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应对大流行危机中的国家与公民响应能力:系统思维视角

State and citizen responsiveness in fighting a pandemic crisis: A systems thinking perspective.

作者信息

Sunder M Vijaya, Prashar Anupama

机构信息

Indian School of Business (ISB) Hyderabad India.

Management Development Institute Gurgaon India.

出版信息

Syst Res Behav Sci. 2022 May 27. doi: 10.1002/sres.2849.

DOI:10.1002/sres.2849
PMID:35941990
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9348510/
Abstract

Management scholars have recognized organizational responsiveness among the essential capabilities of social organizations. It becomes essential for a social change to occur during a crisis, where the uncertainty or environmental dynamism is high. However, a social change cannot be successful unless constituent subsystems of a social organization exhibit responsiveness. Using systems theory, we conceptualize 'nation' as a social system and examine its responsiveness towards environmental uncertainly, taking an example of the COVID-19 pandemic. How can state and citizen community responsiveness help fight a pandemic crisis? We test these direct and moderating effects on data representing 14 countries. We perform a hierarchical regression analysis on the restructured, balanced country-wise panel data. Our findings highlight the importance of state and community interaction effects in controlling pandemic growth. Accordingly, we claim that only a collaborative approach by citizen communities with the respective governments will enable handling an uncertain situation.

摘要

管理学者已经认识到组织响应能力是社会组织的基本能力之一。在危机期间,当不确定性或环境动态性较高时,社会变革的发生就变得至关重要。然而,除非社会组织的组成子系统表现出响应能力,否则社会变革不可能成功。运用系统理论,我们将“国家”概念化为一个社会系统,并以新冠疫情为例,考察其对环境不确定性的响应能力。国家和公民社区的响应能力如何有助于抗击疫情危机?我们在代表14个国家的数据上检验这些直接和调节效应。我们对重组后的、按国家平衡的面板数据进行分层回归分析。我们的研究结果凸显了国家与社区互动效应在控制疫情蔓延方面的重要性。因此,我们认为只有公民社区与各自政府采取合作方式,才能应对不确定的局势。

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本文引用的文献

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Growth Rate and Acceleration Analysis of the COVID-19 Pandemic Reveals the Effect of Public Health Measures in Real Time.新冠疫情的增长率与加速分析实时揭示了公共卫生措施的效果。
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On Determining the Age Distribution of COVID-19 Pandemic.关于确定 COVID-19 大流行的年龄分布。
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