Evaluation of Germany’s Vulnerability Based on Economic Principles and Data Science

Vulnerability refers to the ability of a country or a region to resist internal and external natural factors such as ecological environment, economy, and society during its development. Germany is a country with low overall vulnerability and distinct regional differences, so research on its regional...

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Main Authors: Li Yiliang, Wu Maoguo
Format: Article
Language:English
Published: EDP Sciences 2021-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/29/e3sconf_eem2021_02011.pdf
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spelling doaj-cf7d28637d394b8e962d5a3c65665f802021-05-28T12:35:18ZengEDP SciencesE3S Web of Conferences2267-12422021-01-012530201110.1051/e3sconf/202125302011e3sconf_eem2021_02011Evaluation of Germany’s Vulnerability Based on Economic Principles and Data ScienceLi Yiliang0Wu Maoguo1SILC Business School Shanghai UniversitySILC Business School Shanghai UniversityVulnerability refers to the ability of a country or a region to resist internal and external natural factors such as ecological environment, economy, and society during its development. Germany is a country with low overall vulnerability and distinct regional differences, so research on its regional vulnerability can be a representative case for developing countries, as it provides a comprehensive assessment of regional vulnerability via scientific methodology and at the same time proposes rational solutions. The research collects quarterly data of 16 states of Germany from 2000 to 2015. This study describes a series of features of the data and establishes a comprehensive assessment of regional vulnerability including 33 indicators. Combined with the multi-criteria decision analysis method (MCDM), the analytic hierarchy process (AHP) method and the entropy method are applied to calculate the weights. A linear weighted sum method is applied to obtain the regional vulnerability index of Germany. Afterwards, by performing regression tests, this study empirically assess the influencing factors of the regional vulnerability of Germany. Moreover, this study adopts the neural network training model and forecasts the regional vulnerability of Germany of 2016 to 2020. This study identifies the main factors that influence the regional vulnerability of Germany, and proposes policy implications on the overall regulation to reduce the vulnerability of different regions in Germany accordingly.https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/29/e3sconf_eem2021_02011.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Li Yiliang
Wu Maoguo
spellingShingle Li Yiliang
Wu Maoguo
Evaluation of Germany’s Vulnerability Based on Economic Principles and Data Science
E3S Web of Conferences
author_facet Li Yiliang
Wu Maoguo
author_sort Li Yiliang
title Evaluation of Germany’s Vulnerability Based on Economic Principles and Data Science
title_short Evaluation of Germany’s Vulnerability Based on Economic Principles and Data Science
title_full Evaluation of Germany’s Vulnerability Based on Economic Principles and Data Science
title_fullStr Evaluation of Germany’s Vulnerability Based on Economic Principles and Data Science
title_full_unstemmed Evaluation of Germany’s Vulnerability Based on Economic Principles and Data Science
title_sort evaluation of germany’s vulnerability based on economic principles and data science
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2021-01-01
description Vulnerability refers to the ability of a country or a region to resist internal and external natural factors such as ecological environment, economy, and society during its development. Germany is a country with low overall vulnerability and distinct regional differences, so research on its regional vulnerability can be a representative case for developing countries, as it provides a comprehensive assessment of regional vulnerability via scientific methodology and at the same time proposes rational solutions. The research collects quarterly data of 16 states of Germany from 2000 to 2015. This study describes a series of features of the data and establishes a comprehensive assessment of regional vulnerability including 33 indicators. Combined with the multi-criteria decision analysis method (MCDM), the analytic hierarchy process (AHP) method and the entropy method are applied to calculate the weights. A linear weighted sum method is applied to obtain the regional vulnerability index of Germany. Afterwards, by performing regression tests, this study empirically assess the influencing factors of the regional vulnerability of Germany. Moreover, this study adopts the neural network training model and forecasts the regional vulnerability of Germany of 2016 to 2020. This study identifies the main factors that influence the regional vulnerability of Germany, and proposes policy implications on the overall regulation to reduce the vulnerability of different regions in Germany accordingly.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/29/e3sconf_eem2021_02011.pdf
work_keys_str_mv AT liyiliang evaluationofgermanysvulnerabilitybasedoneconomicprinciplesanddatascience
AT wumaoguo evaluationofgermanysvulnerabilitybasedoneconomicprinciplesanddatascience
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