Do ESG Risk Scores Influence Financial Distress? Evidence from a Dynamic NDEA Approach

Financial distress is a research topic in finance that has attracted attention from academia following past financial crises. Although previous studies associate financial distress with several elements, the relationship between distress and ESG has not been broadly explored. This paper investigates these issues by elaborating a Dynamic Network DEA model to address the underlying connections between accounting and financial indicators. Thus, a model that includes profit and loss, balance sheet, and capital and operating expenditures indicators is demonstrated under the dynamic network structure to compute financial-distress efficiency scores. Then, the impact of carryovers is considered for the accurate calculation of efficiency scores for the three substructures. The influence of contextual variables, such as socioeconomic and macroeconomic variables, and whether the firm owns an ESG Risk Score or not, is assessed through a stochastic non-linear model that combines three distinct regression types: Simplex, Tobit, and Beta. The results indicate that firms that hold an ESG Risk Score are less prone to be in financial distress, and Governance Score is negatively associated with financial distress efficiency.

How, When, & Where Temporary Hospitals Fit in Turbulent Times: A Hybrid MADM Optimization in the Middle East.

Governments have been challenged to provide temporary hospitals and other types of facilities to face the COVID-19 pandemic. This research proposes a novel multi-attribute decision-making (MADM) model to help determine how, when, and where these temporary facilities should be installed based on a set of critical success factors (CSFs) mapped in an uncertain environment. We portray the available facilities for temporary hospitals based on the CSFs that must be considered to make critical decisions regarding the optimal position based on the government's strategic decision-making process, thus indirectly providing better services and maximizing resources. In relation to earlier work, this research builds upon hybrid Pythagorean fuzzy numbers to find weights in Best-Worst Methods and rank temporary facilities based on evaluation by an area-based method for ranking. Policy implications and future directions are derived.

Impacts of the COVID-19 on all aircraft emissions of international routes in South America.

The COVID-19 pandemic has had a significant impact on South America's economic development, as well as its international civil aviation industry. This paper seeks to calculate the emissions of six pollutions (CO2, CO, HC, NOx, SO2, and PM2.5) from the international routes in South America during 2019-2021 and discusses the impacts of COVID-19 on the emission change. The modified BFFM2-FOA-FPM method is proposed to unify the CO2 and non-CO2 calculations. The calculated results' average error rate is about 5.12%. The results showed that COVID-19 affected all emissions, including the number of routes, average flight distance, aircraft configuration, the proportion of CCD phase emissions, average emissions, etc. In addition, some airlines increased the number of flights and aircraft types during the pandemic, increasing emissions. The results give a reasonable data basis for the aviation industry in South America to formulate emission reduction policies.

Towards an improved understanding of the antecedents of digital health service loyalty during a pandemic: An fsQCA approach

Loyalty towards digital health services has received unprecedented attention and acceptance during the Covid-19 pandemic period. However, whether this popularity will be retained into the future and the factors that can influence such loyalty is undetermined. This paper provides insight into this issue through a cross-cultural examination of the influence of digital service quality (e-quality) on consumer satisfaction and loyalty (e-loyalty) in the digital health service sector during a pandemic. A fuzzy-set qualitative comparative analysis (fsQCA) is applied using a sample of 50 customers drawn from different professions across different countries who actively showed loyalty towards digital health during the pandemic. Research constructs evaluation for reliability and internal consistency was subsequently performed using Cronbach's alpha and Correlation analysis. The results reveal a significant positive relationship between service quality and the twin outcomes of consumer satisfaction and loyalty, while the findings established satisfaction as a prominent mediator for digital health. Findings from the fsQCA analysis identified four core factors that underpin loyalty in digital health platforms. Alternative paths have been identified based on gender, current education status, and other professions. In addition, two topologies are introduced taking digital health services from different platforms during the pandemic. Because of the primary nature of the data, this is first-hand experience gathered from the people who are directly or indirectly involved in receiving help from digital health services in a pandemic context. The application of the fsQCA technique for examining loyalty towards digital health services is applied in the e-health or digital health literature for the first time. The study findings will assist digital health service providers seeking insight into the factors that influence loyalty of e-health service consumers, enabling them to focus more accurately on the service quality dimensions that are effective in influencing consumer satisfaction and retention. The findings of this study contain a number of contributions, illustrating different topologies towards digital health that provide educators and policymakers with valuable insights.

Modeling Inventory Cost Savings and Supply Chain Success Factors: A Hybrid Robust Compromise Multi-Criteria Approach

Determining success factors for managing supply chains is a relevant aspect for companies. Then, modeling the relationship between inventory cost savings and supply chain success factors is a route for stating such a determination. This is particularly important in pharmacies and food nutrition services (FNS), where the advances made on this topic are still scarce. In this article, we propose and formulate a robust compromise (RoCo) multi-criteria model based on non-linear programming and time-dependent demand. The novelty of our proposal is in defining a score that allows us to measure the mentioned success factors in a simple way, in meeting together all three elements (RoCo multi-criteria, non-linear programming, and time-dependent demand) to state a new model, and in applying it to pharmacies and FNS. This model relates inventory cost savings for pharmacy/FNS and success factors across their supply chains. Savings of inventory costs are predicted by lot sizes to be purchased and computed by comparing optimal and true inventory costs. We utilize a system that records the movements and costs of products to collect the data. Factors, such as purchasing organization, economies of scale, and synchronized supply, are assumed using the purchase system, with these factors ranked on a Likert scale. We consider multilevel relationships between savings obtained for 79 pharmacy/FNS products, and success factor scores according to these products. To deal with the endogeneity bias of the relationships proposed, internal instrumental variables are employed by utilizing generalized statistical moments. Among our main conclusions, we state that the greatest cost savings obtained from inventory models are directly associated with low-success supply chain factors. In this association, the success factors operate as endogenous variables, with respect to inventory cost savings, given the simultaneity of their relationship with cost savings when inventory decision-making.

The impact of social welfare and COVID-19 stringency on the perceived utility of food apps: A hybrid MCDM approach.

The COVID-19 pandemic has created enormous challenges for society due to the various ways of impacting health. This paper focuses on the impact of the COVID-19 pandemic on people's food consumption patterns in the online environment. We investigate food app reviews and examine whether countries with a high rate of success with COVID-19 control consume more unhealthy food through mobile apps. We also investigate whether the population of countries with low social welfare eat more unhealthy food during the COVID-19 pandemic compared to countries with high social welfare. We take a hybrid multi-criteria decision making (MCDM) approach to calculate indexes based on the technique for order of preference by similarity to an ideal solution, complex proportional assessment, and VlseKriterijuska Optimizacija I Komoromisno Resenje. Results show that country social welfare and success in COVID-19 control negatively affect the perceived utility of the apps. Also, success in COVID-19 control and the perceived utility of food apps positively affect the proportion of unhealthy reviews, whereas social welfare has a negative impact. The results have important implications for public health policymakers, showing that the online food environment can be an important setting for interventions that seek to incentivize healthy eating.

Antecedents of Perceived Service Quality of Online Education During a Pandemic: Configuration Analysis Based on Fuzzy-Set Qualitative Comparative Analysis.

BACKGROUND: During COVID-19 lockdown worldwide, classroom education continues remotely through online. The question remains, comparing with the face-to-face education, does online education has a similar satisfaction level among the students? There are only a few studies that examine the perceived service quality of online education. OBJECTIVE: The study aims to analyze the factors of perceived service quality of online education during a pandemic. RESEARCH DESIGN: A structured questionnaire elicits information from 147 students from different study backgrounds of various universities worldwide. The fuzzy-set qualitative comparative analysis (fsQCA) is used for data analysis and model design. Research constructs evaluation for reliability and internal consistency are subsequently performed. A snowball random sampling method is applied for data collection. RESULTS: Findings from the fsQCA analysis identify four core factors that underpin student satisfaction through positive perceived service quality of online education. Alternative paths are determined based on gender, students' current education status, and their loyalty toward online education. We also introduce two topologies of perceived quality regarding online education and student satisfaction. ORIGINALITY: Because of the primary nature of the data, this is firsthand experience gathered from different universities around the world who have willingly or unwillingly experienced online learning during the pandemic. The fsQCA technique for examining perceived service quality of online education. CONCLUSIONS: The findings contain a number of contributions, illustrating different topologies of the student from different backgrounds and their intention, satisfaction and loyalty towards e-learning, and identifying causal factors that influence willingness to recommend online education.

Inventory pooling decisions under demand scenarios in times of COVID-19.

Governments have been challenged to provide timely medical care to face the COVID-19 pandemic. The aim of this research is to propose a novel inventory pooling model to help determine order sizes and safety inventories in local hospital warehouses. The current study attempts to portray the availability of pharmaceutical items in public hospitals facing COVID-19 challenges. Different from previous studies, this research builds upon the consecrated theory of inventory pooling, extending it to pandemic circumstances where the intractability of kurtosis and skewness in inventory models are critical issues for making sure that medicines have high availability at a low cost. These effects on the total cost of inventory are explored and compared to a supply system with no consolidation. A continuous-review model is assumed with allocation rules for centralization and regular transshipment given different skewness and kurtosis structures for the demand, describing them by the copula method. This method models a multivariate demand considering that the marginal distributions of the demand can be specified by the Generalized Additive Model for Location, Scale and Shape, which offers advantages to model demands considering virtually any marginal statistical distribution. Numerical simulations and an illustrative example show that distributions of demands with more negative skewness and high kurtosis favor to a greater extent obtaining lower total costs with regular supply transshipment systems. Our study points out important considerations for supply chain decision makers when having demands with skewness and kurtosis patterns.

Critical Success Factors for Competitive Advantage in Iranian Pharmaceutical Companies: A Comprehensive MCDM Approach

The unprecedented COVID-19 outbreak strengthened the critical manifestation of the rapid development vs. survival for pharmaceutical companies, deploying strategic conduct worldwide. This study therefore explores the endogenous relationship among pharmaceutical companies' manufacturing strategy and their performance indicators within the ambit of creating a long-lasting competitive advantage in turbulent times. Very often, it is not possible to launch a cause-effect relationship between performance and their drivers. To achieve this end, multiple-criteria decision-making (MCDM) techniques are employed in a hybrid fashion in this study. The notion has simultaneously ranked critical success factors (CSFs) in the manufacturing strategy and performance indicators in the limelight of managerial perceptions, while controlling the inherent bias concerning the causality direction in the ambit of these two entrenched concepts. A case study on the Iranian pharmaceutical companies is piloted to demonstrate this hybrid-fashion multifarious approach. Overall, the results revealed the most pertinent CSFs that reached superior-performance echelons in the Islamic Republic of Iran. [ABSTRACT FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modelling stock market data in China: Crisis and Coronavirus.

Global financial markets experienced distinct collapses during the global financial crisis in 2008 and the COVID-19 pandemic in 2020, and similarity in the underlying nature is still a hot topic to be investigated. This paper investigates their degree of persistence in order to detect whether the shocks affecting them have temporary or permanent effects by examining the closing prices of the Shanghai and Shenzhen Composite Indices from 1991 to 2020. The results before the coronavirus indicate large degrees of persistence with shocks having permanent effects, while during the coronavirus the results indicate a mean reversion with shocks having temporary effects.