Home » Eye-Tracking Analysis for User Interface Design of Shopping Mobile Web Application

Eye-Tracking Analysis for User Interface Design of Shopping Mobile Web Application

Advertisements

Lau King Lieng

Faculty of Computing and Informatics,
Universiti Malaysia Sabah (UMS),
88400 Kota Kinabalu, Sabah,
Malaysia
lau.kinglieng@yahoo.com

Aslina Baharum

Senior Lecturer
Faculty of Computing and Informatics,
Universiti Malaysia Sabah (UMS),
88400 Kota Kinabalu, Sabah,
Malaysia
aslina@ums.edu.my

Abstract

Nowadays, the use of mobile phone has brought great conveniences and contributions to society in daily life. Online shopping takes a large portion in their online activities, due to this, the availability and the adequacy assessment in this situation are becoming increasingly requires. With the help of eye-tracking technology, it can be easy to study how users interact with the visual elements within the mobile applications. Currently, mobile app developers are facing the issue of limited guideline for proper mobile app user interface design. Moreover, the bad interaction between a user and interface design could lead to failure of the mobile app. At the same time, different users’ expectation among users in online shopping could be affected by gender, thus, further study is needed. The objective of this paper is to use eye-tracking technology for user interface design of shopping mobile web application. This paper will present the eye-tracking result of existing design guideline, meanwhile, the result obtained from the eye-tracking analysis will be used to develop a visualization pattern of user interface guideline. The visualization pattern of user interface guideline that develops at the end of this research may satisfy both genders.

Keywords

Eye-tracking;
interface design guideline;
Mental model;
Online shopping;
Shopping mobile web app.

download pdf

Cited as

Lau King Lieng and Aslina Baharum, “Eye-Tracking Analysis for User Interface Design of Shopping Mobile Web Application”, International Journal of Advanced Engineering and Management, Vol. 2, No. 12, pp. 287-301, 2017.

DOI: https://doi.org/10.24999/IJOAEM/02120061

References

  1. Vala, R, Jasek, R, & Malanik, D. (2014) Design of a Software Tool for Mobile Application User Mental Models Collection and Visualization. Applied Mathematics, Computational Science and Engineering, 133-141.
  2. Gagandeep, N. & Gopal, R. (2013). A study of Factors Affecting on Online Shopping Behavior of Consumers. International Journal of Scientific and Research Publications,3(6),1-4.
  3. Lina, Z., Liwei, D. & Dongsong, Z. (2007). Online Shopping Acceptance Model – A Critical Survey of Consumer Factors in Online Shopping. Journal of Electronic Commerce Research, 8(1),41-62.
  4. OFT (2007). “Internet Shopping”, An OFT Market Study. Available at: http://webarchive.nationalarchives.gov.uk/20140402142426/http:/www.oft.gov.uk/shared_oft/reports/consumer_protection/oft921.pdf. Accessed on 13 January 2017.
  5. Dennis, C., Morgan, A., Wright, L. T., & Jayawardhena, C. (2010). The influences of social e-shopping in enhancing young women’s online shopping behavior. Journal of Customer Behaviour, 9(2), 151–174.
  6. Hoeger, I. (2006). Shopping-Differences between Genders or Differences in Interests?.201-254.
  7. Rodgers, S. & Harris, M. (2003). “Gender and E-Commerce: An Exploratory Study,” Journal of Advertising Research 43, No. 3: 322-330.
  8. Awad, N.F. & Ragowsky, A. (2008). ‘Establishing Trust in Electronic Commerce Through Online Word of Mouth: An Examination Across Genders’, Journal of Management Information Systems / Spring 2008, Vol. 24, No. 4.
  9. Sebastianelli, R., Tamimi, N., & Rajan, M. (2008). Perceived quality of online shopping: Does gender make a difference? Journal of Internet Commerce, 7(4), 455-469.
  10. Doolin, B., Dillon, S., Thompson, F. & Corner, J.L. (2005). Perceived Risk, the Internet Shopping Experience and Online Purchasing Behaviour: A New Zealand Perspective, 2(1), 324-345.
  11. Cyr, D., & Bonanni, C. (2005). Gender and website design in e-business. International Journal Electronic Business, 3(6), 565-582.
  12. Seock, Y. K., & Bailey, L. R. (2008). The influence of college students’ shopping orientations and gender differences on online information searches and purchase behaviours. International Journal of Consumer Studies, 32, 113-121.
  13. Flavian, B. C., Gurrea, R., S., & Orus, S. C. (2011). Gender differences regarding the product’s online visual representation: Impact on satisfaction and purchase intention. ESIC Market Economic and Business Journal, Vol. 138 (pp. 145-170).
  14. Ward, M.R., & Lee,M.J. (2000). Internet shopping, consumer search and product branding. Journal of Product & Brand Management, 9(1),6-20.
  15. Brown, J., & Dant, R. (2014). The Role of E-Commerce in Multi-Channel Marketing Strategy. In: Martinez-Lopez, F. (eds.) Handbook of Strategic E-Business Management, Springer, Verlag. (pp. 467–487).
  16. Internet Retailer. (2011). E-commerce sales rise 14.8% in 2010. Available at: http://www.internetretailer.com/2011/02/17/e-commerce-sales-rise-148-2010. Accessed on 12 November 2016.
  17. We are social. (2012). How People Spend Their Time Online. Available at: http://wearesocial.com/uk/blog/2012/05/people-spend-time-online. Accessed on 13 November 2016.
  18. Venkata,N.I., Divya, D.K., Taeghyun,K., & Manikanta, I. (2014). Factors Influencing Quality of Mobile Apps: Role OF Mobile APP Development Life Cycle. International Journal of Software Engineering & Applications, 5(5),115-3.
  19. Chui, Y.W., Chee, W.K., Kimberly, C. (2012). Interface design practice and education towards mobile apps development. Procedia Social and Behavioral Sciences, 51,698-702.
  20. Nurul-Hidayah, M.Z., Fariza-Hanis, A.R., Azizah, J. & Mohd-Firdaus, Z. (2011). Eye Tracking in Educational Games Environment: Evaluating User Interface Design through Eye Tracking Patterns, in Proceedings of the Second International Conference on Visual Informatics: Sustaining Research and Innovations – Volume Part II, ser. IVIC’11.Berlin, Heidelberg: Springer-Verlag. (pp. 64–73).
  21. Velasquez, J.-D. (2013). Combining eye-tracking technologies with web usage mining for identifying Website Keyobjects, in Engineering Applications of Artificial Intelligence No.26 (pp. 1469–1478).
  22. Tullis, T., Siegel, M., & Sun, E. (2009). Are people drawn to faces on webpages? In Proceedings of the 27th International Conference Extended Abstracts on Human Factors in Computing Systems.
  23. Djamasbi, S., Siegel, M., & Tullis, T. (2014). Can fixation on main images predict visual appeal of homepages? Proceedings of the Forty-Seventh Annual Hawaii International Conference on System Sciences, 371-375.
  24. Eraslan, S., & Yesilada, Y. (2015). Patterns in Eyetracking Scanpaths and the Affecting Factors. Journal of Web Engineering – Special Issue on ”Engineering the Web for users, developers and the crowd”, 14(4&5), 363-385.
  25. Underwood, G., Humphrey, K., & Foulsham, T. (2008). Knowledge-Based Patterns of Remembering: Eye Movement Scanpaths Reflect Domain Experience. Lecture Notes in Computer Science, 5298, 125–144.
  26. Pan, B., Hembrooke, H. A., Gay, G. K., Granka, L. A., Feusner, M. K., & Newman, J. K. (2004). The determinants of web page viewing behavior: an eye-tracking study. In Proceedings of the 2004 symposium on Eye Tracking Research and Applications. ACM, New York, NY, USA, 147–154.
  27. Akpinar, E., Yesilada, Y. (2015). “Old Habits Die Hard!”: Eyetracking Based Experiential Transcoding: A Study with Mobile Users. In Proceedings of the 12th Web for All Conference, ACM, New York, NY, USA, W4A ’15, 12:1–12:5.
  28. Eger, N., L. J. Ball, R. Stevens & J. Dodd. (2007). Cueing retrospective verbal reports in usability testing through eye-movement replay, hlm. 129-137.
  29. Rama P., & Baccino T. (2010).Eye fixation-related potentials (EFRPs) during object identification. Visual Neurosci. 27, 187–192.
  30. Rayner, K. (2009). Eye movements and attention in reading, scene perception, and visual search. Quarterly Journal of Experimental Psychology, 62, 1457–1506.
  31. Faulkner, L. (2003). Beyond the five-user assumption: Benefits of increased sample sizes in usability testing. Behaviour Research Methods, Instruments, & Computers 35(3), 379–383.
  32. Pernice, K., & Nielsen, J. (2009). How to Conduct Eyetracking Studies. Tech. rep., Nielsen Norman Group. JANOSCHKA, A. 2004. Web Advertising: New Forms of Communication on the Internet. John Benjamins Publishing Company.
  33. Hwang, W., & Salvendy, G. (2010). Number of People Required for Usability Evaluation: The 10±2 rule. Communications of the ACM 53, 5 (May), 130–133.
  34. Alroobaea, R., & Mayhew, P. (2014). How many participants are really enough for usability studies? In Science and Information Conference (SAI), 2014, 48–56.
  35. Manhartsberger, M. & Zellhofer, N. (2005). Eye tracking in usability research: What users really see. OCG Publication, 198, 141-152.
  36. Johansen, S.A and Hansen, J.P. (2006). Do We Need Eye Trackers to Tell Where people Look?. Montreal Quebec, Canada. ACM 1-59593-298-4/06/0004.
  37. Ellis, K. (2009). Eye Tracking Metrics for Workload Estimation in    flight    Deck    Operation, Thesis, University of Iowa.
  38. Bergstrom, J.R. and Schall, A. (2014). Eye Tracking in User Experience Design. Morgan Kaufmann, Burlington.
  39. Bruggink, J. (2013). More than 6 in 10 people wear glasses or contact lenses. https://www.cbs.nl/en-gb/news/2013/38/more-than-6-in-10-people-wear-glasses-or-contact-lenses. Accessed on 17 July 2017
  40. Rosler, A. (2012). Using the Tobii Mobile Device Stand in Usability Testing on Mobile Devices. Tobii Technology in the United States.
  41. Gatsou, C., Politis, A. Zevgolis, D. (2012). The importance of Mobile Interface Icons on User Interaction. International Journal of Computer Science and Applications, 9(3), 92-107.
  42. Hyrskykari, A., Ovaska, S., Majaranta, P., Räihä, K‐ and Lehtinen, M. (2008). Gaze path stimulation in retrospective think aloud. Journal of Eye Movement Research, 2(4), 1‐18.steakhouse-1
Advertisements
%d bloggers like this: