Proceedings of the 4th International Conference on Crowd Science and Engineering 2019
DOI: 10.1145/3371238.3371252
|View full text |Cite
|
Sign up to set email alerts
|

Analysis of Knowledge Providers' Learning Behavior

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(2 citation statements)
references
References 29 publications
0
2
0
Order By: Relevance
“…Pang, Bao [11] argued that content quality, usefulness, and user recognition are the most important determinants of user demand response. Qi, Ma [12] reported that users make payment decisions based on content creator profile, authentication, content of previous responses, approval number, recognition number, collection number, item number, live number, and title.…”
Section: Knowledge Payment Productsmentioning
confidence: 99%
See 1 more Smart Citation
“…Pang, Bao [11] argued that content quality, usefulness, and user recognition are the most important determinants of user demand response. Qi, Ma [12] reported that users make payment decisions based on content creator profile, authentication, content of previous responses, approval number, recognition number, collection number, item number, live number, and title.…”
Section: Knowledge Payment Productsmentioning
confidence: 99%
“…Therefore, it is important for knowledge providers and platform developers to understand the information adoption mechanisms for different types of knowledge products on online knowledge payment platforms. In particular, understanding the factors driving online knowledge payment behavior is critical for knowledge providers to compete for knowledge seekers, achieve financial gains and sustainability, and improve their interactions with knowledge seekers [10][11][12].…”
Section: Introductionmentioning
confidence: 99%