Managing panic buying-related instabilities in supply chains: A COVID-19 pandemic perspective.

Towfique Rahman, Sanjoy Kumar Paul, Nagesh Shukla, Renu Agarwal, Firouzeh Taghikhah

Abstract read

In one paragraph

Article in IFAC-PapersOnLine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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.

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Towfique RahmanUTS Business School, University of Technology Sydney, Sydney, Australia.

Sanjoy Kumar PaulUTS Business School, University of Technology Sydney, Sydney, Australia.

Nagesh ShuklaFaculty of Engineering & IT, University of Technology Sydney, Sydney, Australia.

Renu AgarwalUTS Business School, University of Technology Sydney, Sydney, Australia.

Firouzeh TaghikhahCrawford School of Public Policy, Australian National University, Canberra, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Global supply chains (SCs) have been severely impacted by the COVID-19 pandemic on several levels. For example, SCs suffered from panic buying-related instabilities and multiple disruptions of supply, demand, and capacity during the pandemic. This study developed an agent-based model (ABM) to predict the effects of panic buying-related instabilities in SCs and offered strategies to improve them. The ABM model includes a simulation and optimization model of a typical SC of an essential product manufacturer (i.e., toilet paper SC) for the analysis of scenarios and strategies to observe improvements in SCs. Among the four strategies identified, the findings suggest boosting production capacity to the maximum and ensuring optimal reorder points, order sizes, and trucks helped the essential product manufacturers reduce panic buying-related instabilities in their SCs.

Indexed as

agent-based modelingCOVID-19 pandemicmitigationpanic buyingSupply chain

Identifiers

PMID38620991

DOI10.1016/j.ifacol.2022.09.405

PMCPMC9605711

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.