Author(s):

  • Sherwani, Dara
  • Stumpf, Simone

Abstract:

With the growing number of systems that provide user-generated reviews come new forms of trust relationships. User trust in vendors can be mediated by trust in either reviews or reviewers, or possibly both. These new forms of trust relationships might be affected by barriers to trust such as uncertainty about offered services and anonymity of users, as well as biased reviews. While current work is dedicated towards investigating the influential factors on trust, this study undertakes a different approach. First, it investigates the influence of interface design on users’ assessment of trustworthiness. Second, it explores the way that interface design can affect users’ perception of trustworthy and untrustworthy reviews and reviewers, by signalling the influential factors on trust. Third, this study investigates the effect of users’ prior beliefs in the form of dispositional trust in the assessment of trustworthiness. To do so, an exploratory study gathering quantitative and qualitative data was conducted with 16 participants who interacted with a high-fidelity prototype. Our results show that users’ assessment of trustworthiness is influenced by interface elements that relate not only to the review, but also to the reviewer, implying that trust in reviews is mediated by trust in reviewers. Furthermore, users’ dispositional trust appears to affect the perceived trustworthiness of reviewers, especially because of elements relate to the reviewers’ background, which transfers onto the reviews. Our results have implications for researchers and designers to help users’ assessment of the trustworthiness of reviews and reviewers.

Document:

https://www.scienceopen.com/document?vid=12031ec3-f93a-4ffd-8276-b28ad02c80e1

References:
  1. Egger, F.N. (2001). Affective Design of E-Commerce User Interfaces: How to maximise perceived trustworthiness. CAHD: Conference on Affective Human Factors Design. ACM Press, New York, NY, pp. 317–324.
  2. Hsu, C.-J. (2008). Dominant Factors for Online Trust. International Conference on Cyberworlds, pp. 165–172. IEEE
  3. Kim, Y. et al. (2008). Building a web of trust without explicit trust ratings. 24th IEEE International Conference on Data Engineering Workshop, pp. 531–536. IEEE
  4. Ku, Y., Li, H., & Wu, F. (2012). Evaluation of Trustworthiness of Reviews in the Online Travel Community. IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications,pp. 1417–1422.IEEE
  5. Lazar, J. et al. (2010) Research Methods in Human-Computer Interaction. John Wiley & Sons Ltd. UK
  6. Lee, J., Park, D. & Han, I. (2008). The effect of negative online consumer reviews on product attitude: An information processing view. Electronic Commerce Research and Applications, 7, 3, 341–352.
  7. Liu, Y., Huang, X., An, A. & Yu, X. (2008). Modeling and Predicting the Helpfulness of Online Reviews. In: IEEE 8th International Conference on Data Mining, pp. 443–452. IEEE
  8. McKnight, D.H., Choudhury, V., & Kacmar, C. (2002). “Developing and Validating Trust Measures for E-Commerce: An Integrative Typology,” Information Systems Research, Vol.13, No.3, pp. 334-359.
  9. Riegelsberger, J., Sasse, M. A., & McCarthy, J. D. (2005). The mechanics of trust: A framework for research and design. International Journal of Human-Computer Studies, 62(3), pp. 381–422. Riegelsberger, J. & Sasse, M.A. (2003). Shiny happy people building trust? Photos on e-Commerce websites and consumer trust. In: CHI (pp. 121-128)
  10. Sasse, M. A. & Kirlappos, I. (2011). Familiarity Breeds Con-victims: Why We Need More Effective Trust Signaling. In Wakeman, I., Gudes, E., Jensen, C. D., Crampton, J. (Eds.).Trust Management V. Springer-Verlag New York Inc