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The Antecedents of Consumer- Generated Media Adoption for Travel Planning: A Literature Review Dandison C. Ukpabi University of Jyväskylä, Finland [email protected] m Heikki Karjaluoto University of Jyväskylä, Finland heikki.karjaluoto @jyu.fi

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The Antecedents of Consumer-Generated Media Adoption for Travel Planning: A Literature Review

Dandison C. UkpabiUniversity of Jyvskyl,[email protected] KarjaluotoUniversity of Jyvskyl, [email protected]

Table of ContentsIntroductionResearch objectivesResearch methodsResultsDiscussion and contributions

IntroductionSocial media platforms have become powerful tools consumers use to spread word-of-mouth (WOM

In the tourism and hospitality services industry, consumer-generated media (CGM) have become effective tools used by tourists to gather information to make travel decisions

Introduction80% read reviews about a hotel before embarking on a trip

53% will not book a hotel that has no reviews- Tsao et al. (2015)

Introduction/Social mediaPlatforms inTourism andtravelVirtual communities e.g., Lonely Planet, MySpaceMedia sharing tools e.g., YouTube, Flickr, Vimeo Blogse.g., Xanga.com, Blogger.com Microblogs e.g., Twitter, Tumblr Review sites e.g., TripAdvisor, EpinionsSocial networking e.g., Facebook, MySpace, LinkedIn,

ResearchobjectivesTo identify the antecedents of CGM adoption in travel planning;

To identify the theories, models and frameworks used in these studies;

To analyze the strengths of the antecedents in predicting CGM adoption in travel planning.

ResearchMethodsLiterature SearchSearch terms used included:social media adoption in tourism, e-WOM in tourism and travel, Web 2.0 adoption in tourism and travel, consumer-generated media in tourism and travel, social networking in tourism and travel, blogs in tourism and travel, online communities in tourism and travel, and virtual communities in tourism and travel

ResearchMethodsLiterature SearchIn the following databases:Google ScholarScience Direct, SAGE, Wiley, Springer, Emerald, JSTOR, IEEE, Taylor & Francis and Inderscience

ResearchMethodsInclusion criteriaquantitativeconsumer-basedinclude measures for independent and dependent variableshave a defined sample size provide detailed results of the data analysis

ResearchMethodsLiterature ExtractionJournal ArticlesPhD DissertationConference PapersTotal512154

29 journals

ResultsTheoriesModelsFrameworks/

Journal distribution22 different and heterogeneous theories, models and frameworks were used

Major ones included: TAM 14 (26%); TPB 5 (9%); ELM 3 (5%); TRA 3 (5%); UTAUT 1 (1.8%)

ResultsGeographical distributionAfricaAsiaAustraliaEuropeNorthAmericaTotalCountriesTunisia11China55Hong Kong11India11Iran22Jordan11Malaysia11Republic of Korea22Singapore11Taiwan1111Turkey11UAE11Australia22Cyprus11Denmark11Italy22Spain66Sweden11United Kingdom22USA1010Canada11Total1272131154

ResultsYear-wise distribution

ResultsConceptual frameworkAdoption antecedentsIntrinsic FactorsEnjoymentInvolvementKnowledgeExperienceSatisfactionBenefitExtrinsic FactorsSocial influenceExpertiseHomophilyReputationTrustAdoptionIntention UsageModeratorsNoveltyValenceAestheticsArgument qualityInformation qualityInformation reliability

ResultsCGM AntecedentsThe study uncovers 61 different antecedents of CGM

Most frequently used ones are:CodeConstructFrequencyATTAttitude16PUPerceived usefulness13PEOUPerceived ease of use11TRUTrust8SISocial influence/subjective norm8ENJEnjoyment8EMPEmpathy3PBCPerceived behavioral control3SCSource credibility3

ResultsAnalysis of Path coefficientsWe extracted the tested path coefficients and their relationships and theories in the 54 reviewed studies E.g.NoAuthor(s)Path coefficients ()Theory1Filieri & McLeay (2014)NAELM2Parra-Lpez et al. (2011)COSINT (.01); BENINT (.44); INCINT (.36)INT3Book et al. (2015)NACDT4Casal et al. (2010)PUATT (.218); PUINT (.301); PUTRU (.547); TRUATT (.600); TRUINT (.306)TPB, TAM, SIT53Ting et al. (2014)PUATT (.32); REPATT (.36); ALTATT (.27); TRUATT (.34), SIINT (.25); ATTINT (.67)TRA, TPB, TAM54Filiery et al. (2015)NAe-WOM

ResultsAnalysis of Path coefficientsConstructsNumber of studiesAttitudeNumber of studiesIntentionAttitude--15.511Perceived usefulness6.18010.432Trust6.3626.352Perceived ease of use5.2645.347Subjective norm/social influence--6.343Enjoyment--3.335

We then analyzed the effect sizes of the frequently used independent variables on the dependent variables.

Trust predicted attitude more than other variables.

DiscussionThe study was to provide a review of consumer-generated media in tourism and travel.

We analyzed the articles and proposed a framework for consumer-generated media adoption.

We also identified 22 heterogeneous and distinct theories, models and frameworks with 61 different antecedents and path coefficients of their relationships.

Discussion

Consumer adoption of CGM depends on the:User characteristics

Source characteristicsModerating factorsContent characteristics

ContributionsFirst, our framework identified antecedents that predict the adoption of CGM in tourism and travel.

These antecedents were based on intrinsic and extrinsic characteristics of the user and on moderating factors.

The identified theories and the antecedents with their path coefficients from different studies provide a solid theoretical background for subsequent research (Okoli & Schabram, 2010)

ContributionsThe contributions of scholars from the information systems field as evidenced from non-tourism based journals show that research on social media in tourism and travel is growing, and not only within the domain of management science.

The identification of trust as having the strongest effect on attitude is in line with earlier studies in which trust has been identified as an important criterion for using CGM (Parra-Lpez et al., 2011)

Emerging markets in India and Africa are lagging behind in research in this stream.

LimitationsIt was based on quantitative studies only

The review was based on CGM and did not incorporate marketer-generated media

Future researchdirections Studies in Africa, India and South America: strong emerging markets

Other social media platforms like YouTube, Lonely Planet, etc.

AppreciationThank you!Dandison C. UkpabiUniversity of Jyvskyl, [email protected] KarjaluotoUniversity of Jyvskyl, [email protected]