Evidence map›Paper›PMID 40691191›Full record

ArticleScientific reports2025

Collaborative decision-making for localized emergency response in major railroad projects.

Yuanyuan Lei, Jingxiao Zhang, Ruixue Zhang, Lean Yu, Pablo Ballesteros-Pérez, Martin Skitmore

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yuanyuan LeiSchool of Economics and Management, Chang'an University, Xi'an, China.
Jingxiao ZhangSchool of Economics and Management, Chang'an University, Xi'an, China. zhangjingxiao964@126.com.
Ruixue ZhangSchool of Economics and Management, Chang'an University, Xi'an, China.
Lean YuBusiness School, Sichuan University, Chengdu, China.
Pablo Ballesteros-PérezInnovation and Sustainability Research Centre (PRINS), Universitat Politècnica de València, Valencia, Spain.
Martin SkitmoreFaculty of Society and Design, Bond University, Gold Coast, Australia.

Funding

Major Program of the National Natural Science Foundation of China 71942006Open Fund of China Academy of Railway Sciences Group Corporation 2021YJ049Scientific Research Project of China Road and Bridge Engineering Co., Ltd 2020zlkj04The Research Plan of Shaanxi Provincial Department of Education 21JK0282
6 · The paper itself

Abstract

This paper examines major railroad projects' emergency response decision-making process, focusing on timeliness, cost-effectiveness, and public involvement. It explores the optimal collaborative strategies of local governments, enterprises, and the public during the construction phase. A novel tripartite decision-making framework is proposed, based on an asymmetric evolutionary game model and dynamic simulation methods. The results show a stable equilibrium in emergency response strategies emerges when public engagement is prioritized. Government subsidy policies are found to significantly influence the strategic choices of all agents, emphasizing the critical role of coordinated collaboration. The study highlights the importance of public participation and multi-agent cooperation in addressing complex emergency challenges. These findings provide valuable guidance for improving localized emergency response strategies, enhancing collaborative decision-making, optimizing resource allocation, increasing response efficiency, and supporting policy formulation in major railroad projects.

Indexed as

Cooperative BehaviorDecision MakingEmergenciesRailroadsHumansEvolutionary gameLocalized emergency responseMajor railroad projectsMulti-agent decision

Identifiers

PMID40691191
PMCPMC12280098

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.