2022
DOI: 10.1007/s10668-022-02875-6
|View full text |Cite
|
Sign up to set email alerts
|

Protective consumption behavior under smog: using a data-driven dynamic Bayesian network

Abstract: In the midst of the deteriorating air pollution and collective stress, people pay close attention to risk mitigation measures such as keeping indoor and purchasing anti-smog products. Through impact evaluations, factors regarding health protective behavior can be identified. However, limited research is available regarding probabilistic interdependencies between the factors and protective behavior and largely relies on subjective diagnosis. These concerns have led us to adopt a data-driven static Bayesian netw… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
3
2

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
references
References 78 publications
0
0
0
Order By: Relevance