Website Affective Evaluation: Analysis of Differences in Evaluations Result by Data Population

  • Anitawati Mohd Lokman
  • Afdallyna Fathiyah Harun
  • Nor Laila Md. Noor
  • Mitsuo Nagamachi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5619)


Studies involving consumer studies have suggested different mechanisms of subject selections. The paper elaborates results of subject’s responses by the methodology adopted from Kansei Engineering. In the research, evaluation of subject’s Kansei towards website interface design was performed, targeting to measure affective quality in website design. Principal Component Analysis was performed to identify semantic structure of Kansei Words. The analyses were based on the average of evaluation results obtained from subjects. Results of PC Loadings were analyzed to see differences of determinants by size of data population. It is evident from the study that population size does not affect determinants of affective web interface design. The study makes decent contribution in determining appropriate population size in designing research instruments for future studies involving website affective evaluations.


Consumer science website affective evaluation Kansei Population size Principal Component Analysis 


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  1. 1.
    Nielsen, J.: Why You Only Need to Test With 5 Users (2000), (retrieved February 2, 2007)
  2. 2.
    Gilbert, J.E., Williams, A., Seals, C.D.: Clustering for Usability Participant Selection. Journal of Usability Studies 3(1), 40–52 (2007)Google Scholar
  3. 3.
    Faulkner, L.: Beyond The Five-User Assumption: Benefits Of Increased Sample Sizes In Usability Testing. Behavior Research Methods, Instruments, & Computers 35(3), 379–383 (2003)CrossRefGoogle Scholar
  4. 4.
    Landesman, L., Perfetti, C.: Eight is not Enough (2001) User Interface Engineering Website, (retrieved September 30, 2008)
  5. 5.
    Arteology: Sampling, (retrieved September 1, 2008)
  6. 6.
    Rosenstein, A.: Managing Risk with Usability Testing, Classic System Solutions (2001), (retrieved September 1, 2008)
  7. 7.
    Li, N., Zhang, P.: Consumer Online Shopping Behavior, in Customer Relationship Management. In: Fjermestad, J., Romano, N. (eds.) Zwass, V (editor-in-chief). Series of Advances in Management Information Systems. M.E. Sharpe Publisher (2005)Google Scholar
  8. 8.
    Tractinsky, N., Katz, A.S., Ikar, D.: What is Beautiful is Usable. Interacting with Computers 13, 127–145 (2000)CrossRefGoogle Scholar
  9. 9.
    Norman, D.A.: Emotional Design: Attractive Things Work Better in Interactions: New Visions of Human-Computer Interaction IX, 36–42 (2002)Google Scholar
  10. 10.
    Buchanan, R.: Good Design in the Digital Age. AIGA Journal of Design for the Network Economy 1(1), 1–5 (2000)Google Scholar
  11. 11.
    Leary, M.R.: Introduction to Behavioural Research Methods, 4th edn. Pearson, London (2008)Google Scholar
  12. 12.
    Hammersley, M., Atkinson, P.: Ethnography: Principles in practice. Tavistock Publications, London (1983)Google Scholar
  13. 13.
    Ward-Schofield, J.: Increasing the generalisability of qualitative research. In: Hammersley, M. (ed.) Social research: Philosophy, politics & practice, pp. 200–225. Open University/Sage, London (1993)Google Scholar
  14. 14.
    Anitawati, M.L., Nor Laila, M.N.: Kansei Engineering: A Study on Perception of Online Clothing Websites. In: Proceedings of the 10th International Conference on Quality Management and Operation Development 2008 (QMOD 2007). Linköping University Electronic Press, Sweden (2007)Google Scholar
  15. 15.
    Nagamachi, M.: The Story of Kansei Engineering. Japanese Standards Association 6, Tokyo (2003) (in Japanese)Google Scholar
  16. 16.
    Nagasawa, S.: Present State of Kansei Engineering in Japan. In: 2004 IEEE International Conference, vol. 1, pp. 333–338 (2004)Google Scholar
  17. 17.
    Horrigan, J.B.: Online Shopping. PEW Internet and American Life Project (2008), (Retrieved August 20)
  18. 18.
    Freeman, J., Lessiter1, J., Pugh1, K., Keogh, E.: When presence and emotion are related, and when they are not. In: Proceedings of PRESENCE 2005, pp. 213–219 (2005)Google Scholar
  19. 19.
    Freedman, R., Taub, S., Silver, J.F., Pell, E., Rowe, J., Chiri, G.: Sampling: A Practical Guide for Quality Management in Home & Community-Based Waiver Programs. Thomson & Medstat (2006)Google Scholar

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© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Anitawati Mohd Lokman
    • 1
  • Afdallyna Fathiyah Harun
    • 1
  • Nor Laila Md. Noor
    • 1
  • Mitsuo Nagamachi
    • 2
  1. 1.Faculty of Information Technology and Quantitative SciencesUniversity Teknologi MARAShah AlamMalaysia
  2. 2.International Kansei Design InstituteJapan

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