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Making Reservations Online: The Impact of Consumer-Written and System-Aggregated User-GeneratedContent (UGC) In Travel Booking Websites onConsumers’ Behavioral IntentionsSeunga Venus Jin & Joe PhuaPublished online: 28 May 2015.

To cite this article: Seunga Venus Jin & Joe Phua (2015): Making Reservations Online: The Impact of Consumer-Written andSystem-Aggregated User-Generated Content (UGC) In Travel Booking Websites on Consumers’ Behavioral Intentions, Journal ofTravel & Tourism Marketing, DOI: 10.1080/10548408.2015.1038419

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MAKING RESERVATIONS ONLINE: THE IMPACT OFCONSUMER-WRITTEN AND SYSTEM-AGGREGATEDUSER-GENERATED CONTENT (UGC) IN TRAVEL

BOOKING WEBSITES ON CONSUMERS’BEHAVIORAL INTENTIONS

Seunga Venus JinJoe Phua

ABSTRACT. This study examines how consumer-written and system-aggregated user-generatedcontent (UGC) on travel booking websites jointly influence consumer behavior. The purpose of thisresearch is to test the effects of different types of UGC on various consumer behavior outcomes.Experiment 1 found a significant interaction effect between UGC type (consumer-written versussystem-aggregated) and valence (positive versus negative) on product evaluation, perceived informa-tion value, and satisfaction. Experiment 2 found a significant interaction between consumer-writtenand system-aggregated UGC valences. When consumer-written UGC was negative, consumersdemonstrated more negative product evaluation and lower buying intention, regardless of system-aggregated UGC valence. When consumer-written and system-aggregated UGC valences matched,consumers indicated greater perceived information value, satisfaction, and future behavioral intention.Trustworthiness partially mediated the effect of the fit between consumer-written and system-aggre-gated UGC on consumer satisfaction.

KEYWORDS. Travel booking websites, user-generated content (UGC), Web 2.0, consumerbehavior, tourism

INTRODUCTION

Searching for travel-related information onthe Web is one of the most popular onlineactivities (Pew Internet and American LifeProject, 2010). Websites like TripAdvisor,Expedia, Kayak, Orbitz, and Travelocity havebecome the first browsing tool for manyInternet users who plan to travel. Recently,

travel booking websites are increasingly capita-lizing on the key features of Web 2.0 technolo-gies and applications, incorporating consumers’product reviews and ratings, as well as activelinks to social media. Web 2.0 applicationsempower consumers to participate in two-waycommunication regarding travel and tourism(Ye, Law, Gu, & Chen, 2011). Consequently,the exponential growth of these participatory

Seunga Venus Jin, PhD, is Assistant Professor, Department of Marketing Communication, EmersonCollege, 120 Boylston Street, Boston, MA 02116, USA (E‑mail: seunga.jin@gmail.com).

Joe Phua, PhD, is Assistant Professor, Department of Advertising and Public Relations, Grady College ofJournalism and Mass Communication, University of Georgia, 120 Hooper Street, Athens, GA 30602-3018(E‑mail: joephua@uga.edu).

Address correspondence to: Seunga Venus Jin, Department of Marketing Communication, EmersonCollege, 120 Boylston Street, Boston, MA 02116, USA (E‑mail: seunga.jin@gmail.com).

Journal of Travel & Tourism Marketing, 2015© 2015 Taylor & FrancisISSN: 1054-8408 print / 1540-7306 onlineDOI: 10.1080/10548408.2015.1038419

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websites has threatened the hegemony of tradi-tional content generators like one-way advertis-ing and expert critics as primary sources oflegitimate information (Beer & Burrows,2010). In light of this trend, the objective ofthis research was to examine the interplaybetween consumer-written and system-aggre-gated user-generated content (UGC) on populartravel booking websites (i.e. Expedia andOrbitz) to determine consumers’ perception ofand attitude toward hotel reviews and beha-vioral intention to book the reviewed hotel.

In this study, we define consumer-writtenUGC on travel booking sites as consumers’anecdotal, evaluative, and subjective reviewsabout their actual experiences with the adver-tised hotel, flight, or package, as well as theirpersonal rating and recommendation of thereviewed product. Conversely, we define sys-tem-aggregated UGC as website-aggregatednumerical indicators of consumer input (e.g.number of reservations made in the last48 hours, number of consumer recommenda-tions, number of people who like the advertisedhotel on Facebook, average consumer star/numerical rating, etc.). This research investi-gated how these multiple sources of UGC andaccompanying information influence consumerbehavior on online travel booking interfaces,drawing upon warranting theory (Walther &Parks, 2002) and the literature on electronicword-of-mouth (WoM) (Herr, Kardes, & Kim,1991).

Walther and Parks’ (2002) warranting theorydifferentiates information according to itssource and warranting value. The warrantingvalue of information is “derived from the recei-ver’s perception about the extent to which thecontent of that information is immune to manip-ulation by the person to whom it refers”(Walther & Parks, 2002, p. 552). Self-generatedinformation has lower warranting value andcredence than other-generated information.Walther and Parks (2002) proposed that com-municators give greater credence to informationabout personal characteristics when the persondescribed cannot easily manipulate the informa-tion provided. Based on the principle of war-ranting theory, “system-aggregated UGC” canbe operationally defined as self-generated

information, whereas “consumer-written UGC”can be operationally defined as other-generatedinformation, since in this study, the retailerwebsite (or “system”) is the self (who is ableto control or manipulate information thatappears on the website) whereas peer consu-mers who write the travel reviews (or “consu-mers”) constitute the other (whose opinions theretailer website cannot control or manipulate).

Several empirical studies have sinceextended warranting theory to a larger body ofresearch on Web credibility and impressionmanagement in different contexts. Specifically,recent research has applied warranting theory toimpression formation on social network sites(SNSs) like Facebook and Twitter, finding thatdifferent sources of informational cues on userprofiles, such as self (e.g. profile owner), other(e.g. the profile owner’s online friends), andsystem (e.g. system-aggregated indicators ofthe number of friends and other-user input),influence perceptions of the social media profileowner (Tong, Van Der Heide, Langwell, &Walther, 2008; Utz, 2010; Walther, Van DerHeide, Hamel, & Shulman, 2009). This studyextends this line of research to UGC on travelbooking websites.

The multiplicity of information sources andtypes online is also relevant to travel bookingsites. Acknowledging the significant value ofconsumer product reviews as a source of infor-mation and trust for potential customers, mar-keters encourage consumers to post productreviews and opinions on their e-retail sites(Sen & Lerman, 2007). Online retailers addressthe issue of UGC credibility by offering ratingsystems and review posting systems in whichconsumers provide feedback about the qualityof information and the advertised product(Smith, Menon, & Sivakumar, 2005).Recognizing the value of peer recommendationsas a powerful promotional tool, online travelbooking sites encourage consumers to reviewtravel products and to share these reviews withother customers.

This research differentiated between consu-mer-written and system-aggregated UGC on tra-vel booking sites. Two experiments examinedthe interplay between UGC type (consumer-written versus system-aggregated) and valence

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(positive versus negative) (Experiment 1) aswell as the interplay between consumer-writtenand system-aggregated UGC valences(Experiment 2).

THEORETICAL BACKGROUND ANDHYPOTHESES OF EXPERIMENT 1

Experiment 1 examined the interactioneffects of UGC type (consumer-written versussystem-aggregated) and valence (positive versusnegative) on consumers’ product evaluation,satisfaction, and perceived information valueof the reviewed product. Recent studies havedemonstrated the positive effects of onlineuser-generated reviews on book and musicsales (Chevalier & Mayzlin, 2006; Dhar &Chang, 2009) and online hotel booking (Yeet al., 2011), revealing a significant positiverelationship between the number of onlineuser-generated reviews and business perfor-mance (e.g. number of online bookings). Inthe travel and tourism marketing discipline, stu-dies have also investigated the influence of user-generated reviews on travel booking outcomes.For instance, Xie, Miao, Kuo, and Lee (2011)found that the presence of online reviewers’personal identifying information, when com-bined with ambivalent hotel reviews, signifi-cantly lowered consumers’ hotel bookingintentions, while Sparks and Browning (2011)found that positively framed reviews, alongwith user-generated numerical ratings, most sig-nificantly increased booking intentions and con-sumer trust. No previous research, however, hasexplicitly examined the main effect of UGCtype (consumer-written versus system-aggre-gated) on consumer behavior. Between-subjectscomparison between consumer-written and sys-tem-aggregated UGC may shed some light onthe causal effects of these two UGC types onconsumer evaluations of the advertised andreviewed product.

Applying Walther and Parks’ (2002) war-ranting principle to distinguish between consu-mer-written and system-aggregated UGC, wepredict that system-aggregated UGC wouldhave lower warranting value than consumer-written UGC, because system-aggregated

UGC is automatically generated by the retailerwebsite (site owner as self) using predefinedalgorithms, whereas consumer-written UGC ispersonally written by consumers (peer consu-mers as other) specifically for other consumersto read. As a result, system-aggregated UGCmay be more prone to manipulation by theretailer website owner or manager than consu-mer-written UGC. Previous marketing litera-ture also suggests that peer consumerrecommendations like WoM have a morepowerful influence on consumer evaluationsthan information received through commercialsources (Herr et al., 1991; Murphy, Mascardo,& Benckendorff, 2007). Electronic form ofWoM (eWoM) refers to “any positive or nega-tive statement made by customers about a pro-duct or a company that is made available topeople and institutions via the Internet” (Pan &Chiou, 2011, p. 68). Information presented onan Internet forum is more credible and trust-worthy than market-generated informationbecause fellow consumers are the source ofthe information (Bickart & Schindler, 2001).It can be argued that warranting theory pro-vides a good theoretical explanation for theeWoM phenomenon of travel booking sitesbecause travel reviews are written by otherconsumers on the site, with whom the personreading the reviews does not have a prior off-line relationship. In the absence of the rela-tional component, UGC can be judged on itswarranting value: the extent to which the contentis immune to manipulation by the party it refersto. This is distinct from the eWoM with a rela-tional component, such as when recommenda-tions come from one’s friends and peers (Phelps,Lewis, Mobilio, Perry, & Raman, 2004).Therefore, it can be predicated that consumersgive greater credence to product reviews pro-duced and posted directly by other consumersthan content aggregated by retailer websites.

It is also possible that UGC type and valenceinteract with each other to induce differentialeffects on consumer behavior. Although abody of literature on website credibility hasexamined the influence of site attributes anduser verification of Web-based information onperceived site trustworthiness (e.g. Flanagin &Metzger, 2007), there is a dearth of theoretical

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discussion and experimental research into pos-sible interactions between UGC type andvalence in the domain of social media andWeb 2.0-based interactive marketing. Toaddress this gap, we designed Experiment 1 toexamine the effects of the two factors: UGCtype (consumer-written versus system-aggre-gated) and valence (positive versus negative).It can be predicted that UGC type has a rela-tively smaller effect on consumer evaluationwhen the UGC valence is positive. In contrast,the power of UGC can be amplified when thevalence is negative. Negative WoM has a stron-ger influence on consumers’ evaluation thanpositive WoM (Laczniak, DeCarlo, &Ramaswami, 2001). Consumers are more likelyto trust negative eWoM information becausepositive information can be self-serving (Pan& Chiou, 2011). Research also shows that thesource of the information moderates the stron-ger effect of unfavorable information(Weinberger, Allen, & Dillon, 1981). Herret al. (1991) empirically tested the interactionbetween the source of product information(WoM versus printed format) and the valence(positive versus negative) of the informationand found that WoM communications and nega-tive information have stronger effects. Based onthese theoretical rationales and empirical evi-dence, the first hypothesis (H1) proposes thefollowing interactions between UGC type andUGC valence:

H1: UGC type will interact with UGCvalence. When UGC valence is nega-tive, there will be a significant differ-ence between consumer-written andsystem-aggregated UGC regardingtheir effects on consumers’ (a) evalua-tion of the reviewed product; (b)information value of the productreview; and (c) satisfaction with theonline retailer, rather than when theUGC valence is positive. Specifically,in the negative consumer-written UGCcondition, the reviewed product willbe more negatively evaluated, andthe information value of the productreview and satisfaction with the online

retailer will be significantly higher,compared with the negative system-aggregated UGC condition.

METHOD OF EXPERIMENT 1

Design and Participants

A 2 (type: consumer-written [U] versussystem-aggregated [S]) × 2 (valence: positive[P] versus negative [N]) between-subjects fullfactorial design was conducted to examine theeffect of consumer-written versussystem-aggregated UGC on consumers’ evaluationsof the hotel and travel booking site.

Participants were recruited from under-graduates enrolled in a major university inthe United States (US). There was no mone-tary compensation. 88 participants (71.6%female and 28.4% male; 62% whites; 9.1%Asians; 1.1% South Asian; 6% AfricanAmerican; 7% Latino; and 4% other) wereinvited to a laboratory where they were ran-domly assigned to one of four conditions(positive consumer-written UGC [PU], nega-tive consumer-written UGC [NU], positivesystem-aggregated UGC [PS], and negativesystem-aggregated UGC [NS]). These condi-tions were operationalized by four screen-shots of the Expedia travel booking sitecreated on Adobe Photoshop (Figure 1).Participants were told that they would bemaking a reservation for a three-day stay ata hotel in Cancun, Mexico, for spring break,and were asked to evaluate a hotel.Consumer-written UGC was represented byuser reviews of the hotel (positive versusnegative), user recommendations (recommendversus not recommend), and user ratings (5-star versus 1-star) while system-aggregatedUGC was represented by system-aggregatednumerical indicators including overall hotelrating (5-star versus 1-star), number of reser-vations made in the last 48 hours (100 versus1), and number of Facebook “likes” (100versus 1). After exposure to one of the fourscreenshots, participants completed an onlinequestionnaire.

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Manipulation Checks

Manipulation checks were incorporated into thestudy design by having participants first answerquestions that asked whether they were able to findconsumer-written or system-aggregated UGC in

the shown screenshot. These questions confirmedthe type and source of the UGC (consumer-writtenversus system-aggregated). In additional questionsparticipants were asked to identify the individualconsumer reviews, recommendations, and numer-ical ratings for the consumer-written UGC

FIGURE 1. Example Manipulation Stimuli for Experiment 1

Note. UGC: user-generated content; positive consumer-written UGC (PU: top); negative system-aggregated UGC (NS:bottom).

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conditions (or travel site’s aggregated numericalrating, number of Facebook “likes,” and numberof reservations in the last 48 hours on the screen-shot for the system-aggregated UGC conditions).These questions confirmed the valences of theconsumer-written or system-aggregated UGC.

Dependent Measures

Using 7-point semantic differential scales,evaluation of the advertised hotel was mea-sured with six items adapted from Holzwarth,Janiszewski, and Neumann’s (2006) attitudetoward product scale and Osgood, Suci andTannenbaum’s (1957) product evaluationscale, namely “The hotel is . . .” “bad” (1),“good” (7); “unpleasant” (1), “pleasant” (7)(Cronbach’s α = .974). Information value wasmeasured with five items adapted fromHolzwarth et al. (2006) using 7-point Likertscales that ranged from “strongly disagree”(1) to “strongly agree” (7) (α = .899): “Theinformation offered is . . .” “useful”, “under-standable”, “sufficient”, “high-quality”, and“helpful”. Satisfaction with the retailer wasmeasured with four items adapted fromHolzwarth et al. (2006) using 7-point Likertscales (α = .941), for example: “This travelWebsite fulfills my needs”, “I am satisfiedwith this travel site.”

RESULTS OF EXPERIMENT 1

Manipulation Checks

Out of 44 participants assigned to the posi-tive valence conditions, 100% (44 participants)answered “Yes” to “I found the hotel reviewpositive.” Out of 44 participants assigned tothe negative valence conditions, 100% (44 par-ticipants) answered “No” to “I found the hotelreview positive.” Out of 44 participantsassigned to the consumer-written UGC condi-tion, 100% (44 participants) answered “Yes” to“I was able to find other travelers’ reviewsabout the hotel on the travel booking siteabove.” Out of 44 participants assigned to thesystem-aggregated UGC condition, 100% (44participants) answered “No” to “I was able to

find other travellers’ reviews about the hotel onthe travel booking site above.” Therefore,manipulations were successful.

Two-Way Analyses of Variance (ANOVAs)

The results of a two-way ANOVA demon-strated a significant interaction effect betweenUGC type (consumer-written versus system-aggregated) and valence (positive versus nega-tive) on consumers’ hotel evaluation, F (1,84) = 20.688, p = .00, η2 = .198, observedpower = 99.4%. When UGC was positivelyvalenced, there was no significant differencebetween consumer-written and system-aggre-gated UGC. In contrast, when UGC was nega-tively valenced, there was a significantdifference between consumer-written UGC(less favorable hotel evaluation, M = 1.681,SD = .892) and system-aggregated UGC (morefavorable hotel evaluation, M = 3.254,SD = 1.324), t (42) = −4.66, p = .00, thussupporting H1a.

The results of a two-way ANOVA demon-strated a significant interaction effect betweenUGC type and valence on consumers’ perceivedinformation value, F (1, 84) = 9.343, p < .01,η2 = .100, observed power = 85.6%. WhenUGC was positively valenced, there was nosignificant difference between consumer-writtenand system-aggregated UGC. In contrast, whenUGC was negatively valenced, there was a sig-nificant difference between consumer-writtenUGC (higher information value, M = 5.321,SD = 1.178) and system-aggregated UGC(lower information value, M = 3.676,SD = 1.229), t = 4.53, p = .00, thus support-ing H1b.

The results of a two-way ANOVA demon-strated a significant interaction effect betweenUGC type and valence on consumers’ satisfac-tion with the travel booking website, F (1,84) = 3.749, p = .05, η2 = .043, observedpower = 48.2%. When UGC was positivelyvalenced, there was no significant differencebetween consumer-written UGC and system-aggregated UGC. In contrast, when UGC wasnegatively valenced, there was a significant dif-ference between consumer-written UGC (higher

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satisfaction, M = 4.478, SD = 1.393) and sys-tem-aggregated UGC (lower satisfaction,M = 3.309, SD = 1.644), t = 2.55, p < .05,thus supporting H1c. Figure 2 presents theresults of Experiment 1.

BRIEF DISCUSSION OFEXPERIMENT 1

In Experiment 1, there was a significant dif-ference between the effects of consumer-writtenUGC and system-aggregated UGC on thedependent variables when UGC valence wasnegative. In contrast, there was no significantdifference between consumer-written and sys-tem-aggregated UGC when the valence of theUGC was positive. Consumers showed a lessfavorable attitude toward the advertised productwhen consumer-written UGC (individualreviews posted by other consumers) was nega-tive than when system-aggregated UGC (retailergenerated numerical indicators) was negative.

In order to find clear-cut effects of consumer-written UGC versus system-aggregated UGC,Experiment 1 manipulated the two types ofUGC in a mutually exclusive manner.However, consumer-written and system-aggre-gated UGC coexist on most travel bookingwebsites. To address this limitation throughimproving external validity and ecological iso-morphism, Experiment 2 designed mixedreviews incorporating both consumer-written

and system-aggregated UGC in a more ecologi-cally valid fashion.

THEORETICAL BACKGROUND ANDHYPOTHESES OF EXPERIMENT 2

Building upon the findings of Experiment 1,Experiment 2 examined the interaction of thevalences of consumer-written and system-aggregated UGC. There are two different possi-bilities: (1) overriding the effects of negativeconsumer-written UGC, and (2) the positiveeffect of the fit between the valence of consu-mer-written UGC and the valence of system-aggregated UGC.

First, it can be predicted that when consu-mer-written UGC is negative, the valence ofsystem-aggregated UGC will have no signifi-cant effect on the dependent variables. Asfound in Experiment 1, negative consumer-writ-ten UGC had significantly stronger effects onhotel evaluation, perceived information value,and satisfaction than negative system-aggre-gated UGC. Therefore, the stronger effect ofnegatively valenced consumer-written UGCwill override the effects of system-aggregatedUGC valence. In contrast, when consumer-writ-ten UGC is positive, the valence of system-aggregated UGC will have a significant effecton the dependent variables. As found inExperiment 1, positive consumer-written UGCdid not have a significantly stronger effect thanpositive system-aggregated UGC. Therefore,

FIGURE 2. Two-Way Interaction between UGC Type (Consumer-Written Versus System-Aggregated) and Valence (Positive Versus Negative) (Experiment 1).

Note. UGC: user-generated content.

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when consumer-written UGC is positive, thevalence of system-aggregated UGC may havesome effects.

Second, it can be predicted that a matchbetween the valences of consumer-writtenUGC and system-aggregated UGC may have apositive effect on the dependent variableswhereas a mismatch between the valences ofconsumer-written and system-aggregated UGCwill have a negative effect on consumers’ eva-luation of the reviewed product and behavioralintentions. For example, when positive consu-mer-written UGC is paired with positive sys-tem-aggregated UGC, and negative consumer-written UGC with negative system-aggregatedUGC, consumers may perceive the review to bemore reliable. Positive system-aggregated UGCreinforced by positive consumer-written UGCwill maximize consumers’ confidence aboutbooking the advertised hotel online. Likewise,negative system-aggregated UGC reinforced bynegative consumer-written UGC will serve as auseful tool for consumers to screen out unfavor-ably reviewed products. In either case, thematch between the valences of consumer-writ-ten and system-aggregated UGC will have apositive influence on consumer evaluation. Incontrast, when negative consumer-written UGCis presented with positive system-aggregatedUGC and vice versa, consumers may perceivethe mixed valences of the reviews to be unreli-able or inaccurate. Negative consumer-writtenUGC combined with positive system-aggre-gated UGC may negatively affect consumers’perception and evaluation of the honesty orbenevolence dimension of source credibilitybecause consumers may think that the onlineretailer is concealing negative informationabout the product, disseminating false advertis-ing, or overlooking poor consumer feedback.Positive consumer-written UGC combinedwith negative system-aggregated UGC maynegatively affect consumers’ perception andevaluation of the competence dimension ofsource credibility because consumers maythink that the online retailer is inaccurate orslow about reflecting consumers’ feedback. Ineither case, the mismatch between the valencesof consumer-written and system-aggregated

UGC will have a negative influence on consu-mer evaluation.

Acknowledging these two possibilities ((1)overriding effects of negative consumer-writtenUGC, and (2) positive effects of the fit betweenconsumer-written and system-aggregatedUGC), the following hypothesis proposes ageneral interaction effect between the valencesof consumer-written and system-aggre-gated UGC:

H2: The valence of consumer-written UGCwill interact with the valence of system-aggregated UGC to influence consu-mers’ (a) evaluation of the reviewedproduct; (b) buying intention; (c) infor-mation value of the product review; (d)satisfaction with the online retailer; and(e) future revisiting intention.

Building trust is a critical factor in e-commerceand participatory marketing websites.Marketing research shows that trustworthiness,one subdimension of the source credibilitymodel (McCroskey & Teven, 1999), has a sig-nificant impact on consumer behavior (Jin,2010). Researchers have found that e-trust(“consumer trust in e-commerce”, Pennanen,2011, p. 233) affects satisfaction (Harris &Goode, 2004) and consumers’ intentions to usea website (Hampton-Sosa & Koufaris, 2005). Itcan be predicted that the match between thevalences of consumer-written and system-aggre-gated UGC increases consumers’ perception oftrustworthiness of the multiple sources.Consumers’ increased trustworthiness, in turn,mediates the relationship between the matchand satisfaction. The following hypothesis pro-poses the positive influence of a reliable andconsistent match between the valences of themultiple sources:

H3: Perceived trustworthiness of the infor-mation sources will mediate the positiveeffects of the fit between the valence ofconsumer-written UGC and the valenceof system-aggregated UGC on consu-mers’ satisfaction with the onlineretailer.

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METHOD OF EXPERIMENT 2

Participants and Design

Seventy-two undergraduates enrolled in a uni-versity in the US participated in a 2 (UGC type:consumer-written versus system-aggregated) × 2(UGC valence: positive versus negative)between-subjects full factorial design experi-ment. Participants were randomly assigned toone of the four conditions (positive consumer-written UGC and positive system-aggregatedUGC [PUPS]; positive consumer-written UGCand negative system-aggregated UGC [PUNS];negative consumer-written UGC and positivesystem-aggregated UGC [NUPS]; negative con-sumer-written UGC and negative system-aggre-gated UGC [NUNS]). Those students whoalready participated in Experiment 1 were noteligible to participate in Experiment 2 and wereexcluded from the recruitment.

While Expedia was chosen for Experiment 1,a different platform (Orbitz) was chosen forExperiment 2 to increase external validity.Participants were invited to the laboratory,where they were randomly assigned to one offour conditions: PUPS, PUNS, NUPS, or NUNS.These four conditions were operationalized byfour screenshots of the Orbitz travel booking sitecreated on Adobe Photoshop (Figure 3).Participants were told they would make a reser-vation for a three-day stay at a hotel in Cancun,Mexico, for spring break, and were asked toevaluate a hotel based on the review screenshot.Consumer-written UGC was represented by userreviews, recommendations, and ratings of thehotel, while system-aggregated UGC was repre-sented by overall hotel rating (5-star versus 1-star), number of reservations in the last 48 hours(100 versus 1), and number of Facebook “likes”(100 versus 1). After being exposed to one of thefour screenshots, participants completed anonline questionnaire about their hotel and travelbooking site evaluations.

Dependent Measures

The same items from Experiment 1 wereused to measure product evaluation, perceived

information value, and satisfaction with theonline retailer. Buying intention was measuredwith three items adapted from Holzwarth et al.(2006) using 7-point Likert scales (Cronbach’sα = .965) (e.g. “I will take this travel websiteinto consideration and have them book thishotel for me”). Future buying intention wasmeasured with four items adapted fromHolzwarth et al. (2006) using 7-point Likertscales (α = .954) (e.g. “I can imagine revisitingthis travel site in the future”). Trustworthinessdimension of source credibility was measuredwith six items from McCroskey and Teven(1999) using 7-point semantic differential scales(α = .974) (e.g. “dishonest” (1), “honest” (7);“untrustworthy” (1), “trustworthy” (7)).

RESULTS OF EXPERIMENT 2

Manipulation Checks

Manipulation checks were conducted by hav-ing participants answer questions to confirmpositive and negative valences of the consu-mer-written and system-aggregated UGC onthe screenshot and whether they were able tofind the positive or negative consumer-writtenand system-aggregated UGC in the image theysaw. In additional questions they were asked toidentify the overall hotel rating, number ofFacebook “likes”, and number of reservationsin the last 48 hours. Participants’ responsesconfirmed the correct valences of the twoUGC types in four different conditions.Between-subjects manipulations were thereforesuccessful.

Two-Way ANOVAs

The results of a two-way ANOVA demon-strated a significant interaction effect betweenthe valences of consumer-written and system-aggregated UGC on consumers’ hotel evalua-tion, F (1, 68) = 11.611, p = .001, η2 = .146,observed power = 91.9%. When the valenceof consumer-written UGC was negative, therewas no significant difference between theeffects of positive and negative system-aggre-gated UGC. In contrast, when the valence of

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consumer-written UGC was positive, therewas a significant difference between theeffects of positive system-aggregated UGC(more favorable hotel evaluation, M = 6.596,SD = .551) and negative system-aggregatedUGC (less favorable hotel evaluation,M = 4.102, SD = 1.581), t (35) = 6.48,p = .00, thus supporting H2a.

The same pattern was found for consu-mers’ buying intention. The results of atwo-way ANOVA demonstrated a significantinteraction effect between the valences ofconsumer-written and system-aggregatedUGC on buying intention, F (1,68) = 16.757, p = .000, η2 = .198, observedpower = 98.1%. When the valence of

FIGURE 3. Example Manipulation Stimuli for Experiment 2.

Note. UGC: user-generated content; positive consumer-written UGC and positive system-aggregated UGC (PUPS match:top); negative consumer-written UGC and positive system-aggregated UGC (NUPS mismatch: bottom).

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consumer-written UGC was negative, therewas no significant difference between theeffects of positive and negative system-aggre-gated UGC. In contrast, when the valence ofconsumer-written UGC was positive, therewas a significant difference between theeffects of positive system-aggregated UGC(higher buying intention, M = 5.632,SD = 1.048) and negative system-aggregatedUGC (lower buying intention, M = 3.111,SD = 1.696), t (35) = 5.47, p = .00, thussupporting H2b. Figure 4 (top section) pre-sents the overriding effects of negative con-sumer-written UGC.

The results of a two-way ANOVA demon-strated a significant interaction effect betweenthe valences of consumer-written and system-aggregated UGC on consumers’ perceivedinformation value, F (1, 68) = 23.557,p = .000, η2 = .257, observed power = 99.8%.When the valence of consumer-written UGC

was negative, negative system-aggregatedUGC resulted in higher information value(M = 5.40, SD = 1.539) than positive system-aggregated UGC (M = 4.155, SD = 1.671),t = −2.29, p < .05. In contrast, when thevalence of consumer-written UGC was posi-tive, positive system-generated UGC resultedin higher perceived information value(M = 5.747, SD = .986) than negative sys-tem-generated UGC (M = 3.633,SD = 1.597), t = 4.87, p = .000, thus support-ing H2c. This consistent pattern was found forconsumer satisfaction, F (1, 68) = 30.105,p = .000, η2 = .307, observed power = 100%;and future behavioral intention, F (1,68) = 20.368, p = .000, η2 = .230, observedpower = 99.4%, thus supporting H2d and H2e.Figure 4 (bottom section) presents the positiveeffects of the match and the negative effects ofthe mismatch between the valences of consu-mer-written and system-aggregated UGC.

FIGURE 4. Two-Way Interaction between the Valence of Consumer-Written UGC and the Valenceof System-Aggregated UGC (Experiment 2): The Overriding Effects of Negative Consumer-WrittenUGC (top) and the Effects of the Match versus Mismatch between the Valence of Consumer-Written UGC and Valence of System-Aggregated UGC (bottom)

Note. UGC: user-generated content.

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The mediating effect of trustworthiness

In order to test H3, we conducted a media-tion analysis using Preacher and Hayes’(2008) SPSS mediation macro. Coefficientsfor direct and indirect paths were computed,as presented in Figure 5. The total model wassignificant (F (2, 69) = 34.049, p = .00) andthe indirect effect of the independent variableon the dependent variable through the media-tor was significant (ab path coefficient = .198,p < .01). The strength of the relationshipbetween the match versus mismatch and satis-faction decreased but remained significant (c-prime path coefficient = 1.229, t = 4.372,p < .01) after trustworthiness was identifiedas the mediator. To test the significance of thisindirect effect in a more rigorous manner, weused bootstrapping techniques as recom-mended by Preacher and Hayes (2008).Across 10,000 bootstrap samples, the meanestimated indirect effect for the mediationalpath was computed, as well as the 95% con-fidence intervals (CIs) and standard errors(SEs) for each of these estimates.Trustworthiness partially mediated the effectof match versus mismatch between thevalences of consumer-written and system-aggregated UGC on satisfaction, as indicatedby bias corrected and accelerated confidencelevels (SE = .198, CI = .131 (lower) .925

(upper)). The confidence interval did notinclude zero, thus supporting H3. Althoughadditional mediation analyses were conductedto test the mediating roles of the other twodimensions (competence and benevolence) ofsource credibility, they were found to be non-significant mediators.

BRIEF DISCUSSION OFEXPERIMENT 2

Among the three different dimensions ofsource credibility, only trustworthiness func-tioned as a significant mediator. A possibleexplanation for this finding is that when evalu-ating online reviews, consumers may look morefor trustworthy sources rather than competent(the ability to accomplish a given task success-fully) or benevolent (the desire to do good toothers) sources (Bickart & Schindler, 2001). Forexample, in their examination of consumertrusting beliefs, Schlosser, White, and Lloyd(2006) found that benevolence of online retai-lers did not have a significant impact on con-sumers’ online purchase intentions whiletrustworthiness of the site did. Other researchstudies in the area of website credibility havealso found mixed results regarding the impactof competence and benevolence on consumers’

FIGURE 5. The Mediating Effect of Trustworthiness (Experiment 2)

Notes.1: Mediation analysis with bootstrapping procedures: the numbers in the parentheses represent (1) the indirect effectof the mediator (ab path), and (2) the direct effect of the relation of the match between the valences of consumer-written UGCand system-aggregated UGC to satisfaction with the travel booking website after accounting for the mediator (c-prime path).2: Bias corrected confidence intervals at 95% ranged from .131 to .925. 3: p** < .01, p* < .05.

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perceptions of e-commerce sites (Garbarino &Lee, 2003; McKnight, Choudhury, & Kacmar,2002). Conversely, there has been much empiri-cal evidence indicating that perceived trust-worthiness of online retailers has a significantinfluence on consumers’ purchase intention onthe sites (Buttner & Goritz, 2008; Jarvenpaa,Tractinsky, Saarinen, & Vitale, 1999; Lee &Turban, 2001; Nah & Davis, 2002; Shankar,Urban, & Sultan, 2002). On travel bookingwebsites, consumers may be more concernedwith trustworthiness of reviews based on theirsource and valence rather than site competenceor benevolence. As such, only trustworthinesswas found to mediate the relationship betweenthe match versus mismatch of consumer-writtenand system-aggregated UGC, and satisfactionwith the online retailer.

GENERAL DISCUSSION

Summary and Key Findings

In two experiments we examined the effectsof consumer-written and system-aggregatedUGC on consumer behavior in the context ofparticipatory travel booking sites. Experiment 1revealed a significant interaction between UGCtype and UGC valence. As presented inFigure 2, this research empirically supportedthe proposition that positive information doesnot significantly affect consumer evaluationwhereas negative information significantlyaffects consumer evaluation. When the valenceof the UGC was positive, there was no signifi-cant difference between consumer-written andsystem-aggregated UGC with regard to theireffects on consumers’ product evaluation, per-ceived information value, and satisfaction. Incontrast, when the UGC was negative, consu-mers (1) perceived the product to be more unfa-vorable when it was reviewed by peerconsumers; (2) perceived the product reviewby peer consumers (consumer-written UGC) asmore informative than the system-aggregatedUGC; and (3) showed higher satisfaction withthe retailer when the product review was offeredin the form of consumer-written UGC ratherthan system-aggregated UGC. These findings

about the significant interaction and the strongereffects of negative information are consistentwith the findings in extant consumer behaviorliterature on the diagnostic value of negativeinformation (Chiou & Cheng, 2003; Mizerski,1982). Negative information is more influentialthan positive information because of its diag-nostic value and consumers’ higher responsive-ness to negative valence. As the body ofresearch on website credibility and impressionmanagement demonstrates, users use informa-tional cues gleaned from online SNS profiles(Tong et al., 2008; Walther et al., 2009) assources of warranting. Similarly, in participa-tory e-commerce like online travel bookingsites, individual product reviews (consumer-written UGC) are seen as being more influentialthan retailer-generated numerical indicators(system-aggregated UGC) because of theirvividness and greater credence or warrantingvalue, particularly when they are negative.

Experiment 2 demonstrated a significantinteraction between the valences of consumer-written and system-aggregated UGC. Whenconsumer-written UGC was negative, consu-mers perceived the advertised hotel to be badregardless of the valence of system-aggregatedUGC, thus strongly demonstrating the powerful,overriding effects of negative consumer-writtenUGC (Figure 4 top section). The same patternwas found regarding consumers’ buying inten-tion. This finding speaks to the stronger diag-nostic value of negative information (Chiou &Cheng, 2003) as well as to the stronger influ-ence of negative consumer-written UGC com-pared with system-aggregated UGC.

A somewhat different pattern emerged forperceived information value, satisfaction, andfuture buying intention. Instead of the overrid-ing effects of negative consumer-written UGC,we found the effects of the match (versus mis-match) between the valences of consumer-writ-ten and system-aggregated UGC (Figure 4bottom section). These two different patternscan be explained with regard to consumers’temporal perspective. Hotel evaluation and buy-ing intentions involve instant perception and areshort-term, imminent decisions whereas infor-mation value, satisfaction with the retailer, andfuture buying intentions are predictors of

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relatively long-term perception and decision-making in the distant future. For example, it ispossible for consumers to decide not to bookthe reviewed hotel instantly (short-term deci-sion-making), but still be willing to revisit thewebsite for future browsing and purchasing(long-term intention). This study’s findings sug-gest that the overriding effect of negative con-sumer-written UGC is important for consumers’short-term evaluation of the advertised productand intention to purchase the product immedi-ately whereas the match between the valencesof the two UGC types (consumer-written andsystem-aggregated) is important for consumers’perception of information value, satisfactionwith the site, and long-term future behavioralintentions.

Theoretical and Managerial Implications

Warranting theory has been actively testedand refined in recent research on online impres-sion formation in contexts like SNSs (Tonget al., 2008; Utz, 2010; Walther et al., 2009).This research attempted to test the theory’sunderlying assumption in consumer studies.These experiments add to the extant literatureon the warranting principle through empiricallyfinding a significant interaction between UGCtype (consumer-written versus system-aggre-gated) and UGC valence (positive versus nega-tive). Thus, this research prompts theoreticaldiscussions about important moderators in con-sumers’ perception of warranting values andconsequent product evaluation and behavioralintentions. Additionally, this research revealedthe trustworthiness dimension of source cred-ibility as a significant mediator between thematch in valences of multiple informationsources and consumers’ satisfaction with theonline retailer. The fact that the competenceand benevolence dimensions were not signifi-cant mediators demonstrates the theoreticalimportance of the trustworthiness dimension ofsource credibility in the context of participatorye-commerce sites.

As for managerial implications, the study’sfindings suggest that it is imperative for travelbooking sites to pay attention to user-generated

eWoM due to its strong influence on consumers;particularly their perceptions of a site’s informa-tion value, satisfaction, and future behavioralintention. Even though negative consumer-writ-ten UGC may prompt consumers to not bookthe reviewed hotel in the short-term, sites thatare willing to ensure that the consumer-writtenUGC is presented accurately can reap long-termrewards because consumers are more likely torevisit these sites for future browsing and pur-chasing. Furthermore, travel booking sitesshould also ensure that system-aggregatednumerical indicators of user input and feedbackon the site are fair and accurate, so that theyappear more trustworthy. When there is a matchbetween the valences of consumer-written andsystem-aggregated UGC, consumers are morelikely to trust and be satisfied with the onlineretailer. As such, sites that incorporate writtenreviews from consumers, in addition to system-aggregated numerical indicators of user input,may stand to gain long-term trust and repeatedvisits by its customer base.

Limitations and Suggestions for FutureResearch

A few limitations of this research need to bediscussed as they provide suggestions and man-agerial implications for future research. First,although we attempted to achieve an acceptablelevel of external validity by providing a real-lifeexample, the present study examined only onepossible travel scenario (i.e. booking a hotel forspring break). Product types (hotel, flight, travelpackage, rental car, etc.) and the nature or pur-pose of travel (e.g. business trips, family vaca-tions, and honeymoons) may play a moderatingrole in determining the effects of the interplaybetween consumer-written and system-aggre-gated UGC. Second, consideration of consu-mers’ motivations to purchase travel, such asutilitarian (e.g. budget travel) versus hedonic(e.g. luxury travel) orientations may enrich ourunderstanding of how individual differencesdrive social media users to identify and buyproducts or services, so as to fulfill their con-scious and unconscious needs and desires.Second, future studies may consider the effect

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of UGC type and valence on experience versussearch products (Girard, Silverblatt, &Korgaonkar, 2002) to find out whether a pro-duct’s prepurchase performance veracity hasany impact on consumer evaluations of travelsite reviews. Third, we did not consider theeffects of between-subjects budget manipulationand real-time interaction with an online virtualagent on consumer behavior in participatory e-commerce sites. Follow-up studies need toexamine between-subjects budget manipula-tions and prompt actual purchase and transac-tion behaviors by offering virtual money toimprove external validity and practical value.Also, the effects of consumers’ participatoryreal-time interaction with virtual agents viaonline help-seeking behaviors like instant chat-ting (Jin, 2009) on their perception of Webcredibility would be a relevant topic to furtherinvestigate. Fourth, for the sake of high controland maximum manipulation of the key indepen-dent variables of interest, this research did notprompt participants’ actual content-generatingbehaviors like rating, review posting, and log-ging into social media to share the reviews; itsimply measured their potential behavioralintentions to engage in these behaviors.Prompting and testing consumers’ actual con-tent-generating behaviors in a field experimentwould be a fruitful pursuit in this line ofresearch. Fifth, more active utilization of thetechnological affordances of social media,including counting and analyzing quantitativeindicators (e.g. the number of “Likes” on theFacebook SNS platform and the number of“Followers”, “Following”, “Favorites”, and“Tweets” on the Twitter microblogging plat-form) can provide helpful insights into theore-tical and practical ways to model and analyze awealth of UGC-based behavioral data.

CONCLUSION

With the exponential growth of participatorye-commerce sites, Internet shoppers are becom-ing increasingly savvy regarding the type ofinformation they find about products and ser-vices online. The distinct advantage afforded bysocial media marketing is that people can act

simultaneously as creators and receivers ofknowledge and information (Ye et al., 2011),thereby enriching the communication processand empowering them before, during, and aftere-commerce transactions.

Through two experiments, this study exam-ined how consumer-written and system-aggre-gated UGC in travel booking sites jointlyinfluence consumer behavior. Key findings ofthe current research extend empirical work onwarranting theory by applying it to consumers’perceptions of travel booking sites, and alsohighlight the important roles that consumer-written and system-aggregated UGC play ininfluencing consumers’ perception of trust-worthiness in social media and Web 2.0-basedinteractive marketing.

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SUBMITTED: September 7, 2014FINAL REVISION SUBMITTED:

January 29, 2015ACCEPTED: April 1, 2015

REFEREED ANONYMOUSLY

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