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IT-enabled Monitoring in the Gig Economy

Abstract Two-sided online platforms are typically plagued by hidden information (adverse selection) and hidden actions (moral hazard), limiting market efficiency. Under the context of the increasingly popular online labor contracting platforms, this dissertation investigates whether and how IT-enabled monitoring systems can mitigate moral hazard and reshape the labor demand and supply by providing detailed information about workers’ effort. In the first chapter, I propose and demonstrate that monitoring records can substitute for reputation signals such that they attract more qualified inexperienced workers to enter the marketplace. Specifically, only the effort-related reputation information is substituted by monitoring but the capability-related r... (more)
Created Date 2019
Contributor Liang, Chen (Author) / Gu, Bin (Advisor) / Hong, Yili (Advisor) / Chen, Peiyu (Committee member) / Arizona State University (Publisher)
Subject Business administration / entry barrier / gig economy / monitoring / platforms / reputation
Type Doctoral Dissertation
Extent 209 pages
Language English
Note Doctoral Dissertation Business Administration 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis