-purchase
and receivers who are motivated to seek
probabil-
• The results also show that the same
ity. The results also show that positive
interpersonal factors govern the impact
Firms also should pay particular
WOM has a stronger impact on brand-
of both positive and negative WOM
attention to the potential influence of
purchase
on the shift in the receiver’s brand-
negative WOM, as these communica-
purchase probability. The authors can
tions reduce the purchase probability.
probability
than
negative
WOM.
information through WOM.
An explanation for positive WOM’s
conclude that the sender’s strength of
Consequently, companies should also
stronger effect in this study is that the
expression has the greatest influence for
adopt decisions about marketing strat-
prior purchase probability tends to be
both positive and negative WOM, fol-
egies directed at senders and receivers
below 5 on a 10-point scale. In particu-
lowed by how actively WOM is sought.
with the objective of minimizing the
lar, the prior purchase probability is
The findings of this study suggest that
sending of negative WOM and/or the
4.2984 for the positive WOM subsample
when the sender’s strength of expres-
effects of exposure to negative commu-
and 4.4721 for the negative WOM sub-
sion is high and when WOM (positive or
nications of people motivated to seek
sample. This situation leaves more room
negative) is actively sought, WOM will
advice actively.
for change in response to positive WOM
have a significant influence (positive or
than in response to negative WOM.
negative) on the shift in the receiver’s
interpersonal factors on the receiver’s
brand-purchase probability.
decision is stronger when the WOM
Thus, the results suggest that nega-
Nevertheless,
the
effect
of
both
tive WOM is less diagnostic than posi-
Thus, marketing strategies designed
information is positive (positive WOM)
tive WOM. There is a “positivity effect”
to promote interpersonal communica-
than when it is negative (negative
(using Fiske’s gap explanation), with
tion will reach more senders/receivers
WOM).
54 JOURNAL
OF ADVERTISING RESEARCH March 2013
the word of mouth dynamic
• The
current
findings
support
the
the less intense will be the active search
WOM messages and increase their effec-
hypothesis that level of receiver’s loy-
for information (positive or negative
tiveness. At the same time, companies
alty (a non-interpersonal factor) reduces
WOM).
should clearly also make efforts to avoid
the impact of both positive and nega-
Furthermore, the greater the receiv-
tive WOM on the shift in the receiver’s
er’s experience, the less risk they will
Thus, academics and marketing direc-
purchase probability. Thus, the effect of
perceive in the purchase; and the greater
tors should pay more attention to the
WOM (positive or negative) is condi-
the perceived risk, the more active the
management of WOM, as WOM can
tioned by the receiver’s previous loyalty.
search for WOM information (positive
complement the firm’s policy of advertis-
or negative WOM).
ing communication and, hence, increase
As the receiver’s level of loyalty
toward a brand increases, positive and
negative WOM.
its efficacy. Likewise, not only are both
negative WOM about that brand will
• For both positive and negative WOM,
types of communication complementary,
have less impact on the shift in the
the receiver’s perceived risk has the
which improves the firm’s performance,
future purchase probability. Looking at
strongest positive effect, followed by the
but traditional media and marketing com-
the plots in Figure 4, positive messages
receiver’s experience (negative effect),
munications have a significant role to play
(positive WOM) clearly have more
sender’s experience (positive) and, to
in influencing conversations. Firms can
impact when the receiver’s pre-WOM
a lesser extent, strength of tie between
use advertising to spread messages in the
loyalty is from 0 to 6, whereas negative
sender and receiver (positive influence
media that stimulate consumers to speak
messages (negative WOM) have more
only for positive WOM).
favorably about their brands and say good
influence in the range 4 to 7 (See Figure 4).
things about their products.
Thus, the potential impact of WOM
The practical implication of these empiri-
This ideal situation, however, will hap-
(positive or negative) can be estimated
cal results is that companies should pay
pen only if the brand is credible, the firm’s
for any segment of consumers if the
particular attention to the consumers who
products/services are reliable, and its
mean pro-WOM loyalty can be assessed
are most motivated to seek advice actively
marketing activities are believable. In such
using purchase records or management
(less experienced consumers who perceive
cases, customers are very likely to initi-
judgment, for example.
more risk in the purchase) to maximize
ate more positive conversations about the
their exposure to positive communications
brand than negative ones.
• Various factors directly influence how
from senders perceived as knowledgeable
Given the need to obtain a positive WOM
actively WOM is sought and indirectly
and with whom they have strong ties and
flow from senders to receivers, companies
affect the shift in the receiver’s purchase
minimize their exposure to negative com-
should aim to keep the senders satisfied
probability.
munications from senders perceived as
by providing a good product or service,
experts.
effectively practicing sender-centered rela-
The current findings indicate that,
when senders are perceived as knowl-
tionship marketing. In this context, WOM
edgeable, the receivers are motivated
Management Implications
programs should create experiences for
to actively seek information (positive or
WOM is one of today’s most powerful
consumers and convey information that
negative WOM) from them. Thus, a sig-
marketing tools. It is reported to be one
encourages
nificant positive relation exists between
of the fastest growing sectors in market-
groups to talk freely, authoritatively, and
the two constructs.
ing and media services. Smart marketers
credibly with others.
influential
individuals
or
Likewise, when the tie between send-
have an opportunity to become a part of
Enabling consumers to co-create brand
ers and receivers is strong, the receivers
the consumer-driven WOM conversation
meaning and tell stories is essential to
are motivated to actively seek positive
through well-planned, well-researched,
WOM. Bain & Co. has reported there
WOM information (empirical evidence
and well-executed WOM marketing pro-
is no better force to drive sales growth
for negative WOM was not found).
grams—at which time, they will be well
than strong customer advocacy. Indeed,
positioned to influence consumers’ pur-
its research shows that the most recom-
chase intentions.
mended company in its category grows
Conversely, the receiver’s experience
was also found to be a significant indicator of how actively WOM is sought.
For marketers, the findings of this study
2.5 times more than the category average.
The more knowledgeable people are
suggest that companies should develop
Likewise, Booz & Co., a leading consul-
or the more experience they possess,
marketing strategies to encourage positive
tancy has advised, “Make your consumer
March 2013 JOURNAL
OF ADVERTISING RESEARCH 55
the word of mouth dynamic
an advocate: shift marketing objectives
2006, advertising-agency/WOM consult-
obtain advice about the product or service.
from sending a message to facilitating con-
ants Keller Fay has compiled data since
Firms can use market research to identify
versations with and between consumers.”
2006 that consistently show that WOM
consumers (receivers) with a moderate
Thus, companies should use marketing
conversations happen most often in off-
purchase probability or loyalty, and distin-
activities to incentivize satisfied consum-
line environments. Clearly, practitioners
guish segments with high (or low) experi-
ers with a high degree of loyalty to act as
cannot ignore the off-line conversations
ence in the product or service category.
senders of positive WOM messages, par-
that take place between people, but they
The aim is for the receivers to seek infor-
ticularly to those people (receivers) with
should also try to exploit to the maximum
mation from satisfied customers so their
whom they maintain a strong tie. It is not
the opportunities opened up by the Inter-
future purchase probability increases. An
just a question of encouraging an “endog-
net (Fong and Burton, 2006) and encourage
advertising campaign could encourage
enous WOM,” which is characterized by a
people to support WOM so the company
both segments of consumers to seek infor-
conversation that occurs naturally among
can benefit from it as soon as possible.
mation from other people: for example,
consumers as a function of the senders’
Much of the importance of the Internet
to seek information from satisfied, loyal
positive experiences with the product or
for WOM communication is grounded in
expert senders with whom they have a
service. Firms also should develop a proac-
the links between people in a social net-
strong tie or who are considered an object-
tive management of customer-to-customer
work. A recommendation is more valu-
ive, third-party source. Receivers with
communications. In other words, they cre-
able in groups that have stronger links.
experience in the product/service cat-
ate an “exogenous WOM” as a result of
People with closer relationships—married
egory and moderate brand loyalty could
its actions (effecting meaningful positive
couples or friends, for example—tend
begin to doubt and eventually conclude
WOM).
to interact more frequently than mere
that they do not possess as much experi-
acquaintances.
ence as they initially had thought.
For this purpose, companies should use
loyalty programs to incentivize satisfied
Knowing this, companies might target
Another possibility to increase the
customers to become effective dissemi-
“evangelical” customers—the most inter-
effectiveness of a positive WOM mes-
nators of information. In fact, companies
connected groups in the Internet—by
sage is to do market research to classify
should put the satisfied customer at the
analyzing social networks, cliques, or the
potential consumers (receivers with a
center of a communications campaign and
groups that such contacts create and iden-
moderate purchase probability and low
encourage them to offer potential con-
tify the most influential people in these
experience) into segments according to the
sumers detailed positive information—
groups.
risk that they primarily associate with the
convincingly argued—about the brand’s
good points.
Companies also should remember that
purchase decision. The resulting groups
the most socially connected individuals
could be addressed with differential com-
The satisfied senders’ experience and
are more liable to offer recommendations
munications and interpersonal influence
strength of expression can help them to be
and that physical proximity is not a sig-
strategies.
perceived as “opinion leaders.” It is in this
nificant variable. It is critical, therefore,
For example, potential customers high
context that a company needs to identify
that companies understand the social net-
in functional risk could be encouraged
the most dynamic consumers in the rec-
works in which consumers operate (their
to connect with satisfied, loyal expert
ommendation activity, as they can help it
links and how they operate in them) to
senders about the superiority of a firm’s
attract new customers with a minimum
extend positive WOM and minimize the
product/service. Customers with high
economic investment. Moreover, the eco-
effects of any negative WOM.
social/psychological
risk
perception
nomic value that an active customer can
In short, the diffusion of opinion lead-
could be recommended to senders in their
generate via WOM is a good means of
ers’ messages in both traditional and mod-
peer group with whom they maintain a
segmenting customers in function of their
ern communications media (e.g., social
strong tie and perceive as being similar to
capacity to influence the rest—the goal of
networks such as Facebook, Twitter, and
themselves.
all marketers.
LinkedIn) will help persuade positive
One other aspect of interest to practitioners in the strategic management of WOM:
WOM receivers to increase their brand-
Limitations and Future Lines of Research
purchase probability.
This study has a number of important
in what environment is WOM communi-
In parallel, companies also should
cation more commonly generated? Since
stimulate the desire in the receiver to
56 JOURNAL
OF ADVERTISING RESEARCH March 2013
limitations, which can be seen as starting
points for future research.
the word of mouth dynamic
It would be advisable in future work to subject the
of justice in the services markets. Other research
receivers to actual positive and negative WOM
channels, retail management, brand equity, and market
situations and record their actual purchase decision.
in the European Journal of Marketing, Industrial
interests include interfirm relationships in distribution
orientation. His recent articles have been published
Marketing Management, International Journal of
Research in Marketing, International Journal of
• The work uses retrospective data in that
the receivers must remember positive
(adoption of new products in their intro-
Service Industry Management, Journal of Applied
duction stage).
Social Psychology, Journal of Business Research,
Journal of Business and Industrial Marketing,
(or negative) WOM messages that have
Marketing Letters, Supply Chain Management, Service
had an impact on their brand choice and
• The current study analyzed only the
indicate the probability of choosing the
final outcome of the WOM (shift in the
Industries Journal, and Psychology and Marketing,
brand before and after the positive (or
purchase probability). Another obvious
among other journals.
negative) recommendation.
possibility for further research would
It would be advisable in future work
be to explore the impact of positive and
to subject the receivers to actual posi-
negative WOM on the intermediate
tive and negative WOM situations and
stages in the receiver’s decision-making
record their actual purchase decision.
process (motivation and desires, search
for information, and attributes consid-
• This study focuses on receivers who
ered in the purchase).
actively seek information: in other
words, receivers who already are inter-
• The current work focused mainly on the
ested in the product or service category.
influence of WOM. The study could be
This analysis is important, but it does
expanded to compare the effects of posi-
not shed any light on why some WOM
tive and negative WOM with those of
communications have no influence at
other types of information obtained by
all, whether positive or negative.
the receivers through different commu-
• The subsamples for the four categories
Leticia Suárez-Álvarez is an Assistant Professor of
Marketing at the University of Oviedo (Spain). Her current
research interests include relationship marketing,
tourism marketing, consumer behavior, and service
recovery strategies in the service sector. She has
presented papers at various academic meetings and
conferences. Her work has appeared in the Journal
of Applied Social Psychology, Journal of Marketing
Management, Journal of Travel Research, Management
Research, Service Industries Journal, and Psychology
and Marketing, among other journals.
nications media (e.g., advertising, direct
Ana Belén del Río-Lanza is an Associate Professor in
marketing, and the firm’s sales force).
Marketing at the University of Oviedo (Spain). Her current
research interest focuses on brand equity, consumer
analyzed have low or moderate mean
behavior, service failure, service recovery strategies, and
pre-WOM purchase probabilities, which
• The current work did not allow the
explains why negative WOM is less
authors to establish whether the receiv-
perceptions of justice in the services markets. She has
diagnostic than positive WOM. Future
ers obtain the information from face-
presented papers at various academic meetings and
research should investigate situations
to-face relationships or through social
conferences. Her recent articles have been published
where negative WOM has a stronger
networks. Given the importance of elec-
in the British Food Journal, Journal of Business
impact.
tronic WOM, it would be useful to study
Research, Journal of Product and Brand Management,
the dynamics of online WOM and prod-
Journal of Applied Social Psychology, and Marketing
uct sales.
Letters, among other journals.
• The consumers in the current study
were familiar with the brands consid-
The aim would be to study e-WOM
ered for the categories analyzed, and
via consumer opinion platforms and
the innovations that the companies had
investigate what motivates senders and
launched in the market represented
receivers to articulate themselves on the
incremental levels of novelty linked to
Internet. product re-launches.
It would be interesting to investigate
Acknowledgments
The authors thank the Spanish Ministry of Science and Innovation for the financial support
Rodolfo Vázquez-Casielles is a Professor of Marketing at
provided for this research under the 2008–2011
the impact of positive and negative
the University of Oviedo (Spain). His current research
Call for R&D Projects (MICINNECO2008-03698/
WOM in the case of radical innovations
interests include consumer behavior and perceptions
ECON).
March 2013 JOURNAL
OF ADVERTISING RESEARCH 57
the word of mouth dynamic
References
Bowman, D., and D. Narayandas. “Man-
Word-of-Mouth on Brand Purchase Probabil-
aging Customer-Initiated Contacts with Man-
ity.” International Journal of Research in Marketing
Ahluwalia, R. “How Prevalent Is the Negativ-
ufacturers: The Impact on Share of Category
25 (2008): 215–224.
ity Effect in Consumer Environments?” Journal
Requirements and Word-of-Mouth Behaviour.”
of Consumer Research 29 (2002): 270–279.
Journal of Marketing Research 38 (2001): 281–297.
Ajzen, I. “The Theory of Planned Behavior.”
Brown, J. J., and P. H. Reingen. “Social Ties
Word-of-Mouth: A Multi-Category Study.”
Organizational Behavior and Human Decision Pro-
and Word-of-Mouth Referral Behaviour.” Jour-
International Journal of Research in Marketing 24
cess 50, 2 (1991): 179–211.
nal of Consumer Research 14, 3 (1987): 350–362.
(2007): 175–184.
Brown, T. J., T. E. Barry, P. A. Dacin, and R.
Fiske, S. T. “Attention and Weight in Per-
East, R., K. Hammond, and M. Wright. “The
Relative Incidence of Positive and Negative
Allsop, D. T., B. R. Bassett, and J. A. Hoskins.
“Word-of-Mouth
Research:
Principles
and
Applications.” Journal of Advertising Research 47,
4 (2007): 398–411.
Anderson, E. W. “Customer Satisfaction and
Word-of-Mouth.” Journal of Service Research 1, 1
(1998): 5–17.
F. Gunst. “Spreading the Word: Investigating
son Perception: The Impact of Negative and
Antecedents of Consumers’ Positive Word-of-
Extreme Behaviour.” Journal of Personality and
Mouth Intentions and Behaviours in a Retailing
Social Psychology 38, 6 (1980): 889–906.
Context.” Journal of the Academy of Marketing Science 33, 2 (2005): 123–138.
Fitzsimons, G. J., and D. R. Lehmann. “When
Unsolicited Advice Yields Contrary Responses.”
Bruyn, A., and G. Lilien. “A Multi-Stage
Marketing Science 23, 1 (2004): 82–95.
Model of Word-of-Mouth Influence Through
Arndt, J. “Role of Product-Related Conversations in the Diffusion of a New Product.” Journal
of Marketing Research 1, 4 (1967): 291–295.
Assael, H. Consumer Behaviour: A Strategic
Approach. Boston, MA: Houghton Mifflin Company, 2004.
Viral
Marketing.”
International
Journal
of
Research in Marketing 25, 3 (2008): 151–163.
Fong, J., and S. Burton. “Electronic Word-ofMouth: A Comparison of Stated and Revealed
Behavior on Electronic Discussion Boards.”
Chevalier, J. A., and D. Mayzlin. “The
Journal of Interactive Advertising 6, 2 (2006),
Effect of Word-of-Mouth on Sales: Online Book
61–70.
Reviews.” Journal of Marketing Research 43, 3
(2006): 345–354.
Frenzen, J. K., and H. L. Davis. “Purchasing
Behaviour in Embedded Markets.” Journal of
Dholakia, U. M. “An Investigation of the
Bansal, H., and P. A. Voyer. “Word-of-Mouth
Processes within a Services Purchase Decision
Consumer Research 17 (1990): 1–12.
Relationship Between Perceived Risk and
Product Involvement.” In Advances in Con-
Frenzen, J. K., and K. Nakamoto. “Structure,
sumer Research, M. Brucks and D. MacInnis, eds.
Cooperation and the Flow of Market Informa-
Provo, UT: Association for Consumer Research,
tion.” Journal of Consumer Research 20 (1993):
1997.
360–375.
of Marketing Efforts.” Journal of Advertising
Dick, A., and K. Basu. “Customer Loyalty:
Gilly, M. C., J. L Graham, M. F. Wolfin-
Research, 25, (June/July) (1985): 31–39.
Toward an Integrated Conceptual Framework.”
barger ,
Journal of the Academy of Marketing Science 22
Interpersonal Information Search.” Journal of the
(1994): 99–113.
Academy of Marketing Science 26, 2 (1998): 83–100.
Context.” Journal of Service Research 3, 2 (2000):
166–177.
Bayus, B. “Word of Mouth: The Indirect Effects
Bergkvist, L., and J. R. Rossiter. “The
and L. J. Yale. “A Dyadic Study of
Predictive Validity of Multiple-Item versus
Single-Item Measures of the Same Constructs.”
Duhan, D. F., S. D. Johnson, J. B. Wilcox,
Goldsmith, R., and D. Horowitz. “Measuring
Journal of Marketing Research 44, May (2007):
and G. D. Harrell. “Influences on Consumer
Motivations for Online Opinion Seeking.” Jour-
175–184.
Use
nal of Interactive Advertising 6, 2 (2006): 1–16.
of
Word-of-Mouth
Recommendation
Sources.” Journal of the Academy of Marketing SciBergkvist, L., and J. R. Rossiter. “Tailor-Made
ence 25, 4 (1997): 283–295.
Single-Item Measures of Doubly Concrete Con-
Gounaris, S., and V. Stathakopoulus. “Antecedents and Consequences of Brand Loyalty:
structs.” International Journal of Advertising 28, 4
East, R., K. Hammond, and W. Lomax. “Meas-
An Empirical Study.” Journal of Brand Manage-
(2009): 607–621.
uring the Impact of Positive and Negative
ment 11, 4 (2004): 283–306.
58 JOURNAL
OF ADVERTISING RESEARCH March 2013
the word of mouth dynamic
Graham, J., and W. Havlena. “Finding the
Growth.“ Journal of Advertising Research 47, 4
Measurement and Analysis of Marketing 12, 1
‘Missing Link’: Advertising’s Impact on Word
(2007): 448–452.
(2003): 82–90.
Lacey, R., J. Suh, and R. M. Morgan. “Differen-
Sichtmann, C. “An Analysis of Antecedents
tial Effects of Preferential Treatment Levels on
and Consequences of Trust in a Corporate
Gruen, T. W., T. Osmonbekov, and A. J.
Relational Outcomes.” Journal of Service Research
Brand.” European Journal of Marketing 41, 9/10
Czaplewski. “eWOM: The Impact of Customer-
9, 3 (2007): 241–256.
(2007): 999–1015.
of Mouth, Web Searches and Site Visits.” Journal
of Advertising Research 47, 4 (2007): 427–435.
to-Customer Online Know-How Exchange on
Customer Value and Loyalty.” Journal of Busi-
Matos, C. A., and A. Vargas. “Word-of-
ness Research 59, 4 (2006): 449–456.
Mouth Communications in Marketing. A
Meta-Analytic Review of the Antecedents and
Guo, C. “A Review on Consumer External
Moderators.” Journal of the Academy of Marketing
Search: Amount and Determinants.” Journal of
Science 36 (2008): 578–596.
Smith, T. J. Coyle, E. Lightfoot, and A. Scott.
“Reconsidering Models of Influence: The Relationship between Consumer Social Networks
and Word-of-Mouth Effectiveness.” Journal of
Advertising Research 47, 4 (2007): 387–397.
Business and Psychology 15, 3 (2001): 505–519.
Maxham, J. G., and R. G. Netemeyer. “A
Harrison-Walker, L. J. “The Measurement of
Word-of-Mouth Communication and Investigation of Service Quality and Customer Commitment as Potential Antecedents.” Journal of
Service Research 4, 1 (2001): 60–75.
Heitmann, M., D. R. Lehmann, and A. Hermann .
“Choice Goal Attainment and Decisions
and Consumption Satisfaction.” Journal of Marketing Research 44 (2007): 234–250.
Henning-Thurau, T., K. P. Gwinner, G.
Walsh, and D. D. Gremler. “Understanding
Relationship Marketing Outcome: An Integration of Relational Benefits and Relationship
Marketing.” Journal of Service Research 4, 3
(2002): 230–247.
Longitudinal Study of Complaining Customers’ Evaluations of Multiple Service Failures
zarol .
“Factors Influencing Word-of-Mouth
and Recovery Efforts.” Journal of Marketing 66,
Effectiveness: Receiver Perspectives.” European
4 (2002): 57–71.
Journal of Marketing 42, 3/4 (2008): 344–364.
Mishra, S., U. N. Umesh, and D. E. Stern.
Wangenheim,
“Antecedents of the Attraction Effect: An
Word-of-Mouth.” Journal of Service Research 8, 1
Information-Processing Approach.” Journal of
(2005): 67–78.
F.
“Postswitching
Negative
Marketing Research 30 (1993): 331–349.
Wangenheim, F., and T. Bayon. “SatisfacMurray, K. B., and J. L. Schlacter. “The
tion, Loyalty and Word-of-Mouth within the
Impact of Services Versus Goods on Consum-
Customer Base of a Utility Provider: Differ-
ers’ Assessment of Perceived Risk and Variabil-
ences Between Stayers, Switchers and Referral
ity.” Journal of the Academy of Marketing Science
Switchers.” Journal of Consumer Behaviour 3, 3
18, 1 (1990): 51–65.
(2004a): 211–220.
Netemeyer, G. R., and W. O. Bearden. “A
Comparative Analysis of Two Models of Behavioural Intention.” Journal of the Academy of Mar-
Hogan, J., K. Lemon, and B. Libai. “Quantify-
Sweeney, J. C., G. N. Soutar, and T. Maz-
keting Science 20, 1 (1992): 49–59.
ing the Ripple: Word-of-Mouth and Advertising
Wangenheim, F., and T. Bayon. “The Effect
of Word-of-Mouth on Service Switching: Measurement and Moderating Variables.” European
Journal of Marketing 38, 9/10 (2004b): 1173–1185.
Effectiveness.” Journal of Advertising Research 44,
Nielsen. “Trust, Value and Engagement in
3 (2004): 271–280.
Advertising.” Nielsen Global Online Consumer
Wangenheim, F., and T. Bayon. “The Chain
Survey, July, 2009. Retrieved March 14, 2011
from Customer Satisfaction Via Word-of-Mouth
Hung, K. H., and S. Y. Li. “The Influence of
from
http://blog.nielsen.com/nielsenwire/
Referrals to New Customer Acquisition.” Jour-
eWOM on Virtual Consumer Communities:
wp-content/uploads/2009/07/trustinadvertis-
nal of the Academy of Marketing Science 35, 2
Social Capital, Consumer Learning, and Behav-
ing0709.pdf.
(2007): 233–249.
Ranaweera, C., and J. Prabhu. “On the Relative
Westbrook, R. A. “The Dimensionality of
ioral Outcomes.” Journal of Advertising Research
47, 4 (2007): 485–495.
Importance of Customer Satisfaction and Trust
Consumption Emotion Patterns and Consumer
Keller, E. “Unleashing the Power of Word of
as Determinants of Customer Retention and
Satisfaction.” Journal of Consumer Research 18, 1
Mouth: Creating Brand Advocacy to Drive
Positive Word-of-Mouth.” Journal of Targeting,
(1987): 84–91.
March 2013 JOURNAL
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the word of mouth dynamic
APPENDIX
Results of Measurement Model: Psychometric Properties of the Scales
Standardised
loading (l)*
Constructs
Indicate your level of agreement with the following statements (Likert: 1 = total disagreement, 7 = total agreement)
1. Receiver’s experience (AVE = 0.972; CR = 0.950; a = 0.955). Similar items can be found in: Bansal and Voyer (2000)
I know this product/service category very well
0.880
I am competent and capable in things concerning this product/service category
0.910
I am very familiar with the current features of this product/service category
0.923
I am very experienced in the purchase of this product/service category
0.847
I think I have enough information about this product/service category
0.889
2. How actively WOM is sought (AVE = 0.704; CR = 0.877; a = 0.906). Similar items can be found in: Bansal and Voyer (2000)
Before buying I seek advice from people unconnected to the firm
0.850
Probability of accepting advice from other people (1 = very low; 7 = very high)
0.821
Explicit requirement of opinion of other people to take decisions (1 = very low; 7 = very high)
0.846
3. Receiver’s perceived risk (AVE = 0.767; CR = 0.908; a = 0.901). Similar items can be found in: Bansal and Voyer (2000) and Wangenheim
and Bayon (2004b, 2007)
Thinking about buying this product worries me because of the possibility of taking a risk
0.817
I think it would be a mistake if I didn’t seek the opinions of other people unconnected to the firm to avoid risks
0.870
I feel that buying this product is risky and I can avoid these risks if I seek advice from other people unconnected to the firm
0.936
4. Tie strength (AVE = 0.846; CR = 0.975; a = 0.975). Similar items can be found in: Bansal and Voyer (2000) and Wangenheim and Bayon
(2004b, 2007)
I speak to this person frequently
0.874
I have a trusting relationship with this person
0.926
This person understands me, shares my concerns, supports me
0.943
I have a strong personal relation with this person
0.952
I have interests and pastimes in common with this person
0.902
This person has social values and lifestyle like mine
0.914
I think that this person generally behaves very similarly to my way of seeing life
0.924
5. Sender’s experience (AVE = 0.846; CR = 0.956; a = 0.950). Similar items can be found in: Bansal and Voyer (2000) and Wangenheim and
Bayon (2004b, 2007)
This person is very knowledgeable about this product/service category
0.924
This person is very competent in things concerning this product/service category
0.930
This person has previously bought this product/service category
0.914
This person is very experienced in this product/service category
0.910
Other scales developed for this study
6. Sender’s strength of expression. Similar items can be found in: East et al. (2007 and 2008)
How convincing/credible do you think were the explanations of the person who gave you this recommendation? (1 = not at all convincing/credible;
7 = very convincing/credible)
7. Probability of choosing brand.** Similar items can be found in: East et al. (2007 and 2008)
What was the probability that you would choose this brand before receiving the recommendation? (receiver’s loyalty) (0 = zero; 10 = very high)
What was the probability that you would choose this brand after receiving the recommendation? (0 = zero; 10 = very high)
* All standardised loadings are significant (p < 0.01); ** The shift in the WOM receiver’s brand-purchase probability is calculated as the difference between the probability of choosing the brand
after and before the recommendation
60 JOURNAL
OF ADVERTISING RESEARCH March 2013
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