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International Tourism Advertisements on Social Media: Impact of Argument Quality and Source

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  • Un-Kon Lee

    (Department of Business Administration, The University of Suwon, 17, Wauan-gil, Bongdam-eup, Hwaseong-si, Gyeonggi-do 18323, Korea)

Abstract

To guarantee sustainable international tourism market growth, challenges for international tourism advertisements (ITAs) include how and by whom they are made. Different to traditional ITAs, a new type of ITA has been created by the international tourists themselves; it contains not only pictures but also their own tour stories, and it is distributed via social media (e.g., Youtube.com). However, few studies have investigated the impacts of this type of ITA. I was challenged to empirically validate the impacts on potential tourist reactions of argument quality and the peer tourist source of ITAs. I developed my research model based on Toulmin’s model of argument, institution-based trust, the information adoption model, and consumer reaction literature. I conducted the quasi-experiment using three types of ITAs that vary by argument quality and advertisement source. A total of 387 data were collected and analyzed using ANOVA and the partial least squares (PLS) analysis. The results indicate that argument quality and peer tourist source significantly increase perceived ITA quality, ITA fit-to-task and trusting belief, and decrease perceived risk. Argument quality and peer tourist source could also significantly increase tourist reactions, such as ITA adoption, planned/unplanned visit, and word-of-mouth intention. These findings could make ITAs more persuasive on social media.

Suggested Citation

  • Un-Kon Lee, 2017. "International Tourism Advertisements on Social Media: Impact of Argument Quality and Source," Sustainability, MDPI, vol. 9(9), pages 1-18, August.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:9:p:1537-:d:110204
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    1. Dongmin Kim & Izak Benbasat, 2006. "The Effects of Trust-Assuring Arguments on Consumer Trust in Internet Stores: Application of Toulmin's Model of Argumentation," Information Systems Research, INFORMS, vol. 17(3), pages 286-300, September.
    2. Stephanie Watts Sussman & Wendy Schneier Siegal, 2003. "Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption," Information Systems Research, INFORMS, vol. 14(1), pages 47-65, March.
    3. Marios Koufaris, 2002. "Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior," Information Systems Research, INFORMS, vol. 13(2), pages 205-223, June.
    4. Peter B. Seddon, 1997. "A Respecification and Extension of the DeLone and McLean Model of IS Success," Information Systems Research, INFORMS, vol. 8(3), pages 240-253, September.
    5. Nelson Granados & Alok Gupta & Robert J. Kauffman, 2010. "Research Commentary---Information Transparency in Business-to-Consumer Markets: Concepts, Framework, and Research Agenda," Information Systems Research, INFORMS, vol. 21(2), pages 207-226, June.
    6. D. Veena Parboteeah & Joseph S. Valacich & John D. Wells, 2009. "The Influence of Website Characteristics on a Consumer's Urge to Buy Impulsively," Information Systems Research, INFORMS, vol. 20(1), pages 60-78, March.
    7. Jaeki Song & Fatemeh Mariam Zahedi, 2005. "A Theoretical Approach to Web Design in E-Commerce: A Belief Reinforcement Model," Management Science, INFORMS, vol. 51(8), pages 1219-1235, August.
    8. Alan R. Dennis & Susan T. Kinney, 1998. "Testing Media Richness Theory in the New Media: The Effects of Cues, Feedback, and Task Equivocality," Information Systems Research, INFORMS, vol. 9(3), pages 256-274, September.
    9. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    10. Paul A. Pavlou & David Gefen, 2004. "Building Effective Online Marketplaces with Institution-Based Trust," Information Systems Research, INFORMS, vol. 15(1), pages 37-59, March.
    11. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    12. Munch, James M & Boller, Gregory W & Swasy, John L, 1993. "The Effects of Argument Structure and Affective Tagging on Product Attitude Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(2), pages 294-302, September.
    13. Andreas I. Nicolaou & D. Harrison McKnight, 2006. "Perceived Information Quality in Data Exchanges: Effects on Risk, Trust, and Intention to Use," Information Systems Research, INFORMS, vol. 17(4), pages 332-351, December.
    14. James E. Bailey & Sammy W. Pearson, 1983. "Development of a Tool for Measuring and Analyzing Computer User Satisfaction," Management Science, INFORMS, vol. 29(5), pages 530-545, May.
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    Cited by:

    1. Hermawan, Hary & , Santosa & Sinangjoyo, Nikasius Jonet, 2022. "The Significance of Tourism Attraction and Social Media Promotion on The Interest of Return Visit," OSF Preprints q5npu, Center for Open Science.
    2. Palos-Sanchez, Pedro & Saura, Jose Ramon & Martin-Velicia, Felix, 2019. "A study of the effects of programmatic advertising on users' concerns about privacy overtime," Journal of Business Research, Elsevier, vol. 96(C), pages 61-72.

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