Elsevier

Tourism Management

Volume 35, April 2013, Pages 132-143
Tourism Management

Predicting the intention to use consumer-generated media for travel planning

https://doi.org/10.1016/j.tourman.2012.06.010Get rights and content

Abstract

Despite the growing enthusiasm about social media, empirical research findings suggest that the majority of Internet users are not using consumer-generated media (CGM) for travel planning. Yet little is presently known about the relevant factors determining CGM usage for the specific purpose of travel planning. Using an online survey of travel consumers, this study investigates the intention to use consumer-generated media for travel planning by introducing new factors into the conventional TAM and using a partial least squares' estimation. Findings shed light on the differences in terms of the antecedents in this context. While the study demonstrates the theoretical validity and the empirical applicability of the TAM model to the context of CGM usage for travel planning, it goes further to verify the significant roles of distinctive factors like travelers' perceptions of similarity of interest, trustworthiness and enjoyment. Several managerial and research implications emerge.

Highlights

► Found support for the conventional TAM related constructs in predicting intention. ► Observed differences in study's context regarding the nature of the relationships. ► Hedonic value is most influential in predicting the utilitarian use for trip planning. ► Findings support the appropriateness of the attitude construct in TAM research. ► Perceived similarity of interest wields a strong relationship with trustworthiness.

Introduction

The emergence of Web 2.0 and user-generated content has profoundly transformed consumer behavior as well as marketing approaches on the Web. As O'Connor (2010) described, “the Internet is evolving from a push marketing medium to one where peer-to-peer generation and sharing of data are the norm” (p. 754). This evolution has impacted hospitality and tourism in at least three fundamental ways: first, the proliferation of numerous online communities centered on travel discussions such as Virtual Tourist, Igo Ugo, Independent Traveler, TripAdvisor and WAYN – even general social networking sites like Facebook and MySpace are integrating special “apps” to stimulate travel discussions; second, the changing behaviors of travelers with regards to information search and travel planning; and third, the integration of social media into the marketing strategies of hospitality and tourism organizations. This trend has given rise to the growing popularity of social media which embody a wide range of “Internet-based applications that build on the ideological and technological foundations of Web 2.0 and that allow the creation and exchange of User Generated Content” (Kaplan & Haenlein, 2010, p. 61).

The hospitality and tourism industry represents one of the principal domains being impacted most by this phenomenon. Social media offer an unequaled platform for travel consumers to share their experiences and opinions online in the form of text, photographs and videos through consumer review sites, social networking sites, blogs, and media sharing sites, among others (Xiang & Gretzel, 2010). The content created by consumers through this platform is generally termed as user-generated content (UGC) or consumer-generated media (CGM). This CGM plays a critical role in the context of travel planning (Litvin, Goldsmith, & Pan, 2008; Yoo & Gretzel, 2011). Also regarded as electronic word-of-mouth, CGM is increasingly becoming a major source of travel information for many travelers, with a number of studies acknowledging its growing influence on travel decision making. Prior work conducted by Gretzel, Yoo, and Purifoy (2007) as well as Arsal, Backman, and Baldwin (2008), for instance, show that user-generated travel reviews are useful for travelers when deciding where to go (destination), where to stay (accommodation) and what to do at the destination (activities). Furthermore, there is some evidence to suggest that CGM significantly impacts decisions on hotel online bookings (Ye, Law, Gu, & Chen, 2011).

However, notwithstanding the growing popularity of social media, research findings suggest that a great proportion of Internet users are still not utilizing CGM for travel planning (e.g. Cox, Burgess, Sellitto, & Buultjens, 2009; World Travel Market, 2010). A recent survey conducted by the World Travel Market (2010), for example, shows that only one-in-three individuals who embarked on holidays in the year 2010 consulted some forms of social media during the planning phase of their trips. This brings to the fore the need to better understand the factors driving the usage of CGM for travel planning. An understanding of the determinants of travelers' utilization of CGM for the specific purpose of travel planning is critical if hospitality and tourism practitioners are to maximize the use of this emerging platform for their online marketing strategies.

This paper reports the findings of an empirical study which investigates the cognitive factors affecting online travel consumers' intentions to use CGM for the specific purpose of travel planning. The rest of the paper is structured as follows. First, we provide a review of previous studies including a description of the research model and the proposed hypotheses. We then explain the various methods employed in the study. The results are presented and discussed in the subsequent section. The final session considers the implications of the study with some concluding remarks.

Section snippets

Theoretical background and research hypotheses

The growing importance of CGM and social media, in general, in the hospitality and tourism context has not escaped the attention of researchers. Recent studies have investigated the role of CGM in information search and the travel planning process (Arsal et al., 2008; Cox et al., 2009; Xiang & Gretzel, 2010), social benefits and membership behaviors in online travel communities (Casaló, Flavián, & Guinalíu, 2010; Qu & Lee, 2011) and CGM implications for hotel online bookings and travel

Measures and data collection

From a post-positivist perspective, this study adopted a quantitative approach to data collection and analysis. The approach followed is similar to those employed in other contexts by Lin (2012), Wu, Lin, and Lin (2011), Ryu et al. (2009) and Venkatesh et al. (2003) in predicting behavioral intention. To collect the necessary data for testing the hypotheses, a survey instrument was developed on the basis of established measures of constructs from the information systems and the general

Sample characteristics

Table 1 presents the profile of the sample respondents. Of the 535 respondents, 52.7% were females and 47.3% were males. Respondents were fairly distributed across the various age groups with those in their twenties representing a slight majority. About two-thirds of the respondents had earned a diploma or above. The participants were largely habitual Internet users who access the Internet several times on a day (87.9%) or once daily (9.5%). Having taken a vacation trip within the previous 12

Key findings

This study introduced new factors into the TAM to investigate travelers' intention to use consumer-generated media for travel planning using a PLS estimation. Comparing our results with previous TAM research reveals several interesting findings. As hypothesized, the study found significant support for the conventional TAM related constructs – perceived usefulness, perceived ease of use, perceived enjoyment, attitude and intention. This would imply that individuals who normally disregard CGM may

Julian K. Ayeh is a Ph.D candidate in the School of Hotel and Tourism Management at the Hong Kong Polytechnic University. His research interests include online travel behavior, social media and web-based marketing.

References (92)

  • J.W. Moon et al.

    Extending the TAM for a world-wide-web context

    Information & Management

    (2001)
  • C. Morosan et al.

    Users' perceptions of two types of hotel reservation Web sites

    International Journal of Hospitality Management

    (2008)
  • H. Qu et al.

    Travelers' social identification and membership behaviors in online travel community

    Tourism Management

    (2011)
  • M.-H. Ryu et al.

    Understanding the factors affecting online elderly user's participation in video UCC services

    Computers in Human Behavior

    (2009)
  • J. Schepers et al.

    A meta-analysis of the technology acceptance model: investigating subjective norm and moderation effects

    Information & Management

    (2007)
  • R.J. Vallerand

    Toward a hierarchical model of intrinsic and extrinsic motivation

  • E.M. van Raaij et al.

    The acceptance and use of a virtual learning environment in China

    Computers & Education

    (2008)
  • Z. Xiang et al.

    Role of social media in online travel information search

    Tourism Management

    (2010)
  • H. Xiao et al.

    The use of tourism knowledge: research propositions

    Annals of Tourism Research

    (2007)
  • D. Yan

    The invisible hands behind web postings

    China Daily

    (2010, June 17)
  • Q. Ye et al.

    The influence of user-generated content on traveler behavior: an empirical investigation on the effects of e-word-of-mouth to hotel online bookings

    Computers in Human Behavior

    (2011)
  • K.H. Yoo et al.

    Influence of personality on travel-related consumer-generated media creation

    Computers in Human Behavior

    (2011)
  • I. Ajzen

    Attitude structure and behavior

  • I. Ajzen et al.

    Understanding attitudes and predicting social behavior

    (1980)
  • I. Arsal et al.

    Influence of an online travel community on travel decisions

  • R.P. Bagozzi

    The self-regulation of attitudes, intentions and behavior

    Social Psychology Quarterly

    (1992)
  • R.P. Bagozzi

    The legacy of the technology acceptance model and a proposal for a paradigm shift

    Journal of the Association for Information Systems

    (2007)
  • R.P. Bagozzi et al.

    On the evaluation of structural equation models

    Journal of Academy of Marketing Science

    (1988)
  • W.M. Bowler et al.

    Relational correlates of interpersonal citizenship behaviour: a social network perspective

    Journal of Applied Psychology

    (2006)
  • J. Brown et al.

    Word of mouth communication within online communities: conceptualizing the online social network

    Journal of Interactive Marketing

    (2007)
  • S. Burgess et al.

    Trust perceptions of online travel information by different content creators: Some social and legal implications

    (2009)
  • J.A. Castañeda et al.

    Extrinsic and intrinsic motivation in the use of Internet as a tourist information source

    International Journal of Internet Marketing & Advertising

    (2007)
  • J.A. Castañeda et al.

    Antecedents of internet acceptance and use as an information source by tourists

    Online Information Review

    (2009)
  • W.W. Chin

    The partial least squares approach to structural equation modeling

  • J.Y. Chung et al.

    Information needs in online social networks

    Information Technology & Tourism

    (2008)
  • C. Cox et al.

    The role of user-generated content in tourists' travel planning behavior

    Journal of Hospitality Marketing & Management

    (2009)
  • J. Curran et al.

    Self-service technology adoption: comparing three technologies

    Journal of Services Marketing

    (2005)
  • Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: theory and...
  • F.D. Davis

    Perceived usefulness, perceived ease of use, and user acceptance of information technology

    MIS Quarterly

    (1989)
  • F.D. Davis et al.

    User acceptance of computer technology: a comparison of two theoretical models

    Management Science

    (1989)
  • F.D. Davis et al.

    Extrinsic and intrinsic motivation to use computers in the workplace

    Journal of Applied Social Psychology

    (1992)
  • E.L. Deci et al.

    The support of autonomy and the control of behavior

    Journal of Personality and Social Psychology

    (1987)
  • E.D. De Leeuw

    Choosing the method of data collection

  • C. Dellarocas

    Reputation mechanisms

  • M. Fishbein et al.

    Belief, attitude, intention, and behavior: An introduction to theory and research

    (1975)
  • A.J. Flanagin et al.

    The credibility of volunteered geographic information

    GeoJournal

    (2008)
  • Cited by (0)

    Julian K. Ayeh is a Ph.D candidate in the School of Hotel and Tourism Management at the Hong Kong Polytechnic University. His research interests include online travel behavior, social media and web-based marketing.

    Norman Au is an Assistant Professor in the School of Hotel and Tourism Management, Hong Kong Polytechnic University. His research interests include information systems satisfaction, internet usage behavior and e-complaints in hospitality and tourism.

    Rob Law is a Professor in the School of Hotel and Tourism Management, Hong Kong Polytechnic University. His research interests are in technology applications to tourism and information management.

    1

    Tel.: +852 3400 2236; fax: +852 2362 9362.

    2

    Tel.: +852 3400 2181; fax: +852 2362 9362.

    View full text