ABSTRACT
This study aims to investigate the effects of the COVID-19 pandemic on the innovation index, Gross Domestic Product (GDP), high technology exports, and human development (HDI) in the world's leading 30 high-tech innovative countries. Using grey relational analysis models, the association between COVID-19 and other economic development indices was investigated. The model selects the country least affected by the pandemic from the top 30 innovative countries through a conservative (maximin) method based on grey association values. Data was collected from World Bank databases and analyzed to compare pre- and post-COVID-19 periods (2019, 2020). The outcomes of this study provide essential recommendations for industries and decision-makers with suitable action plans to preserve economic systems from further harm caused by the global COVID-19 outbreak. The ultimate goal is to boost the innovation index, GDP, high-tech exports, and HDI of high-tech economies and pave the way for a sustainable economy. To the author's knowledge, this is the first study to develop a multidimensional framework to assess COVID-19's impact on the sustainable economy of top 30 high-tech innovative countries, and to conduct a comparative analysis to identify the strong and weak effects of COVID-19 on sustainable economic growth.
ABSTRACT
Outliers, or outlying observations, are values in data, which appear unusual. It is quite essential to analyze various unexpected events or anomalies in economic domain like sudden crash of stock market, mismatch between country’s per capita incomes and overall development, abrupt change in unemployment rate and steep falling of bank interest to find the insights for the benefit of humankind. These situations can arise due to several reasons, out of which pandemic is a major one. The present COVID-19 pandemic also disrupted the global economy largely as various countries faced various types of difficulties. This motivates the present researchers to identify a few such difficult areas in economic domain, arises due to the pandemic situation and identify the countries, which are affected most under each bucket. Two well-known machine-learning techniques DBSCAN (density based clustering approach) and Z-score (statistical technique) are utilized in this analysis. The results can be used as suggestive measures to the administrative bodies, which show the effectiveness of the study. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
This study proposes a model to explain the effect of digital capabilities on firm performance in the “new normal” context from a firm-level perspective. Moreover, it analyzes the mediating role of technological capabilities and the Human Development Index (HDI) in explaining firm performance. Our study used data from the World Bank's Enterprise Surveys 2020, which included 999 firms from 27 countries. We applied the methodological approach, partial least square structural equation modeling (PLS-SEM), to test the hypothetical model. The results show that digital capabilities positively influence firm performance only through technological capabilities. We also empirically demonstrate that digital skills in low HDI economies have a more significant indirect effect on firm performance than in high HDI countries. Finally, some promising avenues for future research and implications for managers and policymakers are suggested based on these findings.
ABSTRACT
The COVID-19 pandemic has been going on for over one year until today. The government of Indonesia has issued various policies to break the chain of transmission of COVID-19, including the imposition of Large-Scale Social Restrictions and the Enforcement of Restrictions on Micro-scale Community Activities. However, in socio-economics dimension, especially on Economic Growth Rate (EGR), Human Development Index (HDI) and Poverty Percentage (PP), this pandemic has changed how they interact each other. This study presents anomaly correlation regarding those three socio-economics dimensions. The data for analysis was taken from Statistics Indonesia that consists of monthly report data in socio-economics fluctuation during two years period (2019-2020). For year 2019, the results of the Bivariate correlation test showed that the increasing of the Economic Growth Rate (EGR) would increase the Human Development Index (HDI) and decrease the Poverty Percentage (PP) in Indonesia. This correlation did not happen in 2020, because when the Economic Growth Rate (EGR) was increased, the Human Development Index (HDI) level was decreased and Poverty Percentage (PP) was increased. The 2020 result behaviour showed an opposite condition compared to normal correlation term. Some analysis has been discussed on the paper regarding this anomaly condition. The worst impact due to the COVID-19 pandemic in this analysis were shown in Bali-Nusa Tenggara region, where the Economic Growth Rate (EGR), Human Development Index (HDI) and Poverty Percentage (PP) values are below the national value. © 2021 IEEE.
ABSTRACT
Coronavirus disease-19 (COVID-19) is perhaps the most worrisome pandemic in the 21st century, having entailed devastating consequences for the whole society during the last year. Different studies have displayed an existing association between pregnancy and COVID-19 severity due to the various physiological changes that occur during gestation. Recent data identified maternal country of origin as an important determinant of COVID-19 presentation in pregnant women. However, the explanation of this fact remains to be fully elucidated. Therefore, the purpose of this work is to analyze the possible relationship between Human Development Index (HDI) of maternal country of origin with the morbimortality of pregnant women and their newborns. Here, we conducted a multicentric, ambispective, observational case-control study (1:1 ratio) and compare with the HDI of each country (group 1-very high HDI, group 2-high HDI, group 3-medium HDI, and group 4-low HDI). In total, 1347 pregnant women with confirmed SARV-CoV-2 infection (cases) were enrolled, and each was paired with one control to give a total number of 2694 participants from 81 tertiary care centers. Among the women with SARS-CoV-2 infection, more cases were produced of perinatal mortality, overall maternal morbidity, COVID-19 maternal morbidity, C-sections, hypertensive maternal morbidity, and perinatal morbidity. Our results described an inverse association between HDI and maternofetal morbidity and mortality. Moreover, the countries with an HDI lower than 1 showed higher rates of patients with maternal COVID-19-related morbidity (6.0% vs. 2.4%, p < 0.001), a need for oxygen therapy (4.7% vs. 1.8%, p < 0.001), and maternal ICU admission (2.6% vs. 1.0%, p = 0.007). Compared to other risk factors such as overweight, obesity, preexisting and obstetric comorbidities, HDI emerged as an independent risk factor explaining much of the increased maternal-perinatal morbidity and mortality detected in our group of cases. Further research is needed to establish to confirm the real impact of this factor and its components on pregnancy outcomes.