Advertisement

Assessment of Perceived Risk in Mobile Travel Booking

  • Sangwon ParkEmail author
  • Iis P. Tussyadiah
  • Yuting Zhang
Conference paper

Abstract

Considering the increasing prevalence of smartphones in travel experiences, a relatively low level of mobile booking for travel products suggests the importance of understanding the perceived risk that inhibits mobile consumption behaviours among travellers. Based on responses from an online panel, this study identified the multidimensional facets of perceived risk associated with mobile travel booking, which include time risk, financial risk, performance risk, security risk, psychological risk, physical risk, and device risk. Further, it was identified that there are antecedents that contribute positively (i.e., collection of personal information) and negatively (i.e., consumer innovativeness, trust, and visibility) to perceived risk. Finally, this research estimated the effects of perceived risk on behavioural outcomes, including perceived usefulness, attitudes, and booking intentions. Implications to alleviate or reduce perceived risks are provided.

Keywords

Perceived risk Mobile booking Smartphones 

References

  1. Aldás-Manzano, J., Lassala-Navarré, C., Ruiz-Mafé, C., & Sanz-Blas, S. (2009). The role of consumer innovativeness and perceived risk in online banking usage. International Journal of Bank Marketing, 27(1), 53–75.CrossRefGoogle Scholar
  2. Aloudat, A., Michael, K., Chen, X., & Al-Debei, M. M. (2014). Social acceptance of location-based mobile government services for emergency management. Telematics and Informatics, 31, 153–171.CrossRefGoogle Scholar
  3. Anuar, F. I., & Gretzel, U. (2013). Privacy concerns in the context of location-based services for tourism. e-Review of Tourism Research, 2013.Google Scholar
  4. Bhatnagar, A., Misra, S., & Rao, H. R. (2000). On risk, convenience, and internet shopping behavior. Communications of the ACM, 11, 98–105.CrossRefGoogle Scholar
  5. Brislin, R. (1986). The wording and translation of research instruments. In W. Lonne & J. Berry (Eds.), Field methods in cross-cultural research. Newbury Park, CA: Sage.Google Scholar
  6. Bromiley, P., & Curley, S. P. (1992). Individual differences in risk taking. In F. F. Yates (Ed.), Risk taking behavior (pp. 87–132). Chichester, UK: Wiley.Google Scholar
  7. Chang, H. H., & Chen, S. W. (2008). The impact of online store environment cues on purchase intention. Online Information Review, 32(6), 818–841.CrossRefGoogle Scholar
  8. Cheung, C., & Lee, M. K. O. (2000). Trust in internet shopping: a proposed model and measurement instrument. In Proceedings of the 6 th Americas Conference on Information Systems (pp. 681–689).Google Scholar
  9. China Internet Watch (2015). More Chinese Travelers Active on Mobile than PC. http://www.chinainternetwatch.com/15053/mobile-tourism-apps-users-pc/
  10. Conchar, M. P., Zinkhan, G. M., Peters, C., & Olavarrieta, S. (2004). An integrated framework for the conceptualization of consumers’ perceived-risk processing. Journal of the Academy of Marketing Science, 32(4), 418–436.CrossRefGoogle Scholar
  11. Crespo, A. H., del Bosque, I. R., & de los Salmones, M. M. G. (2009). The influence of perceived risk on internet shopping behavior: A multidimensional perspective. Journal of Risk Research, 12(2), 259–277.CrossRefGoogle Scholar
  12. Cunningham, L. F., Gerlach, J. H., Harper, M. D., & Young, C. E. (2005). Perceived risk and the consumer buying process: Internet airline reservations. International Journal of Service Industry Management, 16(4), 357–372.CrossRefGoogle Scholar
  13. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.CrossRefGoogle Scholar
  14. Deutch, M. (1960). Trust, trustworthiness and the F scale. Journal of Abnormal and Social Psychology, 61(1), 138–140.CrossRefGoogle Scholar
  15. Dholakia, U. M. (2001). A motivational process model of product involvement and consumer risk perception. European Journal of Marketing, 35(11/12), 1340–1362.CrossRefGoogle Scholar
  16. Donthu, N., & Garcia, A. (1999). The Internet shopper. Journal of Advertising Research, 39(3), 52–58.Google Scholar
  17. Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of Consumer Research, 21, 119–134.CrossRefGoogle Scholar
  18. eRevMax (2014). eRevMax shares key insights on Chinese Travel Industry. http://www.erevmax.com/ratetiger-news/infographic-chinese-travel-industry.html
  19. Expedia Media Solution. (2014). The mobilized travel consumer—Insights to optimize your mobile strategy. White Paper.Google Scholar
  20. Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474.CrossRefGoogle Scholar
  21. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90.Google Scholar
  22. Gefen, D., Rao, V. S., & Tractinsky, N. (2003). The conceptualization of trust, risk, and their relationship in electronic commerce: The need for clarifications. In Proceedings of the 36th Hawaii International Conference on Systems Sciences (HICSS) 2003.Google Scholar
  23. Hirunyawipada, T., & Paswan, A. K. (2006). Consumer innovativeness and perceived risk: implications for high technology product adoption. Journal of Consumer Marketing, 23(4), 182–198.CrossRefGoogle Scholar
  24. Hu, L., & Bentler, P. M. (1999). Cut-off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.CrossRefGoogle Scholar
  25. Jacoby, J., & Kaplan, L. B. (1972). The components of perceived risk. In M. Venkatesan (Ed.), Proceedings of the Third Annual Conference of the Association for Consumer Research (pp. 382–393). Chicago, IL: Association for Consumer Research.Google Scholar
  26. Jarvenpaa, S. L., & Todd, P. A. (1996). Consumer reactions to electronic shopping on the World Wide Web. International Journal of Electronic Commerce, 1(2), 59–88.CrossRefGoogle Scholar
  27. Jarvenpaa, S. L., & Tractinsky, N. (1999). Consumer trust in an Internet store: A cross-cultural validation. Journal of Computer Mediated Communication, 5(2), 1–35.Google Scholar
  28. Jarvenpaa, S. L., Tractisnky, N., Saarinen, M., & Vitale, M. (1999). Consumer trust in an internet store: A cross-cultural validation. Journal of Computer-Mediated Communication, 5(2), 0.CrossRefGoogle Scholar
  29. Junglas, I., & Spitzmuller, C. (2005). A research model for studying privacy concerns pertaining to location-based services. In Proceedings of HICSS’05, Hawaii, January 2005, (pp. 3–6).Google Scholar
  30. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.CrossRefGoogle Scholar
  31. Kim, M.-K., Chang, Y., Wong, S. F., & Park, M.-C. (2013). The effect of perceived risks and switching barriers on the intention to use smartphones among non-adopters in Korea. Information Development. doi: 10.1177/0266666913513279.Google Scholar
  32. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44, 544–564.CrossRefGoogle Scholar
  33. Kim, L. H., Kim, D. J., & Leong, J. K. (2005). The effect of perceived risk on purchase intention in purchasing airline tickets online. Journal of Hospitality & Leisure Marketing, 13(2), 33–53.CrossRefGoogle Scholar
  34. Kline, R. B. (2010). Principles and practice of structural equation modeling. New York: Guilford Press.Google Scholar
  35. Kuhlmeier, D., & Knight, G. (2005). Antecedents to internet-based purchasing: A multinational study. International Marketing Review, 22(4), 460–473.CrossRefGoogle Scholar
  36. Lee, M. S. Y., McGoldrick, P. J., Keeling, K. A., & Doherty, J. (2003). Using ZMET to explore barriers to the adoption of 3G mobile banking services. International Journal of Retail & Distribution Management, 31(6), 340–348.CrossRefGoogle Scholar
  37. Leung, L., & Wei, R. (1999). Who are the mobile phone have-nots? Influences and consequences. New Media & Society, 1(2), 209–226.CrossRefGoogle Scholar
  38. Lim, N. (2003). Consumers’ perceived risk: sources versus consequences. Electronic Commerce Research and Applications, 2, 216–228.CrossRefGoogle Scholar
  39. Lu, H.-P., Hsu, C.-L., & Hsu, H.-Y. (2005). An empirical study of the effect of perceived risk upon intention to use online applications. Information Management & Computer Security, 13(2), 106–120.CrossRefGoogle Scholar
  40. Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: an empirical study of mobile banking services. Decision Support Systems, 46, 222–234.CrossRefGoogle Scholar
  41. Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709–734.Google Scholar
  42. Mitchell, V. W. (1999). Consumer perceived risk: Conceptualisations and models. European Journal of Marketing, 33(1/2), 163–195.CrossRefGoogle Scholar
  43. Mitchell, V. W., & Vassos, V. (1998). Perceived risk and risk reduction in holiday purchases: A cross-cultural and gender analysis. Journal of Euromarketing, 6(3), 47–79.CrossRefGoogle Scholar
  44. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.CrossRefGoogle Scholar
  45. Neuhofer, B., Buhalis, D., & Ladkin, A. (2014). A typology of technology-enhanced tourism experiences. International Journal of Tourism Research, 16, 340–350.CrossRefGoogle Scholar
  46. Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879–903.CrossRefGoogle Scholar
  47. Ratnasingham, P. (1998). The importance of trust in electronic commerce. Internet Research, 8(4), 313–321.CrossRefGoogle Scholar
  48. Roehl, W., & Fesenmaier, D. (1992). Risk perceptions and pleasure travel: An exploratory analysis. Journal of Travel Research, 30(4), 17–26.CrossRefGoogle Scholar
  49. Rogers, E. M. (1995). Diffusions of innovation. New York: The Free Press.Google Scholar
  50. Sitkin, S. B., & Pablo, A. L. (1992). Reconceptualizing the determinants of risk behavior. Academy of Management Review, 17(1), 9–38.Google Scholar
  51. Sonmez, S. F., & Graefe, A. R. (1998). Determining future travel behavior from past travel experience and perceptions of risk and safety. Journal of Travel Research, 37, 171–177.CrossRefGoogle Scholar
  52. van der Heijden, H., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: Contributions from technology and trust perspectives. European Journal of Information Systems, 12, 41–48.CrossRefGoogle Scholar
  53. Vishwanath, A., & Goldhaber, G. M. (2003). An examination of the factors contributing to adoption decisions among late-diffused technology products. New Media & Society, 5(4), 547–572.CrossRefGoogle Scholar
  54. Wang, D., Park, S., & Fesenmaier, D. R. (2012). The role of smartphones in mediating the touristic experience. Journal of Travel Research, 51(4), 371–387.CrossRefGoogle Scholar
  55. Yang, Y., & Zhang, J. (2009). Discussion on the dimensions of consumers’ perceived risk in mobile service. The Proceeding of 2009 Eighth International Conference on Mobile Business. Washington, DC: IEEE Computer Society, 261–266.Google Scholar
  56. Zaltman, G., Duncan, R., & Holbek, J. (1973). Innovations and organizations. New York: Wiley.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Sangwon Park
    • 1
    Email author
  • Iis P. Tussyadiah
    • 2
  • Yuting Zhang
    • 1
  1. 1.School of Hospitality and Tourism ManagementUniversity of SurreyGuildfordUK
  2. 2.School of Hospitality Business ManagementWashington State UniversityPullmanUSA

Personalised recommendations