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Economic resilience dataset in facing physical distancing during COVID-19 global pandemic
The dataset was collected using the survey method with an electronic questionnaire. The use of electronic questionnaires is intended to reach many respondents during the physical distancing caused by the COVID-19 global pandemic. The instrument used in data collection was adapted from Alinovi, Mane,...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7381413/ https://www.ncbi.nlm.nih.gov/pubmed/32766414 http://dx.doi.org/10.1016/j.dib.2020.106069 |
_version_ | 1783563041572388864 |
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author | Rahmadana, Muhammad Fitri Sagala, Gaffar Hafiz |
author_facet | Rahmadana, Muhammad Fitri Sagala, Gaffar Hafiz |
author_sort | Rahmadana, Muhammad Fitri |
collection | PubMed |
description | The dataset was collected using the survey method with an electronic questionnaire. The use of electronic questionnaires is intended to reach many respondents during the physical distancing caused by the COVID-19 global pandemic. The instrument used in data collection was adapted from Alinovi, Mane, and Romano (2008). The instrument was designed anonymously to ensure the privacy and independence of respondents in giving their responses. Data that is captured includes several categories either nominal, ordinal, or interval refers to the information that needs to be captured. Determination of the type of data also refers to the recommendation of previous research. The data was collected using the Google form platform. Questionnaire distribution was conducted on April 12–20, 2020, and 1096 responses were collected. The date is two weeks after the government call of the Republic of Indonesia to carry out Physical Distancing to anticipate the COVID-19 Global Pandemic. The entire data is then screened and filtered so that it only leaves the data with respondents who are domiciled in Medan City. After filtered, there is remained 846 data that is ready for analysis. In order to make more informative data, researchers conducted a descriptive statistical analysis, ANOVA, Kruskal Wallis, and the Spearman's rank correlation. Analysis of the data provides valuable information related to the interrelation of each item and the pattern of economic resilience that the urban city community has as a data of the COVID-19 global pandemic. Researchers can then further analyzed the data with more advanced analytical tools to produce more valuable information in the development of science and in developing strategic policies related to anticipating the economic vulnerability of the household due to the global pandemic disaster. |
format | Online Article Text |
id | pubmed-7381413 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-73814132020-07-28 Economic resilience dataset in facing physical distancing during COVID-19 global pandemic Rahmadana, Muhammad Fitri Sagala, Gaffar Hafiz Data Brief Economics, Econometrics and Finance The dataset was collected using the survey method with an electronic questionnaire. The use of electronic questionnaires is intended to reach many respondents during the physical distancing caused by the COVID-19 global pandemic. The instrument used in data collection was adapted from Alinovi, Mane, and Romano (2008). The instrument was designed anonymously to ensure the privacy and independence of respondents in giving their responses. Data that is captured includes several categories either nominal, ordinal, or interval refers to the information that needs to be captured. Determination of the type of data also refers to the recommendation of previous research. The data was collected using the Google form platform. Questionnaire distribution was conducted on April 12–20, 2020, and 1096 responses were collected. The date is two weeks after the government call of the Republic of Indonesia to carry out Physical Distancing to anticipate the COVID-19 Global Pandemic. The entire data is then screened and filtered so that it only leaves the data with respondents who are domiciled in Medan City. After filtered, there is remained 846 data that is ready for analysis. In order to make more informative data, researchers conducted a descriptive statistical analysis, ANOVA, Kruskal Wallis, and the Spearman's rank correlation. Analysis of the data provides valuable information related to the interrelation of each item and the pattern of economic resilience that the urban city community has as a data of the COVID-19 global pandemic. Researchers can then further analyzed the data with more advanced analytical tools to produce more valuable information in the development of science and in developing strategic policies related to anticipating the economic vulnerability of the household due to the global pandemic disaster. Elsevier 2020-07-25 /pmc/articles/PMC7381413/ /pubmed/32766414 http://dx.doi.org/10.1016/j.dib.2020.106069 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Economics, Econometrics and Finance Rahmadana, Muhammad Fitri Sagala, Gaffar Hafiz Economic resilience dataset in facing physical distancing during COVID-19 global pandemic |
title | Economic resilience dataset in facing physical distancing during COVID-19 global pandemic |
title_full | Economic resilience dataset in facing physical distancing during COVID-19 global pandemic |
title_fullStr | Economic resilience dataset in facing physical distancing during COVID-19 global pandemic |
title_full_unstemmed | Economic resilience dataset in facing physical distancing during COVID-19 global pandemic |
title_short | Economic resilience dataset in facing physical distancing during COVID-19 global pandemic |
title_sort | economic resilience dataset in facing physical distancing during covid-19 global pandemic |
topic | Economics, Econometrics and Finance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7381413/ https://www.ncbi.nlm.nih.gov/pubmed/32766414 http://dx.doi.org/10.1016/j.dib.2020.106069 |
work_keys_str_mv | AT rahmadanamuhammadfitri economicresiliencedatasetinfacingphysicaldistancingduringcovid19globalpandemic AT sagalagaffarhafiz economicresiliencedatasetinfacingphysicaldistancingduringcovid19globalpandemic |