Browsing by Subject "sharing economy"

Now showing 1 - 2 of 2
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    Measuring Psychological Effects of Peer-to-Peer Reputation Systems Involving In-Person Exchanges
    (2019-07) Yousef, Mark
    Reputation systems such as those used by peer-to-peer services have proven significant in helping companies better understand and manage their users. Seemingly the new credit scores for the digital economy, these personal rating systems have unexplored consequences on human psyche. Using a case study of Uber passengers and drivers, this study examines stress and control levels associated with personal rating scores. We found that while drivers indicated more difficult experiences in response to the control of their scores, passengers had issues with distress in relation to factors commonly associated with bias, such as age and ethnicity. Both groups exhibited lower perceptions of distress the more times they had used Uber. Overall, the use of peer-to-peer reputation systems can be improved to provide users a higher level of control and lower distress in response to ratings.
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    Understanding Geographic Bias in Crowd Systems
    (2017-12) Thebault-Spieker, Jacob
    Crowd platforms are increasingly geographic, from the sharing economy to peer production systems like OpenStreetMap. Unfortunately, this means that existing geographic advantages or disadvantages (e.g. by income, urbanness, or race) may also impact these crowd systems. This thesis focuses on two primary themes: (1) how these geographic advantages and disadvantages interact with crowd platform services, and (2) how people’s geographic behavior within these platforms may lead to these biases being reflected. The first chapter in my thesis finds that sharing economy services fare less well in low-income, non-white, and more suburban areas. This chapter introduces the spatial Durbin model to the field of HCI, and shows that geographic factors like distance, socioeconomic status and demographics inform where sharing economy workers provide service. The second chapter in my thesis provides focuses on people in peer production communities contribute geographic content. By considering peer production as a spatial interaction process, this study finds that some kinds of content tend to be produced much more locally than others. Finally, my third contribution focuses on individual contributor behavior, and shows geographic “born, not made” trends. People tend to be consistent in the places, and kinds of places (urban, and non-high poverty counties) they contribute. The findings of this third study help identify mechanisms for how geographic biases may come about. Looking forward, my work helps inform an exciting agenda of future work, including building systems that provide individual crowd members sufficient geographic context to counteract these worrying geographic biases.