Evidence map›Paper›PMID 34708442›Full record

ReviewRisk analysis : an official publication of the Society for Risk Analysis2022

Sharing Knowledge to an Entrant for Production Investment Confronting COVID-19: Incentive Alignment and Lose-Lose Dilemma.

Baozhuang Niu, Zhipeng Dai, Qiyang Li

Open access · bronzeAbstract readReview
In one paragraph

Review in Risk analysis : an official publication of the Society for Risk Analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 25% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Global systemic risk and resilience for novel coronavirus in postpandemic era.Risk analysis : an official publication of the Society for Risk Analysis · 2022
    Article
  2. 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 at 1 institution in 1 country.

Baozhuang NiuSchool of Business Administration, South China University of Technology, Guangzhou, 510640, P.R. China.
Zhipeng DaiSchool of Business Administration, South China University of Technology, Guangzhou, 510640, P.R. China.
Qiyang LiSchool of Business Administration, South China University of Technology, Guangzhou, 510640, P.R. China.
South China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Facing the urgent demand of medical devices for COVID-19 treatment, many automakers have recently begun manufacturing ventilators, even though they are inefficient in production and uninformed of demand variability. To help them, some incumbent ventilator manufacturers have chosen to share knowledge, such as production techniques and demand information. Clearly, the incumbent ventilator manufacturers are fulfilling social responsibility, but is their knowledge sharing rewarding, especially when the automakers are entrant rivals? If possible, are win-win situations in the sense of social responsibility and firms' profitability identifiable? In this work, we develop a game-theoretic model in which an incumbent and an entrant ventilator manufacturer engage in two-dimensional competition in production investment and sales volume. We examine the incumbent manufacturer's profitability with and without knowledge sharing by formulating the tradeoffs among supply expansion, intensified competition, and the entrant's production efficiency improvement and demand variance reduction. We identify both "win-win" and "lose-lose" situations for the two competing manufacturers. Specifically, we find that free knowledge could be harmful for the entrant manufacturer, but the incumbent manufacturer benefits from knowledge sharing when market competition is intense, or when market competition is mild but the production investment efficiency varies.

Indexed as

COVID-19 Drug TreatmentHealth Knowledge, Attitudes, PracticeModels, TheoreticalSARS-CoV-2Antiviral AgentsCOVID-19HumansInvestmentsPandemicsAntiviral AgentsCompetition and cooperationincentive analysisknowledge sharingproduction investment

Identifiers

PMID34708442
PMCPMC8662260
OpenAlexW3161035256

What OpenQuestion holds

Textmetadata
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.