@inproceedings{BossauerNeiferStevensetal.2020,
  author    = {Paul Bossauer and Thomas Neifer and Gunnar Stevens and Christina Pakusch},
  title     = {Trust versus Privacy: Using Connected Car Data in Peer-to-Peer Carsharing},
  series = {CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, April 25–30, 2020, Honolulu, HI, USA},
  publisher = {Association for Computing Machinery},
  address   = {New York, NY, United States},
  isbn      = {978-1-4503-6708-0},
  doi       = {10.1145/3313831.3376555},
  pages     = {1 -- 13},
  year      = {2020},
  abstract  = {Trust is the lubricant of the sharing economy. This is true especially in peer-to-peer carsharing, in which one leaves a highly valuable good to a stranger in the hope of getting it back unscathed. Nowadays, ratings of other users are major mechanisms for establishing trust. To foster uptake of peer-to-peer carsharing, connected car technology opens new possibilities to support trust-building, e.g., by adding driving behavior statistics to users' profiles. However, collecting such data intrudes into rentees' privacy. To explore the tension between the need for trust and privacy demands, we conducted three focus group and eight individual interviews. Our results show that connected car technologies can increase trust for car owners and rentees not only before but also during and after rentals. The design of such systems must allow a differentiation between information in terms of type, the context, and the negotiability of information disclosure.},
  language  = {en}
}