LDR | | 00000nam u2200205 4500 |
001 | | 000000431517 |
005 | | 20200224102132 |
008 | | 200131s2019 ||||||||||||||||| ||eng d |
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▼a 9781085690164 |
035 | |
▼a (MiAaPQ)AAI13904892 |
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▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
082 | 0 |
▼a 658 |
100 | 1 |
▼a Liang, Chen. |
245 | 10 |
▼a IT-Enabled Monitoring in the Gig Economy. |
260 | |
▼a [S.l.]:
▼b Arizona State University.,
▼c 2019. |
260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
300 | |
▼a 210 p. |
500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: A. |
500 | |
▼a Advisor: Gu, Bin |
502 | 1 |
▼a Thesis (Ph.D.)--Arizona State University, 2019. |
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▼a This item must not be sold to any third party vendors. |
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▼a This item must not be added to any third party search indexes. |
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▼a 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 reputation information. In line with this, monitoring can lower the entry barrier for inexperienced workers on platforms. In the second chapter, I investigate if there is home bias for local workers when employers make the hiring decisions. I further show the existence of home bias from employers and it is primarily driven by statistical inference instead of personal "taste". In the last chapter, I examine if females tend to have a stronger avoidance of monitoring than males. With the combination of the observational data and experimental data, I find that there is a gender difference in avoidance of monitoring and the introduction of the monitoring system increases the gender wage gap due to genders differences in such willingness-to-pay for the avoidance of monitoring. These three studies jointly contribute to the literature on the online platforms, gig economy and agency theory by elucidating the critical role of IT-enabled monitoring. |
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▼a School code: 0010. |
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▼a Business administration. |
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▼a 0310 |
710 | 20 |
▼a Arizona State University.
▼b Business Administration. |
773 | 0 |
▼t Dissertations Abstracts International
▼g 81-04A. |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0010 |
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▼a Ph.D. |
792 | |
▼a 2019 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15492572
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
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▼a 202002
▼f 2020 |
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▼a ***1008102 |
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▼a E-BOOK |