The Word-of-Mouth Dynamic

8/12/2019 The Word-of-Mouth Dynamic

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DOI: 10.2501/JAR-53-1-043-060 March 2013 JOURNAL OF ADVERTISING RE 43

INTRODUCTIONIn the elds of social psychology and consumer

behavior, marketing researchers have produceda considerable amount of theoretical work on theeffect of interpersonal communication. Such inter-personal communication has become known as a

process of word of mouth (WOM) communication,which now is regarded as one of the most impor-tant and effective communications channels (Kel-ler, 2007). Firms such as Nestl, Procter & Gamble,LOral, Bosch, Microsoft, GlaxoSmithKline, and

Johnson & Johnson, to name just a few, increas-ingly recognize that WOM is an extremely credible,persuasive, and highly effective tool of informalmeans of creating consumer engagement (Nielsen,2009). Another example of the popularity of WOMis the appearance of consultancies specializing

in this area (e.g., gaspedal.com and trnd [http://company.trnd.com/en]). Such companies buildWOM campaigns as part of integrated marketingcommunication. Likewise, the ofcial trade asso-ciation for the WOM marketing industry (Wordof Mouth Marketing Association, or WOMMA),founded in 2005, promotes and advances WOM byoffering educational programs, ethical guidelines,a standardized language, as well as pursuing aresearch agenda and developing WOM metrics.

During the past decade, advances in electroniccommunications technology have led to considera-

ble expansion in the number and types of informalcommunications channels. Electronic newsgroups,

blogs, virtual communities, instant messaging, cellphones, and Personal Digital Assistants (PDAs),

among other options, offer consumers instantane-ous interactions with advertisers, fellow consum-ers, and other market players (Allsop, Bassett, andHoskins, 2007; Hung and Li, 2007; Smith, Coyle,Lightfoot, and Scott, 2007).

This uptick in activity has helped make WOMa powerful communications channel that has animportant inuence in the formation of consumeropinions and in their purchase decisions. More-over, this type of communication among con-sumers is particularly interesting for advertising

practitioners, for two reasons: 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 stimulateWOM through advertising (Graham and Hav-lena, 2007).

Although previously many advertisers tradition-ally have considered WOM as an alternative to

The Word of Mouth Dynamic: How Positive (andNegative) WOM Drives Purchase Probability

An Analysis of Interpersonal and

Non-Interpersonal Factors

RODOLFO VZQUEZ-CASIELLESUniversity of Oviedo, Spain

[email protected]

LETICIA SUREZ-LVAREZUniversity of Oviedo, Spain

[email protected]

ANA-BELNDEL RO-LANZAUniversity of Oviedo, Spain

[email protected]

This study has two main objectives: (a) to examine the relative impacts of positive and

negative word of mouth (PWOM and NWOM) on the shift in the receivers brand purchase

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

in the receivers purchase probability. The data were collected from a sample of 1,035

consumers in four product/service categories. The results suggest that rms should

develop a proactive management of WOM communications that takes into accountaspects of both the sender and receiver.


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44 JOURNAL OF ADVERTISING RESEARCH March 2013

THE WORD OF MOUTH DYNAMIC

advertising, WOM and advertising noware regarded as two important communi-cations channels that interrelate and com-plement each other.

The main objective of the current arti-cle is to analyze how WOM communica-tion increases (or decreases) the receivers brand-purchase probability.

WOM communication can be said tohave two dimensions (Harrison-Walker,2001):

WOM activity includes such aspectsas how often WOM takes place,

the number of people with whom theWOM sender communicates, and

the quantity of information provided. WOM valence can be positive, nega-

tive, or neutral.

Although the content and strength of bothdimensions of the WOM condition affectthe probability of a consumers choosinga particular brand, few studies have ana-lyzed the impact of both dimensions.

The majority of studies in the WOM lit-erature have focused on the WOM activ-ity dimension. And, in fact, there is littleempirical evidence that helps explain howpositive and negative WOM contributes tothe shift in the probability of choosing a brand (Assael, 2004; East, Hammond, andLomax, 2008).

Moreover, these studies primarily havefocused on positive WOM and its inu-ence on which product is purchased. It also

is necessary to examine negative WOM,which discourages purchase (Bruyn andLilien, 2008). To that end, this researchanalyzes the WOM valence dimensionand the impact of positive and negativeWOM on the shift in the receivers pur-chase probability.

Finally, this study also examines thevariables that explaindirectly or indi-rectlythe shift in the WOM receivers

purchase probability. For this purpose, theauthors have grouped the variables into

interpersonal factors (how actively

WOM is sought, strength of tie betweensender and receiver, and senders expe-rience and strength of expression),and

non-interpersonal factors (receiversloyalty, experience, and perceived risk).

In the current study, the authors researchhas

embraced the perspective of the WOM

receiver, compared the impacts of positive and

negative WOM, and determined the direct and indirect

effects of the different interpersonal andnon-interpersonal factors on the shift inthe purchase probability of the receiverof positive (or negative) WOM.

The balance of this research

presents the authors conceptual den-ition of WOM and the lines of researchexamining how WOM works,

describes a conceptual model, and presents the authors proposed

hypotheses.

Explanations of research design, meth-odology, and results follow. The workconcludes with a discussion of the mainndings of the analysis and then offers

managerial implications.

LITERATURE REVIEW

The literature denes WOM as all infor-mal communications directed at otherconsumers about the ownership, usage,or characteristics of particular goods andservices or their sellers (Westbrook, 1987,p. 261). Additionally, WOM can be any oraland personal communication, positive or

negative, about a brand, product, service,or organization, in which the receiverof the message perceives the sender tohave a non-commercial intention (Arndt,

1967).These denitions are consistent withother WOM studies (Gruen, Osmonbekov,Czaple, 2006; Harrison-Walker, 2001; Wan-genheim, 2005; Wangenheim and Bayon,2007), and share two characteristics:

The receiver of the message must per-ceive the sender to be unconnected withany commercial organization. In otherwords, for it to be credible, a WOM

recommendation must spring from anatural dialogue between the two peo-ple, and it should be the product of thesenders knowledge and the receiversneed to know.

WOM can be either positive or negative.Positive WOM encourages purchase,whereas negative WOM discouragespurchase.

The WOM literature has three lines of

research.

The rst focuses on the perspectiveof the WOM sender and analyzes thereasons why people make positive (ornegative) recommendations on the basisof their experiences with a product.These studies conclude that a numberof forces (non-interpersonal factors)exist and give rise to recommendations.These forces include

satisfaction or dissatisfaction (Ander-son, 1998; Bowman and Narayandas,2001; Brown, Barry, Dacin, and Gunst,2005; Heitmann, Lehmann, andHermann, 2007; Maxham and Nete-meyer, 2002), loyalty (Gounaris andStathakopoulus, 2004);

commitment to the rm (Brownet al., 2005; Dick and Basu, 1994;Henning-Thurau, Gwinter, Walsh,


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March 2013 JOURNAL OF ADVERTISING RE 45


and Gremler, 2002; Lacey, Suh, andMorgan, 2007);

trust (Ranaweera and Prabhu, 2003;Sichtmann, 2007);

service quality (Harrison-Walker, 2001); length of relationship with the rm(Wangenheim and Bayon, 2004a2004b); and

perceived value (Matos and Vargas,2008).

The second line of research aims tounderstand WOM receivers informa-tion search behaviors or, more spe-cically, under what circumstances

(non-interpersonal factors) consumersresort to WOM rather than other infor-mation sources before making their pur-chase decisions.

Researchers have found that con-sumers are more likely to seek otherpeoples opinions before purchasingwhen they have less experience and astronger involvement in the purchaseof the product category (Gilly, Graham,Wolnbarger, and Yale, 1998) or when

they perceive greater risk in the decisionmaking (Bansal and Voyer, 2000).

The third line of research also adoptsthe perspective of the WOM receiverand examines why some personalinformation sources (positive and nega-tive WOM) exert a stronger inuence.Researchers have identied forces(interpersonal factors) that inuence thereceivers behavior, such as

the WOM senders experience andstrength of expression (Bansal andVoyer, 2000; Gilly et al., 1998);

the strength of the personal tie between WOM sender and receiver(Frenzen and Nakamoto, 1993);

the demographic similarity (Brownand Reingen, 1987); and

the perceptual afnity (Gilly et al.,1998).

CONCEPTUAL MODEL AND HYPOTHESES

In line with the aforementioned literatureon WOM, the authors have developed aconceptual framework (See Figure 1) that

adopts the perspective of the WOMreceiver;

describes the relations between the typeof WOM (positive or negative) and theshift in the brand-purchase probability;

analyzes which type of WOM has themost impact on the shift in the brand-purchase probability; and

investigates the effectdirect or indi-recton the shift in the WOM receivers

brand-purchase probability of differentinterpersonal (how actively WOM issought, strength of tie between senderand receiver, and senders experienceand strength of expression) and non-interpersonal factors (receivers loyalty,experience and perceived risk). 1

IMPACT OF POSITIVE AND NEGATIVE WOM

ON SHIFT IN RECEIVERS PURCHASE

PROBABILITY

In general, positive (or negative) WOMis assumed to make the receiver more

1 The model hypothesised in this study is based on the theoryof planned behaviour (Ajzen, 1991). In line with this theory,the authors postulate three conceptually independent deter-minants of behavioral intention (shift in the WOM receiv-ers brand-purchase probability). The rst is theattitudetoward WOM . Attitude toward WOM is measured hereby estimating the impact of positive and negative WOM onthe shift in the receivers purchase probability. The second predictor is the subjective norm , which is concerned with judgments of the effectsdirect or indirecton the shift in

the WOM receivers brand-purchase probability of differentsocial inuences (how actively WOM is sought, strength oftie between sender and receiver, and senders experience andstrength of expression). The third antecedent is the degreeof perceived behavioral control , which is concerned with perceptions of the effects, on the shift in the WOM receiversbrand-purchase probability, of peoples condence in theirability to deal with purchase situations (receivers experi-ence and perceived risk). The authors argue, however, thatthese three variables from the theory of planned behavior areinsufcient to permit prediction of the shift in the WOMreceivers brand-purchase probability. Anther variable past behavior (receivers loyalty)could further enhancethe shift in the WOM receivers brand-purchase probability.

positive (or negative) about the object ofadvice (East et al., 2008).

Some studies, however, have observedthe opposite response among receivers

(Fitzsimons and Lehmann, 2004): peoplesometimes react against negative com-ments and became even more committedto the brand. Such contrary responses canoccur when

people are directed to do things thatthey do not want to do,

the WOM receiver disagrees with thevalues of the advisor, or

when prior commitment to a brand may

prevent consumers from fully acceptinguseful negative information about that brand.

Assuming that contrary responses are notcommon, then conceivably positive WOMhas a positive impactand negativeWOM a negative impacton the brandspurchase.

The authors thus offer their rsthypothesis:

H1: Positive (negative) WOM has apositive (negative) impact on theshift in the receivers purchaseprobability.

It is also interesting to analyze whichtype of WOM (positive or negative) hasthe most impact. The literature offers littleevidence on this question.

Some studies have found that nega-

tive WOM has more impact than positiveWOM. For example, one eld study foundthat negative WOM has twice as muchimpact on judgment or attitudes as posi-tive WOM (Arndt, 1967). The author ofthat report studied only one brand, how-ever, and systematic research should be

based on all the brands in a category andshould include a range of categories. Thisauthor also used a new brand about which


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there could be few established beliefs.Nevertheless, a later study conrmed theprevious results and observes that nega-tive WOM is more inuential than positiveWOM (Assael, 2004).

There is some theoretical justication forthe idea that negative information usuallyhas more impact on judgment than posi-tive information. Indeed, one study foundthat negative information usually was

rarer than positive information becausethe latter can often be presumed (Fiske,1980). In such instances, the relative rar-ity of negative information surprises con-sumers and, consequently, they pay moreattention to it.

This is the so-called negativity effect,which has been observed in other studies(Chevalier and Mayzilin, 2006) and can beexpressed in terms of the gap between the

position implied by the WOM messageand the receivers position.

This gap has diagnostic value: informa-tion that restates what the receiver believesmay increase certainty but is unlikely tochange other aspects of a receivers judg-ment (e.g., purchase probability). In manymarkets, the greater amount of positiveinformation about the different brandsensures that the position of most WOM

receivers is positive, so negative informa-tion will have more impact.

In any case, the impact of positive (ornegative) WOM may differ when the

brands are familiar. For example, onestudy analyzed the response of consum-ers receiving positive and negative infor-mation about brands and compared theresults when the consumers are familiaror unfamiliar with the brand (Ahluwalia,

2002). According to this research, when the brand is unfamiliar, the negative informa-tion is perceived to have more diagnos-ticity, but when the brand is familiar, no

signicant differences exist in the impactsof positive (or negative) information.That study argued that brand familiarityattenuates the perception of the greaterdiagnostic value of negative informationand suggested that, under these circum-stances, positive information may be per-ceived to be more diagnostic than negativeinformation.

Such studies as those referenced heretypically measure how advice changes

judgment and/or attitude. In research onthe purchase of brands, it is more relevantto measure the change in the purchaseprobability brought about by WOM type.From this perspective, using both role-playexperiments and surveys further meas-ured WOMs impact on choice as a shiftin the stated purchase probability, frompre-WOM purchase probability to post-WOM purchase probability (East et al.,2008). These authors contended that, if

the pre-WOM purchase probability is below 0.5, there is more room for changein response to positive WOM than inresponse to negative WOM.

For example, if the pre-WOM pur-chase probability is 0.3, positive WOMcan have a maximum effect of 0.7 (up tounity), whereas negative WOM can havea maximum effect of only 0.3 (down to 0).That study also sought to obtain a meanpre-WOM purchase probability of 0.4, so

the authors argued that positive WOMusually had more effect than negativeWOM.

In short, room for change in the brand-purchase probability is limited by the pre-WOM purchase probability, which couldfavor the impact of either positive (ornegative) WOM, depending on the meanpre-WOM purchase probability.

Thus, conceivably:

WOM COMMUNICATIONBETWEEN SENDER

AND RECEIVER

Positive WOMNegative WOM

SHIFT IN RECEIVERSPURCHASE PROBABILITY

How activelyWOM is sought

Tie strength

Sendersexperience

Senders strength of expression

Receiversexperience

Receivers loyalty

Receiversperceived risk

INTERPERSONAL

FACTORS

NON-INTERPERSONAL

FACTORS

How actively WOMis sought

Figure 1 Factors Associated with Impact of Positive andNegative WOM on Shift in Receivers Purchase Probability


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H2: Positive WOM has more impactthan negative WOM on the shiftin the receivers brand-purchaseprobability when the pre-WOM

purchase probability is low.

INTERPERSONAL FACTORS ASSOCIATED

WITH IMPACT OF POSITIVE AND NEGATIVE

WOM ON SHIFT IN RECEIVERS PURCHASE

PROBABILITY

Figure 2 summarizes the characteristicsof the interpersonal factors (how activelyWOM is sought; strength of tie betweensender and receiver; senders experienceand strength of expression), the relation

between them, and their impact on theshift in the receivers purchase probability.

HOW MARKETERS ACTIVELY SEEK WOM

The active search for information throughWOM is dened as the process of seek-ing and paying attention to personalcommunications.

Associated with the process of activesearch for information through WOM isthe selective exposure to the messages

deriving from WOM communication,which, in turn, implies that the consumerhas a greater predisposition toward theWOM message (Arndt, 1967).

Thus, a message that is sought activelywill have a greater impact on the shift inthe WOM receivers purchase probabilitythan one that is received passively and ismoreover unsought and unrequested.

The authors third hypothesis follows:

H3: The more intense the WOM(positive or negative) receiversactive search for information,the greater the shift in the receiv-ers purchase probability.

TIE STRENGTH

Sources of WOM recommendation can be classied according to the similarity ofthe parties and the proximity or closeness

of the relationship between the WOMreceiver who must make the decision andthe WOM sender (Duhan, Johnson, Wilcox,

and Harell, 1997): in other words, in func-tion of their tie strength. The tie strengthof a relationship is considered to be highwhen the sender knows the receiver per-sonally. Moreover, the tie strength containsthe following interpersonal dimensions(Frenzen and Davis, 1990):

closeness, intimacy, support, and association.

Tie strength, therefore, reects the relationand the type of tie existing between twopeople.

A later work suggested that a high tiestrength will have a stronger inuenceon the receivers behavior than a weak tiestrength (Frenzen and Nakamoto, 1993).When the tie is strong, the WOM sender

and receiver will be more familiar witheach other, and the receiver will attributegreater credibility to the sender. Moreover,

the receiver will be more likely to initiatean active search for information.

In light of the preceding, the fourthhypothesis is as follows:

H4: The stronger the tie betweenthe sender and the receiver, themore actively the receiver willseek information through thetwo types of WOM (positive ornegative).

SENDERS EXPERIENCE AND STRENGTH

OF EXPRESSION

The WOM senders experience conceiv-ably will affect the way the WOM isperceived.

Specically, the receiver will seek infor-mation more actively from a sender seen asexpert: in other words, someone who hasa high level of knowledge, competence,

Positive WOM

Negative WOM

WOM TYPE

H3 (+)

H4 (+)H5 (+)

H6 (+)

Tie strengthCloseness, Intimacy,Support, Association

Senders experienceKnowledge, Competence,

Education, Experiencein the product category

Senders strength of expressionConvincing arguments

How actively WOM is soughtSelective exposure to WOM

Predisposition towards WOM

SHIFT IN RECEIVERS PURCHASE PROBABILITY

Figure 2 Interpersonal Factors: Impact on Shift in ReceiversPurchase Probability


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education, and experience in the productcategory (Netemeyer and Bearden, 1992).

By contrast, if the receiver perceives thesenders knowledge, competence, educa-

tion, and experience in the product cat-egory is low, the receiver is likely to be lesspredisposed to seek or request informa-tion from the sender to form an intentionor make a purchase decision.

The fth hypothesis of the current studyis as follows:

H5: The greater the receivers per-ception of the senders expe-rience, the more actively the

receiver will seek informationthrough the two types of WOM(positive or negative).

Conversely, the WOM senders strengthof expression can be dened as the WOMreceivers perception of the extent to whichthe sender uses convincing arguments intheir positive (or negative) WOM.

Conceivably, the WOM sendersstrength of expression will directly affect

the impacts of the positive and negativeWOM communication on the shift in thereceivers future purchase probability(East et al., 2008).

This leads to the following hypothesis:

H6: The greater the WOM send-ers strength of expression, thegreater the shift in the purchaseprobability of the consumer whohas received positive (or nega-

tive) WOM.

NON-INTERPERSONAL FACTORS

ASSOCIATED WITH IMPACT OF POSITIVE

AND NEGATIVE WOM ON SHIFT IN

RECEIVERS PURCHASE PROBABILITY

Figure 3 summarizes the characteristics ofthe non-interpersonal factors (receiversloyalty, experience, and perceived risk),the relation between them, their relation

with an interpersonal factor (how activelyWOM is sought), and their impact on theshift in the receiver s purchase probability.

Receivers Loyalty

The loyalty of the receiver of the positive(or negative) WOM communication abouta brand can conceivably help explain theshift in their future purchase probability.

Loyal receivers have a stronger moti-vation for processing new positive infor-mation (positive WOM) about the brandthey purchase habitually to reduce theircognitive dissonance (Wangenheim,

2005) and reinforce their future purchase behavior.

Furthermore, loyal receivers will havea strong resistance to being persuaded

by negative information (negative WOM)about the brand they purchase habitu-ally and will try to convince themselvesthat their previous decisions were rightand that the negative recommendation isthe result of the WOM senders one-off

market experience (Matos and Vargas,2008; Sweeney, Soutar, and Mazzarol, 2008).

Thus, the conceptual framework

proposes

H7: The greater the WOM receiversprior brand loyalty, the weakerthe impact of positive and nega-tive WOM about the brand onthe shift in the receivers pur-chase probability.

Receivers Experience

Various studies have suggested that a

negative relation exists between the con-sumers experience and the active searchfor external information before makinga purchase decision (Bansal and Voyer,2000; Mishra, Umesh, and Stern, 1993).This is because the expert receiver alreadypossesses sufcient knowledge about theproduct category and has no need to con-sult with other people before making adecision.

Positive WOM

Negative WOM

WOM TYPE

H3 (+) H7 ()

H8 ()

H9 ()

H10 (+)

SHIFT IN RECEIVERS PURCHASE PROBABILITY

How actively WOM is soughtSelective exposure to WOM

Predisposition towards WOM

Receivers loyaltyMotivation for processing positive WOM

Resistance to being persuaded by negative WOM

Receivers perceived risk

Subjective expectation of lossesIndividual characteristic

Receivers experience

Confidence about ability tomake an appropriate decision

Figure 3 Non-Interpersonal Factors: Impact on Shift inReceivers Purchase Probability


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By contrast, WOM receivers with littleexperience or knowledge about the prod-uct category are likely to lack condenceabout their ability to make an appropriate,

satisfying decision. Thus, they will feel theneed to consult with other consumers.Hypothesis 8 of this work follows:

H8: The greater the WOM receiversexperience, the less actively theywill seek information throughthe two types of WOM (positiveor negative).

Receivers Perceived Risk

A perceived risk is dened as a subjec-tive expectation of losses (Dholakia, 1997,p. 161). The perceived risk variable is tiedto each product category, so the purchaseof different product categories is associ-ated with different levels of perceived risk.Perceived risk also is an individual char-acteristic, as different people can perceivedifferent levels of risk when purchasingthe same product.

A relation conceivably exists between

WOM receivers experience in the prod-uct category and their perceived risk inits purchase. Consumers who are lessexperienced in a particular product cat-egory probably will perceive more riskin that purchase and, from the informa-tion economics perspective, they willgain more from the information that theWOM sender provides (Gilly et al., 1998).The penultimate hypothesis of this workfollows:

H9: The more experienced thereceiver of the two types ofWOM (positive or negative), thelower the perceived risk associ-ated with the purchase of theproduct/service.

In an effort to reduce the risk associatedwith a purchase decision, consumers seek

information about the product. WOM isone of the most effective sources of infor-mation for reducing the risk associatedwith the purchase of a particular product(Guo, 2001).

People who perceive more risk in a pur-chase situation tend to seek informationthrough WOM more actively than those

who perceive a lower risk (Arndt, 1967).WOM, in fact, may be the most import-ant information source for reducing risk(Bansal and Voyer, 2000). It also has thestrongest impact on the receiver of thecommunication, mainly because it permitsclarication of any doubts and offers thechance of leaving feedback (Murray andSchlacter, 1990).

The nal hypothesis of the currentstudy:

H10: The greater the receivers per-ceived risk in relation to the pur-chase of the product, the moreactively they will seek informa-tion through the two types ofWOM (positive or negative).

METHODOLOGY

Sample and Data Collection

To test the 10 hypotheses, the authors

chose two consumer durables productmarkets: mobile phones and laptop com-puters; and two services: mobile-phonecompanies and travel agencies.

These products and services were cho-sen because

consumers need to make evaluationsand comparisons when purchasingthem (high involvement),

their use and consumption is very wide-spread, and

consumers are likely to perceive risk inthe purchase decision.

The nature of the choices helped ensurethat the authors could gather a sampleof subjects that had received positive (or

negative) WOM communications frompeople unconnected to the different mar-ket players.

The study participants were recruitedrandomly in various shopping centers innorthern Spain. To ensure familiarity, theconsumers interviewed had to own anduse a mobile telephone or laptop com-puter or use the services of a mobile-phonecompany or travel agency. They also hadto have received, in the past 3 months,

positive (or negative) WOM for different brands of the aforementioned products orservices.

After this random sampling system, theauthors obtained information from a sam-ple of 1,100 individuals. They excluded65 questionnaires due to incomplete data,which resulted in a net sample size of1,035.

Each subject was asked about only oneproduct or service. The sample, therefore,

consisted of 1,035 different individuals.Furthermore, the sample consisted ofactual consumers of the products or ser-vices analyzed, not of students.

The distribution of the subjects by prod-ucts/services was as follows (Table 1):

258 subjects owned and used a mobilephone,

253 owned and used a laptop,

A relation conceivably exists between WOM

receivers experience in the product category

and their perceived risk in its purchase.


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268 used the services of a mobile-phonecompany, and

256 used a travel agency.

The distribution by gender was 47.7 per-cent male and 52.3 percent female. A totalof 45.4 percent of the respondents were between ages 18 and 34 years, 40.5 percent between 35 and 54 years, and 14.1 percent

older than 54 years. Finally, 52.6 percentof the respondents had received positiveWOM, whereas 47.4 percent had receivednegative WOM.

The authors collected the informationthey required using structured question-naires presented in the course of personalinterviews. The rst part of the ques-tionnaire asked the respondents (WOMreceivers) about their experience with thecategory, their current brand, their ten-

dency to ask for advice before making thepurchase, and their perception of the riskin the purchase.

The second part of the questionnairefocused on the WOM received by theindividuals. The interviewees were askedwhether they had received many or onlya few positive (or negative) WOM com-munications about a particular product orservice in recent months.

If they had received a number ofWOM communications, they were askedto consider the single communicationthey felt had had the most impact on theirdecision.

The questionnaire then asked surveyparticipants about the following:

the brand that was the subject of the

positive (or negative) recommendation;

a number of points relating to the WOMsender: strength of relationship with them, experience in the product/service cat-egory, and

credibility of arguments used; and

the probability of choosing the brand before and after the positive (or nega-

tive) recommendation.

The questionnaire concluded with ques-tions about the age and gender of therespondents.

Variable Measures

Using construct denitions and pre-existing measures available from the liter-ature, the authors generated a set of items

for each construct. They also consultedve practitioners and academic experts.Any problematic items were either deletedor appropriately modied.

The authors presented the resultingitems to 20 consumers of the productsand services analyzed in this research inface-to-face meetings to ensure that thequestions were worded with appropri-ate consistency. They then revised severalitems on the basis of the feedback. Finally,to measure each of the constructs of inter-est, they adopted single-item and multi-item scales (Appendix).

The authors used three single-item

measures to capture information about brand-purchase probability before receiv-ing the WOM recommendation (receiversloyalty), brand-purchase probability afterreceiving the WOM recommendation, andsenders strength of expression.

A single-item measure is sufcient ifthe construct is such that in the mind ofraters (e.g., respondents in a survey),the object or attribute of the construct isconcrete, meaning that it consists of one

object or attribute that is easily and uni-formly imagined (Bergkvist and Rossiter2007, 2009).

In the current study, the object (brand)or the attribute (how convincing/cred-ible were the explanations of the personwho sent the WOM) is concrete, so theauthors used single-item measures to cap-ture information about brand-purchaseprobability (a 10-point scale) and sendersstrength of expression (7-point scale).

The shift in the receivers brand-purchase probability was calculated asthe difference between the probability ofchoosing the brand after and before therecommendation.

The authors also use multi-item meas-ures to capture information about veconstructs linked to interpersonal andnon-interpersonal factors of the WOMcommunication:

TABLE 1

Sample CharacteristicsProduct Service

Mobile

phone Laptop

Mobile-phone

services

Travel agency

services Total

SUBJECTS 258 253 268 256 1,035

Male (%) 46.8 53.8 44.6 46.2 47.7

Female (%) 53.2 46.2 55.4 53.8 52.3

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


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how actively WOM is sought, tie strength, senders experience, receivers experience, and

receivers perceived risk.

To evaluate each of these measures, theauthors used 7-point scales. The principaltheoretical argument for using a multi-item measure of a construct is that a multi-item measure captures more informationand is more likely to tap all facets of theconstruct of interest (Bergkvist and Ros-siter, 2007, 2009). Another argument formultiple items is that it increases reliabil-

ity by allowing the calculation of the coef-cient alpha, which indicates the internalconsistency of all the items that representthe presumed underlying construct.

This reliability argument, however,needs to be qualied. The coefcient alphanever should be used without rst estab-lishing the unidimensionality of the scales;this can be investigated by factor analysis.Thus, the authors ran ve exploratory fac-tor analyses for the constructs linked to

interpersonal and non-interpersonal fac-tors of the WOM communication. Thesetests conrmed the unidimensionality ofeach of the ve scales, which means thecoefcient alpha can be used.

The resulting coefcient alphas werehigh, indicating internal consistencyand supporting the use of multi-itemmeasures to capture information aboutthe constructs linked to interpersonal andnon-interpersonal factors of the WOM

communication (See Appendix).Another problem that the authors con-

sidered was common-method bias, whichoccurs when the correlation between twoor more constructs is high. To analyzecommon-method bias, the authors ranan exploratory factor analysis with allthe attributes linked to interpersonal andnon-interpersonal factors of the WOMcommunication.

The results obtained allowed the authorsto identify ve factors corresponding tointerpersonal and non-interpersonal con-structs of the WOM communication. Thefactor loadings were high in each of theve dimensions identied, and the factorstogether explained 85 percent of the vari-ance (KMO = 0.897).

As a result, the common-method biaswas not a problem for the current analysis,so multi-item measures could be used insubsequent analyses to obtain informationabout the constructs linked to interper-sonal and non-interpersonal factors of theWOM communication.

Data Analysis: The Measurement Model

The data analysis employed a two-stepprocedure. The measurement model was

estimated for the entire sample (positiveand negative WOM receivers) prior to theanalysis of the structural model. 2 All vari-ables of interest were conceptualized asreective rst-order constructs. A meas-urement model including how activelyWOM is sought, tie strength, sendersexperience, receivers experience and per-ceived risk was subjected to conrmatoryfactor analysis using structural equationmodeling (with EQS).

As a result, a 22-item, ve-factor covari-ance structure measurement model wasestimated to assess the t, reliability, andvalidity of the measurement scales of themodel constructs. In addition, the averagevariance extracted (AVE), the compositereliability coefcient (CR), and the stand-ardized lambda parameters also were

2 The results of the structural model (causal analysis) can beseen in the Results section.

examined. Together, these tests provideevidence of reliability and validity. SeeAppendix for a summary of the scalespsychometric properties, which wereobtained from the measurement model. 3

RESULTS

Descriptive Analysis: Impact of WOM

Communications on Purchase ProbabilityDescriptive analysis (using SPSS) wasemployed to test the hypothesized rela-tions H1 and H2 in the four product/ser-vice categories. Table 2 (col. 1) shows thecategories. Columns 2 and 3 are the pur-chase probabilities prior to positive andnegative WOM, respectively, and columns4 and 5 are the mean shifts in the purchaseprobability produced by positive and neg-ative WOM, respectively.

According to these results, positiveWOM has a positive impact, and negativeWOM has a negative impact on the shift inthe receivers brand-purchase probability.H1 is supported.

Furthermore, when the mean impacts ofpositive and negative WOM are measuredas the shift in purchase probability, posi-tive WOM produces a mean shift of 1.8542,and negative WOM produces a mean shift

3

The measurement model ts the data well. Regardingreliability, each construct has a composite reliability and AVE greater than the recommended threshold values of 0.and 0.6, respectively. In addition, for all constructs, theCronbach alpha coefcient exceeds 0.9. Convergent validis supported as all lambda parameters are signicant and greater than 0.5. Discriminant validity is supported, asthe condence intervals of the correlations between all thevariables do not include 1.0 and the squared correlationsdo not exceed the AVE. Finally, the t statistics indicate a good model t (Root Mean Square Error of Approximatio= 0.065; Bentler-Bonett Non-Normed Fit Index = 0.955;General Fit Index = 0.966; robust Comparative Fit Index= 0.961).

Another problem that the authors considered was

common-method bias, which occurs when the

correlation between two or more constructs is high.


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of 1.6261, which means positive WOM is14 percent more inuential than negativeWOM. When absolute numbers are tested,positive WOM has signicantly moreimpact than negative WOM in the meansdata and across categories of products( p < 0.001 one-tailed exact tests).

Thus, analyzing the shifts in purchaseprobability, H2 is supported. Overall, posi-tive WOM has more impact that negative

WOM.The authors also used descriptive anal-

ysis (with SPSS) to test the hypothesizedrelation H7 in the four product/servicecategories. The results do show that thegreater the WOM receivers previous loy-alty, the weaker the impact of both posi-tive and negative WOM communicationson the shift in the brand-purchase probability. Table 3 and Figure 4 present the rela-tion between previous brand loyalty and

shift in the brand purchase probability ina more accessible form. For both positiveand negative WOM, a relatively straightsection on each plot is evident, whichthen deects toward the x-axis. Thesedeections can be attributed to the effectof brand commitment and show how thisfactor constrains the impact.

Thus, this work provides support forH7: the receivers loyalty reduces the

impact of positive and negative WOM onthe brand-purchase probability.

Causal Analysis: Structural Model

Evaluation

The authors used structural-equationmodeling (with EQS) to test the remaining

hypotheses in the two subsamples: con-sumers who had received positive WOMor negative WOM (Table 4).

Most of the proposed relations are

supported in both subsamples: consum-ers who had received positive (or nega-tive) WOM. Thus, the more intense thereceivers active search for informationand senders strength of expression, thegreater the shift in the brand-purchaseprobability (See Table 4).

Thus, H3 and H6 are supported.The results also conrm the inuence

of senders experience, receivers experi-ence, and receivers perceived risk on how

actively WOM is sought, and H5, H8, andH10 are supported.

The results also show that H9 is sup-ported in both subsamples: the greater theexperience of the receiver of the positive(or negative) WOM communication, thelower the risk perceived in the purchase ofthe product/service.

TABLE 3Mean Shift in Brand Purchase Probability as Function of Loyalty

Purchase probability prior to

WOM (receivers loyalty)

Mean shift in purchaseprobability after positive

WOM

Mean shift in purchaseprobability after negative

WOM

X-axis Y-axis Y-axis

0 1.2206 0.0000

1 1.5778 0.3846

2 1.9029 0.9526

3 2.2857 1.2806

4 2.4240 1.6907

5 2.5563 2.18526 1.9337 2.5957

7 1.3508 2.5222

8 0.7143 1.6870

9 0.6471 0.7143

10 0.0000 0.4667

TOTALS 16.6132 14.4796

The relation between previous brand loyalty and shift in the brand purchase

TABLE 2Impact of Positive and Negative WOM on Shift in ReceiversPurchase Probability

Product/Service

Category

Purchase probability Shift in purchase probabilityPrior 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

Descriptive analysis: impact of receivers loyalty on purchase probability


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The results, however, only partially

support the inuence of the strength ofthe tie between sender and receiver onhow actively WOM is sought. The param-eters obtained are signicant for thesubsample of consumers who receivedpositive WOM but non-signicant for thesubsample of consumers who receivednegative WOM.

H4 is supported for positive WOM butnot for negative WOM.

DISCUSSION AND CONCLUSIONS

WOM long has been recognized as a pow-erful force affecting consumers attitudeand choice. The results of the current studyenhance current understanding of howWOM inuences the receivers choice.

This article, unlike previous studies,represents an attempt to explicitly test thedifferential impact of positive and nega-tive WOM on the mean shift in the brand-purchase probability.

Furthermore, this work differs from

most earlier studies on WOM in that theauthors investigated various brands in arange of categories of products (mobilephones and laptops) and services (mobile-phone companies and travel agen-cies). From this perspective, this studymakes various contributions to the lit-erature on WOM communications inmarketing.

Specically:

0,0000

0,1250

0,25000,3750

0,5000

0,6250

0,7500

0,8750

1,0000

1,1250

1,2500

1,3750

1,5000

1,6250

1,7500

1,8750

2,0000

2,1250

2,2500

2,3750

2,5000

2,6250

2,7500

2,8750

3,0000

0 1 2 3 4 5 6 7 8 9 10

Positive WOM Negative WOM

Purchase probability prior to WOM (receivers loyalty)

M e a n s

h i f t i n p u r c

h a s e p r o

b a

b i l i t y a

f t e r p o s i

t i v e a n

d n e g a

t i v e

W O M

Figure 4 Mean Shift in Purchase Probability after Positive and Negative WOM


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The empirical analysis shows that posi-

tive (negative) WOM has a positive(negative) impact on the shift in thereceivers brand-purchase probabil-ity. The results also show that positiveWOM has a stronger impact on brand-purchase probability than negativeWOM.

An explanation for positive WOMsstronger effect in this study is that theprior purchase probability tends to be below 5 on a 10-point scale. In particu-

lar, the prior purchase probability is4.2984 for the positive WOM subsampleand 4.4721 for the negative WOM sub-sample. This situation leaves more roomfor change in response to positive WOMthan in response to negative WOM.

Thus, the results suggest that nega-tive WOM is less diagnostic than posi-tive WOM. There is a positivity effect(using Fiskes gap explanation), with

positive WOM having more impact than

negative WOM.

The results also show that the sameinterpersonal factors govern the impactof both positive and negative WOMon the shift in the receivers brand-purchase probability. The authors canconclude that the senders strength ofexpression has the greatest inuence for

both positive and negative WOM, fol-lowed by how actively WOM is sought.

The ndings of this study suggest thatwhen the senders strength of expres-sion is high and when WOM (positive ornegative) is actively sought, WOM willhave a signicant inuence (positive ornegative) on the shift in the receivers

brand-purchase probability.Thus, marketing strategies designed

to promote interpersonal communica-tion will reach more senders/receivers

and be more efcient if they are directed

at senders with strength of expressionand receivers who are motivated to seekinformation through WOM.

Firms also should pay particularattention to the potential inuence ofnegative WOM, as these communica-tions reduce the purchase probability.Consequently, companies should alsoadopt decisions about marketing strat-egies directed at senders and receiverswith the objective of minimizing the

sending of negative WOM and/or theeffects of exposure to negative commu-nications of people motivated to seekadvice actively.

Nevertheless, the effect of bothinterpersonal factors on the receiversdecision is stronger when the WOMinformation is positive (positive WOM)than when it is negative (negativeWOM).

TABLE 4

Structural Models: Parameter Estimates

Hypothesised paths

Positive WOM

subsample 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: Senders experience How actively WOM is sought 0.155** YES 0.135** YES

H6: Senders strength of expression Shift in brand purchase probability 0.489** YES 0.440** YES

H7: Receivers loyalty Shift in brand purchase probability 0.325** YES 0.426** YES

H8: Receivers experience How actively WOM is sought 0.159** YES 0.126 YES

H9: Receivers experience Receivers perceived risk 0.218** YES 0.219** YES

H10: Receivers 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

Satorra-Bentler Scaled Chi Square S-B 2

(probability value)

1231.1561

(0.000)

1279.0923

(0.000)

Standardised parameters are shown (**p < 0.01)


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The current ndings support thehypothesis that level of receivers loy-alty (a non-interpersonal factor) reducesthe impact of both positive and nega-

tive WOM on the shift in the receiverspurchase probability. Thus, the effect ofWOM (positive or negative) is condi-tioned by the receiver s previous loyalty.

As the receivers level of loyaltytoward a brand increases, positive andnegative WOM about that brand willhave less impact on the shift in thefuture purchase probability. Looking atthe plots in Figure 4, positive messages(positive WOM) clearly have more

impact when the receivers pre-WOMloyalty is from 0 to 6, whereas negativemessages (negative WOM) have moreinuence in the range 4 to 7 (See Figure 4).

Thus, the potential impact of WOM(positive or negative) can be estimatedfor any segment of consumers if themean pro-WOM loyalty can be assessedusing purchase records or management judgment, for example.

Various factors directly inuence howactively WOM is sought and indirectlyaffect the shift in the receivers purchaseprobability.

The current ndings indicate that,when senders are perceived as knowl-edgeable, the receivers are motivatedto actively seek information (positive ornegative WOM) from them. Thus, a sig-nicant positive relation exists betweenthe two constructs.

Likewise, when the tie between send-ers and receivers is strong, the receiversare motivated to actively seek positiveWOM information (empirical evidencefor negative WOM was not found).

Conversely, the receivers experiencewas also found to be a signicant indi-cator of how actively WOM is sought.The more knowledgeable people areor the more experience they possess,

the less intense will be the active searchfor information (positive or negativeWOM).

Furthermore, the greater the receiv-

ers experience, the less risk they willperceive in the purchase; and the greaterthe perceived risk, the more active thesearch for WOM information (positiveor negative WOM).

For both positive and negative WOM,the receivers perceived risk has thestrongest positive effect, followed by thereceivers experience (negative effect),senders experience (positive) and, to

a lesser extent, strength of tie betweensender and receiver (positive inuenceonly for positive WOM).

The practical implication of these empiri-cal results is that companies should payparticular attention to the consumers whoare most motivated to seek advice actively(less experienced consumers who perceivemore risk in the purchase) to maximizetheir exposure to positive communications

from senders perceived as knowledgeableand with whom they have strong ties andminimize their exposure to negative com-munications from senders perceived asexperts.

Management Implications

WOM is one of todays most powerfulmarketing tools. It is reported to be oneof the fastest growing sectors in market-ing and media services. Smart marketers

have an opportunity to become a part ofthe consumer-driven WOM conversationthrough well-planned, well-researched,and well-executed WOM marketing pro-gramsat which time, they will be wellpositioned to inuence consumers pur-chase intentions.

For marketers, the ndings of this studysuggest that companies should developmarketing strategies to encourage positive

WOM messages and increase their effec-tiveness. At the same time, companiesshould clearly also make efforts to avoidnegative WOM.

Thus, academics and marketing direc-tors should pay more attention to themanagement of WOM, as WOM cancomplement the rms policy of advertis-ing communication and, hence, increaseits efcacy. Likewise, not only are bothtypes of communication complementary,which improves the rms performance,

but traditional media and marketing com-munications have a signicant role to playin inuencing conversations. Firms can

use advertising to spread messages in themedia that stimulate consumers to speakfavorably about their brands and say goodthings about their products.

This ideal situation, however, will hap-pen only if the brand is credible, the rmsproducts/services are reliable, and itsmarketing activities are believable. In suchcases, customers are very likely to initi-ate more positive conversations about the

brand than negative ones.

Given the need to obtain a positive WOMow from senders to receivers, companiesshould aim to keep the senders satised

by providing a good product or service,effectively practicing sender-centered rela-tionship marketing. In this context, WOMprograms should create experiences forconsumers and convey information thatencourages inuential individuals orgroups to talk freely, authoritatively, andcredibly with others.

Enabling consumers to co-create brandmeaning and tell stories is essential toWOM. Bain & Co. has reported thereis no better force to drive sales growththan strong customer advocacy. Indeed,its research shows that the most recom-mended company in its category grows2.5 times more than the category average.Likewise, Booz & Co., a leading consul-tancy has advised, Make your consumer


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an advocate: shift marketing objectivesfrom sending a message to facilitating con-versations with and between consumers.

Thus, companies should use marketing

activities to incentivize satised consum-ers with a high degree of loyalty to act assenders of positive WOM messages, par-ticularly to those people (receivers) withwhom they maintain a strong tie. It is not just a question of encouraging an endog-enous WOM, which is characterized by aconversation that occurs naturally amongconsumers as a function of the senderspositive experiences with the product orservice. Firms also should develop a proac-

tive management of customer-to-customercommunications. In other words, they cre-ate an exogenous WOM as a result ofits actions (effecting meaningful positiveWOM).

For this purpose, companies should useloyalty programs to incentivize satisedcustomers to become effective dissemi-nators of information. In fact, companiesshould put the satised customer at thecenter of a communications campaign and

encourage them to offer potential con-sumers detailed positive informationconvincingly arguedabout the brandsgood points.

The satised senders experience andstrength of expression can help them to beperceived as opinion leaders. It is in thiscontext that a company needs to identifythe most dynamic consumers in the rec-ommendation activity, as they can help itattract new customers with a minimum

economic investment. Moreover, the eco-nomic value that an active customer cangenerate via WOM is a good means ofsegmenting customers in function of theircapacity to inuence the restthe goal ofall marketers.

One other aspect of interest to practition-ers in the strategic management of WOM:in what environment is WOM communi-cation more commonly generated? Since

2006, advertising-agency/WOM consult-ants Keller Fay has compiled data since2006 that consistently show that WOMconversations happen most often in off-

line environments. Clearly, practitionerscannot ignore the off-line conversationsthat take place between people, but theyshould also try to exploit to the maximumthe opportunities opened up by the Inter-net (Fong and Burton, 2006) and encouragepeople to support WOM so the companycan benet from it as soon as possible.

Much of the importance of the Internetfor WOM communication is grounded inthe links between people in a social net-

work. A recommendation is more valu-able in groups that have stronger links.People with closer relationshipsmarriedcouples or friends, for exampletendto interact more frequently than mereacquaintances.

Knowing this, companies might targetevangelical customersthe most inter-connected groups in the Internetbyanalyzing social networks, cliques, or thegroups that such contacts create and iden-

tify the most inuential people in thesegroups.

Companies also should remember thatthe most socially connected individualsare more liable to offer recommendationsand that physical proximity is not a sig-nicant variable. It is critical, therefore,that companies understand the social net-works in which consumers operate (theirlinks and how they operate in them) toextend positive WOM and minimize the

effects of any negative WOM.In short, the diffusion of opinion lead-

ers messages in both traditional and mod-ern communications media (e.g., socialnetworks such as Facebook, Twitter, andLinkedIn) will help persuade positiveWOM receivers to increase their brand-purchase probability.

In parallel, companies also shouldstimulate the desire in the receiver to

obtain advice about the product or service.Firms can use market research to identifyconsumers (receivers) with a moderatepurchase probability or loyalty, and distin-

guish segments with high (or low) experi-ence in the product or service category.

The aim is for the receivers to seek infor-mation from satised customers so theirfuture purchase probability increases. Anadvertising campaign could encourage

both segments of consumers to seek infor-mation from other people: for example,to seek information from satised, loyalexpert senders with whom they have astrong tie or who are considered an object-

ive, third-party source. Receivers withexperience in the product/service cat-egory and moderate brand loyalty could

begin to doubt and eventually concludethat they do not possess as much experi-ence as they initially had thought.

Another possibility to increase theeffectiveness of a positive WOM mes-sage is to do market research to classifypotential consumers (receivers with amoderate purchase probability and low

experience) into segments according to therisk that they primarily associate with thepurchase decision. The resulting groupscould be addressed with differential com-munications and interpersonal inuencestrategies.

For example, potential customers highin functional risk could be encouragedto connect with satised, loyal expertsenders about the superiority of a rmsproduct/service. Customers with high

social/psychological risk perceptioncould be recommended to senders in theirpeer group with whom they maintain astrong tie and perceive as being similar tothemselves.

Limitations and Future Lines of Research

This study has a number of importantlimitations, which can be seen as startingpoints for future research.


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The work uses retrospective data in thatthe receivers must remember positive(or negative) WOM messages that havehad an impact on their brand choice andindicate the probability of choosing the brand before and after the positive (ornegative) recommendation.

It would be advisable in future work

to subject the receivers to actual posi-tive and negative WOM situations andrecord their actual purchase decision.

This study focuses on receivers whoactively seek information: in otherwords, receivers who already are inter-ested in the product or service category.This analysis is important, but it doesnot shed any light on why some WOMcommunications have no inuence at

all, whether positive or negative.

The subsamples for the four categoriesanalyzed have low or moderate meanpre-WOM purchase probabilities, whichexplains why negative WOM is lessdiagnostic than positive WOM. Futureresearch should investigate situationswhere negative WOM has a strongerimpact.

The consumers in the current studywere familiar with the brands consid-ered for the categories analyzed, andthe innovations that the companies hadlaunched in the market representedincremental levels of novelty linked toproduct re-launches.

It would be interesting to investigatethe impact of positive and negativeWOM in the case of radical innovations

(adoption of new products in their intro-duction stage).

The current study analyzed only thenal outcome of the WOM (shift in thepurchase probability). Another obviouspossibility for further research would

be to explore the impact of positive and

negative WOM on the intermediatestages in the receivers decision-makingprocess (motivation and desires, searchfor information, and attributes consid-ered in the purchase).

The current work focused mainly on theinuence of WOM. The study could beexpanded to compare the effects of posi-tive and negative WOM with those ofother types of information obtained by

the receivers through different commu-nications media (e.g., advertising, directmarketing, and the rms sales force).

The current work did not allow theauthors to establish whether the receiv-ers obtain the information from face-to-face relationships or through socialnetworks. Given the importance of elec-tronic WOM, it would be useful to studythe dynamics of online WOM and prod-

uct sales.The aim would be to study e-WOM

via consumer opinion platforms andinvestigate what motivates senders andreceivers to articulate themselves on theInternet.

RODOLFO V ZQUEZ-CASIELLES is a Professor of Marketing at

the University of Oviedo (Spain). His current research

interests include consumer behavior and perceptions

of justice in the services markets. Other research

interests include interfrm relationships in distribution

channels, retail management, brand equity, and market

orientation. His recent articles have been published

in the European Journal of Marketing, Industrial

Marketing Management , International Journal of

Research in Marketing, International Journal of

Service Industry Management , Journal of Applied

Social Psychology , Journal of Business Research ,

Journal of Business and Industrial Marketing ,

Marketing Letters , Supply Chain Management , Service

Industries Journal , and Psychology and Marketing ,

among other journals.

LETICIA SUREZ-LVAREZ 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.

ANA BELN DEL RO-LANZA is an Associate Professor in

Marketing at the University of Oviedo (Spain). Her current

research interest focuses on brand equity, consumer

behavior, service failure, service recovery strategies, and

perceptions of justice in the services markets. She has

presented papers at various academic meetings and

conferences. Her recent articles have been published

in the British Food Journal , Journal of Business

Research , Journal of Product and Brand Management ,

Journal of Applied Social Psychology , and Marketing

Letters , among other journals.

ACKNOWLEDGMENTS

The authors thank the Spanish Ministry of Sci-

ence and Innovation for the nancial support

provided for this research under the 20082011

Call for R&D Projects (MICINNECO2008-03698/

ECON).

It would be advisable in future work to subject the

receivers to actual positive and negative WOM

situations and record their actual purchase decision.


16/19



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APPENDIXResults of Measurement Model: Psychometric Properties of the Scales

Constructs

Standardised

loading ( )*

Indicate your level of agreement with the following statements (Likert: 1 = total disagreement, 7 = total agreement)

1. Receivers experience (AVE = 0.972; CR = 0.950; = 0.955). Similar items can be found in: Bansal and Voyer (2000)

I know this product/service category very well

I am competent and capable in things concerning this product/service category

I am very familiar with the current features of this product/service category

I am very experienced in the purchase of this product/service category

I think I have enough information about this product/service category

0.880

0.910

0.923

0.847

0.889

2. How actively WOM is sought (AVE = 0.704; CR = 0.877; = 0.906). Similar items can be found in: Bansal and Voyer (2000)

Before buying I seek advice from people unconnected to the rm

Probability of accepting advice from other people (1 = very low; 7 = very high)Explicit requirement of opinion of other people to take decisions (1 = very low; 7 = very high)

0.850

0.8210.846

3. Receivers perceived risk (AVE = 0.767; CR = 0.908; = 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

I think it would be a mistake if I didnt seek the opinions of other people unconnected to the rm to avoid risks

I feel that buying this product is risky and I can avoid these risks if I seek advice from other people unconnected to the rm

0.817

0.870

0.936

4. Tie strength (AVE = 0.846; CR = 0.975; = 0.975). Similar items can be found in: Bansal and Voyer (2000) and Wangenheim and Bayon

(2004b, 2007)

I speak to this person frequently

I have a trusting relationship with this person

This person understands me, shares my concerns, supports meI have a strong personal relation with this person

I have interests and pastimes in common with this person

This person has social values and lifestyle like mine

I think that this person generally behaves very similarly to my way of seeing life

0.874

0.926

0.9430.952

0.902

0.914

0.924

5 . Senders experience (AVE = 0.846; CR = 0.956; = 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

This person is very competent in things concerning this product/service category

This person has previously bought this product/service category

This person is very experienced in this product/service category

0.924

0.930

0.914

0.910

Other scales developed for this study

6. Senders 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? (receivers 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 signicant (p < 0.01); ** The shift in the WOM receivers brand-purchase probability is calculated as the difference between the probability of choosing the after and before the recommendation


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The Word-of-Mouth Dynamic

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