Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
9-2016
Abstract
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.
Keywords
Crowd-sourcing, context-aware, empirical study, user behaviour
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp; Heidelberg; Germany; 2016 September 12-16
First Page
392
Last Page
402
ISBN
9781450344616
Identifier
10.1145/2971648.2971690
Publisher
ACM
City or Country
New York
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/2971648.2971690