Online travel purchasing: A literature review

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Online travel purchasing: A literature reviewSuzanne Amaro & Paulo DuartePublished online: 12 Nov 2013.

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Journal of Travel & Tourism Marketing, 30:755–785, 2013Copyright © Taylor & Francis Group, LLCISSN: 1054-8408 print / 1540-7306 onlineDOI: 10.1080/10548408.2013.835227

ONLINE TRAVEL PURCHASING:A LITERATURE REVIEW

Suzanne AmaroPaulo Duarte

ABSTRACT. Over the past two decades, there has been an increasing focus on the developmentof Information and Communication Technologies (ICTs), as well as the impact that they have hadon the tourism industry and on travelers’ behaviors. However, research on what drives consumers topurchase travel online has typically been fragmented. In order to better understand consumers’ behaviortoward online travel purchasing, this article offers a review of articles that were published in leadingtourism and hospitality journals, the ENTER proceedings, and several articles from other peer-reviewedjournals, found on the main academic search databases. The antecedents of online travel shopping foundare classified into three main categories: Consumer Characteristics, Perceived Channel Characteristics,and Website and Product Characteristics. Finally, this study identifies several gaps and provides someorientation for future research.

KEYWORDS. Consumer behavior online, online travel shopping, online travel purchase intentions,review, tourism and hospitality

INTRODUCTION

The development of Information andCommunication Technologies (ICTs) and par-ticularly the Internet has had a profound impacton the travel industry (Buhalis & Law, 2008;Kamarulzaman, 2007). These developmentshave changed travelers’ behavior (Buhalis &Law, 2008; Hung, Yang, Yang, & Chuang,2011) that now depend on the Internet to searchfor information, plan their travel, and pur-chase (Jeong & Choi, 2005). Over a decadeago, Werthner and Klein (1999) had alreadystressed that tourism and ICTs fit well togethersince travel products and services have the

Suzanne Amaro is with the School of Technology and Management at the Polytechnic Campus Repesesin Viseu, Portugal.

Paulo Duarte is with NECE-Research Unit in Business Sciences of the Human and Social Sciences Facultyat the University of Beira Interior in Covilhã, Portugal (E-mail: [email protected]).

Address correspondence to: Suzanne Amaro, Escola Superior de Tecnologia e Gestão de Viseu, CampusPolitécnico de Repeses, 3504-510 Viseu, Portugal. E-mail: [email protected]

ideal characteristics to be sold online (Lewis,Semeijn, & Talalayevsky, 1998). Predictions thatthe Internet would have an enormous impacton how hospitality and tourism services aredistributed are certainly proved true (Buhalis,1998; Marcussen, 1999; Werthner & Klein,1999). Different sources evidence the impor-tance of online travel shopping. For instance,in a survey lead by Nielsen (2008), travel wasthe most important online transaction category.According to the Danish Centre for Regional andTourism Research (http://www.crt.dk), onlinetravel sales increased by 17% from 2007 to2008 and reached 58.4 billion Euros in theEuropean market in 2008. Forty percent of

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756 JOURNAL OF TRAVEL & TOURISM MARKETING

Americans and 30% of Europeans book travelonline. Despite the 20% in Asia, it is expectedthat this percentage will rise to about 30 or40% over the next few years (Leggatt, 2011).While in 1998, airline companies did not sellmore than 1% of their tickets online (Marcussen,1999), this figure rose to a worldwide 26%by 2008, and to more than 50% in NorthAmerica (SITA, 2008). Due to this, the future ofonline travel shopping looks promising. In fact,PhoCusWright, one of the leading travel indus-try research firms, predicts that by the end of2012 travelers will book one third of the world’stravel sales online (Travel Pulse, 2011).

Given the importance of online travel shop-ping, it is fundamental to examine which factorsinfluence consumers to purchase online (Brown,Muchira, & Gottlieb, 2007; Kah, Vogt, &Mackay, 2008). Notwithstanding the growingbody of literature in this field, the existentresearch is fragmented and has contradictoryresults. In view of the importance of onlinetravel shopping, this article makes two valuablecontributions to the body of knowledge. First, itprovides researchers with a comprehensive syn-thesis of the extant studies related to this topic.Second, as it identifies the main gaps, it providesacademics with directions for future research inthis area.

The remainder of the article is organized asfollows: the next section outlines the method-ology used to conduct the literature review; theresults from the literature review and the catego-rization of the variables affecting online travelshopping are then presented; following is a sec-tion where research gaps are identified and someguidelines for future research are suggested; andfinally, the last section summarizes this studyand indicates some limitations.

METHODOLOGY

For the purposes of this study, only full-length peer-reviewed articles that established arelationship with intentions to purchase travelonline1 or actual usage of the Internet as a pur-chase mode were selected. Another criterionthat articles had to meet was that they needed toaddress the purchase of travel online in general

opposed to the purchase of travel on a specifictravel website. Articles examining, for exam-ple, the effect of website quality on intentionsto purchase on a specific website (e.g., Bai,Hu, Elsworth, & Countryman, 2004), the impor-tance of value-added services on online travelwebsites (e.g., Lexhagen, 2005), or the evo-lution of online travel purchase behaviors ingenerational cohorts (e.g., Beldona, Nusair, &Demicco, 2009) were discarded.

A structured approach based on Websterand Watson’s (2002) recommendations was fol-lowed to conduct the literature review. Theseauthors recommend examining leading journalsand conference proceedings with a reputationfor quality in order to find relevant articles sincethey are more likely to have the major contribu-tions. Furthermore, to guarantee that other rel-evant articles from peer-reviewed journals werenot excluded from this review, online databasesfor academic journals were also used. Usingonline databases to search for suitable articlesfor a literature review is a procedure that hasbeen conducted by other well-known authors(e.g., Buhalis & Law, 2008; Ip, Law, & Lee,2011).

Identifying the leading journals in theTourism and Hospitality field was a challeng-ing task. Arendt, Ravichandran, and Brown(2007) indicated that there were 57 tourismand hospitality related journals. Several aca-demics suggest there are more than 100(Ma & Law, 2009; McKercher, Law, & Lam,2006). Nevertheless, a standard list of rankedtourism journals accepted by all universitiesand researchers does not exist (Law, 2010;McKercher et al., 2006). More recently, eversince several hospitality, leisure, sports, andtourism related journals were included in theThomson Reuters Social Sciences CitationIndex (SSCI), impact factors have also beenused to evaluate journals. However, manyauthors argue that impact factors should notbe used to evaluate research (Jamal, Smith, &Watson, 2008; Seglen, 1997). The leadingjournals included in this study were the top10 selected from four tourism and hospi-tality journal rankings listed in the studiesof Pechlaner, Zehrer, Matzler, and Abfalter(2004), Ryan (2005), McKercher et al. (2006),

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Suzanne Amaro and Paulo Duarte 757

TABLE 1. Rankings of Hospitality and Tourism Journals

Journals (in alphabetic order of journalnames)

Pechlaner et al.(2004)

Ryan(2005)

McKercheret al. (2006)

Murphy andLaw (2008)

SSCI 2-Yearimpact factor

(2010)

USA Othercountries

Annals of Tourism Research 2 1 1 1 1 2Asia Pacific Journal of Tourism Research 16 19 − 8 − −British Food Journal − − − − 5 −Cornell Quarterly 3 9 23 − 2 14Current Issues in Tourism − − − − − 15International Journal of Contemporary

Hospitality Management13 18 − − 6 −

International Journal of HospitalityManagement

8 7 − − 11 5

International Journal of Tourism Research − − 17 6 18 9Journal of Gambling Studies − − − − 9 −Journal of Hospitality & Tourism Research 7 8 − − 12 10Journal of Leisure Research 5 14 6 − − 6Journal of Sustainable Tourism 11 4 4 4 − 4Journal of Tourism Studies 10 6 10 9 − −Journal of Travel and Tourism Marketing 4 5 20 5 13 8Journal of Travel Research 1 3 3 3 4 3Leisure Management − − 7 − − −Leisure Sciences − − 8 − 10 7Leisure Studies − − 5 − 7 13Scandinavian Journal of Hospitality and

Tourism− − − − − 16

Therapeutic Recreation Journal − − 9 − − −Tourism Analysis 9 10 14 7 − −Tourism Economics 20 12 25 10 21 12Tourism Geography − − − − − 11Tourism Management 6 2 2 2 3 1

and Murphy and Law (2008; see Table 1).Moreover, the 2-year impact factors from SSCIwere also considered to select leading journals.The 2010 SSCI list includes 33 journals fromhospitality, leisure, sports, and tourism (ISI Webof Science, 2010). For the purpose of ranking,sports journals were eliminated. By selectingthe top 10 rated journals from these studiesand impact factors, a total of 24 journalswere obtained. After carefully examining theaims and scope of these journals, nine wereeliminated; some due to the fact that theywere not related to the topic under review andothers for not being peer-reviewed journals. TheJournal of Hospitality and Tourism Technology,the Journal of Information Technology &Tourism, and the annual proceedings of ENTERConferences (organized by the InternationalFederation for Information Technology and

Travel & Tourism since 1994 and published inInformation and Communication Technologiesin Tourism), were added to the list of jour-nals; this because they address two importantdomains relevant to the literature review:Information Communication Technologies(ICTs) and Tourism. A total of 17 researchjournals in hospitality and tourism and theENTER conference proceedings were obtainedfor the purpose of this study (see Appendix).

In late 2011, the table of contents ofthe selected journals were analyzed. Thearticles addressing determinants of onlinetravel purchase intentions or actual usagewere then selected. Considering that theInternet became popular among the generalpublic in 1995 (Marcussen, 1999), alongwith the fact that in the late 1990s air-line companies and online travel agencies

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with booking functions (such as Expedia,Travelocity, Bookings, British Airways, Iberia,Finnair) were launched (Marcussen, 1999;Mitra, 2007; Microsoft, 1997), articles pub-lished between January 1995 and December2011 were considered for the literature review.

As aforementioned, to guarantee that otherrelevant articles from peer-reviewed jour-nals were not excluded from this literaturereview, the online databases for academic jour-nals ScienceDirect (http://www.sciencedirect.com) and EBSCO (http://www.ebscohost.com),as well as Google Scholar (http://www.scholar.google.com) were used to search for suitablearticles. These are considered to be the largestand most popular databases (Ip et al., 2011;Ryan, 2005). The keywords used for this searchincluded different word combinations related toonline travel shopping such as “travel shoppingonline,” “travel e-commerce,” and “e-travelerspurchasing behavior.”

FINDINGS

A total of 54 full-length articles were foundrelevant to the review. Table 2 presents the distri-bution of these articles, per journal and year.

After carefully reading each article, vari-ables affecting online travel purchasing usageand intention were classified according to theantecedents of online shopping based on Chang,Cheung, and Lai’s (2005) reference model (seeFigure 1). This model is composed of three cat-egories with subcategories. The three major cat-egories are: (a) characteristics of the consumers,(b) perceived characteristics of the Internet asa sales channel, and (c) characteristics of thewebsite or products. Minor adaptations weremade to the subcategories of this frameworkto account for specific antecedents of onlineshopping in the travel context.

Consumer Characteristics

Demographic Variables

Consumer demographics are among the mostfrequently studied factors and were the focus ofthe first article addressing online travel shop-ping. In their seminal study, Weber and Roehl

(1999) found that there were no differencesbetween online purchasers and nonpurchasersregarding gender and race. However, individ-uals between the ages of 25 to 55, possess-ing higher levels of education and income,were more likely to purchase travel online.Effectively, the majority of the succeeding stud-ies also found that travelers with higher edu-cation levels were more likely to purchasetravel online (Heung, 2003; Kamarulzaman,2007, 2010; Kim & Kim, 2004; Law & Bai,2008; Law, Leung, & Wong, 2004; Lee, Qu, &Kim, 2007; Li & Buhalis, 2006; Morrison,Jing, O’Leary, & Cai, 2001; Wolfe, Hsu, &Kang, 2004), but not without some contradic-tory evidence (e.g., Weber & Roehl, 1999).In fact, in Morrison et al.’s model (2001),education was found to be the only sociode-mographic variable that affected the likelihoodof using the Internet to purchase travel. Yet,other studies found that there was no rela-tionship between them (Beldona, Racherla, &Mundhra, 2011; Garín-Muñoz & Pérez-Amaral,2011; Li & Buhalis, 2006; Moital, Vaughan, &Edwards, 2009; Wolfe et al., 2004). Strangely,Chen (2006) found that consumers with highereducation levels did not trust travel websitesas much.

Online travel purchasers also seem to havehigher levels of income (e.g., Card, Chen, &Cole, 2003; Heung, 2003; Law & Bai, 2008;Law et al., 2004) and are generally younger(e.g., Kamarulzaman, 2007; Kim & Kim, 2004;Wolfe et al., 2004) than those who purchase intraditional travel agencies. Once again there isno consensus on this subject matter. For exam-ple, Kim and Kim (2004) found that online pur-chasers and nonpurchasers did not differ accord-ing to level of income. On the contrary, Wolfeet al. (2004) actually claimed that travelers whoused a travel agent were more likely to be inthe upper income levels. Regarding China, Liand Buhalis (2006) found that there were nosignificant differences in income levels betweenlookers and bookers. Regarding age, there arealso contradictory results. Wolfe et al. (2004)reported that younger consumers were morelikely to purchase online, while Law and Bai(2008) noted the opposite. Other researchers(Moital, Vaughan, & Edwards, 2009) concluded

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FIGURE 1. Antecedents of Online Shopping

Antecedents ofOnline Shopping

ConsumerCharacteristics

ChannelCharacteristics

Website andProduct

Characteristics

Website FeaturesDemographic

VariablesPrivacy and

Perceived Risk

Computer/InternetKnowledge and

Usage

RelativeAdvantages

ProductCharacteristics

Travel-RelatedBehaviors

RelativeDisadvantages

PsychologicalVariables

OnlineSatisfaction

Personal Traits Trust

ConsumerShopping

Orientations

that age did not influence the probability ofpurchasing travel online.

These contradictory findings regardingdemographic variables may be the result ofa shift in the demographic profile of onlinetravel purchasers. This is due to the fact that asthe Internet becomes more widespread, onlinetravel purchase has become more commonin individuals with lower incomes and lowereducation levels. However, these differencesmay also be due to other factors such as differ-ent sampling methods or cultural differences.In either case there is a clear need to expandresearch in this area.

Computer/Internet Knowledge and Usage

Computer and Internet knowledge as well asusage are frequently and positively associatedwith online shopping predilection. Early studieshave shown that consumers who purchase travelonline were more likely to have more years

of Internet experience (Card et al., 2003; Kahet al., 2008; Kamarulzaman, 2007, 2010; Kim &Kim, 2004; Weber & Roehl, 1999), spend moretime online (Beldona et al., 2011; Kah et al.,2008; Kim & Kim, 2004; Morrison et al., 2001;Weber & Roehl, 1999), and have prior onlineshopping experience (Kim, Ma, & Kim, 2006;Moital, Vaughan, Edwards, & Peres, 2009).

Such findings are not surprising since it isnecessary to have computer and Internet knowl-edge to purchase travel online. However, otherstudies have found that neither Internet experi-ence (Jensen, 2009), frequency of Internet use(Garín-Muñoz & Pérez-Amaral, 2011), com-puter usage (Moital, Vaughan, & Edwards,2009) or travelers’ prior experience with onlineshopping (Jensen, 2009; Morosan & Jeong,2008) had an effect on intentions to purchasetravel online or actual usage.

It is, however, important to note that earlyInternet adopters and individuals that use theInternet more frequently do have higher self-perceptions of technology use (Kah et al., 2008),also known as user’s self-efficacy. This is posi-tively associated with the probability of adopt-ing online travel shopping (Li & Buhalis, 2005,2006). Having a positive attitude toward theInternet (e.g., “the Internet is as essential inmy life as any other thing”) seems to be adeterminant to adopt online travel shopping(Ryan & Rao, 2008). In fact, individuals thatare apprehensive toward the use of the Internetare less likely to purchase or search for travelonline (Susskind, Bonn, & Dev, 2003) whileconsumers’ with higher perceptions of Internetvalue are more likely to purchase travel online(Beldona et al., 2011).

The type of travel websites visited canalso affect the probability of purchasing travelonline. Li and Buhalis (2005) claim that thosewho often visit travel suppliers’ websites (suchas BritishAirways.com) are more likely tobecome bookers than those who often visitwebsites of online travel services (such asTravelocity.com). In contrast, Morrison et al.(2001) argued that those who visit websites ofonline travel services most often are more likelyto purchase travel online. Similar to Morrison’sfindings, Kamarulzaman (2007, 2010) foundthat online travel purchasers prefer to purchase

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from online travel agents, since they provide allsorts of travel products to customers on the samewebsite. For hotel bookings, Morosan and Jeong(2006, 2008) also found that users had a morefavorable attitude and stronger intention to usethird-party websites than hotel websites.

Park and Chung (2009) found that con-sumers who entered a travel website directlywere more likely to make a purchase onlinethan those that entered the site via a referringwebsite. Furthermore, their study indicated thatthe longer the travel website visit length was,along with the fewer number of pages viewed,the more likely a consumer was to purchaseonline.

Travel-Related Behaviors

Researchers have found that certain travel-related behaviors are linked to the purchaseof travel online. For instance, several studieshave found that travelers that search for travelinformation online are more likely to purchasetravel online (Jensen, 2012; Kamarulzaman,2007, 2010; Susskind & Stefanone, 2010; Wen,2010; Wolfe et al., 2004). Despite this beingan expectable finding, Jensen (2012) found thatthis relationship was weak, reflecting that onlinetravel search may not necessarily be followedby an online travel purchase. Furthermore, otherstudies were even more dramatic suggesting thatthere was no relationship between searchingfor travel information online and the intentionto purchase travel online (Li & Buhalis, 2005,2006; Powley, Cobanoglu, & Cummings, 2004).In fact, Jun, Vogt, and MacKay (2007) reportedthat travelers were more likely to use the Internetfor travel information search than for travelpurchase.

Other travel-related behaviors have beenexplored to determine their effect on the like-lihood of purchasing online. For instance,Morrison et al. (2001) acknowledged that peoplewho had traveled to other countries in the past12 months were more likely to purchase travelonline, while several other studies have shownthat individuals with higher levels of travelexperience are more likely to purchase travelonline (Jensen, 2012; Jun et al., 2007; Moital,Vaughan, & Edwards, 2009; Wolfe et al., 2004).

In contrast, other studies found that the num-ber of trips taken did not distinguish onlinepurchasers from nonpurchasers (Li & Buhalis,2006) and that travel frequency was not relatedto the likelihood of purchasing airline ticketsonline (Beldona et al., 2011). Morrison et al.(2001) and Li and Buhalis (2005, 2006) inter-estingly found that having a membership in afrequent flyer program did not influence thatprobability of purchasing travel online. Anotherinteresting variable that was only examined inone study was the purpose of the trip. Lawet al. (2004) found that those whose purpose wastraveling for business were more likely to pur-chase online, while those whose purpose was tovisit relatives were less likely.

Psychological Variables

The psychological variables are variablesderived from psychological theories such as thetheory of reasoned action (TRA; Fishbein &Ajzen, 1975) and the theory of planned behav-ior (TPB; Ajzen, 1991). The TRA suggests thata person’s behavioral intention depends on theperson’s attitude about behavior and also byperceived social pressure to perform or not toperform the behavior, a social factor termed sub-jective norm (Ajzen, 1991). The TPB is actuallyan extension of the TRA, made to overcomethe original model’s limitations in dealing withbehaviors over which people have incompletevolitional control. It adds a third determinantof behavioral intention: perceived behavioralcontrol (Ajzen, 1991).

In the online travel context, studies haveconsistently found that attitude toward onlineshopping is a determinant of intention to pur-chase travel online (Bigné, Sanz, Ruiz, & Aldás,2010; Lee et al., 2007; Morosan & Jeong, 2006,2008). However, regarding subjective norm, theavailable empirical evidence is contradictory.Lee et al. (2007) found that referents’ opinions(subjective norm) had an impact on travelers’intention to purchase online. Yet, San Martínand Herrero (2012), whose study containedsimilar hypotheses, evidenced that the socialinfluence regarding the use of rural accom-modation websites did not affect online pur-chase intentions. Morrison et al. (2001) also

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studied the influence of friends and others onthe intention to purchase travel online, usinga factor labeled “Communicability.” They con-cluded that travelers are more likely to purchasetravel online if they know that others are doingsimilarly. In contrast, Li and Buhalis (2006)asserted that communicability was not impor-tant in explaining the adoption of online travelshopping.

Another important psychological variable isperceived behavioral control (PBC) defined as“the perceived ease or difficulty of performingthe behavior” (Ajzen, 1991, p. 188). Bigné et al.(2010) decomposed PBC into self-efficacy andfacilitating conditions. Self-efficacy is relatedto perceived ability, while facilitating condi-tions are external resource constraints (Taylor &Todd, 1995). Their results indicated that none ofthese dimensions influenced Spanish travelers’intention to purchase airline tickets online, butdid influence their attitude, which then influ-enced intention. San Martín and Herrero (2012)also found that facilitating conditions did notaffect intentions to purchase online.

PBC is a concept similar to self-efficacy(Ajzen, 1991, 2002) that in the online shop-ping context is defined as “a consumer’s self-assessment of his/her capabilities to shop on-line” (Vijayasarathy, 2004, p. 751). Li andBuhalis (2005, 2006) used the self-efficacydimension and found that Chinese online travelpurchasers had a higher degree of self-efficacythan lookers, indicating a positive relationshipbetween self-efficacy and online travel pur-chases.

Personal Traits

Despite being commonly accepted that per-sonal traits influence online purchasing behav-ior, few studies have addressed personal traits asdeterminants of online travel shopping. Indeed,only three personal characteristics were foundin the studies addressing online travel shop-ping: innovativeness, opinion leadership, andinvolvement.

Innovativeness was the personal char-acteristic that most researchers examined.Evidence was found to support that con-sumers’ innovativeness has a positive

relationship with online travel shoppingadoption (Kamarulzaman, 2007; Li & Buhalis,2005, 2006), and moderates the effect betweentravelers’ attitude and their intention to purchasetravel online (Lee et al., 2007). In fact, onlinetravel purchasers are more likely to be high-techprone (Card et al., 2003), are more receptiveto new technological innovations (Kim et al.,2006), and like trying new technologies (Heung,2003).

Opinion leadership, defined as the degreeto which an individual is able to influenceother individuals’ attitudes or behavior (Rogers,1995), was examined in two studies with contra-dictory results. Card et al. (2003) reported thatonline travel purchasers had higher scores onopinion leadership than nonpurchasers. On theother hand, Kamarulzaman’s (2007) resultsindicated that there was not a significantrelationship between opinion leadershipand the adoption of online travel shopping.Kamarulzaman (2007) argues that in spiteof this insignificant relationship, marketersshould not ignore the role of opinion leaders ininfluencing Internet users’ decisions to adoptonline travel shopping.

Involvement was another personal char-acteristic considered in Kamarulzaman’s(2007) study. Although there does not exist acommonly accepted definition of involvement,broad definitions of involvement—such asRothschild’s (1984) as “a state of motivation,arousal, or interest” (p. 217)—paved the way forthe concept to be applied in multiple contexts.Kamarulzaman (2007) found that there was adirect effect between consumers’ involvementwith online shopping and online travel pur-chasing. Two different studies conducted at alater time (Moital, Vaughan, & Edwards, 2009;Moital, Vaughan, Edwards, et al., 2009) reachedidentical conclusions. Therefore, retailers needto get consumers more involved with onlinepurchasing in order to increase online travelpurchasing (Kamarulzaman, 2007; Moital,Vaughan, Edwards, et al., 2009).

Consumer Shopping Orientations

A topic that has received little attention isthe relationship between shopping orientations

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and online travel shopping. Shopping orienta-tions refer to general predispositions towardthe act of shopping (Gehrt & Carter, 1992)and can be applied to the online context.In an earlier study, Jensen (2009) investigatedif two shopping orientations, time-saving orien-tation and store-enjoyment orientation, had aneffect on intentions to purchase travel online.The study concluded that a direct relation-ship did not exist. However, travelers’ shoppingorientation affected their perceived motivatorsand barriers to purchase online which in turnaffected intentions. For example, travelers thatare time-saving oriented tend to value conve-nience that was found to influence intentionsto purchase travel online. In a later study,using price-saving orientation, time-saving ori-entation, information orientation, personalizedorientation, and store-enjoyment orientation,Jensen (2012) found that the only shoppingorientation that had a direct effect on onlinetravel purchasing was store-enjoyment orien-tation. Indeed, the results revealed that store-enjoyment oriented consumers were less likelyto purchase travel products online. In a simi-lar vein, Kolsaker, Lee-Kelley, and Choy (2004)argued that one of the reasons why Hong Kongconsumers appear to be reluctant to purchasingairline tickets online is due to the fact that theyenjoy shopping and view it as a social activ-ity. Jensen (2012) suggests that online retailersneed to improve travelers’ perceived enjoymentof visiting online travel stores to attract travelersto purchase online. The effects of consumercharacteristics on intentions to purchase travelonline and actual purchases of travel online aresummarized in Table 3.

Perceived Channel Characteristics

Privacy and Perceived Risk

In the travel and tourism context, risk issuesplay a significant role in inhibiting purchase oftravel online. This can be observed in Kolsakeret al.’s (2004) study on why Hong Kongconsumers seem reluctant to purchase airlinetickets online even though Hong Kong isamong the countries with the highest broadbandpenetration and Internet access. Their findings

revealed that Hong Kong consumers recognizedthat it was convenient to purchase airline ticketsonline, but the risk involved in the purchaseoutweighed the convenience. Using the sameproduct, Kim, Kim, and Leong (2005) havealso investigated the effect of perceived risk onthe intention to purchase airline tickets online.In their study, perceived risk was considereda multidimensional construct, consisting ofseven types of risk: performance risk, financialrisk, physical risk, psychological risk, socialrisk, time risk, and security risk. The authorsfound that all seven risk dimensions werenegatively correlated with consumers’ purchaseintentions.

Using the same seven dimensions of per-ceived risk, but this time in the United States,Kim, Qu, and Kim (2009) found the expected—i.e., nonpurchasers perceived a higher risk onfinancial, performance, psychological, security,and time risks than online purchasers of airlinetickets. Considering not just airline tickets butall types of travel services, Jensen (2012) real-ized that perceived risk was negatively related toconsumers’ intention to purchase travel online.This relationship between perceived risk andonline travel purchases also seems to be con-sistent across studies conducted worldwide. Forinstance, in Spain, Bigné et al. (2010) noticedthat Spanish Internet users who did not buy air-line tickets online were essentially concernedwith three risk dimensions: performance, psy-chological, and privacy.

Privacy concerns are often pointed outas one of the main reasons consumers donot make online purchases (George, 2004).However, Brown, Muchira, and Gottlieba (2005,2007) studied the effects of privacy on onlinetravel purchase behavior and unexpectedlyfound that although privacy issues concernedconsumers, they did not have an impact on theiractual or intended online travel purchase. Theauthors argued that these results may be dueto the young age of their sample, as youngergroups tend to have lower privacy concerns thanolder ones. These findings could also be theresult of the increasing trust and security incomputer systems as asserted by Bogdanovych,Berger, Simoff, and Sierra (2006).

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TAB

LE3.

The

Effe

cts

ofC

onsu

mer

Cha

ract

eris

tics

onIn

tent

ions

and

Usa

geof

Onl

ine

Trav

elP

urch

asin

g

Con

sum

erch

arac

teris

tics

Stu

dies

with

empi

rical

evid

ence

Maj

orfin

ding

s

Dem

ogra

phic

varia

bles

Edu

catio

nle

vel

Web

eran

dR

oehl

(199

9);M

orris

onet

al.(

2001

);K

iman

dK

im(2

004)

;Lee

etal

.(20

07)

Con

sum

ers

with

high

ered

ucat

ion

leve

lsar

em

ore

likel

yto

purc

hase

trav

elon

line.

Wol

feet

al.(

2005

)E

duca

tion

leve

lsar

esi

mila

rbe

twee

nth

ose

who

purc

hase

trav

elon

line

and

thos

ew

hodo

not.

Heu

ng(2

003)

;Law

etal

.(20

04);

Law

and

Bai

(200

8)T

hepr

obab

ility

ofpu

rcha

sing

onlin

ein

crea

ses

with

educ

atio

n.Li

and

Buh

alis

(200

6)N

odi

ffere

nces

betw

een

book

ers

and

look

ers.

Kam

arul

zam

an(2

007,

2010

)M

osto

nlin

etr

avel

purc

hase

rsha

vehi

gher

educ

atio

nall

evel

s.M

oita

l,V

augh

an,a

ndE

dwar

ds(2

009)

Edu

catio

ndo

esno

tinfl

uenc

eth

epr

obab

ility

ofpu

rcha

sing

trav

elon

line.

Bel

dona

etal

.(20

11)

Edu

catio

nle

veli

sno

trel

ated

toth

epu

rcha

seof

airli

netic

kets

onlin

e.G

arín

-Muñ

ozan

dP

érez

-Am

aral

(201

1)E

duca

tion

leve

lis

notr

elat

edto

the

purc

hase

oftr

avel

onlin

e.G

ende

rW

eber

and

Roe

hl(1

999)

;Mor

rison

etal

.(20

01);

Kim

and

Kim

(200

4);W

olfe

etal

.(20

04);

Lian

dB

uhal

is(2

006)

;Moi

tal,

Vau

ghan

,and

Edw

ards

(200

9);

Bel

dona

etal

.(20

11)

No

rela

tions

hip

betw

een

gend

eran

don

line

trav

elpu

rcha

sing

was

foun

d.

Law

and

Bai

(200

8)M

ense

emto

purc

hase

mor

etr

avel

onlin

eth

anw

omen

.G

arín

-Muñ

ozan

dP

érez

-Am

aral

(201

1)W

omen

have

asl

ight

lyhi

gher

prop

ensi

tyto

purc

hase

trav

elon

line.

Inco

me

leve

lW

eber

and

Roe

hl(1

999)

;Heu

ng(2

003)

Con

sum

ers

with

high

erin

com

ele

vels

are

mor

elik

ely

topu

rcha

setr

avel

onlin

e.M

orris

onet

al.(

2001

)T

here

isno

rela

tions

hip

betw

een

inco

me

leve

land

prob

abili

tyof

purc

hasi

ngtr

avel

onlin

e.C

ard

etal

.(20

03)

Con

sum

ers

that

purc

hase

trav

elon

line

have

high

erin

com

es.

Kim

and

Kim

(200

4)O

nlin

epu

rcha

sers

and

non-

purc

hase

rsdo

notd

iffer

byin

com

e.La

wet

al.(

2004

);La

wan

dB

ai(2

008)

The

prob

abili

tyof

purc

hasi

ngon

line

incr

ease

sw

ithin

com

e.Li

and

Buh

alis

(200

6)N

odi

ffere

nces

betw

een

book

ers

and

look

ers.

Gar

ín-M

uñoz

and

Pér

ez-A

mar

al(2

011)

Inco

me

leve

lis

notr

elat

edto

the

purc

hase

oftr

avel

onlin

e.A

geW

eber

and

Roe

hl(1

999)

Indi

vidu

als

unde

r25

orov

er55

are

less

likel

yto

purc

hase

trav

elon

line.

Mor

rison

etal

.(20

01)

Age

does

nota

ffect

the

prob

abili

tyof

bein

ga

book

er,b

utit

does

affe

ctth

epr

obab

ility

ofbe

ing

are

peat

book

er.

Kim

and

Kim

(200

4)C

onsu

mer

sov

erth

eag

eof

30ar

em

ore

likel

yto

purc

hase

trav

elon

line.

Wol

feet

al.(

2004

)Yo

unge

rco

nsum

ers

are

mor

elik

ely

topu

rcha

seon

line. (C

ontin

ued

)

765

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TAB

LE3.

(Con

tinue

d)

Con

sum

erch

arac

teris

tics

Stu

dies

with

empi

rical

evid

ence

Maj

orfin

ding

s

Lian

dB

uhal

is(2

006)

Look

ers

who

are

aged

betw

een

31an

d40

are

mor

elik

ely

tobo

okon

line,

whi

lepe

ople

aged

over

51ar

ele

sslik

ely.

Law

and

Bai

(200

8)T

hepr

obab

ility

ofpu

rcha

sing

onlin

ein

crea

ses

with

age.

Moi

tal,

Vau

ghan

,and

Edw

ards

(200

9)A

gedo

esno

tinfl

uenc

eth

epr

obab

ility

ofpu

rcha

sing

trav

elon

line.

Gar

ín-M

uñoz

and

Pér

ez-A

mar

al(2

011)

The

35−4

4ag

egr

oup

ism

ore

likel

yto

use

the

Inte

rnet

for

purc

hasi

ngan

dse

arch

ing

for

trav

el.

Occ

upat

ion

Web

eran

dR

oehl

(199

9)T

hose

who

purc

hase

trav

elon

line

are

mor

elik

ely

tobe

empl

oyed

inm

anag

emen

t,pr

ofes

sion

al,o

rco

mpu

ter-

rela

ted

occu

patio

ns.

Lian

dB

uhal

is(2

006)

No

diffe

renc

esbe

twee

nbo

oker

san

dlo

oker

s.M

arita

lsta

tus

Mor

rison

etal

.(20

01)

Mar

itals

tatu

sdo

esno

taffe

ctth

epr

obab

ility

ofpu

rcha

sing

trav

elon

line.

Kam

arul

zam

an(2

010)

Onl

ine

trav

elsh

oppe

rsar

em

ore

likel

yto

bem

arrie

dor

livin

gw

itha

part

ner.

Soc

ial/

econ

omic

stat

usM

oita

l,V

augh

an,a

ndE

dwar

ds(2

009)

Eco

nom

icst

atus

does

noti

nflue

nce

the

prob

abili

tyof

purc

hasi

ngtr

avel

onlin

e.K

amar

ulza

man

(201

0)M

iddl

ecl

ass

cons

umer

sar

em

ore

likel

yto

purc

hase

trav

elon

line

Rac

eW

eber

and

Roe

hl(1

999)

Rac

edi

dno

tdis

tingu

ish

betw

een

onlin

epu

rcha

sers

and

nonp

urch

aser

s.C

ultu

reH

eung

(200

3)O

nlin

etr

avel

purc

hase

rsar

em

ore

likel

yto

befr

omW

este

rnco

untr

ies,

espe

cial

lyA

mer

ican

s.La

wet

al.(

2008

)A

mer

ican

sha

vea

high

erpr

open

sity

than

the

Chi

nese

topu

rcha

setr

avel

onlin

e.H

ouse

hold

size

Mor

rison

etal

.(20

01)

Hou

seho

ldsi

zedo

esno

taffe

ctlo

oker

s’pr

obab

ility

ofbe

ing

book

ers.

Lian

dB

uhal

is(2

005)

Hou

seho

ldsi

zeha

sno

rela

tions

hip

with

inte

ntio

nsto

purc

hase

trav

elon

line.

Com

pute

r/In

tern

etkn

owle

dge

and

usag

e

Leve

lofc

ompu

ter/

Inte

rnet

usag

eW

eber

and

Roe

hl(1

999)

;Kim

and

Kim

(200

4)R

espo

nden

tsth

atha

vepu

rcha

sed

trav

elon

line

have

high

erw

eekl

yIn

tern

etus

age.

Lian

dB

uhal

is(2

006)

Look

ers

and

book

ers

dono

tdiff

erin

term

sof

wee

kly

Inte

rnet

usag

e.M

oita

l,V

augh

an,a

ndE

dwar

ds(2

009)

Ahi

ghle

velo

fcom

pute

rus

age

does

notn

eces

saril

yle

adto

the

adop

tion

ofon

line

purc

hase

s.G

arín

-Muñ

ozan

dP

érez

-Am

aral

(201

1)Fr

eque

ncy

ofus

eof

the

Inte

rnet

isno

trel

ated

toth

epu

rcha

seof

trav

elon

line.

(Con

tinue

d)

766

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nloa

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by [

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liote

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nhec

imen

to o

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V]

at 0

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12

Nov

embe

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13

TAB

LE3.

(Con

tinue

d)

Con

sum

erch

arac

teris

tics

Stu

dies

with

empi

rical

evid

ence

Maj

orfin

ding

s

Inte

rnet

expe

rienc

eW

eber

and

Roe

hl(1

999)

;Kim

and

Kim

(200

4)R

espo

nden

tsth

atha

vepu

rcha

sed

trav

elon

line

wer

em

ore

likel

yto

have

mor

eye

ars

ofIn

tern

etex

perie

nce.

Lian

dB

uhal

is(2

005,

2006

)Lo

oker

sw

ithm

ore

Inte

rnet

expe

rienc

ear

em

ore

likel

yto

purc

hase

trav

elon

line.

Kah

etal

.(20

08)

Inte

rnet

expe

rienc

ean

dpu

rcha

sing

trav

elon

line

are

posi

tivel

yre

late

d.K

amar

ulza

man

(201

0)O

nlin

etr

avel

purc

hase

rsar

eex

perie

nced

Inte

rnet

user

s.Je

nsen

(200

9)In

tern

etex

perie

nce

ispo

sitiv

ely

rela

ted

with

onlin

esh

oppi

ngin

gene

ral,

buti

sno

trel

ated

with

the

inte

ntio

nto

purc

hase

trav

elon

line.

Bel

dona

etal

.(20

11)

Inte

rnet

expe

rienc

eis

posi

tivel

yre

late

dto

adop

tion

ofth

eIn

tern

etto

purc

hase

airli

netic

kets

.C

ompu

ter

use

for

fun

Web

eran

dR

oehl

(199

9)C

ompu

ter

use

for

fun

has

nore

latio

nshi

pw

ithpr

obab

ility

topu

rcha

setr

avel

onlin

e.Ta

sk-o

rient

edus

eof

Inte

rnet

Bel

dona

etal

.(20

11)

Apo

sitiv

ere

latio

nshi

pw

asfo

und

with

buyi

ngai

rline

ticke

tsdi

rect

lyfr

omth

eai

rline

web

site

s.A

ttitu

deto

war

dth

eva

lue

ofth

eIn

tern

etB

eldo

naet

al.(

2011

)P

ositi

vely

rela

ted

toad

optio

nof

the

Inte

rnet

topu

rcha

seai

rline

ticke

ts.

Non

-Int

erne

tin-

hom

esh

oppi

ngex

perie

nce

Car

det

al.(

2003

)O

nlin

esh

oppe

rsar

em

ore

likel

yto

have

used

TV

shop

ping

.

Gen

eral

Inte

rnet

appr

ehen

sive

ness

Sus

skin

det

al.(

2003

);S

ussk

ind

and

Ste

fano

ne(2

010)

Neg

ativ

ere

latio

nshi

pw

ithth

ede

sire

tose

arch

info

rmat

ion

orbo

okon

line.

Tran

sact

iona

lInt

erne

tap

preh

ensi

vene

ssS

ussk

ind

etal

.(20

03);

Sus

skin

dan

dS

tefa

none

(201

0)N

egat

ive

rela

tions

hip

with

the

desi

reto

sear

chin

form

atio

nor

book

onlin

e.O

nlin

ein

form

atio

nse

ekin

gac

tiviti

es(in

clud

esre

sear

chfo

rsc

hool

orw

ork,

job

sear

chac

tiviti

es,e

tc.)

Sus

skin

dan

dS

tefa

none

(201

0)O

nlin

ein

form

atio

n-se

ekin

gac

tiviti

esar

em

oder

atel

yre

late

dto

onlin

epu

rcha

sing

.

Com

pute

rex

perie

nce

Chr

isto

uet

al.(

2004

)C

ompu

ter

expe

rienc

eis

anin

fluen

cing

fact

orfo

rth

ead

optio

nof

the

Inte

rnet

topu

rcha

seai

rline

ticke

ts.

Type

oftr

avel

web

site

svi

site

dM

orris

onet

al.(

2001

)T

hose

who

visi

tweb

site

sof

onlin

etr

avel

serv

ices

are

mor

elik

ely

topu

rcha

setr

avel

onlin

eth

anth

ose

who

visi

ttra

vels

uppl

iers

’w

ebsi

tes.

Lian

dB

uhal

is(2

005,

2006

)In

Chi

nape

ople

who

visi

ttra

vels

uppl

iers

’web

site

sm

ore

ofte

nar

em

ore

likel

yto

purc

hase

trav

elon

line.

(Con

tinue

d)

767

Dow

nloa

ded

by [

b-on

: Bib

liote

ca d

o co

nhec

imen

to o

nlin

e IP

V]

at 0

9:36

12

Nov

embe

r 20

13

TAB

LE3.

(Con

tinue

d)

Con

sum

erch

arac

teris

tics

Stu

dies

with

empi

rical

evid

ence

Maj

orfin

ding

s

Dire

ctly

ente

ring

atr

avel

web

site

Par

kan

dC

hung

(200

9)C

onsu

mer

sth

aten

ter

atr

avel

web

site

dire

ctly

are

mor

elik

ely

topu

rcha

setr

avel

onlin

eth

anth

ose

who

ente

rth

ew

ebsi

tevi

aa

refe

rrin

gw

ebsi

te.

Trav

elw

ebsi

tedu

ratio

nP

ark

and

Chu

ng(2

009)

The

long

erco

nsum

ers

stay

ona

trav

elw

ebsi

teth

em

ore

likel

yto

purc

hase

trav

elon

line.

Num

ber

ofw

ebpa

ges

view

edP

ark

and

Chu

ng(2

009)

The

few

erth

enu

mbe

rof

web

page

svi

ewed

,the

mor

elik

ely

the

purc

hase

oftr

avel

onlin

e.P

rior

expe

rienc

ew

ithon

line

shop

ping

Prio

rex

perie

nce

with

onlin

esh

oppi

ng(in

gene

ral)

Kim

etal

.(20

06)

Itaf

fect

se-

satis

fact

ion

and

inte

ntio

nsto

purc

hase

trav

elon

line.

Moi

tal,

Vau

ghan

,Edw

ards

,and

Per

es(2

009)

Peo

ple

who

have

shop

ped

onlin

ear

em

ore

likel

yto

purc

hase

trav

elon

line.

Jens

en(2

009)

Itdo

esno

taffe

ctin

tent

ion

topu

rcha

setr

avel

onlin

e;ho

wev

er,i

tis

nega

tivel

yre

late

dw

ithpe

rcei

ved

risk.

Prio

rex

perie

nce

with

onlin

etr

avel

purc

hase

sM

oros

anan

dJe

ong

(200

6)P

rior

expe

rienc

ew

ithon

line

trav

elpu

rcha

ses

does

nota

ffect

inte

ntio

nsto

purc

hase

,but

does

affe

ctpe

rcei

ved

ease

ofus

e,pe

rcei

ved

usef

ulne

ss,a

ndat

titud

e.Tr

avel

-rel

ated

beha

vior

sN

umbe

rof

inte

rnat

iona

ltrip

sM

orris

onet

al.(

2001

)Tr

avel

ers

who

had

trav

eled

toot

her

coun

trie

sin

the

past

12m

onth

sw

ere

mor

elik

ely

tobe

book

ers.

Lian

dB

uhal

is(2

006)

No

diffe

renc

esbe

twee

nlo

oker

san

dbo

oker

s.G

arín

-Muñ

ozan

dP

érez

-Am

aral

(201

1)T

hehi

gher

the

prop

ortio

nof

trav

elab

road

,the

mor

eth

eIn

tern

etis

used

for

purc

hasi

ngpu

rpos

es.

Num

ber

ofdo

mes

tictr

ips

Mor

rison

etal

.(20

01)

The

num

ber

ofdo

mes

tictr

ips

does

nota

ffect

the

prob

abili

tyof

beco

min

ga

book

er.

Lian

dB

uhal

is(2

006)

No

diffe

renc

esbe

twee

nlo

oker

san

dbo

oker

s.N

umbe

rof

trip

s(t

rave

lex

perie

nce)

Wol

feet

al.(

2004

)T

henu

mbe

rof

trip

sin

fluen

ces

the

prob

abili

tyof

purc

hasi

ngtr

avel

onlin

e.Ju

net

al.(

2007

)In

divi

dual

sw

ithhi

gher

leve

lsof

trav

elex

perie

nce

are

mor

elik

ely

topu

rcha

setr

avel

onlin

e.Je

nsen

(201

2)T

henu

mbe

rof

trip

spo

sitiv

ely

affe

cts

onlin

ese

arch

,onl

ine

purc

hase

s,an

dpe

rson

aliz

edor

ient

atio

nbu

tis

nega

tivel

yre

late

dto

info

rmat

ion

orie

ntat

ion

and

perc

eive

dris

k.G

arín

-Muñ

ozan

dP

érez

-Am

aral

(201

1)D

oes

nota

ffect

onlin

etr

avel

purc

hasi

ng.

(Con

tinue

d)

768

Dow

nloa

ded

by [

b-on

: Bib

liote

ca d

o co

nhec

imen

to o

nlin

e IP

V]

at 0

9:36

12

Nov

embe

r 20

13

TAB

LE3.

(Con

tinue

d)

Con

sum

erch

arac

teris

tics

Stu

dies

with

empi

rical

evid

ence

Maj

orfin

ding

s

Trav

elin

gfr

eque

ncy

(day

saw

ayfr

omho

me

ontr

avel

ina

year

)

Bel

dona

etal

.(20

11)

Itis

notr

elat

edw

ithth

epu

rcha

seof

airli

netic

kets

onlin

e.

Mem

bers

hip

ina

freq

uent

flyer

prog

ram

(FF

P)

Mor

rison

etal

.(20

01)

Bei

nga

mem

ber

ofa

FF

Pin

fluen

ces

the

prob

abili

tyof

purc

hasi

ngtr

avel

for

thos

ew

hoha

veal

read

ypu

rcha

sed

trav

elin

the

past

,but

does

noti

nflue

nce

the

prob

abili

tyof

look

ers

beco

min

gbo

oker

s.Li

and

Buh

alis

(200

5,20

06)

No

diffe

renc

esbe

twee

nlo

oker

san

dbo

oker

s.In

tern

etas

trav

elin

form

atio

nso

urce

Wol

feet

al.(

2004

)T

hose

who

purc

hase

onlin

ear

em

ore

likel

yto

have

sear

ched

for

trav

elin

form

atio

non

the

Inte

rnet

.P

owle

yet

al.(

2004

)N

ore

latio

nshi

pw

ithth

elik

elih

ood

ofpu

rcha

sing

onlin

e.Li

and

Buh

alis

(200

5,20

06)

The

freq

uenc

yof

usin

gth

eIn

tern

etfo

rtr

avel

info

rmat

ion

does

nota

ffect

the

prob

abili

tyof

purc

hasi

ngtr

avel

onlin

e.Ju

net

al.(

2007

)Tr

avel

ers

wer

em

ore

likel

yto

use

the

Inte

rnet

for

thei

rtr

avel

info

rmat

ion

sear

chth

anfo

rth

eir

trav

elpu

rcha

ses.

Kam

arul

zam

an(2

007,

2010

)T

hem

ajor

ityof

onlin

etr

avel

purc

hase

rsse

arch

for

trav

elin

form

atio

nm

ore

freq

uent

lyth

anot

hers

.W

en(2

010)

Inte

ntio

nsto

use

the

Inte

rnet

for

info

rmat

ion

sear

chis

posi

tivel

yre

late

dw

ithpu

rcha

sein

tent

ions

.Je

nsen

(201

2)∗

Onl

ine

trav

elin

form

atio

nse

arch

and

onlin

etr

avel

purc

hasi

ngha

vea

posi

tive

rela

tions

hip.

See

kfo

rtr

avel

info

rmat

ion

Car

det

al.(

2003

)O

nlin

etr

avel

purc

hase

rsar

em

ore

invo

lved

inin

form

atio

nse

ekin

gth

anno

npur

chas

ers.

Offl

ine

trav

elin

form

atio

nso

urce

Pow

ley

etal

.(20

04)

No

rela

tions

hip

with

the

likel

ihoo

dof

purc

hasi

ngon

line.

Trip

purp

ose

Law

etal

.(20

04)

Tho

sew

hose

trip

purp

ose

isbu

sine

ssar

em

ore

likel

yto

purc

hase

onlin

e.T

hose

who

are

visi

ting

rela

tives

are

less

likel

yto

purc

hase

trav

elon

line.

Vis

iting

onlin

etr

avel

com

mun

ities

Lin,

Jone

s,an

dW

estw

ood

(200

9)V

isiti

ngon

line

trav

elco

mm

uniti

esre

duce

spe

rcei

ved

risk

and

incr

ease

sth

elik

elih

ood

ofpu

rcha

sing

onlin

e.P

sych

olog

ical

varia

bles

Atti

tude

tow

ard

onlin

esh

oppi

ngLe

eet

al.(

2007

);M

oros

anan

dJe

ong

(200

6,20

08);

Big

néet

al.(

2010

)A

favo

rabl

eat

titud

eto

war

don

line

shop

ping

posi

tivel

yaf

fect

sin

tent

ion

topu

rcha

setr

avel

onlin

e.S

ubje

ctiv

eno

rmLe

eet

al.(

2007

);B

igné

etal

.(20

10)

Itis

posi

tivel

yas

soci

ated

with

inte

ntio

nto

purc

hase

.S

anM

artín

and

Her

rero

(201

2)∗

No

rela

tions

hip

with

onlin

epu

rcha

sein

tent

ions

.C

omm

unic

abili

tyM

orris

onet

al.(

2001

)Tr

avel

lers

are

mor

elik

ely

tobo

okon

line

and

tofr

eque

ntly

book

onlin

eif

they

know

that

othe

rsar

edo

ing

likew

ise.

Lian

dB

uhal

is(2

006)

No

diffe

renc

esbe

twee

nlo

oker

san

dbo

oker

s.

(Con

tinue

d)

769

Dow

nloa

ded

by [

b-on

: Bib

liote

ca d

o co

nhec

imen

to o

nlin

e IP

V]

at 0

9:36

12

Nov

embe

r 20

13

TAB

LE3.

(Con

tinue

d)

Con

sum

erch

arac

teris

tics

Stu

dies

with

empi

rical

evid

ence

Maj

orfin

ding

s

Sel

f-ef

ficac

yLi

and

Buh

alis

(200

5,20

06)

Itis

posi

tivel

yas

soci

ated

with

the

likel

ihoo

dof

look

ers

purc

hasi

ngtr

avel

onlin

e.P

erce

ived

beha

vior

alco

ntro

lB

igné

etal

.(20

10)

Itdo

esno

taffe

ctin

tent

ion

topu

rcha

setr

avel

onlin

e,bu

taffe

cts

attit

ude.

Faci

litat

ing

cond

ition

sS

anM

artín

and

Her

rero

(201

2)∗

The

faci

litat

ing

cond

ition

spe

rcei

ved

inth

eus

eof

web

site

sdo

not

affe

cton

line

purc

hase

inte

ntio

ns.

Per

sona

ltra

itsIn

nova

tiven

ess

Car

det

al.(

2003

);Li

and

Buh

alis

(200

6)O

nlin

esh

oppe

rsar

em

ore

inno

vativ

e.Li

and

Buh

alis

(200

5)In

nova

tiven

ess

ispo

sitiv

ely

asso

ciat

edw

ithth

elik

elih

ood

oflo

oker

spu

rcha

sing

trav

elon

line.

Lee

etal

.(20

07)

Atti

tude

and

pers

onal

inno

vativ

enes

sin

tera

ctto

pred

icti

nten

tion

topu

rcha

se.

Kam

arul

zam

an(2

007)

Inno

vativ

enes

sis

posi

tivel

yas

soci

ated

with

adop

tion

ofon

line

trav

elsh

oppi

ngO

pini

onle

ader

ship

Car

det

al.(

2003

)O

nlin

esh

oppe

rste

ndto

beop

inio

nle

ader

s.K

amar

ulza

man

(200

7)O

pini

onle

ader

ship

has

nore

latio

nshi

pw

ithad

optio

nof

onlin

etr

avel

shop

ping

.In

volv

emen

tK

amar

ulza

man

(200

7)In

volv

emen

tis

posi

tivel

yas

soci

ated

with

adop

tion

ofIn

tern

etsh

oppi

ng,t

rust

,and

perc

eive

dris

k.M

oita

l,Vau

ghan

,Edw

ards

,&P

eres

(200

9);

Moi

tal,

Vau

ghan

,and

Edw

ards

(200

9)In

volv

emen

twith

purc

hasi

ngle

isur

eon

line

ispo

sitiv

ely

asso

ciat

edw

ithin

tent

ions

topu

rcha

sele

isur

eon

line.

Con

sum

ersh

oppi

ngor

ient

atio

n

Pric

e-sa

ving

orie

ntat

ion

Jens

en(2

012)

∗P

ositi

vely

rela

ted

with

onlin

ese

arch

,but

notw

ithon

line

purc

hase

s.In

form

atio

nor

ient

atio

nJe

nsen

(201

2)∗

No

rela

tions

hip

with

onlin

ese

arch

.T

ime-

savi

ngor

ient

atio

nJe

nsen

(200

9)N

odi

rect

effe

cton

inte

ntio

nto

purc

hase

,but

indi

rect

via

conv

enie

nce.

Jens

en(2

012)

∗N

ore

latio

nshi

pw

ithon

line

sear

chor

onlin

epu

rcha

ses.

Per

sona

lized

orie

ntat

ion

Jens

en(2

012)

∗P

ositi

vely

rela

ted

with

onlin

ese

arch

,but

notw

ithon

line

purc

hase

s.S

tore

-enj

oym

ent

orie

ntat

ion

Jens

en(2

009)

No

dire

ctef

fect

onin

tent

ion

topu

rcha

setr

avel

,but

trav

eler

sth

atar

est

ore-

enjo

ymen

torie

nted

are

less

likel

yto

pref

erco

nven

ienc

ean

dpe

rcei

veon

line

purc

hasi

ngas

alo

ssof

expe

rienc

e.Je

nsen

(201

2)∗

Neg

ativ

ely

affe

cts

onlin

epu

rcha

ses.

Not

e.∗ A

rtic

les

avai

labl

eon

line

in20

11.

770

Dow

nloa

ded

by [

b-on

: Bib

liote

ca d

o co

nhec

imen

to o

nlin

e IP

V]

at 0

9:36

12

Nov

embe

r 20

13


Relative Advantages

Grounded on Rogers’ (1995) definition ofrelative advantages, the current study considersthat relative advantages concern the degree towhich online travel shopping provides benefitsto consumers or is better than its alternatives.

Based on Chang et al.’s (2005) framework,two factors from Davis’s (1989) technologyacceptance model (TAM)—perceived useful-ness and perceived ease of use—are catego-rized as relative advantages of online shopping.Applied to online shopping, perceived useful-ness is “the extent to which a consumer believesthat online shopping will provide access to use-ful information, facilitate comparison shopping,and enable quicker shopping”; while perceivedease of use is “the extent to which a consumerbelieves that on-line shopping is free of effort”(Vijayasarathy, 2004, p. 750). Cho and Agrusa(2006) found that perceived ease of use andusefulness affected consumer’s attitude towardonline travel agencies, which in turn affectedconsumers’ satisfaction or intention to use.

Adding perceived playfulness to the originalTAM, Morosan and Jeong (2006, 2008) exam-ined the adoption of hotel reservation websites,and found that perceived usefulness, ease ofuse, and playfulness had an impact on atti-tudes toward using hotel reservation websites.Moreover, attitudes and perceived playfulnesshad an impact on users’ intentions to use hotelreservation websites.

Kamarulzaman (2007) added perceived risk,trust, and e-consumers’ personal characteristicsto the original TAM to investigate which fac-tors influenced UK consumers in the adoptionof travel e-shopping. She found that perceivedusefulness was positively correlated to the adop-tion of online travel shopping, but contrary towhat was expected, perceived ease of use didnot affect the adoption of online travel shop-ping directly. This suggests that user-friendlyand easy to use websites are not decisive in thedecision to purchase travel online. Nevertheless,researchers have found that perceived ease ofuse does have an indirect effect on the deci-sion to purchase travel online, since it affectsperceived usefulness, which in turn affects theadoption of online travel shopping (Bigné et al.,2010; Kamarulzaman, 2007).

More recently, San Martín and Herrero(2012) used the unified theory of acceptanceand use of technology as a reference frame-work to explore variables influencing the inten-tion to purchase rural tourism accommodationonline. They found that performance expectancyand effort expectancy (concepts similar to per-ceived usefulness and perceived ease of use,respectively) have a positive influence on onlinepurchase intention.

Convenience has been recognized as oneof the main advantages of online travel shop-ping in numerous studies (e.g., Bai et al.,2004; Bogdanovych et al., 2006; Christou &Kassianidis, 2003; Heung, 2003) and as adimension affecting intention to book hotelsonline (Kim & Kim, 2004; Kim et al., 2006)as well as intentions to purchase overall travelonline (Jensen, 2009). Furthermore, conve-nience has been found to be strongly associatedwith e-satisfaction (Kim et al., 2006; Kolsakeret al., 2004), which in turn will affect thewillingness to make future purchases (Kolsakeret al., 2004). Surprisingly, nonfinancial benefitssuch as convenience, ease of use, and self-satisfaction with using the Internet for travelplanning and booking were not found to besignificant as advantages in Morrison et al.’s(2001) model to predict the probability of book-ing online.

Despite the importance of nonfinancialadvantages, lower prices or further financialbenefits are other advantages usually associatedwith online travel purchases (Morrison et al.,2001). Actually, a significant number of thearticles reviewed provide evidence to supportthe importance of lower prices on consumers’decision to purchase travel online (e.g., Baiet al., 2004; Kim, Kim, & Han, 2007; Kim et al.,2006; Li & Buhalis, 2006; Wong & Law, 2005).Notwithstanding several researchers’ claimsof the importance of price, Ku and Fan (2009)argue that consumers purchasing travel onlineconsider privacy and safety more relevant thanprice.

Relative Disadvantages

In addition to risk, privacy, and trust issues,researchers have identified other factors thatnegatively affect the intention to purchase travel

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online and are, therefore, barriers to the adop-tion of online travel shopping. For instance,perceiving online travel shopping as a complextask has been pointed out in numerous studies asnegatively affecting intentions to purchase travelonline (Christou & Kassianidis, 2003; Klein,Kohne, & Oorni, 2004; Li & Buhalis, 2005;Moital, Vaughan, & Edwards, 2009; Morrisonet al., 2001; Powley et al., 2004). Jensen (2009)argues that travelers who feel they have to giveup hedonic aspects by not shopping at a travelagency, will be less likely to purchase online.Other reasons for not purchasing online are asfollows: being uncomfortable with the Internet(Christou, Avdimiotis, Kassianidis, & Sigala,2004), the lack of experience (Wolfe et al.,2004), price discrepancies among travel web-sites (Klein et al., 2004), lack of personal service(Wolfe et al., 2004), and the preference forother alternatives (Heung, 2003; Kolsaker et al.,2004).

Online Shopping Experience

For many consumers, the online shoppingexperience refers to whether purchasing travelonline is satisfying and entertaining. In thecontext of online travel shopping, researchershave approached online satisfaction differently.Several researchers consider that online travelsatisfaction is related to previous satisfactionwith online travel purchases. For instance,Kolsaker et al. (2004) examined customer sat-isfaction from their online experience with thepurchase of airline tickets. The study found thatonline satisfaction with previous purchases leadto a higher intention to purchase airline tick-ets online. Kim et al.’s (2006) experimentalfindings also revealed that previous satisfactionwith online shopping was the greatest deter-minant in explaining intention to book a hotelonline.

Several researchers (Bai, Law, & Wen, 2008;Law, Bai, & Leung, 2008) have looked atonline satisfaction from a different perspective,exploring satisfaction with the travel website,rather than with the overall shopping experi-ence. These studies concluded that customer sat-isfaction with travel websites leads to a higherintention of purchasing online. In this context,

customer satisfaction will be affected by websitecharacteristics such as navigation functionality,perceived security, transaction cost, interactiv-ity, customization, and website attractiveness(Bai et al., 2008; Khare & Khare, 2010; Law &Bai, 2008; Law et al., 2008).

Other factors identified as being associatedwith the online shopping experience affect-ing consumers’ likelihood of purchasing travelonline were: service performance and repu-tation (Kim et al., 2006), feeling confidentwith online shopping (Powley et al., 2004),perceiving it as enjoyable and entertaining(Morosan & Jeong, 2006; Powley et al., 2004),and being compatible with consumers’ lifestyle(Christou & Kassianidis, 2003; Li & Buhalis,2006).

Trust

Surprisingly, only a few studies examinedthe effect of trust on online travel purchasing.Chen (2006) theorized that consumers’ over-all trust in online travel websites will influencetheir intention to purchase and McCole (2002)argued that trust has an important effect on thepropensity to purchase online. More recently,Wen (2010) claimed that consumers’ trust hada positive effect on intentions to purchase travelonline.

Kamarulzaman (2007) did not find a directeffect of trust on the adoption of online travelshopping. Still, she did find that the more con-sumers trust online travel shopping, the lowertheir risk perception will be. Therefore, trust hasan indirect effect on the adoption of online travelshopping since they will perceive a higher use-fulness in online travel shopping and will bemore likely to adopt it. Bigné et al. (2010) alsofound that trust had an indirect effect on inten-tion to purchase airline tickets online as it hada significant influence on a favorable attitudetoward the use of the Internet to purchase. Thus,regardless of being mediated by perceived riskor not, trust is vital to the success of online travelshopping.

The main findings of the effects of perceivedchannel characteristics on usage and intentionsto purchase travel online are summarized inTable 4.

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TABLE 4. The Effects of Channel Characteristics on Intentions and Usage of Online TravelPurchasing

Perceived channel characteristics Studies withempirical evidence

Major findings

Perceivedrisk/security

Concerns ofsystem security

Heung (2003); Wolfeet al. (2004)

Security issues were one of the most importantreasons why respondents had not purchasedtravel online.

Kim and Kim (2004) Safety influences online reservation intention.Uncertainty of

reservation/cancel-lation

Morrison et al. (2001) Consumers highly concerned with the uncertaintyof reservations are less likely to purchase online.

Credit card security Weber and Roehl(1999)

Main reason for not purchasing travel online.

Morrison et al. (2001) Consumers highly concerned with credit card faultrisk are less likely to purchase online.

Unauthorizedsecondary use ofdata

Brown et al. (2005,2007)

Concerns with unauthorized secondary use of datado not affect actual online travel purchases orintention to purchase travel online.

Invasion of privacy Brown et al. (2005,2007)

Concerns with invasion of privacy does not affectactual online travel purchases or intention topurchase travel online.

Inaccuracy/manipu-lation of personaldata

Brown et al. (2005,2007)

Concerns with manipulation of personal data donot affect actual online travel purchases orintention to purchase travel online.

Concerns withoverall privacy

Ku and Fan (2009) Concerns with privacy were one of the mainfactors considered by consumers purchasingtravel online.

Overall perceivedrisk

Kolsaker et al. (2004) Strong negative correlation with willingness topurchase airline tickets online.

Kamarulzaman(2007)

It is not associated with the adoption of onlinetravel shopping, but is negatively associated withperceived usefulness.

Ku and Fan (2009) One of the main factors considered by customerspurchasing travel online.

Kim et al. (2009) Nonpurchasers perceive higher risks than onlinepurchasers when purchasing airline ticketsonline.

Bigné et al. (2010) It negatively affects trust and attitudes towardonline shopping.

Jensen (2009,2012∗)

It negatively related with intention to purchasetravel online.

Financial risk Kim et al. (2005) Financial risk is negatively associated withintention to purchase online.

Kim et al. (2009) Perceived much riskier by nonpurchasers thanonline purchasers.

Performance risk Kim et al. (2005) Performance risk is negatively associated withintention to purchase travel online.

Kim et al. (2009) The most influential risk in potential consumersavoiding online purchases.

Psychological risk Kim et al. (2005) Psychological risk is negatively associated withintention to purchase travel online.

Kim et al. (2009) It is perceived much riskier by nonpurchasers thanonline purchasers.

Social risk Kim et al. (2005) Social risk was negatively associated with intentionto purchase online.

Kim et al. (2009) No differences of perceived social risk betweenonline purchasers and nonpurchasers.

(Continued)

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TABLE 4. (Continued)


Major findings

Physical risk Kim et al. (2005) Physical risk does not affect intention to purchasetravel online.

Kim et al. (2009) No differences of perceived physical risk betweenonline purchasers and nonpurchasers.

Time risk Kim et al. (2005) Time risk is negatively associated with intention topurchase travel online.


Security risk Kim et al. (2005) It is negatively associated with intention topurchase online.


Relativeadvantages

Convenience Morrison et al. (2001) No relationship with the likelihood to purchasetravel online.

Heung (2003) One of the main reasons to purchase travel online.Kolsaker et al. (2004) Positive correlation with willingness to purchase

airline tickets online.Kim and Kim (2004) It affects intention to purchase online.Bai et al. (2004) Main reason why college students purchase travel

online.Kim et al. (2006) It affects e-satisfaction and online purchase

intention.Ku and Fan (2009) Not a main factor attracting consumers to

purchase travel online.Mayr and Zins (2009) Online shoppers value convenience.Jensen (2009) Consumers that value convenience are more likely

to purchase travel online.Time saving Morrison et al. (2001) No relationship with online travel purchases.

Wong and Law(2005)

Affects intention to purchase travel online.

Heung (2003) One of the main reasons to purchase travel online.Christou &

Kassianidis (2003)The larger the perceived time pressure, the larger

the perceived relative advantage and perceivedcompatibility of purchasing travel online.

Easy to order Morrison et al. (2001) No relationship with intention to purchase travelonline.

Perceived easeof use/effortexpectancy

Morrison et al. (2001) No relationship with the probability to book online.Morosan and Jeong

(2006, 2008)It has a positive impact on attitude toward hotel

reservation sites, on perceived playfulness, andon perceived usefulness.

Cho and Agrusa(2006)

Affects consumer’s attitude toward online travelagencies, which in turn affects consumers’satisfaction and intention to purchase travelonline.

Kamarulzaman(2007)

It does not have a direct influence on the adoptionof online purchases, but has an impact on trustand perceived usefulness.

Bigné et al. (2010) Affects intentions to purchase airline tickets onlineindirectly via perceived risk and trust.

San Martín andHerrero (2012)∗

It positively affects online purchase intention.

(Continued)

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Major findings

Perceivedusefulness/

performanceexpectancy

Morosan and Jeong(2006, 2008)

Has a positive impact on attitudes toward hotelreservation sites.

Cho and Agrusa(2006)

Affects consumers’ attitude toward online travelagencies, which in turn affects consumers’satisfaction and intentions to purchase travelonline.

Kamarulzaman(2007)

It is positively associated with online travelpurchases.

Bigné et al. (2010) Affects attitude toward the purchase of airlinetickets which in turn influences intentions topurchase airline tickets online.

San Martín andHerrero (2012)∗

It positively affects online purchase intentions.

Price Morrison et al. (2001) Consumers tend to purchase online to get lowerprices.

Kim and Kim (2004) Price affects intention to purchase online.Wong and Law

(2005)Price level was more important than web security

and web features.Beldona et al. (2005) Price motivates the purchase of less complex

travel online.Kim et al. (2006) Price affects intentions to purchase travel online.Ku and Fan (2009) Price is not a main factor attracting consumers to

purchase travel online. Consumers considerprivacy, safety, and product quality moreimportant when purchasing travel online.

Finding low fares Kim et al. (2007) Finding low fares was found to be the most criticalattribute for consumers to use online travelagencies.

Special discounts Morrison et al. (2001) Consumers looking for special discounts weremore likely to purchase online.

Physical effort ofin-store travelshopping

Christou andKassianidis (2003)

The larger the perceived physical effort of in-storetravel shopping, the larger the perceived relativeadvantage of shopping for travel online.

Overall relativeadvantages

Christou andKassianidis (2003);Moital, Vaughan,Edwards, andPeres (2009)

Higher levels of perceived relative advantages arepositively related to intentions to purchase travelonline.

Points/rewards Beldona et al. (2005) Being offered points or rewards motivates thepurchase of less-complex travel online.

Self-satisfaction ofplanning travel byown

Morrison et al. (2001) It has no relationship with purchasing travel online.

Overall financialadvantages

Li and Buhalis (2006) No significant differences between bookers andlookers.

Product variety Jensen (2009) A greater product variety influences consumers’intention to purchase online.

Relative disad-vantages

Time consuming Wolfe et al. (2005) Reported reason why people had not bought travelonline.

Lack of personalservice

Wolfe et al. (2004) Lack of personal service was one of the reportedreasons why people had not bought travelonline.

(Continued)

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Major findings

Mayr and Zins (2009) Nonshoppers value personal services of traditionaltravel agencies.

Loss of experiencewith onlineshopping

Christou andKassianidis (2003)

No relationship with perceived relative advantage ofpurchasing for travel online.

Jensen (2009) Negatively associated with intentions to purchasetravel online.

Perceivedcomplexity

Christou andKassianidis (2003);Powley et al.(2004); Li andBuhalis (2005);Klein et al. (2004);Moital,Vaughan,Edwards, andPeres (2009)

All studies found that perceived complexity isnegatively associated with intentions to purchasetravel online.

Onlinesatisfaction

Customersatisfaction

Kolsaker et al. (2004) Previous satisfaction with the purchase of airlinetickets online affects willingness to purchase airlinetickets online.

Law et al. (2008);Law and Bai(2008); Bai et al.(2008)

Customer satisfaction with travel websites affectsintentions to purchase travel online.

Kim et al. (2006) Previous satisfaction with online travel shopping wasthe greatest determinant in explaining intention tobook a hotel online.

Perceivedcompatibility

Christou andKassianidis (2003);Li and Buhalis(2006)

Both studies found that perceived compatibility ispositively associated with intention to purchasetravel online.

Enjoyable Powley et al. (2004) Positive relationship with likelihood of purchasingtravel online.

Confident Powley et al. (2004) Positive relationship with likelihood of purchasingtravel online.

Li and Buhalis (2006) Lookers and bookers showed the same degree ofconfidence in using the Internet to purchase travel.

Entertaining Cho and Agrusa(2006)

Entertainment affects perceived ease of use andperceived usefulness, which in turn affectsintentions to purchase travel online.

Perceivedplayfulness

Morosan and Jeong(2006, 2008)

Perceived playfulness affects attitudes toward usinghotel reservation sites and intentions to use hotelwebsites for purchasing.

Serviceperformance andreputation

Kim et al. (2006) Service performance and reputation does not affecte-satisfaction, but affects online purchase intention.

Trust Overall trust McCole (2002) Trust is important to consumers who purchase travelonline.

Chen (2006) Theorizes that overall trust influences consumerintention and adoption of purchasing travel online.

Kamarulzaman(2007)

Trust has a positive impact on perceived risk, but doesnot have a direct impact on online travel shopping.

Bigné et al. (2010) Trust positively affects attitude towards purchasingairline tickets online which in turn influencesintentions to purchase airline tickets online.

Wen (2010) Trust has a positive impact on online purchaseintentions.

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Website and Product Characteristics

Website Features

Despite the growing body of literature aboutwebsite quality assessment in the tourism andhospitality fields (see Ip et al., 2011; Law,Qi, & Buhalis 2010), there is still a lackof research regarding the relationship betweenwebsite quality and online consumers’ behavior(Bai et al., 2008). Indeed, few studies establisha relationship between website characteristicsand intentions to purchase travel online or actualusage. The few existent studies suggest that agood website design has a significant effect onconsumers’ online purchase intentions (Wen,2010) and on consumers’ trust (Chen, 2006).Consumers that had enjoyable experiences onthe website are more willing to purchase travelonline (Powley et al., 2004). Bai et al. (2008)and Law et al. (2008) suggested that websitequality, measured by usability and functionalitydimensions, had an indirect influence on pur-chase intentions through customer satisfaction.Lin, Jones, and Westwood (2009) noted that theuse of pictures and the presence of contact infor-mation on travel websites reduced the perceivedrisk of online travel purchase by Taiwanese con-sumers. Regardless of the importance of websitedesign on consumers online behavior, Wong andLaw (2005) found that price was more importantthan web features when booking hotel roomsonline.

Product Characteristics

Travel products can be classified basedon their complexity (Beldona, Morrison, &O’Leary, 2005). Beldona et al. (2005) clas-sify products such as flights, accommodation,and car rentals as low-complexity travel prod-ucts; while land-based holidays, cruises, andtours are considered high complexity (Beldonaet al., 2005). Another distinction comes fromAnckar and Walden (2001), who classifydomestic travel and single-leg flights as low-complexity travel arrangements, whereas inter-national travel with multi-legged flights are con-sidered high-complexity travel arrangements.Bogdanovych et al. (2006) found that the major-ity of the respondents of their study, which

were heavy computer users, prefer bookingtheir international trips from a travel agent,while domestic trips are usually booked online.Law et al. (2004) also observed that short-haultravelers’ perception of the online channel wasmuch more positive than long-haul travelers.

This distinction between high- and low-complex travel is important since travelers’motivations to purchase online vary acrosslow- and high-complex travel products (Beldonaet al., 2005). However, very few studies haverelated travel complexity to online travel pur-chasing usage or intentions.

The main findings of the effects of websiteand product characteristics on intentions to pur-chase travel online and actual usage are summa-rized in Table 5.

DISCUSSION AND FUTURERESEARCH DIRECTIONS

As the literature review has shown, priorwork on online travel shopping has focused onseveral antecedents of online travel shoppingand has included theories that were originallyfrom other fields (e.g., TAM, TRA, and TPB).Nevertheless, understanding travelers’ purchasebehavior online is still a challenging issue andthere are several research gaps that can beexplored.

Consumer characteristics and the perceivedchannel characteristics have been the mostresearched variables. Even so, the findings inthese categories present contradictory results.For example, the relationship between onlinetravel search and online travel purchases is notclear. Another example is opinion leadership;Kamarulzaman (2007) found that it did not havean effect on the adoption of online travel, whileCard et al. (2003) claimed that online travelpurchasers tended to be opinion leaders. Futureresearch should be undertaken in order to clearcontradictory results or investigate findings thathave not been fully explored.

Website and product characteristics is clearlythe category with the least amount of stud-ies. Most studies concerning website evalu-ation in Tourism research usually generateperformance indices or scores to capture the

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TABLE 5. The Effects of Website and Product Characteristics on Intentions and Usage of OnlineTravel Purchasing

Website and product characteristics Studies with empirical evidence Major findings

Website features Functionality Law and Bai (2008); Bai et al.(2008); Law, et al. (2008)

Functionality is positively associatedwith customer satisfaction andonline purchase intentions.

Usability Law and Bai (2008); Law et al.(2008); Bai et al. (2008)

Usability is positively associated withcustomer satisfaction and onlinepurchase intention.

Information quality Wong and Law (2005) It is positively associated withintentions to purchase travelonline.

Beldona et al. (2005) Information quality motivates thepurchase of more complex travelonline.

Kim et al. (2006) Affects e-satisfaction, but notpurchase intention.

Overall websitequality

Powley et al. (2004) No association with the likelihood ofpurchasing travel online.

Wen (2010) It positively affects consumer trust,search intentions, and onlinepurchase intentions.

Risk relievers Lin et al. (2009) Risk relievers (e.g., security labeland privacy policy) have a positiveimpact on consumers’ decision topurchase travel online.

Productcharacteristics

Short haul, longhaul

Law et al. (2004) Short-haul travelers have a morepositive perception of the onlinechannel than long-haul travelers.However, they were less willing topurchase online than long-haultravelers.

Domestic flights,internationalflights

Bogdanovych et al. (2006) Travelers prefer booking theirinternational trips from a travelagent, while domestic trips areusually booked online.

overall quality of a website (Law et al., 2010)and do not relate the website evaluation withthe purchase of travel online. Thus, researchregarding website quality should go beyondsimply ascertaining whether certain websitedimensions/attributes are present to consideringwhich dimensions/attributes have the greatestimpact and consumer intentions to purchase (Ipet al., 2011).

The majority of the studies focus on travelproducts without distinguishing specific productcategories. However, as previously noted, sometravel-related services such as flights, accommo-dation, and car rentals are categorized as low-complexity travel products; while land-basedholidays, cruises, and tours are considered high

complexity. This distinction is acknowledged ina few studies that have shown that online shop-ping motivations differed for the two categories.Although several studies focused specifically onlow-complexity travel services, such as accom-modation (e.g., Kim & Kim, 2004) or airlinetickets (e.g., Kim et al., 2009), no researchstudy focuses exclusively on high-complexityproducts. Thus, further studies should studyonline purchasing motivations considering dis-tinct travel product categories rather than con-sidering travel as one category. Moreover, fur-ther studies should be conducted specifically tocompare high- and low-complexity products.

Research on online travel purchasing behav-ior has been majorly conducted with travelers

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TABLE 6. Article Distribution by Travel Products and Services and by Region

Travel products andservices

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Total

Airline tickets − − − − − 2 2 − − − 1 1 1 7Accomodation − − − − − 1 1 2 − 1 − − 1 6Travel in general 1 − 1 1 4 2 4 4 5 5 7 4 3 41RegionAsia − − − − − 2 1 2 2 1 2 − 2 11

China − − − − − 1 1 2 1 2 − − 7Korea − − − − − 1 − − 1 − − − − 2India − − − − − − − − − − − − 2 2

America 1 − 1 − 2 2 3 3 1 2 2 2 − 19USA + Canada − − − − − 1 1 − − − − − − 2Canada − − − − − − − − − 1 − − − 1USA 1 − 1 − 2 1 2 3 2 1 2 2 − 17

Europe − − − − − − − − − − − − − 14Austria − − − − − − − − − − 1 − − 1Denmark − − − − − − − − − − − 1 1 2Finland − − 1 − − − − − − − − − − 1Finland andGermany

− − − − − − 1 − − − − − − 1

Greece − − − − 1 1 − − − − − − 2Portugal − − − − − − − − − − 2 − − 2Spain − − − − − − − − − − − 1 1 2UK − − − 1 − − − − 1 − − 1 − 3

Oceania − − − − − − 1 1 1 − − − − 3Worldwide − − − − − − − − − − − − − 6

China, Taiwan,Singapore,Malaysia, USA,Australia andWestern Europe

− − − − − 1 1 − − 1 − − − 3

China, Canada,Taiwan,Singapore, USA,Australia,Malaysia

− − − − 1 − − − − − − − − 1

Australia, UK andNorth America

− − − − − − − − − 1 − − − 1

China and USA − − − − − − − − − 1 − − − 1

from the United States and China (see Table 6).Studies should be conducted in other coun-tries in order to confirm and generalize results.On the other hand, although six studies usedtravelers from different countries, only one (Lawet al., 2008) conducted a cross-cultural com-parison. Consumers in different countries havedifferent shopping preferences due to culturaldifferences (Kim & Lee, 2006) and this shouldbe further researched. Law et al. (2008) considerthat the influence of culture on Internet usage isstill a relatively unexplored field and that morework should be performed to further examinethis issue.

Another relatively unexplored field is theeffect of the purpose of travel on online travelpurchasing behavior. For example, Law et al.(2004) found that international travelers visitingrelatives purchased less online than those whotraveled for leisure, business, or to visit friends.No other studies addressed this issue, butnumerous studies have tried to provide usefulprofiles of travelers that purchase online, mainlyby using demographic variables. Surprisingly,only one study (Moital, Vaughan, & Edwards,2009) conducted a cluster analysis to iden-tify market segments with similar views towardonline travel purchasing. It would be useful to

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carry out other segmentation studies using dif-ferent measures such as shopping motivations,personality, or attitudes. Furthermore, it wouldbe interesting to identify which variables mostinfluence online travel shopping behavior foreach segment in order to develop online mar-keting strategies that meet the needs of eachsegment.

Social media are a very interesting topic toexplore. The evolution of the social Internetis changing how people search, shop for, andpurchase travel (PhoCusWright, 2011). Onlinesocial networking applications have becomehighly popular throughout the hospitality indus-try (Kasavana, Nusair, & Teodosic, 2010). Notonly do they offer the opportunity for busi-nesses to interact with their customers, butcustomers are able to interact with other cus-tomers. It is believed that online social net-working will play a crucial role in online trans-actions (Kasavana et al., 2010). Several stud-ies have confirmed the importance of socialmedia in searching for travel information andthe important role they have in the trip plan-ning and purchase decision-making process(Gretzel & Yoo, 2008; Gretzel, Yoo, & Purifoy,2007; O’Connor, 2008; Xiang & Gretzel, 2010).Therefore, future research needs to addressthe relationship between social media use andonline travel purchasing behavior. For exam-ple, a traveler’s use of user-generated contentor being a member of a travel community, suchas Tripadvisor, could predict online travel shop-ping behavior.

In Law et al.’s (2004) study, respondentsfelt that travel agencies were better than travelwebsites in terms of human touch and per-sonal services. However, as Hassanein and Head(2007) have reported, it is possible to integratehuman warmth and sociability through the webinterface to positively impact consumer atti-tudes toward online shopping. Their study, inthe particular context of clothing, revealed thatthe perception of social presence on a commer-cial website had a positive impact on perceivedusefulness, trust, and enjoyment, which in turnpositively affect attitudes toward online shop-ping. Future investigations could examine thepotential impact of social presence on onlinepurchase intentions and actual purchases along

with how social presence may help to build trustand reduce consumers’ perceived risk, particu-larly in the travel and tourism industry.

Another interesting finding to explore istravelers’ prior experience with online shoppingof other products and services since it appearsto have had no direct effect on their intentionsto purchase travel online (Jensen, 2009). Futureinvestigations could examine if there are anyparticular reasons for online shoppers of otherproducts and services not to buy travel onlineand if there are any perceived differences.

Few studies have focused on personality traitsof those who purchase travel online. It is knownthat online travel purchasers tend to be inno-vative, more high-tech prone and have higherdegrees of involvement. Yet, further investi-gations should address the role of personalityon online travel purchasing behavior. It wouldbe valuable to incorporate theories and mod-els from other academic disciplines such aspsychology and sociology.

Many studies have focused on intentionalbehavior rather than the actual behavior.Although past studies have proven that inten-tion leads to actual behavior, this is questionablewith online travel shopping. For instance, Shaoand Gretzel (2010) found that a high percent-age of travelers abandon travel websites aftersearching for a hotel room and before sub-mitting the final confirmation. Future researchshould assert this relationship between intentionand actual behavior, in the specific context ofonline travel shopping.

FINAL REMARKS, IMPLICATIONS,AND LIMITATIONS

Online travel shopping has attractedresearchers due to its significant growthand there is a growing body of literature in thisfield. This study reviewed 54 articles publishedbetween 1999 and 2011 in leading tourismjournals, highlighting the main contributions ofthese studies to the tourism field. Moreover, aclear and comprehensive review of factors thataffect online travel shopping was provided bycategorizing all of the variables identified intothree main groups: consumer characteristics,

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perceived channel characteristics, and websiteand product characteristics. Such a thoroughreview enabled the identification of several gapsand suggestions of research directions.

Indeed, further research should be conductedfor several reasons. First, as aforementioned,several determinants of online travel shoppinghave been clearly overlooked. For instance, therelationship between social media with the pur-chase of travel online has never been carriedout. Second, research should also be undertakento clarify contradictory results. In some cases,the contradictory findings may be the result ofresearchers’ different approaches to the sameconstruct (e.g., online shopping experience).However, in several studies it is not clear howresearchers conceptualize certain constructs.Thus, to facilitate comparisons with other stud-ies, this study recommends researchers to pro-vide a clear definition of the constructs includedin their studies and how they were operational-ized. Finally, research on online travel shoppinghas typically been fragmented. The literaturereview has revealed that there is a lack of stud-ies that integrate several constructs to betterunderstand online travel shopping and deter-mine which factors are indeed more importantto consumers.

A major limitation of this study is that theliterature review is predominantly based onarticles from tourism and travel journals. Thereview could be enriched with articles fromother academic journals that address onlinetravel shopping. On the other hand, althougha structured methodology was conducted tosearch for suitable articles, it is possible thatsome relevant articles could be missing. In fact,articles may occasionally address online travelpurchase, but they may not be explicit throughthe title or keywords, making it difficult to spotthese articles.

In spite of these limitations, academicresearchers, tourism practitioners, and mar-keters can take advantage of this study to betterunderstand the work that has been carried out inthe area of online travel shopping. Practitionersand marketers can identify variables that influ-ence the purchase of travel online and conse-quently improve online travel distribution strate-gies. Understanding online traveler’s buying

behavior is important to implement successfulonline marketing strategies (Lee et al., 2007).In the academic field, it is expected that thisresearch will make an important contributionto the current body of literature by extendingthe knowledge on the purchase of travel online.Furthermore, the research gaps identified alsoprovide researchers with challenging directionsfor future research.

NOTE

1. Online travel purchase intentions are derived fromFishbein and Ajzen’s (1975) theory of reasoned action thatposits that behavioral intentions are the main predictorsof actual behavior. Behavioral intentions have been wellestablished as a strong predictor of online shopping (e.g.,Ajzen, 2011; Chen, Gillenson, & Sherrell, 2002; Limayem,Khalifa, & Frini, 2000; Lin, 2007; Pavlou & Fygenson,2006).

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SUBMITTED: May 15, 2012FIRST REVISION SUBMITTED:

October 4, 2012ACCEPTED: October 25, 2012

REFEREED ANONYMOUSLY

APPENDIX

Selected Journals and ConferenceProceedings Included in the Literature Review

Journals and Proceedings (in alphabetic order)

Annals of Tourism ResearchAsia Pacific Journal of Tourism ResearchCornell QuarterlyInternational Journal of Contemporary HospitalityManagementInternational Journal of Hospitality ManagementInternational Journal of Tourism ResearchJournal of Hospitality and Tourism TechnologyJournal of Information Technology & TourismJournal of Sustainable TourismJournal of Leisure ResearchJournal of Tourism StudiesJournal of Travel and Tourism MarketingJournal of Travel ResearchInformation and Communication Technologies in TourismTourism AnalysisTourism EconomicsTourism Management

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Documents

Online travel purchasing: A literature review