Safety Regulations and the Uncertainty of Work-Related Road Accident Loss: The Triple Identity of Chinese Local Governments Under Principal-Agent Framework.

Clicks: 411
ID: 94600
2020
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #9 of 27 articles by views in Risk analysis : an official publication of the Society for Risk Analysis

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
This study examines how government safety regulations affect the uncertainty of work-related road accident loss (UWRAL) by considering the multi-identity of local governments in the relationship among the central government, the local governments, and enterprises. Fixed effects panel models and mediation analyses with bootstrapping were conducted to test the hypotheses using Chinese provincial panel data from 2008 to 2014. Given the complexity and nonlinear characteristics of road safety systems, a new approach based on self-organized criticality theory is proposed to measure the uncertainty of road accident loss from a complex system perspective. We find that a regional government with detailed safety work planning (SWP), high safety supervision intensity (SSI), and safety information transparency (SIT) can decrease the UWRAL. Furthermore, our findings suggest that SSI and SIT partially mediate the relationship between the SWP of regional governments and the UWRAL, with 19.7% and 23.6% indirect effects, respectively. This study also provides the government with managerial implications by linking the results of risk assessment to decision making for risk management.
Reference Key
lu2020safetyrisk Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Lu, Liangdong;Huang, Hong;Wei, Jiuchang;Xu, Jia;
Journal Risk analysis : an official publication of the Society for Risk Analysis
Year 2020
DOI
10.1111/risa.13452
URL
Keywords
risk assessment power-law distribution principal-agent framework safety regulation uncertainty of accident loss

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.