TASKer: behavioral insights via campus-based experimental mobile crowd-sourcing
While mobile crowd-sourcing has become a game-changer for many urban operations, such as last mile logistics and municipal monitoring, we believe that the design of such crowdsourcing strategies must better accommodate the real-world behavioral preferences and characteristics of users. To provide a...
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Main Authors: | , , , , , , , , |
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Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2016
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Online Access: | https://ink.library.smu.edu.sg/sis_research/5389 https://ink.library.smu.edu.sg/context/sis_research/article/6393/viewcontent/TASKer__Behavioral_insights_via_campus_based_experimental_mobile.pdf |
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Institution: | Singapore Management University |
Language: | English |
Summary: | While mobile crowd-sourcing has become a game-changer for many urban operations, such as last mile logistics and municipal monitoring, we believe that the design of such crowdsourcing strategies must better accommodate the real-world behavioral preferences and characteristics of users. To provide a real-world testbed to study the impact of novel mobile crowd-sourcing strategies, we have designed, developed and experimented with a real-world mobile crowd-tasking platform on the SMU campus, called TA$Ker. We enhanced the TA$Ker platform to support several new features (e.g., task bundling, differential pricing and cheating analytics) and experimentally investigated these features via a two-month deployment of TA$Ker, involving 900 real users on the SMU campus who performed over 30,000 tasks. Our studies (i) show the benefits of bundling tasks as a combined package, (ii) reveal the effectiveness of differential pricing strategies and (iii) illustrate key aspects of cheating (false reporting) behavior observed among workers. |
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