Canadian Journal of Administrative Sciences
Revue canadienne des sciences de l’administration
27: 5–23 (2010)
Published online in Wiley Interscience (www.interscience.wiley.com). DOI: 10.1002/CJAS.129
e-WOM Scale: Word-of-Mouth
Measurement Scale for
e-Services Context*
Isabelle Goyette
CROP Inc.
Line Ricard**
Université du Québec à Montréal (ÉSG-UQAM)
Jasmin Bergeron
ÉSG-UQAM
François Marticotte
ÉSG-UQAM
Résumé
Dans cet article, nous proposons, à partir d’une enquête
réalisée auprès de 218 répondants, une échelle de mesure
du concept de bouche-à-oreille (échelle BAO ou e-WOM
scale) dans le contexte de services électroniques. La batterie de tests statistiques réalisés révèle que le concept
de BAO comprend quatre dimensions, à savoir :
l’intensité du BAO, la polarité positive du BAO, la polarité négative du BAO et le contenu du BAO. L’échelle de
mesure proposée peut être utilisée comme un outil stratégique par les gestionnaires d’entreprises de services
en ligne désireux d’améliorer leurs stratégies de marketing en matière de bouche-à-oreille. Copyright © 2010
ASAC. Published by John Wiley & Sons, Ltd.
Abstract
In this article, using data from a survey of 218 consumers
across two samples, we propose a measurement scale for
word of mouth (e-WOM scale) in the context of electronic service. A battery of statistical tests reveals that
the WOM construct encompasses four dimensions: WOM
intensity, positive valence WOM, negative valence WOM,
and WOM content. Our proposed e-WOM scale can be
used as a strategic tool for business managers aiming to
improve their word-of-mouth marketing strategies.
Copyright © 2010 ASAC. Published by John Wiley &
Sons, Ltd.
JEL Classifications: M31, L81, C3
Mots clés : Bouche-à-oreille, e-WOM scale, marketing,
Internet, équations structurelles
Keywords: word-of-mouth, e-WOM scale, marketing,
Internet, structural equations
The authors would like to offer their sincere gratitude to the guest editor, the anonymous referees, Jean-Mathieu Fallu (MBA, ÉSG-UQAM), and MarcAntoine Vachon (post-graduate student, ÉSG-UQAM) for their apt and constructive recommendations. The second database that was used to validate
the scale is the result of a survey undertaken by Mrs. Olfa Gmach in her master’s thesis. The authors would also like to highlight the logistical and
financial contribution from SSHRC and the Chair in Financial Services Management ÉSG-UQAM.
*Please note that this paper was originally submitted in French and translated into English. Both versions are available on Wiley Interscience.
**Please address correspondence to: Line Ricard, ÉSG, Université du Québec à Montréal, Case Postale 6192, succursale Centre-ville, Montréal (Québec),
Canada, H3C 4R2. Email: [email protected]
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
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e-WOM SCALE: WORD-OF-MOUTH MEASUREMENT SCALE FOR e-SERVICES CONTEXT
Word-of-mouth (WOM) is probably the oldest
means of exchanging opinions on various goods and
services offered by markets. At one time, word-of-mouth
occurred mostly among neighbours exchanging news on
what was being offered by neighbourhood stores (Whyte,
1954). As early as 1955, Katz and Lazarsfeld believed
that word-of-mouth was seven times more effective than
newspaper ads, four times more effective than direct
sales, and twice as effective as radio advertising. Later,
Day (1971) estimated that word-of-mouth was nine times
more effective than advertising in changing consumer
attitudes, whereas Morin (1983) showed that “other
people’s recommendations” were three times more
effective in terms of stimulating purchases of over 60
different products than was advertising. According to
Reicheld (1996), these effects are amplified by a higher
degree of customer loyalty and profitability. Today,
many researchers continue to maintain that word-ofmouth constitutes one of the most effective ways of
attracting and keeping customers (Duhan, Johnson,
Wilcox, & Harrell, 1997).
Studies on word-of-mouth have demonstrated that
its effectiveness is based on the overwhelming influence
that it has on consumer behaviour. Researchers have
shown that word-of-mouth was strongly and positively
associated with clients’ levels of trust (Bergeron, Ricard,
& Perrien, 2003), service quality (Parasuraman, Zeithaml,
& Berry, 1988), satisfaction (Anderson, 1998), perceived
value (Hartline & Jones, 1996), relationship quality
(Boles, Barksdale, & Johnson, 1997), and with clients’
intention to purchase (Crocker, 1986).
In today’s virtual era, the power of word-of-mouth
has grown exponentially. For example, the international
bank HSBC announced in the summer of 2007 that it was
introducing a charge of 9.9% interest for each student
account (previously free) with a balance of under 1,500
pounds Sterling (approx. CAD 3000). The National
Union of Students (NUS) immediately created a group
on the Facebook website to bring together the largest
possible number of students opposed to this change of
policy at HSBC. In a few short weeks, the power of
virtual word-of-mouth managed to mobilize 5,000 students on summer break, each threatening to boycott or
to change bank. Under pressure, HSBC reversed the
change, indicating it had “answered the needs of its
customers.”
Although many studies target WOM, very few have
focused on a measure of word-of-mouth, especially in
the context of e-services. The recent concept of viral
marketing (Godin, 2001), which represents a modern
version of word-of-mouth, also shows the relevance of
word-of-mouth (WOM) in an online context. Thus, our
objective here was to develop a multidimensional word-
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
GOYETTE ET AL.
of-mouth measurement scale in the area of e-services.
Given the enormous potential benefits of favourable
word-of-mouth (especially online), such a scale could
serve as an important tool for managers wishing to
measure their companies’ performance and the effect of
their strategies on people’s propensity to talk favourably
about them. In addition, this scale could be used to
predict customers’ purchasing intentions and their inclination to speak well of the company (Arndt, 1968; Brown
& Reingen, 1987; Maxham III, 2001; Ying & Chung,
2007).
This article is structured as follows. The first section
reviews prior research of the concept of WOM. Subsequent sections are dedicated to the methodology, presentation of our WOM model, and an analysis of results,
respectively. The paper closes with a discussion of the
intended contribution and the implications for theory and
management.
Literature Review
Word-of-Mouth (WOM)
Here we briefly explain what is meant by word-ofmouth by placing it alongside new concepts such as viral
marketing and buzz marketing, among others. Additionally, relevant research on the subject, and especially
studies that have developed a measure of WOM, are
reviewed.
Over the past five years, WOM has been the object
of multiple studies in the field of marketing. Authors
have sometime associated this concept with personal recommendations (Arndt, 1967a), interpersonal communication (Godes & Mayzlin, 2004), interpersonal
relationships (Arndt, 1967a), informal communication
(Silverman, 2001), personal and interpersonal influence
(Arndt, 1967a, Brown & Reingen, 1987), and with
informal advertising (Arndt, 1967a).
WOM definitions by Westbrook (1987), Bone (1992,
1995), Silverman (2001), and Anderson (1998) have all
been inspired by that of Arndt (1967a), which focused
on the informal aspect of WOM communication, the
communicator’s independence from a commercial
source, and on the phenomenon of information diffusion
(cf. Table 1).
Table 1 indicates that word-of-mouth is usually
defined as an exchange, flow of information, communication, or conversation between two individuals. There
is but a single author (Haywood, 1989) who considered
word-of-mouth as formal conversation. Other authors
agree that word-of-mouth is an informal and noncommercial conversation. The term “informal” makes reference to something that is not organized in an official
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Table 1
Definitions of Word-of-Mouth
Definitions1
Dimensions2
I
Arndt (1967a, p. 3)
Richins (1983, p. 17)
Brown and Reingen
(1987, p. 350)
Higie, Feick, and
Prince (1987,
p. 263)
Westbrook (1987,
p. 261)
Haywood (1989,
p.58)
Swan and Oliver
(1989, p. 523)
Singh (1990, p. 1)
File, Jude, and
Prince (1992, p. 7)
File, Cermark, and
Prince (1994,
p. 302)
Bone (1992, p. 579)
Bone (1995, p. 213)
Silverman (2001,
p. 4)
Anderson (1998, p.
6)
Mangold & al. (1999,
p. 83)
Kim, Han, and Lee
(2001, p. 276)
Salzman, Matathia,
and O’Reilly
(2004)
WOMMA (2006)
“. . . is defined as oral, person-to-person communication between a receiver and a
communicator whom the receiver perceives as non-commercial, concerning a
brand, a product, or a service.”
“The WOM communication was defined as the act of telling at least one friend or
acquaintance about the dissatisfaction”
“The WOM exists at the macro level of inquiry (e.g., flows of communication across
groups), as well as the micro level (e.g., flows within dyads or small groups)”
“Conversations motivated by salient experiences are likely to be an important part of
information diffusion”
X
“In a postpurchase context, consumer word-of-mouth transmissions consist of
informal communications directed at other consumers about the ownership, usage,
or characteristics of particular goods and services and/or their sellers.”
“WOM is a process that is often generated by a company’s formal communications
and the behavior of its representatives.”
“Postpurchase communications included positive versus negative word-of-mouth and
complaints and praising directed at the three entities in the exchange (i.e., the
salesperson, dealer, and manufacturer)”
“(c) telling others about the unsatisfactory experience (that is, negative
word-of-mouth).”
“Positive and negative word-of-mouth are examples of exit behaviors exhibited by
consumers at the conclusion of a service encounter.”
“Word-of-mouth, both Input and Output, is the means by which buyers of services
exchange information about those services, thus diffusing information about a
product throughout a market.”
“WOM communication is conceptualized herein as a group phenomenon—an
exchange of comments, thoughts, and ideas among two or more individuals in
which none of the individuals represent a marketing source.”
“Word-of-mouth communications (WOM), interpersonal communications in which
none of the participants are marketing sources, . . .”
“1) Word-of-mouth is communication about products and services between people
who are perceived to be independent of the company providing the product or
service, in a medium perceived to be independent of the company.”
2) Word-of-mouth is originated by a third party and transmitted spontaneously in a
way that is independent of the producer or seller.”
“Word of mouth refers to information communications between private parties
concerning evaluations of goods and services.”
“WOM was far more likely to be initiated by receivers’ need for information than
by communicators’ satisfaction level.”
“Word of mouth is the interpersonal communication between two or more
individuals, such as members of a reference group or a customer and a
salesperson.”
Buzz is a “WOM effect, a transfer of information through social networks. It
frequently occurs in a spontaneous manner, without so much as a raised finger on
the part of a marketing specialist or any other person.”
WOM is “an act by consumers providing information to other consumers.”
X
Total
F
N
C
X
E
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
5
1
5
7
13
1
Loose translation.
I = Informal, F = Formal, N = Noncommercial, C = Post-purchase behavior, E = Exchange/Flow of information/Communication/
Conversation.
2
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
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manner (Rey-Debove & Rey, 2007). In addition, WOM
communications are occasionally defined as postpurchase behaviours.
In addition, according to previous work, for a consumer to be considered involved in a WOM-type conversation, the message being transmitted and the medium
used for the transmission must be perceived as independent from influence by the company (Silverman, 2001).
For instance, can the context of e-services where many
companies have discussion forums on their websites be
regarded as independent? In fact, in the current study
such forums are considered to be a source of WOM
insofar as consumers perceive these communications to
be informal and not sponsored or subsidized by the
company. According to Silverman, any other type of
communication would be perceived as commercial and
formal because advertising, public, and media relations
communicate a message specifically selected, conceived,
and expressed by the product or service vendor through
an owned or leased medium. Including media relations
could be debatable because, although these are well
planned, managers do not necessarily have any direct
control over the end result.
WOM communications can occur face to face, by
phone, email, mailing list, or any other means of communication (Silverman, 2001). In addition, there are personal and impersonal sources of recommendations that
have to be considered. Friends, family, and acquaintances are personal sources of recommendations (Brown
& Reingen, 1987, Duhan, et al., 1997) recognized as
WOM vehicles. Columns, articles, and commentary by
journalists, columnists, consumers, and experts to be
found in newspapers, magazines, specialized publications, online discussion forums, and expert systems are
regarded as impersonal sources of WOM recommendations. Expert systems and discussion forums are included
as impersonal recommendation sources (Sénécal, Kalczynski & Nantel, 2005) because consumers are influenced in their choice of products online by
recommendations posted online (Sénécal & Nantel,
2004). Consumers should not perceive any commercial
or marketing intent behind the statements in these sources
of recommendations. If that is not the case, these communications cannot be considered WOM. Thus, a WOM
communication can be based both on personal and
impersonal sources.
In short, WOM could be affected by a marketing
effort such as advertising, media relations, and public
relations as well as by spontaneous conversations
between two individuals and by accounts of satisfactory
or unsatisfactory buying experiences. WOM sources can
be both personal and impersonal. On the other hand, a
conversation that follows a series of triggers may not
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
GOYETTE ET AL.
contain anything that may be perceived as a commercial
or marketing intention to persuade or to inform one of
the communicating parties. Generally, it is this informal
and independent side of WOM that makes it unique.
New Terms Emerge
Since the advent of information technologies and the
Internet, word-of-mouth has acquired several new names.
Thus, mention is made of viral marketing, email marketing, Internet word-of-mouth, word-of-mouth marketing,
and electronic WOM (e-WOM). In addition, the concept
of “buzz marketing” has made itself known as a new
marketing strategy derived from conventional word-ofmouth and bearing a strong resemblance to the concept
of viral marketing.
Viral marketing is associated with word-of-mouth
through electronic media. Internet is the central component of viral marketing and it is this necessary connection
with the Internet that makes it distinct from general
word-of-mouth. The word viral refers, according to
Godin (2001), to a virus, epidemic, or rather to an idea
virus, which he defined as follows: A big idea that runs
amok in the target audience, a fashionable idea that
propagates through a segment of the population, teaching
and changing and influencing everyone it touches (p. 17).
The consumer takes an active part in the advertising
process of a company by becoming its supporter, advertising propagator, and, on occasion, advertising concept
developer (Stanbouli, 2003) or salesperson (Phelps,
Lewis, Mobilio, Perry, & Raman, 2004). One of the
consumer’s strengths is that he or she is perceived as
independent from the company that “hires” him or her.
Whether it is viral marketing or electronic word-ofmouth, these strategies serve as a way for companies to
empower the consumer (Hennig-Thurau, Gwinner,
Walsh, & Gremier, 2004). Godin suggested that helping
consumers communicate amongst themselves would be
preferable to attempting to address them directly. This
could be done voluntarily by a group of consumers or
encouraged by financial incentives made available by a
company. The latter option is further from the WOM
definition because customer independence is not as
obvious in this case.
Compared to viral marketing, the concept of buzz
marketing is even less clearly defined. This situation is
probably the result of the fact that these two notions are
frequently confused with each other (ABC-Netmarketing.
com, 2009). However, there is a difference. In fact,
unlike viral marketing, buzz marketing is not at all associated with the Internet or any other electronic communication medium. It does sometime happen that the word
“Internet” crops up in explanations of buzz marketing
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given by authors, but it is not done in a restrictive manner.
Propagation rates inherent in an epidemic are not mentioned. Rather, buzz marketing plays the part of a catalyst
of a WOM conversation. For example, a classic buzz
catalyst is to place interesting and/or nice-to-look-at
people who know what they are talking about, in locations on the Internet or in the real world where they are
able to share reflections and their personal ideas on one
product or another (Salzman, Matathia, & O’Reilly,
2004, p. 30).
The objective of buzz marketing is to create a relationship between brands and people as a means to influence purchase choices and create loyalty to a single
brand (Salzman, et al., 2004). Unlike WOM, buzz marketing is structured to provide people with incentives to
speak favourably of a good or a service among themselves. The spontaneity of exchanges is in evidence to a
lesser degree as demonstrated in the previous example.
In short, the illusion of spontaneity should be well
orchestrated by buzz marketing specialists such that consumers do not at all suspect that a company is behind the
entire communication process.
The three concepts could be summarized as follows:
Appendix A lists authors who have conducted an empirical study of WOM. This summary shows for each author
the type of measurement scale used (unidimensional or
multidimensional), Cronbach’s alpha or a reliability
index, the recommended methodology, the WOM measurements and context (the way the researchers conceived
WOM), and the viewpoint from which WOM was measured (receiver or communicator).
Among the authors presented, Harrison-Walker
(2001) and Godes and Mayzlin (2004) are the only ones
to have dedicated their research primarily to the study of
WOM measurement. For others, a WOM measure mostly
follows from the need to include this dependent or
independent variable into their research. On the other
hand, there are only six papers that explicitly present a
Cronbach’s alpha. In these cases, the internal consistency
level is high with coefficients ranging from 0.78 to 0.80.
Appendix A shows that most WOM measurement
scales presented in published research are unidimensional, that is, they measure a single dimension of WOM
using in most cases a single statement or a single question. Moreover, those authors who use unidimensional
scales do not specify which dimension they were
attempting to measure. Only through an in depth analysis
of statements and a comparison of dimensions measured
by other authors using multidimensional scales was it
possible to identify the WOM dimension measured by
these authors. For example, Burzynski and Bayer (1977)
focused on the valence of a WOM conversation, Higie,
Feick, and Price (1987) analyzed the volume of WOM,
while Bone (1992) concentrated on WOM content.
Appendix A also shows that authors mostly utilized
self-administered questionnaires, and, to a lesser degree,
telephone questionnaires or interviews. In other words,
personal interviews and telephone surveys are the second
data collection method used by these authors. Finally,
some authors used experiments to test the impact of
WOM on other variables rather than to measure WOM
itself.
Since the WOM construct is not the primary object
of the majority of studies, specific items or scales for
measuring WOM are rarely found. Rather, they are found
in the context that enabled the construct to be measured.
Appendix A takes this feature into account by providing
a two-column representation: for the statements themselves and for the context.
Higie et al. (1987), Bone (1992), and Mangold,
Miller, and Brockay (1999) studied the “WOM content
dimension.” Harrison-Walker (2001) focused on four
aspects of WOM: (1) frequency, (2) number of contacts,
(3) detail, and (4) word-of-mouth praise. Further refinement of this measurement scale led Harrison-Walker to
retain only two primary WOM dimensions: word-of-
• Word-of-Mouth is defined as a verbal informal
communication occurring in person, by telephone,
email, mailing list, or any other communication
method regarding a service or a good. A recommendation source may be personal or impersonal.
• Viral Marketing is defined as a rapidly spreading
informal online communication between individuals
regarding a service or a good.
• Buzz Marketing is defined as a catalyst for a WOM
conversation to occur in person or online derived from
a formal corporate strategy with a view to creating an
illusion of spontaneity.
Given that the Internet has changed the dynamic of
word-of-mouth, this technological evolution will be
taken into account. In fact, in the current study we seek
to define and develop a reliable and valid measurement
scale in an e-service context.
Word-of-Mouth (WOM) Measure
A review of studies on WOM reveals the small
number of works dedicated to WOM measurement.
Although WOM has been in existence for many years,
researchers and managers are still interested in it because
it is an important driver of consumer behaviour. Yet, few
researchers have focused explicitly on measuring it.
Harrison-Walker (2001, p.62) stated: “. . . WOM was not
treated as a construct to be measured but rather as a
category to be assigned based on responding to a survey.”
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
GOYETTE ET AL.
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mouth praise with two items and word-of-mouth activity
with four items. WOM activity includes all items associated with the action of engaging in WOM. As for Godes
and Mayzlin (2004), they analyzed two WOM dimensions: volume and dispersion.
To identify other potential WOM dimensions, we
conducted a detailed analysis of the published works on
this subject. Following this analysis we discovered
another dimension measured by several authors: valence
(Black, Mitra, & Webster, 1998; Bone, 1995; Burzynski,
& Bayer, 1977; Singh, 1990; Swan & Oliver, 1989).
Researchers verified whether conversations were positive or negative, or whether they reflected satisfaction or
dissatisfaction with respect to a good or a service. This
dimension, when positive, reflects praise. Negative
valence remains to be explored.
Finally, the WOM viewpoint refers to the perspective from which the communication process is examined.
The examination could be based around the communicator (i.e., researchers wish to interview the individuals that
start the conversation) of information or the receiver (i.e.,
the person on the receiving end of the comments). An
analysis of research statements and contexts helped show
that in measuring WOM, the communicator’s viewpoint
had mostly been taken into consideration while the
receiver’s viewpoint had been ignored.
In conclusion, four major dimensions are identified
to measure online word-of-mouth (WOM): (1) WOM
intensity (activity, volume, dispersion), (2) positive
valence (praise), (3) negative valence, and (4) content.
e-services. The objective set for these exploratory interviews was to gain better insight into the WOM phenomenon in the context of e-services. Respondents were also
asked about online companies pertinent to their word-ofmouth activity. As direction for these meetings, one of
the authors used an interview guide with four primary
open questions regarding: (a) their reasons for engaging
in WOM online; (b) the credibility of these conversations; (c) their propensity to initiate a positive or a negative conversation; and (d) the content of their electronic
messages. An analysis and an interview report were produced by one of the researchers that developed a classification matrix. In addition, there was an informal
meeting with two consultants specializing in buzz marketing, which helped assess the scope of the word-ofmouth phenomenon in the electronic context and better
differentiate between buzz, viral marketing, and WOM.
This first phase also enabled us to explore the different
dimensions of WOM (WOM intensity, negative and
positive valance, and content).
A self-administered questionnaire was selected for
the survey. This method enabled information to be collected on multiple dimensions. Based on previous work
and exploratory meetings, one of the researchers wrote
the first draft of the questionnaire and another researcher
critiqued it. In the end, researchers arrived at a four-page
questionnaire intended to be concise, clear, and in
keeping with the objectives of the present study. To
ensure this objective was met, the questionnaire was
presented to two other researchers who made minor suggestions mostly with respect to the sociodemographic
variables (for example, adding income) and the wordings
of some of the statements. Finally, the questionnaire was
pretested on ten e-service users with an inclination
towards WOM. The respondents independently completed the questionnaire under the watchful eye of one
of the researchers. The time required to answer the questions was calculated and any remaining points of confusion cleared up as required. Following updates based on
several minor comments primarily with respect to
rewording the first question, the questionnaire was finalized. Again, not a single statement was eliminated.
The questionnaire consists of three sections: (1)
WOM activities; (2) assessment of the various dimensions of word-of-mouth; and (3) the general propensity
on the part of respondents to engage in WOM, their
online buying activities, and their social and demographic characteristics. The respondents were expected
to evaluate their WOM activities with respect to the last
e-services company they had discussed (six such companies were proposed, namely: amazon.com or .ca, eBay.
com, admission.com, chapters.indigo.ca, expedia.com or
expedia.ca, and archambault.ca). The companies were
Method
This paper is an extension of the train of thought
started by Harrison-Walker (2001). This author developed
a measurement scale comprised of six items and two
WOM dimensions. She tested her scale using a sample
made up of veterinary clinic and hair salon customers.
The author observed that although interesting, it is
important that her scale be refined using different contexts and that the possibility of adding other dimensions
be examined. As such, we proceeded in the context of
e-service companies because it is considered higher risk
(thus favouring WOM activity) and because this context
promotes the use of personal sources of information
(Murray, 1991).
Before proceeding to the development of the questionnaire and subsequent data collection, a few steps
were required to define a reliable and valid measurement
scale. After the primary WOM dimensions and measures
derived from a detailed review of existing works were
identified, meetings were held with ten consumers of
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
GOYETTE ET AL.
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GOYETTE ET AL.
sented in the in-class sample (65.8%) but not in the email
group. Overall, however, men accounted for 41.3% of
the total (combined) sample.
Although there were differences in the sample profiles, this was not the case in terms of the assessment of
the measurement scale statements. Of the 19 items in the
measurement scale, only 3 have significantly different
means (t-test) for the two samples, namely: I speak more
often of this company than about any other type of
company (3.26 in class vs. 2.43 by email); I speak favourably of this company to others (4.69 in class vs. 5.21),
and I discuss variety (5.57 in class vs. 4.80 by email).
Since there were few significant differences between the
two groups in the assessment of WOM statements, the
model was tested on the combined samples.
selected based on a Statistics Canada (2004) study in
which the above-mentioned sites were cited as the most
popular in Canada.
Those that had not recommended any e-service
company had to answer the questions in Section 3 of the
questionnaire nonetheless. Table 2 presents the 19 statements used to measure the four dimensions of WOM.
Since this study is of a rather theoretical nature, the
sample had to have a certain degree of homogeneity
(Calder, Philips, & Tybout, 1981). The first data collection using a suitable sample was performed in four
university classrooms. It produced 116 completed questionnaires. To complement data collection that was initiated in class and to obtain respondents of a different
profile, “snowball” sampling was subsequently performed using electronic mail. Some 475 questionnaires
were sent out by email and 107 were completed and
returned. Following an analysis of outliers, the size of
the final sample was 218 respondents.
The respondents’ profile is shown in Table 3. Certain
differences between the samples are apparent: the sample
collected in-class had a lower age (mean of 27 years as
compared to 32 years for email), lower income (84.6%
have incomes below $70,000 vs. 52% for email respondents), and was mostly made up of junior college students
(51.4%) vs. four-year university programs (88.6% email
respondents). On the other hand, women were overrepre-
Analysis and Results
Assessment of Measurement Scale Quality
The psychometric properties of the scale were analyzed in multiple ways. This section presents the analysis
of unidimensionality and reliability as well as of convergent and discriminant validity. The results are summarized in Table 4.
Unidimensionality. A scale is regarded as unidimensional whenever a group of statements measures
Table 2
Word-of-Mouth Dimensions and Statements
Word-of-Mouth (WOM) dimensions
Statements
WOM intensity
• I spoke of this company much more frequently than about any other e-services company.
• I spoke of this company much more frequently than about companies of any other type.
• I spoke of this company to many individuals.
Positive valence WOM
•
•
•
•
•
•
Negative valence WOM
• I mostly say negative things to others.
• I have spoken unflatteringly of this company to others.
WOM content
•
•
•
•
•
•
•
•
I
I
I
I
I
I
I
I
I
I
I
I
I
I
recommended this company
speak of this company’s good sides.
am proud to say to others that I am this company’s customer.
strongly recommend people buy products online from this company.
mostly say positive things to others.
have spoken favourably of this company to others.
discuss the user-friendliness of its website.
discuss security of transactions and its Internet site.
discuss the prices of products offered.
discuss the variety of the products offered.
discuss the quality of the products offered
discuss ease of transactions.
speak of the rapid delivery.
speak of the company’s notoriety.
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
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Table 3
Respondent Profiles
Variable*
Classification
In class
111 respondents
(%)
By email
107 respondents
(%)
Gender
Men
Women
Primary/Secondary
College
University
Under $ 29,999
$ 30,000 to $ 69,999
$ 70,000 and more
In class
By email
34.2
65.8
8.1
51.4
40.5
41.3
43.3
15.4
48.6
51.4
3.8
7.6
88.6
17.5
30.1
52.4
Mean
Mean
27
32
Education
Household revenue
Data collection method
Age
Total
N (%)
218 (100 )
90 (41.3)
128 (58.7)
13 (6.0)
65 (30.1)
138 (63.9)
61 (29.5)
76 (36.7)
70 (33.8)
111 (50.9)
107 (49.1)
Mean (Standard
Deviation)
29.5 (8.1)
* At 95% confidence, the four sociodemographic variables are significantly different.
the ratio χ2/degrees of freedom of 1.96 (43.14/22), a CFI
of 0.95, an AGFI of 0.88, an NFI of 0.91, an NNFI of
0.92, and a GFI of 0.94 (Bagozzi & Yi, 1988; Bentler,
2005).
Reliability. Baumgartner and Homburg (1996) recommended that the reliability of measurement scales be
evaluated from different angles. Therefore, three different types of analysis were performed. Suggestions by
Churchill (1979) were used to calculate first the adjusted
item-total correlations (Table 4). The results show that
all dimensions have adjusted item-total correlations
greater than 0.35, which is satisfactory (McKelvey,
1976). Subsequently, component Cronbach’s alphas and
reliability indices for each dimension were generated.
The results shown in Table 4 indicate that the alphas
range between 0.69 (WOM intensity) and 0.89 (WOM
positive valence), which is satisfactory (Peterson, 1994).
As for component reliability indices (CFI), they range
between 0.64 (WOM intensity) and 0.85 (positive
valence), exceeding the minimum of 0.60 suggested by
Bagozzi and Yi (1988), as well as by Fornell and Larcker
(1981).
Convergent and discriminant validity. To assess
convergent validity, many authors have suggested that it
is important to determine if each statement is associated
with the factor that it measures (Anderson & Gerbing,
1988; Bagozzi & Yi, 1988). Estimated coefficients as
the same thing. Many authors agree that unidimensionality is fundamental to measurement theory (Hattie, 1985)
and is crucial in the development of a quality scale
(Anderson & Gerbing, 1988). Cox and Cox (2002) tested
the unidimensionality of their measurement scale using
principal component analysis. This technique was
employed, and the results of Table 4 (first column of
results) indicate that each dimension of the scale is
unidimensional.
A confirmatory factor analysis using the EQS 6.1
structural equation modelling software (Bentler, 2005)
was also performed for a more in depth validation of the
scale’s psychometric properties. Baumgartner and
Homburg (1996) emphasized that this statistical method
helps validate the quality of the measurement tool. As
mentioned by Anderson and Gerbing (1988), structural
equation modelling holds great potential in measurement
scale validation. Table 4 (first column of results—CFA)
also indicates that the coefficients are all associated with
their respective dimensions, that they are all greater than
0.50, and that they are statistically significant.
Multiple statistics were used to assess the model’s
goodness of fit to the data. Firstly, the average offdiagonal standardized residual (AOSR) is 0.067 and the
RMSEA index is 0.08, which is somewhat high but
nonetheless acceptable. However, we can reconfirm a
satisfactory validation of goodness of fit to the data with
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
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Table 4
Results of Reliability and Validity Analyses
DIMENSIONS
Principal component
analysis/CFAa
Adjusted item-total
correlations
0.76/0.58
0.47
0.84/0.80
0.58
0.77/0.60
0.49
Positive valence word-of-mouth
I recommended this company
I speak of this company’s good sides.
I am proud to say to others that I am this company’s customer.
I strongly recommend people buy products online from this company.
I mostly say positive things to others.
I have spoken favourably of this company to others.
0.86/0.84
0.83/0.79
0.70/0.61
0.81/0.80
0.81/0.82
0.84/0.73
0,78
0,73
0.60
0.73
0.70
0.74
Negative valence word-of-mouth
I mostly say negative things to others.
I have spoken unflatteringly of this company to others.
0.92/0.93
0.92/0.74
0.69
0.69
Word-of-mouth content
I discuss the user-friendliness of its website.
I discuss security of transactions and its Internet site.
I discuss the prices of products offered.
I discuss the variety of the products offered.
I discuss the quality of the products offered.
I discuss ease of transactions.
I speak of the rapid delivery.
I speak of the company’s notoriety.
0.58/0.51
0.65/0.56
0.61/0.58
0.70/0.67
0.70/0.66
0.62/0.52
0.69/0.60
0.62/0.54
0.46
0.51
0.45
0.55
0.55
0.50
0.56
0.48
Word-of-mouth intensity
I spoke of this company much more frequently than about any other
e-services company.
I spoke of this company much more frequently than about companies of
any other type.
I spoke of this company to many individuals.
Alpha
(α)/CFIb
0.69/0.64
0.89/0.85
0.82/0.78
0.80/0.77
a
The first number represents the factor coefficient generated by principal component analysis. The second number represents the factor
coefficient generated by confirmatory factor analysis (CFA), performed using EQS 6.1 software (Bentler, 2005).
b
The first number represents Cronbach’s alpha. The second number represents the reliability index of the CFI components (cf. Fornell
and Larcker, 1981).
computed by the EQS software are all high (i.e., ≥0.50)
and statistically significant (p < 0.01).
To evaluate discriminant validity, the model presented in Figure 1 was assessed several times by combining two different dimensions together every time
(Anderson & Gerbing, 1988). The Chi-square of the original model was a great deal lower than in the models
where two dimensions were combined, which is an
excellent indication of the discriminant validity of the
model’s dimensions (Bagozzi & Philips, 1982). In other
words, for each pair of measures forcing two dimensions
into one, we saw a reduced goodness of fit to the data as
compared to the original model (Figure 1). We also
evaluated discriminant validity by following recommendations by Gaski (1984), who state that the correlation
between two dimensions should not exceed the reliability
of the respective dimensions. Results indicate that the
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
fidelity indices of word-of-mouth dimensions were still
higher than the correlation between the respective
dimensions.
Assessment of WOM Measurement Scale in an
E-services Context
For reasons of statistical parsimony, the method
of partial aggregation of statements was used for the
dimensions of positive valence and WOM content
(Bagozzi & Heatherton, 1994). For example, we randomly selected two items from the “positive valence
word-of-mouth” construct as a sample of the six-item
scale. Hence, this strategy helped us reduce the number
of items from 19 to 9 with each factor measured by two
or three items. Thus, random error is reduced, a complex
model is simplified, and the items aggregated at random
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GOYETTE ET AL.
Figure 1.
Standardized results for word-of-mouth measurement scale in an e-services context
Item 1
Item 2
0.63
0.75
WOM Intensity
0.62
Item 3
0.65
0.92
Item1
Item 2
0.71
Item 1
0.93
Item 2
0.74
Positive Valence
WOM
0.81
-0.22
Word-ofMouth
Negative Valence
WOM
0.57
Item 1
Item 2
*
**
***
0,87
0,72
WOM Content
χ2 / DF = 43.14 / 22 = 1.96
AOSR = 0.067 ; RMSEA =
0.08
NFI = 0.91 ; NNFI =0.92
AGFI = 0.88 ; GFI = 0.94
All the coefficients are statistically significant (p< 0.05).
A satisfactory goodness of fit of the model to the data is possible whenever the average off-diagonal
standardized residual (AOSR) and the RMSEA index approach zero. In addition, the model is deemed
satisfactory whenever the majority of the indices NFI, NNFI, AGFI, GFI, and CFI are greater than 0.9. Finally,
the goodness of fit of the data to the model is satisfactory whenever the ratio χ2 / DF is under 4 (Bentler, 2005).
For reasons of statistical parsimony, the method of partial aggregation of statements was used for the
dimensions of positive valence and WOM content (Bagozzi & Heatherton, 1994). Hence, the two following
items were randomly selected for each construct: “I recommended this company” and “I have spoken
favourably of this company to others” for the Positive Valence WOM construct and “I discuss the quality of the
product offer” and “I discuss the variety of the product offer” for the WOM Content construct.
sors, and students of a Québec university. Thus, a new
database of 150 respondents was created. The percentage
of men in the second sample is 51.3%. The mean age is
31.3 with a standard deviation of 8.49. Just over 75% of
the respondents make under $ 50,000 a year.
Here again the psychometric properties of the scale
were satisfactory. Cronbach’s alphas are 0.78, 0.83, 0.94,
and 0.84, respectively for the following dimensions:
content, WOM intensity, positive valence, and negative
valence. A confirmatory factor analysis was performed
again with the same statements shown in Figure 1.
Indices of model goodness of fit to the data are satisfactory (e.g., NFI = 0.92 and CFI = 0.94). As in the first
model, the dimension of positive valence explains
the greater part of the variance in the WOM construct
are more reliable than dimensions measured using a
single statement (Bagozzi & Heatherton).
The results presented in Figure 1 show that the
dimension of positive valence (i.e., WOM praise)
explains the greater part of the variance in the WOM
construct (λ = 0.81) followed by the dimensions of WOM
intensity (λ = 0.65), content (λ = 0.57), and negative
valence (λ = −0.22). All these coefficients are statistically significant (p < 0.01).
To improve scale validity, a new round of data collection was undertaken. A second survey was carried out
by email using the snowball sampling method. This
method involved asking the respondents to complete the
questionnaire and to forward it on. A Word.doc file with
the questionnaire was sent out to acquaintances, profes-
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
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(λ = 0.87) followed by the dimensions of WOM intensity
(λ = 0.83), content (λ = 0.74), and negative valence
(λ = −0.16).
In addition to performing the same reliability and
validity analyses, we empirically demonstrated the
nomological validity of the scale. We analyzed the correlation coefficients for the four dimensions of our scale
and three constructs strongly associated with WOM in
previous research, namely, service quality, trust, and
satisfaction (Anderson, 1998; Bergeron et al. 2003;
Reicheld & Sasser, 1990). Absolute correlation coefficients between each scale dimension and each construct
measuring service quality, respondent trust, and satisfaction range between 0.22 and 0.50. They are all statistically significant, which indicates that the nomological
validity of our scale is acceptable. Thus, we can conclude
that the internal validity of our scale is acceptable because
it has been tested using two different samples.
of Desormeaux and Labrecque (1999), which showed a
difference between “satisfaction” and “dissatisfaction.”
Recognition of valence as a dual concept is theoretically
interesting; more so given that the effects of one seem
not to have the same impact as the other. According to a
frequently cited statistic, a dissatisfied customer mentions his or her dissatisfaction to nine people, while satisfaction is only expressed to five individuals. However,
the results show that the principal constituent of WOM
is positive valence. Does that mean that the propagation
of valence is reversed in the specific context of
e-commerce?
Applied Implications
The strategic importance of word-of-mouth as a
communication medium for an organization no longer
has to be proven. Paradoxically, companies have very
little, if any control over its reach or content. A company
is dependent on the message that will be communicated
by its consumers and others with whom it has never had
and never will have any contact. The virtual environment and its global scope only increase the power of
word of mouth and, consequently, the level of dependence of the companies in question. The instant popularity and notoriety of trading and noncommercial sites
such as Facebook, YouTube, eBay, or Wikipedia are
irrefutable evidence of the ubiquity of WOM in the
online world. Virtual communities such as DPReview
owe their existence and their growth only to word-ofmouth. An integral part of our everyday life, some, like
Google, have even become common names. It is difficult to imagine how much these online companies would
have had to invest in conventional communications
media to achieve the same result. It is understandable;
WOM and the essence of these companies are one on
the Web.
Although these companies rarely have the means to
control their members’ and nonmembers’ word-ofmouth, thanks to the e-WOM Scale, they now have the
opportunity to measure its impact and to make the necessary adjustments. This scale fills a void whereby an
organization is now able to assess how its brand and
products are communicated through WOM. It enables
the organization to measure what is being said about it
(content), the scope of what is being said (intensity), and
the surfers’ attitude towards the organization (positive or
negative valence). The company will then have the
capability to see if, for instance, the valence being
expressed is compatible with the content or if the intensity correlates with the valence or the content. In the
event that the results observed are not the results sought
by management, managers will be able to retarget the
Discussion
Summary
The primary objective of the study was to create a
multidimensional measurement scale for WOM in the
context of electronic services—the e-WOM Scale. A
review of prior research highlighted the paucity of studies
focusing on this set of problems, especially in the domain
of e-services. Taking inspiration from the results of a
study by Harrison-Walker (2001) and from many others,
the nine items of the e-Scale measure four dimensions of
word-of-mouth: (1) intensity (activity); (2) positive
valence/praise; (3) negative valence; (4) content. Statistical tests applied to two different samples helped confirm
the validity and the reliability of this measurement tool.
Contributions to Scholarship
The e-WOM Scale adapted to the e-services domain
helped double the number of measured dimensions with
respect to the scale of Harrison-Walker (2001), while
slightly increasing the number of items (from six to
nine). Thus, the e-WOM Scale enabled us to grasp in a
more complete manner the concept of word-of-mouth
without complicating the scale by increasing the number
of items. This increased precision provides a better
understanding of the components of word-of-mouth. For
example, Burzynski and Bayer (1977) spoke of valence
in a global way. The e-WOM Scale, on the other hand,
shows that valence is divisible into two distinct dimensions: positive valence—frequently described as praise—
and negative valence. This result is similar to the results
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
GOYETTE ET AL.
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message to their advantage by propping up those aspects
that are seen as weak in the e-WOM Scale. For example,
should those surfers that are favourably disposed towards
the company (positive valence) be encouraged to speak
of it more (i.e., increased intensity through specials, for
instance), or should the message target those that transmit negative valence to convince them to change their
minds? It is obvious that the measurement tool helps
target and adapt the steps to be undertaken to use WOM
to its full potential.
The quality of the scale (validity and reliability) and
its relative length (nine items) make its application
simple and accessible to every manager.
strength of the association between WOM and future
sales would have to be assessed in further research.
The multidimensional WOM measurement scale
developed in the context of electronic services is an
anchor point in the pursuit of a reliable and valid scale.
Since no measurement scale has been developed to date
in the context of e-services, this study contributes to the
advancement of research in the domains of WOM and
electronic services.
References
ABC-Netmarketing.com (July 7, 2009). Buzz marketing ou
marketing viral? Retrieved from http://www.abcnetmarketing.com/article.php3?id_article = 1765
Anderson, E.W. (1998). Customer satisfaction and Word-ofMouth. Journal of Service Research, 1(1), 5–17.
Anderson, J.C., & Gerbing, D.W. (1988). Structural equation
modeling in practice: A review and recommended two
step approach. Psychological Bulletin, 103(May),
411–423.
Arndt, J. (1967a). Word of Mouth Advertising: A review of the
literature. New York: The Advertising Research Foundation Inc.
Arndt, J. (1967b). Role of product-related conversations in the
diffusion of a new product. The Journal of Marketing
Research, 4(2), 291–295.
Arndt, J. (1968). Selective processes in Word of Mouth.
Journal of Advertising Research, 8(3), 19–22.
Bagozzi, R.P., & Heatherton, T.F. (1994). A general approach
to representing multifaceted personality constructs. Structural Equation Modeling, 1(1), 35–67.
Bagozzi, R.P., & Philips, L.W. (1982). Representing and
testing organizational theories. Administrative Science
Quarterly, 27(3), 459–489.
Bagozzi, R.P., & Yi, Y. (1988). On the evaluation of structural
equation models. Journal of the Academy of Marketing
Science, 16(1), 74–79.
Baumgartner, H., & Homburg, C. (1996). Applications of
structural equation modeling in marketing and consumer
research: A review. International Journal of Research in
Marketing, 13(2), 139–161.
Bentler, P.M. (2005). EQS 6.1: Structural Equation Program
Manual. Encino, CA: Multivariate software.
Bergeron, J., Ricard, L., & Perrien, J. (2003). Les déterminants
de la fidélité des clients commerciaux dans l’industrie
bancaire canadienne. Canadian Journal of Administrative
Sciences, 20(2), 107–120.
Black, D.S.S., Mitra, K., & Webster, C. (1998). Word-ofMouth communications: A motivational analysis.
Advances in Consumer Research, 25, 527–531.
Boles, J.S., Barksdale, H.C. Jr., & Johnson, J.T. (1997). Business relationships: An examination of the effects of buyersalesperson relationships on customer retention and
willingness to refer and recommend. Journal of Business
& Industrial Marketing, 12(3/4), 248–258.
Limitations and Future Research Directions
The newness of the WOM measure makes the
development of a multidimensional measurement scale
more urgent as this important topic should develop on
sound methodological grounds. With its four distinct
dimensions, the e-WOM Scale appears to be the most
complete WOM measurement tool to date. However,
this does not suggest that there are no new or secondorder factors underlying the four e-WOM Scale
components.
Another avenue of research is to apply the e-WOM
Scale to word of mouth related to brick-and-mortar companies. The tool would help compare WOM components
showing similarities or differences depending on what
respondents say about the same company based on their
in-person or online experience.
This research has demonstrated the need for companies to measure WOM. It is also imperative proves
imperative to identify the antecedents and consequences
of WOM in the context of e-services. As for WOM antecedents that were investigated in conventional markets,
we note client trust (Bergeron et al. 2003), service quality
(Parasuraman et al., 1988), and satisfaction (Anderson,
1998). As far as the consequences of WOM are concerned, many researchers have found impacts on relationship quality (Boles et al., 1997) and customer
purchasing intention (Crocker, 1986; Maxham III, 2001;
Ying & Chung, 2007). Given the power of WOM online,
it would be appropriate to study these relationships in the
context of e-services. The e-WOM Scale would help
measure WOM both against its antecedents and its
consequences.
Since many researchers have established a significant association between word of mouth and intention to
purchase (Crocker, 1986; Maxham III, 2001; Ying &
Chung, 2007), the e-WOM Scale could also be useful in
predicting future demand for e-services companies. The
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
GOYETTE ET AL.
16
Can J Adm Sci
27(1), 5–23 (2010)
e-WOM SCALE: WORD-OF-MOUTH MEASUREMENT SCALE FOR e-SERVICES CONTEXT
Harrison-Walker, L.J. (2001). The measurement of Word-ofMouth communication and an investigation of service
quality and customer commitment as potential antecedents. Journal of Service Research, 4(1), 60–75.
Hartline, M.D., & Jones, K.C. (1996). Employee performance
cues in a hotel service environment: Influence on perceived service quality, value and word-of-mouth intentions. Journal of Business Research, 35(March),
207–215.
Hattie, J.R. (1985). Methodological review: Assessing unidimensionality of tests and items. Applied Psychological
Measurement, 9(June), 139–164.
Haywood, K.M. (1989). Managing Word of Mouth communications. The Journal of Services Marketing, 3(2), 55–67.
Hennig-Thurau, T., Gwinner, K.P., & Gremler, D.D. (2002).
Understanding relationship marketing outcomes. Journal
of Service Research, 4(3), 230–247.
Hennig-Thurau, T., Gwinner, K.P., Walsh, G., & Gremier,
D.D. (2004). Electronic Word-of-Mouth via consumeropinion platforms: what motivates consumers to articulate
themselves on the Internet?. Journal of Interactive Marketing, 18(1), 38–52.
Herr, P.M., Kardes, F.R., & Kim, J. (1991). Effects of Wordof-Mouth and product-attribute information on persuasion: An accessibility-diagnostic perspective. Journal of
Consumer Research, 17(4), 454–462.
Higie, R.A., Feick, L.F., & Price, L.L. (1987). Types and
amount of Word-of-Mouth communications about retailers. Journal of Retailing, 63(3), 260–279.
Katz, E., & Lazarsfeld, P.F. (1955). Personal influence.
Glencoe, IL: Free Press.
Kim, W.G., Han, J.S., & Lee, E. (2001). Effects of relationship
marketing on repeat purchase and Word of Mouth. Journal
of Hospitality & Tourism Research, 25(3), 272–288.
Mangold, W.G., Miller, F., & Brockay, G.R. (1999). Word-ofMouth communication in the service marketplace. Journal
of Services Marketing, 13(1), 73–89.
Maxham III, J.G. (2001). Service recovery’s influence on consumer satisfaction, positive Word-of-Mouth, and purchase
intentions. Journal of Business Research, 54(1), 11–29.
McKelvey, W.W. (1976). An approach for developing shorter
and better measuring instruments. Working Paper 76–6.
Human Systems Development Study Center, Graduate
School of Management, UCLA.
Morin, S.P. (1983). Influentials advising their friends to sell
lots of high-tech gadgetry. Wall Street Journal, February
28, 30.
Murray, K.B. (1991). A Test of Services Marketing Theory :
Consumer Information Acquisition Activities. Journal of
Marketing, 55(1), 10–25.
Parasuraman, A., Zeithaml, V.A., & Berry, L.L. (1988).
SERVQUAL: A multiple-item scale for measuring customer perceptions of service quality. Journal of Retailing,
64(1). 12–40.
Peterson, R.A. (1994). A meta-analysis of Cronbach’s coefficient alpha. Journal of Consumer Research, 21(2),
381–391.
Bone, P.F. (1992). Determinants of Word-of-Mouth communication during product consumption. Advances in Consumer Research, 19, 579–583.
Bone, P.F. (1995). Word of Mouth effects on short-term and
long-term product judgments. Journal of Business
Research, 32(3), 213–223.
Brown, J.J., & Reingen, P.H. (1987). Social ties and Word-ofMouth referral behavior. Journal of Consumer Research,
14(3), 350–362.
Burzynski, M.H., & Bayer, D.J. (1977). The effect of positive
and negative prior information on motion picture appreciation. The Journal of Social Psychology, 101(1),
215–218.
Calder, B.J., Philips, L.W., & Tybout, A.M. (1981). Design
research for application. Journal of Consumer Research,
8(1), 197–206.
Churchill, G.A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing
Research, 16(1), 64–73.
Cox, D., & Cox, A.D. (2002). Beyond first impressions: The
effects of repeated exposure on consumer liking of visually complex and simple product designs. Journal of the
Academy of Marketing Science, 30(2), 119–130.
Crocker, K.E. (1986). The influence of the amount and type of
information on individuals’ perception of legal services.
Journal of the Academy of Marketing Science, 14(4),
18–27.
Day, G.S. (1971), Attitude change, media, and word of mouth.
Journal of Advertising Research, 11(6), 31–40.
Desormeaux, R., & Labrecque, J. (1999). La mesure de la
satisfaction de la clientèle, Gestion, 24(2), 74–81.
Duhan, D.F., Johnson, S.D., Wilcox, J.B., & Harrell, G.D.
(1997). Influences on consumer use of Word-of-Mouth
recommendation sources. Journal of the Academy of Marketing Science, 25(4), 283–295.
File, K.M., Cermark, D.S.P., & Prince, R.A. (1994). Word-ofMouth effects in professional services buyer behavior. The
Service Industries Journal, 14(3), 301–314.
File, K.M., Judd, B.B., & Prince, R.A. (1992). Interactive marketing: The influence of participation. Journal of Services
Marketing, 6(4), 5.
Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement
error. Journal of Marketing Research, 18(February),
39–50.
Gaski, J. (1984). The theory of power and conflict in channels
of distribution. Journal of Marketing, 48(Summer), 9–29.
Godes, D., & Mayzlin, D. (2004). Se servir des conversations
en ligne pour étudier le bouche-à-oreille. Recherche et
Applications en marketing, 19(4), 89–111.
Godin, S., (2001). Les secrets du marketing viral : le boucheà-oreille à la puissance 10!. Paris : Maxima Laurent Du
Mesnil Éditeur, 197p.
Goyette, I. (2007). Élaboration d’une échelle de mesure multidimensionnelle du bouche-à-oreille dans le secteur des
services électroniques. Mémoire de maîtrise, École des
Sciences de la Gestion, UQAM, 149p.
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
GOYETTE ET AL.
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e-WOM SCALE: WORD-OF-MOUTH MEASUREMENT SCALE FOR e-SERVICES CONTEXT
ior: a clickstream analysis. Journal of Business Research,
58, 1599–1608.
Sheth. J.N. (1971). Word-of-Mouth in low-risk innovations.
Journal of Advertising Research, 11(3), 15–18.
Silverman, G. (2001). The Power of Word of Mouth. Direct
Marketing, 64(5), 47.
Singh, J. (1990). Voice, exit, and negative Word-of-Mouth
behaviors: An investigation across three service categories. Journal of the Academy of Marketing Science, 18(1),
1–15.
Stanbouli, K. (2003). Marketing viral et publicité. Revue Française du Marketing, 192/193(May) , 97–106.
Statistics Canada (September 23, 2004). Achats en ligne:
magasinage des ménages sur Internet. Retrieved from
http://www.statcan.ca/Daily/Francais/040923/q040923a.
htm
Swan, J.E., & Oliver, R.L. (1989). Postpurchase communications by consumers. Journal of Retailing, 65(4),
516–533.
Westbrook, R.A. (1987). Product/consumption-based affective
responses and postpurchase processes. Journal of Marketing Research, 24(3), 258–270.
Whyte, W.H. Jr. (1954). The web of Word of Mouth. Fortune,
50(5), 140–143.
Ying H.L., & Chung C.M. (2007). The effects of single-message single-source mixed Word-of-Mouth on product
attitude and purchase intention. Asia Pacific Journal of
Marketing and Logistics, 19(1), 75–93.
Phelps, J.E., Lewis, R., Mobilio, L., Perry, D., & Raman, N.
(2004). Viral marketing or electronic Word-of-Mouth
advertising: Examining consumers responses and motivations to pass along email. Journal of Advertising Research,
44(4), 333–348.
Ranaweera, C., & Prabhu, J. (2003). On the relative importance
of customer satisfaction and trust as determinants of customer retention and positive word of mouth. Journal of
Targeting, Measurement and Analysis of Marketing,
12(1), 82–90.
Reicheld, F.F. (1996). The loyalty effect. Boston, MA: Harvard
Business School Press.
Reichheld, F.F., & Sasser, W.E. (1990). Zero defections:
Quality comes to services. Harvard Business Review,
5(September/October), 105–111.
Rey-Debove, F. & Rey, A. (2007). Le Nouveau Petit Robert :
Dictionnaire alphabétique et analogique de la langue
française, Paris, Éditions Le Robert.
Richins, M.L. (1983). Negative Word-of-Mouth by dissatisfied
consumers: A pilot study. Journal of Marketing, 47,
68–78.
Salzman, M., Matathia, I., & O’Reilly, A. (2004). Buzz . . . Le
marketing du bouche-à-oreille. Paris: Village Mondial.
Sénécal, S., & Nantel, J. (2004). The Influence of online
product recommendations on consumer’s online choices.
Journal of Retailing, 80(2), 159–169.
Sénécal, S., Kalczynski, P.J., & Nantel, J. (2005). Consumers’
decision making process and their online shopping behav-
Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
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Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
19
Unidimensional
Brown and
Reingen
(1987)
Goyette (2007), p.28–35
Unidimensional
Richins (1983)
NA
Sheth (1971)
Unidimensional
Information not
available (NA)
Arndt (1967b)
Burzynski and
Bayer (1977)
Type of
measurement
scale
Authors
NA
NA
NA
NA
Information
not
available
(NA)
Cronbach’s
Alpha
Self-administered
questionnaire
Respondents: adult
consumers
Sector: clothing and
apparel (electronic)
Telephone interview
Respondents:
professors, adults,
piano students.
Sector: music
Field experiment and
self-administered
questionnaire
Respondents: adults
going to see a movie
Sector: cinema
Personal interview
Respondents: men
Sector: razor blades
Personal interview
Respondents: married
female students
Sector: food products
Methodology
NA
(1) Respondents were asked to recollect the time they became
aware of the new blades, what source informed them for the
first time.
(2) Respondents were asked whether they adopted them
immediately after becoming aware or some time later, and
whether friends and other personal informal sources were
influential in their adoption decision.
(3) Respondents were also asked if they had influenced someone
else after their own adoption. (p.16)
Respondents were exposed to either positive, negative, or no
comments about the film they were about to see. (p.216)
(1) positive prior information: “I wouldn’t mind seeing this one
again,” and “The acting was fantastic, but the plot was even
better”. (p.216)
(2) negative prior information: “You couldn’t pay me to see that
thing again” and “Well, another two bucks shot,” (p.216)
The act of telling at least one friend or acquaintance about the
dissatisfaction. (p. 71)
Since each respondent was questioned about comments received
and given, the conversations could be cross-checked by
comparing the questionnaires of both parties in the
conversation. (p.291)
WOM measurement context
Word-of-Mouth Measurement Scales
Appendix A
“Who-toldwhomabout-theservice” (p.
351)
NA
NA
NA
Information
not
available
(NA)
WOM
statements
Receiver (HarrisonWalker, 2001)
and
communicator
(HarrisonWalker, 2001)
Receiver (HarrisonWalker, 2001)
and
communicator
(Goyette, 2007)
Receiver (HarrisonWalker, 2001)
Receiver (HarrisonWalker, 2001)
and
communicator
(Goyette, 2007)
Receiver and
communicator
(Goyette, 2007)
Viewpoint for
WOM
measurement
e-WOM SCALE: WORD-OF-MOUTH MEASUREMENT SCALE FOR e-SERVICES CONTEXT
GOYETTE ET AL.
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Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
20
Unidimensional
dichotomous,
(0) for no
and (1) for
yes.
Singh (1990)
NA
Westbrook
(1987)
Unidimensional
seven-point
Likert.
NA
Higie, Feick, and
Price (1987)
Swan and Oliver
(1989)
Type of
measurement
scale
Authors
NA
Reliability index:
0.86 (measured
by frequency,
number of
persons and
number of
topics)
NA
NA
Cronbach’s Alpha
Self-administered
questionnaire by mail
Respondents: Households
that have had an
unsatisfactory experience
with one of the services
being studied.
Sector: grocery trade,
vehicle repair, medical
services
Personal interview and selfadministered
questionnaire
Respondents: adult men and
women
Sector: automotive and
cable TV
Self-administered
questionnaire
Respondents: new car
buyers
Sector: automotive
Telephone questionnaire
Respondents: residents of a
metropolitan region in
north-eastern United
States.
Sector: retail sales
Methodology
NA
NA
The respondents were given the opportunity to recall
and report “any other attributes of retail outlets that
they discussed with other people.” Dimensions which
pilot respondents did not discuss (e.g., location and
store hours) and topics that were too broad or general
(e.g, service) were dropped (p.266)
Dimensions included in the final instrument were:
(1) quality of merchandise, (2) special sales,
(3) usual or everyday prices, (4) helpfulness and
friendliness of employees, (5) variety of products
available, (6) availability of particular brands,
(7) return policy.
The response categories were: never, a few times a
year, about once a month, a few times a month, and
once a week or more.
(1) Reported frequency of discussions with others about
CATV and local cable operator.
(2) Number of persons involved.
(3) Number of topics discussed. (p.263)
WOM measurement context
(1) “Did you say
mostly positive
or mostly
negative things
about the car.”
(2) “Did you
recommend
“buy the car”
or “not buy the
car”.” (p. 522)
“Told my friends
and relatives
about my bad
experience.”
(p. 7)
NA
NA
WOM
measurement
items
Communicator
(Goyette,
2007)
Communicator
(Goyette,
2007)
Communicator
(Goyette,
2007)
Communicator
(HarrisonWalker, 2001)
Viewpoint for
WOM
measurement
e-WOM SCALE: WORD-OF-MOUTH MEASUREMENT SCALE FOR e-SERVICES CONTEXT
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Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
21
Bone (1995)
NA
Unidimensional
File,
Cermark,
and
Prince
(1994)
Multidimensional
with three
statements
Bone (1992)
Unidimensional
NA
Herr,
Kardes,
and Kim
(1991)
File, Judd,
and
Prince
(1992)
Type of
measurement
scale
Authors
NA
NA
NA
The three
statements
were
standardized
and added for
αWOM = 0.79
NA
Cronbach’s
Alpha
Experimental presentation.
Complete a card on
product expectations and
performance.
Respondents: students
Test product: biscuit
Questionnaire
Respondents: clients of an
attorney
Sector: Trust and estate
planning
Structured personal
interview
Respondents: company
executives
Sector: professional
services (consultants)
Individual self-administered
questionnaire
Respondents: group of two
or more after a meal.
Sector: restaurants
Experiment
Subjects: students
(undergraduate)
Experimental unit: printed
or verbal information
about a product
Methodology
The respondents were exposed to
either a positive conversation or
with a negative conversation
between two students. (p. 217).
WOM for this study refers to:
“recommending the firm and the
service to others as well as
communications with the firm.”
(p. 6)
NA
The respondents are subjected to a
negative OR positive conversation.
(1) WOM (+): “It’s the best car he’s
ever had. He hasn’t spent a dime
on repairs since he bought it. He
says if it ever wears out he’ll get
another just like it.” (2) WOM (−):
“It’s the worst car he’s ever had. It
seems like it’s always in the shop
being repaired. I think he’s spent
more to keep it running than it
originally cost him.” (p. 458)
NA
WOM measurement context
“A personal endorsement of the
(professional services firm) from a
business associate in the decision
to retain the professional service
provider.”
“Telling other business associates
what you thought of the (service
provider).” (p. 308).
NA
(1) “We did not talk about the food
at all” and “We talk about the
food a lot.”
(2) Whether the food eaten was a
large part of the mealtime
conversation.
(3) How much of the table
conversation dealt with the food
being eaten. Responses ranged
from “nothing was said about the
food” to “the biggest topic of
conversation was our food.”
(p. 580)
NA
NA
WOM measurement items
Receiver (HarrisonWalker, 2001)
Communicator
(Harrison-Walker,
2001)
Receiver (HarrisonWalker, 2001) &
communicator
(Goyette, 2007)
Communicator
(Goyette, 2007)
Receiver (HarrisonWalker, 2001)
Viewpoint for
WOM measurement
e-WOM SCALE: WORD-OF-MOUTH MEASUREMENT SCALE FOR e-SERVICES CONTEXT
GOYETTE ET AL.
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Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
Information
unavailable
Multidimensional
Black, Mitra,
and Webster
(1998)
Mangold, Miller,
and Brockway
(1999)
Unidimensional
seven-point
Likert
Unidimensional
Anderson (1998)
Kim, Han, and
Lee (2001)
Type of
measurement scale
Authors
Self-administered
questionnaire
Respondents:
students
Sector: 77 different
services
Self-administered
questionnaire
Respondents: hotel
customers
Sector: hospitality
αWOM: 0.80
Telephone
interview
Respondents: users
Sector: various
Critical incident
technique
Respondents:
persons stopped
on location
Sector: various
businesses.
Methodology
NA
NA
NA
Cronbach’s
Alpha
The respondents were then asked to think about the last
time someone told them something positive about a
service that they may have had an interest in
purchasing. Then, they were asked to think about the
last time someone told them something negative about
a service that they may have had an interest in
purchasing. Thus, each respondent reported on two
WOM communication incidents, one positive and the
other negative. In regard to each event, respondents
were asked: (1) what service they were thinking about,
(2) how long ago the communication had occurred, (3)
what was said, (4) respondents’ relationship with the
person to whom they were speaking, (5) how the
particular WOM came about, (6) whether the WOM
was part of a broader conversation; and, if so, (7) how
that broader conversation came about.
“Desire to recommend a hotel to other people and
willingness to say good things about a hotel to other
people” (p. 279)
(Influences: Swan and Oliver (1989)
The respondents were asked to provide details on a
recent positive WOM and a negative WOM. The
respondents were probed about the product discussed,
approximate time period of conversation with the
other person, specifics of the WOM conversation, and
motivations behind the WOM. (p.527)
Respondents report word-of-mouth activity in terms of
the number of individuals spoken to about recent
experiences with quality. (p. 10)
WOM measurement context
(1) “I am willing to tell
other people about
the good aspects of
this hotel”
(2) “I am willing to
recommend this
hotel to others”
(p. 281)
NA
“Willingness to
recommend”,
“recommendations to
others” (p. 6)
“Exactly what did you
tell the other person
and what motivated
you to share this
particular
experience?” (p. 528)
WOM measurement
items
Communicator
(Goyette, 2007)
Receiver (Goyette,
2007)
Communicator
(Goyette, 2007)
Communicator
(Harrison-Walker,
2001)
Viewpoint for
WOM measurement
e-WOM SCALE: WORD-OF-MOUTH MEASUREMENT SCALE FOR e-SERVICES CONTEXT
22
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Copyright © 2010 ASAC. Published by John Wiley & Sons, Ltd.
23
Unidimensional
Two-item
measurement
scale
NA
Ranaweera and
Prabhu (2003)
Godes and
Mayzlin (2004)
Multidimensional
7-point Likert
with
“completely
agree” and
“completely
disagree” at
either end.
Harrison-Walker
(2001)
Hennig-Thurau,
Gwinner,
Gremler
(2002)
Type of
measurement
scale
Authors
NA
αWOM: 0.79
(statements
unavailable)
Direct observation of
interpersonal
conversations
(thousands of
discussion forums)
on the “Usenet” site.
Respondents: audience
of a new TV series
Sector: new TV series
(44)
Self-administered
questionnaire
Respondents: students
(undergraduate)
Sector: service
Qualitative interview
Respondents: consumers
Sector: phone service
Self-administered
questionnaire
Respondents:
Consumers of one of
the two services
under investigation.
Sector: veterinary clinic
and hair salon
α WOMpraise =
0.80
α WOMactivity =
0.78
NA
Methodology
Cronbach’s
Alpha
(1) Recommendation of the service
(2) Involuntary recommendation
based on the two-dimensional
typology, which identified two
key types of WOM – receiver
initiated and sender initiated (p.
85)
Measure WOM on the Internet
using online conversations.
Study of two distinct WOM
dimensions: volume and
dispersion (p. 94).
Based on 13 statements (cf. righthand column) created to
measure 4 aspects of WOM.
Statements (1) to (3) : Frequency
Statements (4) to (6) : Number of
contacts
Statements (7) to (9): Details
Statements (10) to (13): Praise
Following a factor analysis in
principal components, the author
cleaned up the measurement
scale retaining only the
statements in bold in the righthand column.
Statements (2), (4), (5), and (7) :
WOM activity
Statements (10) and (13):
Praise WOM
Statements (1), (3), (6), (8), (9),
(11), and (12):
Rejected during scale
purification process
Information unavailable
WOM measurement context
(1) Volume: “what is the scope of word of mouth?”
(p. 94)
(2) Dispersion: “extent and diversity of virtual
communities in which conversations on a given
product are found” (p. 90)
NA
“I often recommend this service provider to others”
(p. 245)
Since I have been with this service organization, I have
mentioned the name of this service organization very
rarely. 2) I mention this service organization to
others quite frequently. 3) I rarely have occasion to
mention the name of this organization to others. 4)
I’ve told more people about this service organization
than I’ve spoken about most other service
organizations. 5) I seldom miss an opportunity to tell
others about this service organization 6) I’ve told
very few people about this service organization. 7)
When I tell others about this service organization, I
tend to talk about the organization in great detail. 8)
I seldom do more than mention the name of this
service organization to others. 9) Once I get talking
about this service organization, it’s hard for me to
stop. 10) I have only good things to say about this
service organization. 11) Although I use this service
organization, I tell others that I do not recommend it.
12) In general, I do not speak favourably about this
service organization. 13) I am proud to tell others
that I use this service organization . . . (p. 72–73).
WOM measurement items
Communicator
and receiver
(Goyette, 2007)
Communicator
and receiver
(Goyette, 2007)
Communicator
(Goyette, 2007)
Communicator
(HarrisonWalker, 2001)
Viewpoint for
WOM
measurement
e-WOM SCALE: WORD-OF-MOUTH MEASUREMENT SCALE FOR e-SERVICES CONTEXT
GOYETTE ET AL.
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27(1), 5–23 (2010)