Usability Guidelines for WAP-based Travel Planning Tools

Conference paper


Designing effective and efficient user interfaces for supporting complex tasks on mobile devices remains an intriguing problem. The rapidly evolving hardware and software mobile environments are complicating the design of elaborated applications like travel planning. Allowing mobile users to review their travel-plan information while travelling has been addressed by a recent R&D project. In order to improve usability and derive good design guidelines, two alternative WAP-based solutions were experimented: one based on providing explicit guidance and information, and another focussed on brevity and iconic metaphors. These two designs enabled to investigate mobile users’ preferences and behaviour and the effects on usability and effectiveness. A user study was conducted and users’ behaviour on both variants was logged. Using objective measures and users’ subjective perceptions, the effects of design options, users’ age and proficiency with WAP applications were tested. This study allowed deriving some guidelines by analysing which graphical components better support mobile usability, and which solutions should be avoided.


Travel Planning Usability Mobile Internet WAP Web Portal 


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  1. Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734–749.CrossRefGoogle Scholar
  2. Bertelè, U., & Rangone, A. (2008). Rapporto mobile and wireless business. Politecnico di Milano.Google Scholar
  3. Buchanan, G., Farrant, S., Jones, M., Thimbleby, H., Marsden, G., & Pazzani, M. (2001). Improving mobile internet usability. In Proceedings of the 10th international Conference on World Wide Web (Hong Kong, Hong Kong, May 01–05, 2001). WWW’ 01. ACM, New York, NY, 673-680.Google Scholar
  4. Buhalis, D., & Pistidda, L. (2009). Wireless Applications in Destinations. Information and Communication Technologies in Tourism 2009, 161–171.Google Scholar
  5. Cena, F., Console, L., Gena, C., Goy, A., Levi, G., Modeo, S., & Torre, I. (2006). Integrating heterogeneous adaptation techniques to build a flexible and usable mobile tourist guide. AI Communications 19(4), 369–384.Google Scholar
  6. Fesenmaier, D. R., Werthner, H., & Woeber, K. (2006). Destination Recommendation Systems: Behavioural Foundations and Applications. CABI Publishing.Google Scholar
  7. Forum Nokia. (2008). Getting Started with Mobile Design. Version 1.0; June 5, 2008. Scholar
  8. Haid, E., Kiechle, G., Göll, N., & Soutshek, M. (2008). Evaluation of a Web-based and Mobile Ski Touring Application for GPS-enabled Smartphones. Information and Communication Technologies in Tourism 2008, 313–323.Google Scholar
  9. Jones, M., & Marsden, G. (2005). Mobile Interaction Design. John Wiley and Sons.Google Scholar
  10. Kramer, R., Modsching, M., & ten Hagen, K. (2007). Behavioural Impacts of Mobile Tour Guides. Information and Communication Technologies in Tourism 2007, 109–118.Google Scholar
  11. Lee, J., & Mills, J. E. Exploring Tourist Satisfaction with Mobile Technology. Information and Communication Technologies in Tourism 2007, 141–152.Google Scholar
  12. Lewis, J. R. (1995). IBM Computer Usability Satisfaction Questionnaires: Psychometric Evaluation and Instructions for Use. ACM — International Journal of Human-Computer Interaction. (May 07, 2009).Google Scholar
  13. Nielsen, J. (2009). Mobile Usability Test Findings. Scholar
  14. Ricci, F., & Nguyen, Q.N. (2007). Acquiring and revising preferences in a critique-based mobile recommender system. IEEE Intelligent Systems 22(3), 22–29.CrossRefGoogle Scholar
  15. Shiller, J.H. (2003). Mobile Communications. Addison-Wesley.Google Scholar
  16. Turban, E., Lee, J.K., King, D., McKay, J., & Marshall, P. (2008). Electronic Commerce. Prentice Hall.Google Scholar
  17. Venturini, A. & Ricci, F. (2006). Applying trip@dvice recommendation technology to In Proceedings of the 17th European Conference on Artificial Intelligence, Riva del Garda, Italy, Aug 28th–Sept 1st, 607–611.Google Scholar

Copyright information

© Springer-Verlag/Wien 2010

Authors and Affiliations

  1. 1.eCTRL SolutionsItaly
  2. 2.Faculty of Computer ScienceFree University of Bozen-BolzanoItaly
  3. 3.Center for Information TechnologyFondazione Bruno KesslerItaly

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