Crowd-sourcing Task Research Based on Big Data--Math Model of Pricing Done

DOI

10.2991/ammsa-18.2018.20How to use a DOI?

Keywords

crowd sourcing; reverse pricing method

Abstract

Aiming at practical situations, multiple tasks may be because the location is relatively concentrated, leading users will choose, is a consideration of these tasks jointly issued together package. In such case, the pricing model of how to modify the front, to the final completion of the mission and what's the effect? In two under the premise of the model taken together, the task Crowd-sourcing issued to members of the APP program, combined with the Crowd-sourcing mode of operation of the process, the use of reverse guide price method, get a new pricing method, Shenzhen Baoan District City, Shenzhen Luohu District City, Nanhai District of Foshan city in the more populous intensive article using the above Crowd sourcing pricing at In the less expensive areas, the pricing game between members and task providers is adopted.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chenghui Yang
AU  - Ning Cai
AU  - Xing Peng
AU  - Zhongfu Luo
AU  - Zeyi Liu
PY  - 2018/05
DA  - 2018/05
TI  - Crowd-sourcing Task Research Based on Big Data--Math Model of Pricing Done
BT  - Proceedings of the 2018 2nd International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2018)
PB  - Atlantis Press
SP  - 92
EP  - 95
SN  - 1951-6851
UR  - https://doi.org/10.2991/ammsa-18.2018.20
DO  - 10.2991/ammsa-18.2018.20
ID  - Yang2018/05
ER  -