Dark Patterns in Online Shopping: of Sneaky Tricks, Perceived Annoyance and Respective Brand Trust | SpringerLink
Skip to main content

Dark Patterns in Online Shopping: of Sneaky Tricks, Perceived Annoyance and Respective Brand Trust

  • Conference paper
  • First Online:
HCI in Business, Government and Organizations (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12783))

Included in the following conference series:

Abstract

Dark patterns utilize interface elements to trick users into performing unwanted actions. Online shopping websites often employ these manipulative mechanisms so as to increase their potential customer base, to boost their sales, or to optimize their advertising efforts. Although dark patterns are often successful, they clearly inhibit positive user experiences. Particularly, with respect to customers’ perceived annoyance and trust put into a given brand, they may have negative effects. To investigate respective connections between the use of dark patterns, users’ perceived level of annoyance and their expressed brand trust, we conducted an experiment-based survey. We implemented two versions of a fictitious online shop; i.e. one which used five different types of dark patterns and a similar one without such manipulative user interface elements. A total of \(n=204\) participants were then forwarded to one of the two shops (approx. 2/3 to the shop which used the dark patterns) and asked to buy a specific product. Subsequently, we measured participants’ perceived annoyance level, their expressed brand trust and their affinity for technology. Results show a higher level of perceived annoyance with those who used the dark pattern version of the online shop. Also, we found a significant connection between perceived annoyance and participants’ expressed brand trust. A connection between participants’ affinity for technology and their ability to recognize and consequently counter dark patterns, however, is not supported by our data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 11439
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 14299
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    Online: https://darkpatterns.org [accessed: November 2nd 2020].

  2. 2.

    Online: https://www.pewresearch.org/fact-tank/2019/01/17/where-millennials-end-and-generation-z-begins/ [accessed: February 12th 2021].

References

  1. Alexander, C.: A Pattern Language: Towns, Buildings, Construction. Oxford University Press, Oxford (1977)

    Google Scholar 

  2. Bösch, C., Erb, B., Kargl, F., Kopp, H., Pfattheicher, S.: Tales from the dark side: Privacy dark strategies and privacy dark patterns. In: Proceedings on Privacy Enhancing Technologies, vol. 2016, no. 4, pp. 237–254 (2016)

    Google Scholar 

  3. Chromik, M., Eiband, M., Völkel, S.T., Buschek, D.: Dark patterns of explainability, transparency, and user control for intelligent systems. In: IUI Workshops, vol. 2327 (2019)

    Google Scholar 

  4. Delgado-Ballester, E., Munuera-Aleman, J.L., Yague-Guillen, M.J.: Development and validation of a brand trust scale. Int. J. Mark. Res. 45(1), 35–54 (2003)

    Google Scholar 

  5. Di Geronimo, L., Braz, L., Fregnan, E., Palomba, F., Bacchelli, A.: UI dark patterns and where to find them: a study on mobile applications and user perception. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–14 (2020)

    Google Scholar 

  6. Franke, T., Attig, C., Wessel, D.: A personal resource for technology interaction: development and validation of the affinity for technology interaction (ATI) scale. Int. J. Human-Comput. Interact. 35(6), 456–467 (2019)

    Article  Google Scholar 

  7. Friedman, B.: Value-sensitive design. Interactions 3(6), 16–23 (1996)

    Article  Google Scholar 

  8. Friedman, B., Hendry, D.G.: Value Sensitive Design: Shaping Technology with Moral Imagination. MIT Press, Cambridge (2019)

    Book  Google Scholar 

  9. Gamma, E.: Design Patterns: Elements of Reusable Object-oriented Software. Pearson Education India, Chennai (1995)

    Google Scholar 

  10. Gray, C.M., Kou, Y., Battles, B., Hoggatt, J., Toombs, A.L.: The dark (patterns) side of UX design. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–14 (2018)

    Google Scholar 

  11. Jones, V., Jo, J., Martin, P.: Future schools and how technology can be used to support millennial and generation-z students. In: ICUT 2007 (Proc. B), 1st International Conference on Ubiquitous Information Technology, pp. 886–891. Citeseer (2007)

    Google Scholar 

  12. Lewis, C.: Irresistible Apps: Motivational Design Patterns for Apps, Games, and Web-Based Communities. Springer, Heidelberg (2014). https://doi.org/10.1007/978-1-4302-6422-4

    Book  Google Scholar 

  13. Mohan, J., Wasserman, M., Chidambaram, V.: Analyzing GDPR compliance through the lens of privacy policy. In: Gadepally, V., et al. (eds.) DMAH/Poly -2019. LNCS, vol. 11721, pp. 82–95. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33752-0_6

    Chapter  Google Scholar 

  14. Narayanan, A., Mathur, A., Chetty, M., Kshirsagar, M.: Dark patterns: past, present, and future. Queue 18(2), 67–92 (2020)

    Article  Google Scholar 

  15. Nouwens, M., Liccardi, I., Veale, M., Karger, D., Kagal, L.: Dark patterns after the GDPR: scraping consent pop-ups and demonstrating their influence. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–13 (2020)

    Google Scholar 

  16. Prensky, M.: Digital natives, digital immigrants part 1. Horizon 9(5), 1–6 (2001). https://doi.org/10.1108/10748120110424816

    Article  Google Scholar 

  17. Shilton, K.: Values levers: building ethics into design. Sci. Technol. Human Values 38(3), 374–397 (2013)

    Article  Google Scholar 

  18. Sommerer, C., Mignonneau, L.: The Art and Science of Interface and Interaction Design (Vol. 1), vol. 141. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-79870-5

    Book  Google Scholar 

  19. European Union: Regulation (EU) no 2016/679 of the European parliament and of the council n the protection of natural persons with regard to the processing of personal data and on the free movement of such data (general data protection regulation – GDPR). OJ (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Stephan Schlögl .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Voigt, C., Schlögl, S., Groth, A. (2021). Dark Patterns in Online Shopping: of Sneaky Tricks, Perceived Annoyance and Respective Brand Trust. In: Nah, F.FH., Siau, K. (eds) HCI in Business, Government and Organizations. HCII 2021. Lecture Notes in Computer Science(), vol 12783. Springer, Cham. https://doi.org/10.1007/978-3-030-77750-0_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-77750-0_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77749-4

  • Online ISBN: 978-3-030-77750-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics