全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

危机学习是否有效——一项基于SDID的实证研究
Is Crisis Learning Effective—An Empirical Study Based on SDID

DOI: 10.12677/sd.2025.152058, PP. 222-237

Keywords: 生产安全事故,危机学习,合成差分法,广东“12·20”事故
Production Safety Accidents
, Crisis Learning, Synthetic Difference-in-Differences, Guangdong “12?20” Accident

Full-Text   Cite this paper   Add to My Lib

Abstract:

在新发展理念稳步推进、总体国家安全观深入落实的时代背景下,发展与安全成为当代社会的两大关键命题,如何统筹二者关系是亟待解决的重要时代难题。发展进程中频发的生产安全事故危害巨大,不仅造成了巨额经济损失,还引发了社会各界的高度关注,使政府面临严峻的舆论压力。危机学习作为针对性策略,能回溯事故全貌、剖析问题根源、弥补监管短板,优化生产安全政策制度。当前,危机学习研究在理论构建和案例分析等方面取得了一定成果,但受限于文本数据定性分析的局限,对其效能的量化研究仍显不足,缺乏广泛的实证支撑。基于此,本研究聚焦于探究影响危机学习效果的因素、衡量危机学习效果的方式以及危机学习成效的时效跨度,即其是仅具有短暂警示效应,还是能产生持久的正向驱动作用。为深入解答这些问题,本研究选取广东“12·20”特别重大滑坡事故作为案例,利用省级面板数据,采用合成差分法(SDID)进行实证分析。实证结果显示,广东省在事故发生后持续开展危机学习,取得了良好的效果,显著降低了年生产安全事故死亡人数。
Against the backdrop of the steady advancement of new development concepts and the in-depth implementation of the overall national security concept, development and security have become two key propositions in contemporary society. How to coordinate the relationship between the two is an important and urgent issue that needs to be addressed. Frequent production safety accidents during the development process cause huge harm. They not only lead to huge economic losses, but also attract the high attention of all sectors of society, putting the government under severe public opinion pressure. As a targeted strategy, crisis learning can trace back the entire picture of the accident, analyze the root causes of problems, make up for regulatory shortcomings, and optimize the policy and institutional framework of production safety. At present, crisis learning research has achieved certain results in aspects such as theoretical construction and case analysis. However, due to the inherent limitations of qualitative analysis of text data, quantitative research on its effectiveness is still relatively scarce, lacking extensive empirical support. Based on this, this study focuses on exploring the factors that affect the effectiveness of crisis learning, the ways to measure the effectiveness of crisis learning, and the time span of the effectiveness of crisis learning, that is, whether it only has a short-term warning effect or can generate a lasting positive driving force. To deeply answer these questions, this study selects the “12?20” especially major landslide accident in Guangdong as a case, uses provincial panel data, and conducts empirical analysis using the Synthetic Difference-in-Differences (SDID) method. The empirical results show that Guangdong Province has continuously carried out crisis learning after the accident and achieved good results, significantly reducing the annual number of deaths in production safety accidents.

References

[1]  国新办就应急管理部组建以来改革和运行情况举行发布会[J]. 中国减灾, 2019(3): 8.
[2]  王晓晔. 深刻把握时代特点聚焦发展现实之需[N]. 中国应急管理报, 2022-11-01(001).
[3]  Heinrich, H.W., Peterson, D. and Room, N. (1980) Industrial Accident Prevention. McGraw-Hill Book Company, 22.
[4]  Benner, L. (1985) Rating Accident Models and Investigation Methodologies. Journal of Safety Research, 16, 105-126.
https://doi.org/10.1016/0022-4375(85)90038-6
[5]  Leveson, N. (2004) A New Accident Model for Engineering Safer Systems. Safety Science, 42, 237-270.
https://doi.org/10.1016/s0925-7535(03)00047-x
[6]  Leveson, N.G. (2011) Applying Systems Thinking to Analyze and Learn from Events. Safety Science, 49, 55-64.
https://doi.org/10.1016/j.ssci.2009.12.021
[7]  Reason, J. (1990). Human Error. Cambridge University Press, 2-16.
https://doi.org/10.1017/cbo9781139062367
[8]  Rasmussen, J. (1997) Risk Management in a Dynamic Society: A Modelling Problem. Safety Science, 27, 183-213.
https://doi.org/10.1016/s0925-7535(97)00052-0
[9]  Rasemussen, J. and Svedung, I. (2000) Proactive Risk Management in a Dynamic Society. Swedish Rescue Service Agency.
[10]  Surry, J. (1996) Industrial Accident Research: A Human Engineering Approach. Journal of Occupational & Environment Medicine, 11, 492-493.
[11]  Lawrance, A.C. (1974) Human Error as a Cause of Accidents in Gold Mining. Journal of Safety Research, 6, 78-88.
[12]  杨伟民, 旦雅宁. 突发事件问责“堕距”的生成与弥合[J]. 学术交流, 2022(10): 134-145.
[13]  梁玉柱. 安全与发展双重视域下生产事故责任追究转型[J]. 湖北社会科学, 2021(2): 33-41.
[14]  杨占科. 建立依法严格科学的安全生产问责机制[J]. 现代职业安全, 2011(9): 29-31.
[15]  高恩新. 特大生产安全事故行政问责“分水岭”效应: 基于问责立方的分析[J]. 南京社会科学, 2016(3): 84-92.
[16]  杜宇. 在报应与功利之间——刑罚视野中的公平与效益[J]. 上海市政法管理干部学院学报, 2000(5): 9-13.
[17]  叶麒麟. 理性看待“矿难问责” [J]. 人大建设, 2008(11): 50.
[18]  Argyris, Ch. and Schön, D.A. (1978) Organizational Learning: A Theory of Action Perspective. Addison-Wesley, 17-47.
[19]  Smith, D. and Elliott, D. (2007) Exploring the Barriers to Learning from Crisis: Organizational Learning and Crisis. Management Learning, 38, 519-538.
https://doi.org/10.1177/1350507607083205
[20]  Schiffino, N., Taskin, L., Donis, C. and Raone, J. (2016) Post-Crisis Learning in Public Agencies: What Do We Learn from both Actors and Institutions? Policy Studies, 38, 59-75.
https://doi.org/10.1080/01442872.2016.1188906
[21]  Wang, J. (2008) Developing Organizational Learning Capacity in Crisis Management. Advances in Developing Human Resources, 10, 425-445.
https://doi.org/10.1177/1523422308316464
[22]  唐雲, 王英. “吃一堑”能“长一智”吗?——重特大事故中地方政府危机学习的溢出效应研究[J]. 暨南学报(哲学社会科学版), 2022, 44(10): 56-71.
[23]  姜雅婷, 柴国荣. 目标考核如何影响安全生产治理效果: 政府承诺的中介效应[J]. 公共行政评论, 2018, 11(1): 166-186+223.
[24]  姜雅婷, 柴国荣. 目标考核、官员晋升激励与安全生产治理效果——基于中国省级面板数据的实证检验[J]. 公共管理学报, 2017, 14(3): 44-59+156.
[25]  Clarke, D., Pailañir, D., Carleton Athey, S. and Imbens, G.W. (2023) Synthetic Difference-in-Differences Estimation. SSRN Electronic Journal.
[26]  Arkhangelsky, D., Athey, S., Hirshberg, D.A., Imbens, G.W. and Wager, S. (2021) Synthetic Difference-in-Differences. American Economic Review, 111, 4088-4118.
https://doi.org/10.1257/aer.20190159
[27]  吕海燕, 张宏元, 王便文. 对安全生产事故统计指标改革的思考[J]. 中国统计, 2003(11) : 17-19.
[28]  汪崇鲜, 孙万彪, 黄盛初. 北京市安全生产与经济社会发展耦合关系研究[J]. 中国安全科学学报, 2008, 18(5): 61-67.
[29]  任英, 彭红星. 中国交通事故伤亡人数影响因素的实证分析[J]. 预测, 2013, 32(3): 1-7.
[30]  魏玖长, 丁䶮. 重特大安全事故震慑效应的影响因素研究[J]. 中国行政管理, 2020(6): 137-143.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133