Evidence map›Paper›PMID 40242537›Full record

ArticleFundamental research2025

Supply chain resilience enhancement strategies in the context of supply disruptions, demand surges, and time sensitivity.

Xin Yan, Jian Li, Yanan Sun, Robert De Souza

Abstract read
In one paragraph

Article in Fundamental research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
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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

4 authors.

Xin YanCollege of Economics and Management, Beijing University of Technology, Beijing 100124, China.
Jian LiCollege of Economics and Management, Beijing University of Technology, Beijing 100124, China.
Yanan SunCollege of Economics and Management, Beijing University of Technology, Beijing 100124, China.
Robert De SouzaThe Logistics Institute-Asia Pacific, National University of Singapore, Singapore 119613, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Supply chain disruptions, including trade disputes, regional conflicts, and the COVID-19 pandemic, have highlighted the importance of supply chain resilience. This study focuses on investment decisions related to supply chain resilience, including considerations of supply disruptions, demand surges, and demand time sensitivity. The study uses a Stackelberg game model, with the retailer as the leader and the supplier as the follower, to analyze and compare optimal strategies for supply chain participants under different levels of risk. The results show that the severity of risk events impacts the optimal retail price, optimal wholesale price, supply chain recovery time, and expected profits for each participant. The investment in supply capacity enhancement not only expands the ability to meet demand but also encourages suppliers to expedite supply chain recovery, elevate demand fulfillment rates, and enhance the overall return on investment in supply chain resilience. As a result, the resilience of the entire supply chain is fortified. Similarly, it has been found that centralized decision-making leads to lower prices, shorter recovery times and greater supply chain resilience than decentralized decision-making. This study offers theoretical underpinning for corporations to effectively address risky occurrences, ensure supply security, enhance supply chain resilience, and imparts support for governments involved in humanitarian relief efforts.

Indexed as

Demand surgeStackelbergSupply capacity enhancementSupply chain recoverySupply chain resilience

Identifiers

PMID40242537
PMCPMC11997578

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.