Evidence map›Paper›PMID 35124776›Full record

ArticleEnvironmental science and pollution research international2022

A multi-stage supply chain disruption mitigation strategy considering product life cycle during COVID-19.

Jingze Chen, Hongfeng Wang, Yaping Fu

Abstract read
In one paragraph

Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Jingze ChenCollege of Information Science and Engineering, Northeastern University, Shenyang, 110819, People's Republic of China.
Hongfeng WangCollege of Information Science and Engineering, Northeastern University, Shenyang, 110819, People's Republic of China. hfwang@mail.neu.edu.cn.ORCID http://orcid.org/0000-0002-8954-0876
Yaping FuSchool of Business, Qingdao University, Qingdao, 266071, People's Republic of China.

Funding

Fundamental Research Funds for the Central Universities N180408019National Key Research and Development Program of China 2020YFB1708200National Natural Science Foundation of China 62173076Natural Science Foundation of Jilin Province 71671032
6 · The paper itself

Abstract

The global pandemic of COVID-19 has caused severe damage to the supply chain such that manufacturers may face long-term supply disruptions. In this paper, a disruption recovery strategy of a supply chain system is investigated from the perspective of product change, in which the life cycle and design change time of a new product are both considered in order to minimize the losses of manufacturer after disruptions. A mixed-integer linear programming (MILP) model is presented to address the disruption recovery problem for this multi-period, multi-supplier, and multi-stage supply chain system. A two-stage heuristic algorithm is designed to solve the problem. Experimental results show that the proposed disruption mitigation strategy can effectively reduce the profit loss of manufacturer due to supply disruption, and demonstrate the impact of product life cycle in the selection of new product design planning. A sensitivity analysis is performed to ensure the applicability of the model in the actual environment, which illustrates the effect of different parameter changes on the results. This work can help manufacturers establish an optimal recovery strategy whenever the supply chain system experiences supply disruptions.

Indexed as

COVID-19Mitigation strategyProduct design changeProduct life cycleSupply chain

Identifiers

PMID35124776
PMCPMC8817668

What OpenQuestion holds

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Registered trials

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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.