Institute of Information Science, Academia Sinica



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Campus-Scale Mobile Crowdsourcing: Design, Deployment, and Behavioral Insights

  • LecturerProf. Shih-Fen Cheng (Singapore Management University)
    Host: Sheng-Wei Chen
  • Time2017-06-05 (Mon.) 10:00 – 12:00
  • LocationAuditorium 106 at IIS new Building

Mobile crowdsourcing markets are growing at an unprecedented rate with increasing number of smartphone users. Such platforms differ from their online counterparts in that they demand physical mobility and can benefit from smartphone processors and sensors for verification purposes. Despite the importance of such mobile crowdsourcing markets, little is known about the labor supply dynamics and mobility patterns of the users. Most important of all, we know little about what could potentially make mobile crowdsourcing more efficient and effective.

In this talk, I present TA$Ker, a real-world mobile crowdsourcing platform that allows us to empirically study various innovations in the area of mobile crowdsourcing. Our contributions in the field are two-fold: (a) We designed and developed TA$Ker, which is a platform that is capable of sensing daily routines from the collected mobility traces and generating personalized recommendations. (b) We use TA$Ker to conduct a series of real-world experiments over a period of two years, participated by more than 1,000 students, completing more than 100,000 tasks. Through these real-world experiments, we established that the centralized push-based approach is far superior to the decentralized pull-based approach. We also illustrate how innovative designs such as "task bundles", "differential pricing", and "peer collaborations" can help the mobile crowdsourcing platform to be even more effective.



Shih-Fen Cheng is an Associate Professor of Information Systems and Deputy Director of the Fujitsu-SMU Urban Computing and Engineering Corp Lab at the Singapore Management University. He received his Ph.D. degree in industrial and operations engineering from the University of Michigan, Ann Arbor, and B.S.E. degree in mechanical engineering from the National Taiwan University.

His research focuses on the modeling and optimization of complex systems in engineering and business domains. He is particularly interested in the application areas of transportation, computational markets, and human decision-making. He has regularly served as program committee members for premier AI conferences (e.g., AAMAS, IJCAI, AAAI) and has helped organized several major conferences. He is a member of INFORMS, AAAI, and IEEE, and serves as Area Editor for Electronic Commerce Research and Applications.