Wireless Personal Communications

, Volume 69, Issue 3, pp 1067–1075 | Cite as

Effect of Culture, Age, and Language on Quality of Services and Adoption of IP Applications



Mobile phones with applications on Internet Protocol (IP) can be seen almost in anyplace and anytime at present. This enables development of new types of applications for various user segments, using smart phones as user devices. Different people around the world have different needs to suit their personal and cultural tastes. A better understanding of quality of service (QoS) will help enhance adoption and use of IP technology. Although there are many recent research related to adoption of new information technology application, there were only a few study related to user perception of QoS. This study proposed factors that can be used as dimensions for assessment of perception of QoS (QOS) of IP application by users with different human centric factors. The proposed perceived QOS includes 3 dimensions; culture, ageing, and language. Cultural dimensions in this research include Power Distance, Individualism, Masculinity, and Uncertainty Avoidance. Ageing dimensions cover expectancy of knowledge, experience, and physical degradation. Two more dimensions related to ability to notice and coping with unexpected events are also used as assessment dimensions. Language dimensions are language visibility and speech intelligibility. With the proposed perceived QOS, application developers can identify features and quality required by users with different culture, ageing and language. Besides, the proposed dimensions can also be used for predicting user adoption of new IP application among different groups of users.


Quality of service (QOS) Culture dimensions IP applications  User’s perception User’s adoption 



The authors appreciate all comments and suggestions from the reviewers that help making the paper better. We also thank the editor of this journal for valuable suggestions. This work was supported by the Higher Education Research Promotion and National Research University Project of Thailand, Office of the Higher Education Commission.


  1. 1.
    Dixit, S., Ojanpera, T., Nee, V. R., Prasad, R., et al. (2011). Chapter 1. Introduction to globalization of mobile and wireless communications today and in 2020. In R. Prasad (Ed.), Globalization of mobile and wireless communications: Today and in 2020, signals and communication technology (pp. 1–8). Berlin: Springer.CrossRefGoogle Scholar
  2. 2.
    Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioural impacts. International Journal of Man-Machine Studies, 38, 475–487.CrossRefGoogle Scholar
  3. 3.
    Papasratorn, B. (2010). Mobile broadband application framework for e-Government services for aging society. The Asia-Pacific Telecommunity (APT) workshop on e-Application/e-Government, Bangkok, Thailand.Google Scholar
  4. 4.
    Han, L., & Jin, Y. (2009). A review of technology acceptance model in the e-commerce environment. In Proceeding of international conference on management of e-Commerce and e-Government (ICMECG) (pp. 28–31). Nanchang, China.Google Scholar
  5. 5.
    Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. Educational Technology and Society, 12(3), 150–162.Google Scholar
  6. 6.
    Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.CrossRefGoogle Scholar
  7. 7.
    Venkatesh, V., Morris, M. G., Davis, F. D., & Davis, G. B. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.Google Scholar
  8. 8.
    ITU-T Recommendation E.800 (08/94). Terms and definitions related to quality of service and network performance including dependability.Google Scholar
  9. 9.
    Wu, Y., Tao, Y., & Yang, P. (2007). Using UTAUT to explore the behavior of 3G mobile communication users. In Proceedings of the international conference on industrial engineering and engineering management (IEEM) (pp. 199–203). Singapore.Google Scholar
  10. 10.
    Doney, P. M., Cannon, J. P., & Mullen, M. R. (1998). Understanding the influence of national culture on the development of trust. Academy of Management Review, 23, 601–620.Google Scholar
  11. 11.
    Taylor, V., & Whittier, N. (1995). Analytical approaches to social movement culture: The culture of the women’s movement. In H. Johnston & B. Klandermans (Eds.), Social movements and culture (pp. 163–187). Minneapolis: University of Minnesota Press.Google Scholar
  12. 12.
    Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations (2nd ed.). Thousand Oaks, CA: SAGE Publications.Google Scholar
  13. 13.
    Lim, K., Leung, K., Sia, C. L., & Lee, M. (2004). Is e-commerce boundary-less? Effects of individualism-collectivism and uncertainty avoidance on internet shopping. Journal of International Business Studies, 35, 545–559.CrossRefGoogle Scholar
  14. 14.
    Cyr, D., & Trevor-Smith, H. (2004). Localization of web design: An empirical comparison of German, Japanese, and US website characteristics. Journal of the American Society for Information Science and Technology, 55(13), 1199–1208.CrossRefGoogle Scholar
  15. 15.
    Asano, Y., Yonemura, S., Hayashi, A., & Hashimoto, R. (2011). ICT service design for senior citizens based on aging characteristics. NTT Technical Review, 9(9), 1–5.Google Scholar
  16. 16.
    Hanson, V. L. (2009). Age and web access: The next generation. In Proceedings of the international cross-disciplinary conference on web accessibility (W4A) (pp. 7–15). Madrid, Spain.Google Scholar
  17. 17.
    Kovalchik, S., Camerer, C. F., Grether, D. M., Plott, C. R., & Allman, J. M. (2005). Aging and decision making: A comparison between neurologically healthy elderly and young individuals. Journal of Economic Behavior and Organization, 58(1), 79–94.CrossRefGoogle Scholar
  18. 18.
    Bhat, S., Bevans, M., & Sengupta, S. (2002). Measuring users’ web activity to evaluate and enhance advertising effectiveness. Journal of Advertising, 31(3), 97–106.Google Scholar
  19. 19.
    Friedman-Berg, F., Allendoerfer, K., & Deshmukh, A. (2009). Voice over internet protocol: Speech intelligibility assessment (DOT/FAA/TC-TN-09/04). Atlantic City International Airport, NJ: Federal Aviation Administration William J. Hughes Technical Center.Google Scholar
  20. 20.
    Schmandt, C., Kim, J., Lee, K., Vallejo, G., & Ackerman, M. (2002). Mediated voice communication via mobile IP. In Proceedings of the 15th annual ACM symposium on user interface software and technology (UIST) (pp. 141–150). New York, USA.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Requirements Engineering Laboratory, School of Information TechnologyKing Mongkut’s University of Technology ThonburiBangkokThailand

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