The COVID-19 pandemic has already led to over 94 million confirmed cases and over 2 million deaths globally (John Hopkins CRC, 2021). Due to the magnitude of the socio-economic damage of COVID-19 all over the world, we analyzed the critical country-level determinants of the death rate during the COVID-19 pandemic. We have examined the effects of GDP (allocated to pandemics and health), education, gender, cultural factors, number of physicians (per 1000 of the population) on the death rate. A correlation between the death rate and socio-economic conditions has been observed. The finding shows that power distance, individualism, gender, and age affect the death rate more than other socio-economic factors we use. We have also performed the same analysis by using Lockdown levels as a moderator. Lockdown levels have a more significant moderating effect on cultural factors rather than the other socio-economic factors. However, due to the topic's sensitivity, we still need to pay attention to the socio-economic factors that may have lower levels of significant relationship with the death rate, since even 0.1 % of changes in coefficients of our other socio-economic variables could mean thousands of lives. The study results will help health organizations, administration, and policymakers take the necessary steps to combat and manage the pandemic.

Social sustainability in organizations has been externally focused and, given its socio-ecological importance and potential, it requires further attention. This study examines social sustainability in business organizations (a) as an antecedent of environmental and economically related constructs, and (b) as a component of a multiplicity of relationships among social, environmental, and economically associated constructs. We examine a diverse set of 41 model configurations of 10 first-order constructs, and a diverse set of second-order constructs following a gradient ranging from a relatively moderate degree of order to quasi-random construct arrangements ending with model configurations fully determined at random. These sets reflect variability and commonality among respondents from various organizations, industries, and regions of the United States. Constructs may be antecedents, mediators, or outcomes. Analyses were conducted using PLS-SEM software. Results show (a) that social constructs are at the core of organizational life, given their frequent moderate to strong positive effects on other social constructs, as well as on environmental and economically related organizational constructs; and (b) construct variability within sustainability dimensions. Contributions include examining both constructs’ gradient ordering and constructs’ variability effects contingent on both construct nature and position. Theoretical and practical implications, as well as limitations and future research, are discussed.

This study explores several global and country cluster sustainable development (herein SD) models. It jointly examines constructs from the “Neoliberal-turn” ((e.g., Institutional Enhancers (e.g., business freedom, property rights, government integrity, and judicial effectiveness), Financial Enhancers (e.g., government spending and monetary, trade, investment, and financial freedoms), Foreign Direct Investment, Global Competitiveness-institutions, and Global Competitiveness-innovation-sophistication)), and the “Social-turn” (five SD pillars (e.g., Planet, People, Peace, Prosperity, and Resources), which synthesize the 17 United Nations SD goals); and Happiness and Life Satisfaction (herein H&LS). The study examines a large and diverse set of relationships encompassing 11 years of data of 108 social, economic, and environmental indicators from 129 countries at the global, country cluster, and country levels. We analyze data using structural equation modeling. Remarkably, Planet, an SD pillar constituted by biophysical variables, is the least of the five SD pillars positively related to the "neoliberal-turn" constructs and H&LS. Results show model configurations and scale effects. Furthermore, findings reveal both synergies between neoliberal and the five SD pillars as well as both negative and non-significant relationships among them. The diversity of results calls for further model integration and specificity. Diverse findings entail caution and difficulties in generalizing knowledge. Similarly, results suggest that it is not advisable, since there may be many different and partly legitimate alternatives, to rely on just one perspective (e.g., giving primacy to economic-based analyses) and or in analyses at only one scale. The perspective effects and the stakes involved in SD urgently call for more collaborative efforts at all levels.

This study explores several global and country cluster sustainable development (herein SD) models. It jointly examines constructs from the “Neoliberal-turn” ((e.g., Institutional Enhancers (e.g., business freedom, property rights, government integrity, and judicial effectiveness), Financial Enhancers (e.g., government spending and monetary, trade, investment, and financial freedoms), Foreign Direct Investment, Global Competitiveness-institutions, and Global Competitiveness-innovation-sophistication)), the “Social-turn” (five SD pillars (e.g., Planet, People, Peace, Prosperity, and Resources), which synthesize the 17 United Nations SD goals), and Happiness and Life Satisfaction (herein H&LS). This study examines a large and diverse set of relationships encompassing 11 years of data of 108 social, economic, and environmental indicators from 125 countries at the global, country cluster, and country levels. We analyze data using structural equation modeling. Remarkably, Planet, an SD pillar constituted by biophysical variables, is the least of the five SD pillars positively related to the “neoliberal-turn” constructs and H&LS. The results show model configurations and scale effects. Furthermore, the findings reveal both synergies between neoliberal and the five SD pillars, as well as both negative and nonsignificant relationships among them. The diversity of the results calls for further model integration and specificity. The diverse findings entail caution and difficulties in generalizing knowledge. Similarly, the results suggest that it is not advisable, since there may be many different and partly legitimate alternatives, to rely on just one perspective (e.g., giving primacy to economic-based analyses) and/or in analyses at only one scale. The perspective effects and the stakes involved in SD urgently call for more collaborative efforts at all levels.