EconPapers    
Economics at your fingertips  
 

How to Bid Success in Crowdsourcing Contest? ― Evidence from the Translation Tasks of Tripadvisor

Dong Kunxiang (), Sun Yan (), Xie Zongxiao () and Zhen Jie ()
Additional contact information
Dong Kunxiang: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan250014, China
Sun Yan: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan250014, China
Xie Zongxiao: China Financial Certification Authority, Beijing100054, China
Zhen Jie: School of Business Planning, Chongqing Technology and Business University, Chongqing400067, China

Journal of Systems Science and Information, 2020, vol. 8, issue 2, 170-184

Abstract: Material incentive is the main motivation for solvers to attend crowdsourcing tasks. So raising the bidding success rate is benefit to inspire the solvers attendance’ and increase the answering quality. This paper analyzes the effect of participation experience, task-fit capability, participation strategy and task attribute on the solvers bidding success by the solvers attending the series tasks of Tripadvisor. The results show that: 1) Participation times enrich the participation experiences and promote the bidding success, while bidding success times and last performances lower the bidding success because of the cognitive fixation; 2) The chance of bidding success will be increase when the solver own high task-fit capability; 3) The relationship between task submit sequence and bidding success is the type of reverse U shape, and the optimal submit sequence rate on the top of the reverse U shape; 4) Higher task difficulty lower bidding success, while higher task density easier bidding success.

Keywords: crowdsourcing contest; participation experience; task-fit capability; participation strategy; task characteristics (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.21078/JSSI-2020-170-15 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:8:y:2020:i:2:p:170-184:n:6

DOI: 10.21078/JSSI-2020-170-15

Access Statistics for this article

Journal of Systems Science and Information is currently edited by Shouyang Wang

More articles in Journal of Systems Science and Information from De Gruyter
Bibliographic data for series maintained by Peter Golla ().

 
Page updated 2025-03-19
Handle: RePEc:bpj:jossai:v:8:y:2020:i:2:p:170-184:n:6