Emergency Capacity Pool to Respond to Unconventional Emergencies Based on Principal–Agent Theory

To address the conflict of interest between the government and enterprises regarding urban emergency transportation resources in unconventional emergencies and to enhance resource allocation and response efficiency. This paper proposes a collaborative government–enterprise model for emergency transport capacity reserves and develops an incentive model based on principal–agent theory. First, by comprehensively considering enterprise characteristics, high-quality enterprises are selected to collaborate with the government in building an emergency capacity pool of social vehicles. Second, to address potential conflicts of interest between the government and enterprises within the emergency capacity pool, this paper uses principal–agent theory to analyze the interest game process under information asymmetry, constructs a corresponding incentive model, and determines the government’s optimal incentive coefficient, the enterprise’s optimal actual capacity supply ratio, and the benefit distribution between both parties. Finally, numerical simulations and sensitivity analyses were used to verify the model’s applicability. The findings reveal that transport effort cost, economic requisition compensation, and government supervision cost influence the optimal decisions and outcomes in government–enterprise interactions. This study provides theoretical guidance and managerial insights for coordinating emergency transport scheduling between the government and enterprises during unconventional emergencies.

Authors

Institutions

Publication Details

Journal
Urban Science
Published
2024-12-20
DOI
https://doi.org/10.3390/urbansci8040262
Citations
2
Primary Topic
Disaster Response and Management
Type
article
Field-Weighted Citation Impact
1.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Emergency Capacity Pool to Respond to Unconventional Emergencies Based on Principal–Agent Theory

Haiyan Wang, A P Sang, Na Jin, Shipeng Wang et al.
2 citations
Urban Science
Disaster Response and Management
1.49
article

Emergency Capacity Pool to Respond to Unconventional Emergencies Based on Principal–Agent Theory

Haiyan Wang, A P Sang, Na Jin, Shipeng Wang, F. Hadipriono Tan
article en
2 citations

Abstract

To address the conflict of interest between the government and enterprises regarding urban emergency transportation resources in unconventional emergencies and to enhance resource allocation and response efficiency. This paper proposes a collaborative government–enterprise model for emergency transport capacity reserves and develops an incentive model based on principal–agent theory. First, by comprehensively considering enterprise characteristics, high-quality enterprises are selected to collaborate with the government in building an emergency capacity pool of social vehicles. Second, to address potential conflicts of interest between the government and enterprises within the emergency capacity pool, this paper uses principal–agent theory to analyze the interest game process under information asymmetry, constructs a corresponding incentive model, and determines the government’s optimal incentive coefficient, the enterprise’s optimal actual capacity supply ratio, and the benefit distribution between both parties. Finally, numerical simulations and sensitivity analyses were used to verify the model’s applicability. The findings reveal that transport effort cost, economic requisition compensation, and government supervision cost influence the optimal decisions and outcomes in government–enterprise interactions. This study provides theoretical guidance and managerial insights for coordinating emergency transport scheduling between the government and enterprises during unconventional emergencies.

Urban ScienceVol. 8(4)
Wuhan University of Technology (CN)
Strong
Openalex Percentile: Top 16%
Disaster Response and Management
1.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.