Evaluating the social outcomes of COVID-19 pandemic: empirical evidence from Pakistan.

The study aims to assess and analyze the social outcomes of the COVID-19 pandemic. The study uses the discourse of comprehensive literature review to identify the outcomes, Interpretive Structural Modeling (ISM) for developing a structural model and Matrices' Impacts Cruise's Multiplication Appliquée a UN Classement (MICMAC) for analysis, classification of societal outcomes, and corroboration of results of ISM. Data from fifteen experts was collected through a survey questionnaire. As a result of the literature review, a list of sixteen outcomes was generated and verified by a panel of experts. Results of ISM revealed that the outcomes, namely, "emotional instability," "mental health self-harm," loneliness reduced recreational activities, obesity, and "increased screen time" come at the top of the model; therefore, they are less vital outcomes, whereas the most significant outcome which is at the bottom of the model is "employment instability"; hence it has a major impact on the society. The remaining outcomes fall in the middle of the model, so they have a moderate-severe impact. Results of MICMAC validate the findings of ISM. Overall findings of the study reveal that "employment instability" is the crucial social outcome of the COVID-19 pandemic. It is an original attempt based on real-time data, which is helpful for society at large, researchers, the international community, and policymakers because this study provides a lot of new information about the phenomenon. The study includes understanding society at large, policymakers, and researchers by illustrating the complex relations and simplifying the connections among a wide range of social outcomes of COVID-19.

Assessment of sustainable green financial environment: the underlying structure of monetary seismic aftershocks of the COVID-19 pandemic.

The study aims to assess a sustainable green financial environment by exploring the underlying structure of monetary seismic aftershocks of the COVID-19 pandemic. This study is qualitative and uses a review of literature, primary data collection methods, and qualitative analysis techniques as the study's overall design. The data is collected by one-to-one interview using a matrix style questionnaire from a panel of experts based on the purposive sampling technique. Interpretive structural modeling (ISM) combined with Matrices' Impacts Cruise's Multiplication Appliquée a UN Classement (MICMAC) is used for assessment, modeling, and analysis of data. The monetary aftershocks, namely, "more cash in hand required," "decreased travel costs," "shift to more certain or fixed revenue streams," "lower rent costs," "more zealous monitoring of cash collection cycle," and "decreased entertainment costs," occupy level I (top of the model being least critical shocks), and "tedious regulations" occupy level VIII (bottom of the model being the most vital). Other aftershocks form the middle of the model being moderate critical. Analysis of MICMAC shows that monetary seismic aftershocks high fees for assistance regarding SOPs, tedious regulations, and more downtime due to pandemic alerts are independent. This study addresses the core issue from within the aftermath of the COVID-19 pandemic. It provides new important information regarding the structure of a sustainable green financial environment that is useful for economists, financial analysts, commercial and central bankers, accountants and finance managers from the organization's public/and private sectors, local and international community, and researchers of the domain. It provides an informative structural model and classification of critical aftershocks. There are specific data/methodological/resource-related limitations of the study. The study's data are collected from a focus group; the study's methodology is qualitative and indicates relations among variables that do not quantify the associations. The study is a typical initiative of academic researchers with limited financial/physical resources; therefore, the generalizability of the study results is accordingly limited. The study is based on original, essential data and innovatively and creatively approaches the problem. It provides a unique model of an unprecedented phenomenon for reverberating the sustainable green financial environment.

Effects of the COVID-19 Pandemic on the Success of Traditional Small and Medium Enterprises (SMEs): An Investigation of the Footprints of Economic Crisis Attributable to COVID-19.

The COVID-19 pandemic created a significant economic decline and altered market behavior, forcing buyers and dealers online. The traditional local market merchants are not fully equipped with e-commerce business techniques and strategies, which is a barrier to their e-commerce behavior and success. The study aims to help small-medium firms adapt to an uncertain economic environment instead of reducing or shutting down business-like in Pakistan. From health to education, economy to domestic and social protection, various researches have been done since 2020. The researcher used primary data sources and did a Quantitative study after collecting the 240 samples size of data from the successful e-commerce players of Pakistan. The results confirm that customer satisfaction is essential for entrepreneurs to succeed, as customers were not satisfied with online shopping during COVID-19. Customer knowledge management (CKM) and job satisfaction (JS) are studied as potential and realized capacity variables. CKM act as a strategic asset to collect and assimilate the external customer knowledge. In contrast, satisfied employees act as a valuable asset that dynamically responds to changing customer needs and business environment by efficiently utilizing their knowledge and skills and reaching business success which is mirrored in customer satisfaction. Conclusive results enable practitioners to perceive the business success during economic crises in the organization's absorptive capacity.

Understanding the interaction among enablers of quality enhancement of higher business education in Pakistan.

This study aims to generate a list of enablers of quality enhancement of higher business education in Pakistan and build a structural model of enablers to prioritize them. It also intends to impose direction and hierarchy on the inter-relationships of the enablers. The study's design consists of a literature review, data collection from primary sources, and qualitative analysis. Interpretive Structural Modeling (ISM) coupled with Matriced' Impacts Cruise's Multiplication Appliquée a UN Classement (MICMAC) is used as a research methodology. The classical procedure of ISM and MICMAC is applied to primary data collected by a field survey from a panel of experts recruited from folks of stakeholders of business education. Results of the literature show that eighteen critical enablers enhance the quality of higher business education in Pakistan. Results of ISM show that the enabler 'job placement of graduates' occupies the top-level of the ISM model being least critical. In contrast, the enabler 'intra-academia linkages' occupying the bottom of the model is the most vital. Results of MICMAC show that all enablers, except 'job placement of graduates, are classified into linkage clusters, whereas 'job placement of graduates' is classified as an independent cluster. Overall results of the study show that enablers of quality enhancement of higher business education in Pakistan are agile and not settled. The study has profound theoretical, managerial, and practical implications for all stakeholders of business education. It also provides a research framework for future studies concerning subject phenomena. The discussion about the structural model culminates into policy guidelines for the regulators. The study is subject to some methodological/data/resources limitations like the limited review of literature, collection of data from a medium-size panel of experts from Pakistan only, using majority rule for aggregating responses, answering only that what is related to what, other common limitations of qualitative studies, shot period and absence of financial support. The authors conduct this study in a real-life field setting is built on the original dataset and address the efficient issue of phenomenon understudy differently. It is theory-building research, therefore, does not require prior theory. It exploits simple elementary concepts of Boolean algebra, set theory, and graph theory that generates new in-depth information for stakeholders.

Analyzing the Stressors for Frontline Soldiers Fighting Against Coronavirus Disease 2019 Pandemic.

This study aimed to analyze stressors to which medical staff is vulnerable due to the coronavirus disease 2019 (COVID-19) pandemic. It also imposes a hierarchy on complex relations among stressors for excavating underlying structure and builds a model of interrelationships contrasting reality. The design of this study comprises a literature survey, data collection from primary sources, and analysis. Stressors have been explored from within current published/unpublished literature and validated by experts through approval vote. Data were collected from the focus group (panel of experts), and interpretive structural modeling (ISM) was used as the research methodology. Findings of ISM are avowed through "cross-impact matrix multiplication applied to classification" (MICMAC) analysis. As a result of the literature survey, a list of stressors was generated, and a total of 19 stressors qualified as representative of the phenomenon. The results of ISM show that two stressors (i.e., "unavailability of proper personal protective equipment (PPE)" and "lack of proper communication") emerged as the most critical stressors since they occupy the bottom of the model, whereas, four stressors (i.e., "anxious about isolation/quarantine," "subject to violent crimes," "feeling frustrated and powerless," and "exhausting shifts/hours without clear end") are relatively less critical since they occupy the top of the model. The rest of the stressors occupy the middle of the model and therefore, have moderate-severe effects on frontline soldiers. The results of MICMAC show that the stressor "subject to violent crimes" is classified in the dependent cluster and the remaining fall in the linkage cluster but no stressor falls in independent and autonomous. Overall results indicate that all stressors are relevant to the phenomenon under this study, but they are currently not settled. This study is invaluable for policymakers, frontline soldiers, researchers, the international community, and society since it provides a lot of new information that is helpful in refining strategies and combating influential stressors.

Structural Modeling on the Determinants of Effectiveness of SOPs Containing COVID-19 in Mass Gatherings.

The study is aimed to analyze the determinants of the effectiveness of SOPs in mass gatherings for containing COVID-19. The overall design of the study involves a literature review, data collection by field survey, structural modeling, and analysis. The study is built on the experts' opinion of a focus group (representing people who recently participated in and are responsible for mass gatherings). The study uses the discussion of the literature review to identify the determinants, interpretive structural modeling (ISM) for developing and analyzing a structural model, and Matrice d'Impacts Croises Multiplication Appliquée a un Classement (MICMAC) for corroboration of results of the ISM/classification of determinants. From the literature review, a list of determinants is generated and verified by a panel of experts. The results of the ISM revealed that the determinants "legal environment of the country," "practicability of SOPs," "perceived benefit of adapting SOPs," and "possibilities of avoiding gathering" occupied the top of the model, therefore, they are less critical determinants, whereas "nature of gathering" occupied the bottom of the model, and is thus the most critical determinant. The remaining determinants form the middle of the model, and are therefore moderately severe. The results of MICMAC show that the determinant "perceived benefit of adapting SOPs" is dependent, "nature of gathering" is independent, and all others are linked. The results of MICMAC implicitly substantiate the findings of the ISM. The overall results of the study show that "nature of gathering" is the key determinant. This research does not require a priori theory since it is a theory-building study that uses an inductive approach. It is based on real data and it is useful for local authorities, organizers, participants (attendees/visitors) of mass gatherings, health officials/regulators, researchers, and the community at large. This study has fundamental importance for planning and preparing for such events while ensuring the minimum risk of COVID-19 transmission.

Evaluating the Immediate Response of Country-Wide Health Systems to the Covid-19 Pandemic: Applying the Gray Incidence Analysis Model.

The purpose of the study is to evaluate county-wide health systems using the data set of the first wave of the COVID-19 pandemic. The overall design of study comprises a literature review, secondary data, and a mathematical analysis. It is a cross-sectional quantitative study following a deductive approach. It uses the data of the first wave of the COVID-19 pandemic taken from the website of Worldometer as of April 8, 2020. The study uses a gray incidence analysis model (commonly known as Gray Relational Analysis, i.e., GRA) as its research methodology. On the basis of the results of GRA, a classification has been made under a predetermined scheme of ensigns: much better, better, somewhat better, fair, poor, somewhat worse, and worse health systems. There are a total 211 countries that have been divided into the seven aforementioned categories. Findings of the study show that Southern Africa Development Community (SADC) countries fall predominantly under the much better ensign, whereas Organization for Economic Co-operation and Development (OECD), Schengen Area (SA), and/or European Union (EU) countries fall under the worse ensign. Pakistan falls under the ensign of poor. It is an original attempt to evaluate the response of health systems based on real data using a scientific methodology. The study provides valuable information about the health systems of the countries for forming an informed opinion about the health systems herein. The study provides useful new information for stakeholders and a new framework for future research.

Analyzing the Underlying Structure of Online Teaching During the COVID-19 Pandemic Period: An Empirical Investigation of Issues of Students.

The aim of the study is to reveal the underlying structure of issues of university students taking online classes during the COVID-19 pandemic period. The overall design of the study includes a review of contemporary literature and field survey for data collection and analysis. Discourse of literature coupled with expert opinion has been employed for identification of issues. Interpretive Structural Modeling (ISM) is used for the determination of intra-issue relationships and analyzing the underlying structure. Cross impact matrix multiplication applied to classification (MICMAC analysis) is used as a technique for classifying issues on the basis of driving-dependence power. Results of the literature show that there are 21 major issues faced by the students taking online classes. ISM shows that lack of institutional guidelines, lack of regulators' guidelines, stress of pandemic situation, and abrupt (not planned) start of online classes are the most critical issues. MICMAC analysis reveals that there is no autonomous issue, 4 (i.e., connectivity issue, shy to use technology, lack of institutional guidelines, and stress of pandemic situation) are independent, 6 other issues are dependent, and the remaining 11 are linking. This is a valuable study having practical implications for regulators, students, parents, and society to understand the current problem. It is an original attempt that contributes toward literature in the form of a structural model and a diagram of classification of issues.