Trust signals in the babysitting industry in the sharing economy

Author/Creator

Author/Creator ORCID

Date

2023-05

Type of Work

Department

University of Baltimore. Division of Science, Information Arts and Technologies

Program

University of Baltimore. Master of Science in Interaction Design and Information Architecture

Citation of Original Publication

Rights

Attribution-NonCommercial-NoDerivs 3.0 United States
This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by the University of Baltimore for non-commercial research and educational purposes.

Abstract

This thesis will explore the meaning of trust, trust propensity, trust signals/cues, and other trust builders. It will then relate how trust drives the sharing economy and is essential in the babysitting industry. It will then fill in the gaps found in the research by testing the trust cues of mutual friends and star ratings in the babysitting industry of the sharing economy. These trust cues were tested through two surveys. The results were analyzed using t-tests, ANOVA (Analysis of Variance), and post hoc tests. The findings showed that star ratings are a stronger immediate trust cue than written reviews and that mutual friends substantially impact hiring rates. It found that as the number of mutual friends increased, so did hiring rates. It also found that mutual friends seem to have more strength than star ratings and that the presence of mutual friends may affect users' willingness to pay.