Evidence map›Paper›PMID 36733660›Full record

ArticleFrontiers in psychology2023

Emergency engineering reconstruction mode based on the perspective of professional donations.

Hanyu Li, Xinli Zhang, Usama Khaliq, Faheem Ur Rehman

Abstract read
In one paragraph

Article in Frontiers in psychology, 2023. 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

4 authors.

Hanyu LiSchool of Management and Engineering, Nanjing University, Nanjing, Jiangsu, China.
Xinli ZhangSchool of Business, Sichuan University, Chengdu, China.
Usama KhaliqSchool of Business, Sichuan University, Chengdu, China.
Faheem Ur RehmanGraduate School of Economics and Management, Ural Federal University, Ekaterinburg, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In the construction of emergency engineering, the effective participation of organizations such as government and construction enterprises can improve engineering emergency services to emergency adaptive, which faces the challenge of the enthusiasm of enterprises' emergency participation. This study proposed a new diversified social governance mode for public emergency facility construction. Methods: This paper empirically analyzes the performance of stock market returns before and after construction enterprises' participation in emergency engineering. Results: Against the backdrop of COVID-19, the analysis based on the sample data of 141 listed companies found that both construction enterprises directly involved in emergency hospital construction and non-state-owned enterprises involved in donations have higher excess return rates. In contrast, social concern has a positive mediating effect between emergency donations and stock market returns. The study suggests that stock market returns from donation behavior and reputation capital become incentives for firms to actively participate in emergency donations, providing a behavioral basis for professional donations by construction firms. Discussion: Based on the above assumptions, this paper proposes the organizational model of emergency engineering construction and the "Engineering Community" relationship based on the "Engineering Multi-governance" theory. This paper is the first to study the emergency engineering construction model from the perspective of professional donation behavior.

Indexed as

cumulative excess returndouble differentialemergency engineeringmultiple collaborativereconstruction mode

Identifiers

PMID36733660
PMCPMC9887034

What OpenQuestion holds

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LicenceCC BY
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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.