The document discusses the measurement of trust within the sharing economy, highlighting that two-thirds of American shoppers lack trust in retailers with personal information. It explores the roles of consumers as both users and service providers and the impact of online ratings on trust. Additionally, it emphasizes the importance of understanding risk attitudes and trust for recruiting participants in service markets characterized by dynamic consumer-provider relationships.

1. TrustA NEW APPROACH
TO MEASURE IT IN
THE SHARING
ECONOMY
Paolo Parigi
Lead Trust Scientist, Uber
Adjunct Professor Civil and Environmental
Engineering, Stanford University
Jessica Santana
PhD Candidate, Stanford University

3. Another study shows that nearly 2/3 of American
shoppers do not trust retailers with their payment
and personal information
67%
33%
0% 18% 35% 53% 70% 88%
Retailers
Distrust Trust
Level of trust Americans have in Banks, Tech Firms, and Retailers

8. One "slice" represents
one month.
There are two slices
per second
This movie depicts the real-time evolution of the local friendship network of
CouchSurfers in San Francisco, from January 2003.
Sharing economy
platforms like Uber
or Airbnb are social
spaces where users
interact and build
relationships.
Red ties are
between people
that met in a
CouchSurfing
event.
Blue ties are pre-
existing ties.

9. In the sharing economy,
consumers can play two roles
interchangeably:
Users and Service Providers
How do you measure trust
between them?
What is the impact of ratings
on trust?

10. A New Methodology for
Measuring Sentiments
for a New Era
“Engineering Trust” Abrahao, Parigi, Gupta, and Cook. 2017. PNAS
“Online Field Experiments” Parigi, Santana, and Cook. 2017. SPQ

11. Online
Experiment
Mechanisms
Causation
Precision
Field
Experiment
Behavior
Context
Complexity
Online
Field
Experiment

15. PRE-TEST
TREATMENT
POST-TEST
Platform Data

16. PRE-TEST
TREATMENT
POST-TEST
Platform Data
Males,
Less active
hosts

17. Some Findings
Satisfaction
RiskAversion
Frequency
RiskAversion
“Risk Aversion and Engagement in the Sharing Economy,” Santana and Parigi. 2015. Games.

18. When does it make sense to use OFE?
Not standardized work force:
• Customers can play both roles
of consumers and service
providers
• The workforce is made of
independent contractors
Big data is used for scaling
non customizable
experiences:
• Matching between consumers
and service providers
• Optimization
Beliefs and opinions make
the market segment
extremely fluid and dynamic
• Viral diffusion of social media
content that swings adoption of
the service
• Public opinion can force
regulators to intervene to restrict
/ enable access

19. An Example of Using OFE for Studying Participation
Markets that have some of the
characteristics previously described
require active recruitment of
consumers.
For example, suppose we want to
know the offering of services at
particular times of the day
(e.g. night) or particular areas
of a city (e.g. areas in
gentrifying neighborhoods)
Knowing risk attitudes of the
service providers becomes crucial.
Measuring trust / risk attitudes is
key for understanding recruitment

20. Produced by Urban Design + Media
Tymn Urban 2017