Opportunistic Solvers Identification of a Crowdsourcing Innovation Platform

DOI

10.2991/assehr.k.200428.039How to use a DOI?

Keywords

crowdsourcing innovation, opportunistic solvers, identification system, PCA-BP neural network

Abstract

Crowdsourcing innovation is characterized by loose organizational structures, free will of participants, strong innovation goals and information asymmetry, which can easily induce solvers’ opportunistic behaviors, such as fraud, intellectual property theft, free-riding and so on. In order to create an attractive and supportive platform environment, identifying and avoiding opportunistic solvers is essential. In this study, a four-dimensional opportunistic solvers’ identification system, including the work ability, the reputation level, the service level and the historical transaction level, is constructed. Then, the opportunistic solvers’ identification model was proposed based on the PCA-BP neural network. The data is based on www.zbj.com, and taken into empirical research to verify the feasibility and effectiveness of the identification model.

Copyright

© 2020, 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  - Jintong Hua
AU  - Qingliang Meng
PY  - 2020
DA  - 2020/05/01
TI  - Opportunistic Solvers Identification of a Crowdsourcing Innovation Platform
BT  - Proceedings of the 6th International Conference on Humanities and Social Science Research (ICHSSR 2020)
PB  - Atlantis Press
SP  - 169
EP  - 173
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200428.039
DO  - 10.2991/assehr.k.200428.039
ID  - Hua2020
ER  -