English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Contact tracing apps have become one of the main approaches to control andslow down the spread of COVID-19 and ease up lockdown measures. While theseapps can be very effective in stopping the transmission chain and saving lives,their adoption remains under the expected critical mass. The public debateabout contact tracing apps emphasizes general privacy reservations and isconducted at an expert level, but lacks the user perspective related to actualdesigns. To address this gap, we explore user preferences for contact tracingapps using market research techniques, and specifically conjoint analysis. Ourmain contributions are empirical insights into individual and grouppreferences, as well as insights for prescriptive design. While our resultsconfirm the privacy-preserving design of most European contact tracing apps,they also provide a more nuanced understanding of acceptable features. Based onmarket simulation and variation analysis, we conclude that addinggoal-congruent features will play an important role in fostering mass adoption.

Towards Mass Adoption of Contact Tracing Apps -- Learning from Users' Preferences to Improve App Design