Designing for Trust: A Behavioral Framework for Sharing Economy Platforms

TLDR: This work conducts an online experiment with 4,499 Airbnb users in the form of an investment game in order to capture users’ propensity to trust other users on Airbnb, and generates both explanatory and predictive models of trust propensity, which can be used to measure trust propensity in sharing economy platforms via online and offline signals.

Abstract: Trust is a fundamental prerequisite in the growth and sustainability of sharing economy platforms. Many of such platforms rely on actions that require trust to take place, such as entering a stranger’s car or sleeping at a stranger’s place. For this reason, understanding, measuring, and tracking trust can be of great benefit to such platforms, enabling them to identify trust behaviors, both online and offline, and identify groups which may benefit from trust-building interventions. In this work, we present the design and evaluation of a behavioral framework to measure a user’s propensity to trust others on Airbnb. We conducted an online experiment with 4,499 Airbnb users in the form of an investment game in order to capture users’ propensity to trust other users on Airbnb. Then, we used the experimental data to generate both explanatory and predictive models of trust propensity. Our contribution is a framework that can be used to measure trust propensity in sharing economy platforms via online and offline signals. We discuss which affordances need to be in place so that sharing economy platforms can get signals of trust, in addition to how such a framework can be used to inform design around trust in the short and long term.