Organizational Identification and Alternative Job Opportunities of Hotel Internship Students During COVID-19

This study highlights the major challenges faced by hotel interns in their career development and the human resource management of hotels in the current macroeconomic environment, particularly during the COVID-19 pandemic. The paper developed a conceptual model for organizational identification, turnover intention, and perceived alternative job opportunities in the context of hotel internships. A total of 350 samples were collected from hotel internships in Macau. The presented results indicate that organizational identification has a significant negative impact on turnover intention. In addition, alternative job opportunities do not moderate the relationship between organizational identification and turnover intention. The results also showed that females had a higher level of evaluative identification for hotel internships compared to males. In addition, interns from high-income families had a higher level of evaluative identification compared to those from low- and middle-income families. The theoretical contribution extends the concept of organizational socialization to include internship stages in the field of hospitality management. Finally, this paper proposes measures for managing hotel internships during the COVID-19 pandemic.

Performance Analysis of Learner Behavior Through Online Learning Using Learning Management System

This paper discusses the performance analysis of learner behavior through online learning using Learning Management System (LMS). The analysis is performed based on the survey of lecturers and students activities. The parameters of survey consist of the problems discussion which arise in the online learning, the level of student absorption of lecture material, the level of student attendance, and the feedback on lecturer performance carried out by students. Problems that arise in the online learning include lecturers are not being able to control as much as 37%, network disturbances are as much as 22%, students having difficulty understanding lecture material are as much as 19% which are indicated by students with D score of 10%, C score of 60%, and B score of 30%. Meanwhile 17% of students use LMS and the remaining 5% have no problems with the online learning. On the other hand, students have difficulty obtaining connection for online learning of 45%, do not have a quota of 28%, and lazy of 17%. Lecturer performance feedback carried out by students based on competency parameters of pedagogic, personality, professionalism, and social shows very good score. © 2023 IEEE.

COVID-19 Data Prediction and Visualization in Mainland China

Contemporarily, COVID-19 shows a sign of recurrence in Mainland China. To better understand the situation, this paper investigates the growth pattern of COVID-19 based on the research of past data through regression models. The proposed work collects the data on COVID-19 in Mainland China from January 21st, 2020, to April 30th, 2020, including confirmed, recovered, and death cases. Based on polynomial regression and support vector machine regressor, it predicts the further trend of COVID-19. The paper uses root mean squared error to evaluate the performance of both models and concludes that there is no best model due to the high frequency of daily changes. According to the analysis, support vector machine regressors fit the growth of COVID-19 confirmed case better than polynomial regression does. The best solution is to utilize different types of models to generate a range of prediction result. These results shed light on guiding further exploration of the growth of COVID-19. © 2023 SPIE.

Emotional well-being and performance of middle leaders: the role of organisational trust in early childhood education

PurposeThe current study investigated the impact of organisational trust on emotional well-being and performance of middle leaders during the coronavirus disease 2019 (COVID-19) pandemic.Design/methodology/approachA convenience sample of 265 middle leaders in kindergartens in China responded involving trust in schools (e.g. trust in principal and trust in colleagues), emotional well-being and job performance. Both confirmatory factor analysis and structural equation modelling (SEM) were used in the investigation.FindingsThree hypotheses on the relationships between the three constructs were verified. Trust in schools significantly influenced emotional well-being and job performance of middle leaders which correlated with each other. The interactive effects of trust in principal and trust in colleagues were discussed for improving the well-being and job performance of middle leaders. Relationships between the two kinds of trust and pride were also identified in the research.Research limitations/implicationsFurther studies may put efforts towards improving these three outcomes synchronously.Practical implicationsBased on the evidence of the current study, future research may focus on how middle leaders act as a bridging role between different stakeholders such as principal and teachers, principal and parents, teachers and children, meanwhile how to boost the leaders' own well-being and performance in the early childhood education (ECE).Originality/valueThis study established the empirical linkages between school trusts, emotional well-being and job performance.

Evaluation of a Video Generation Method Linking Dance and Scenes

Owing to the impact of COVID-19, the venues for dancers to perform have shifted from the stage to the media. In this study, we focus on the creation of dance videos that allow audiences to feel a sense of excitement without disturbing their awareness of the dance subject and propose a video generation method that links the dance and the scene by utilizing a sound detection method and an object detection algorithm. The generated video was evaluated using the Semantic Differential method, and it was confirmed that the proposed method could transform the original video into an uplifting video without any sense of discomfort. © 2023 SPIE.

A study on the assessment of risk management performance in maritime start-ups: evidence from China

Due to the COVID-19 pandemic, the international shipping market has been highly volatile, posing a serious threat to the survival and development of many maritime start-ups. With the development of the digital economy, digital transformation is affecting the evolution and upgrading of many traditional enterprises, including maritime enterprises. In the post-COVID-19 era, start-up small and medium-sized enterprises will need to consider the importance of enterprise risk management to achieve transformation and upgrading. The purpose of this study is to provide guidance for the establishment and upgrading of risk management systems for start-ups based on the identification of risk management strategies of maritime enterprises and the evaluation of their performance. The fuzzy analytic hierarchy process and importance-performance analysis methods were used to rank the operational risk, financial risk, market risk, innovation risk, and disaster risk according to sub-items and screen out the risk management schemes for priority improvements. Through empirical research, it was found that the financial risk and market risk response schemes have the lowest performance and need to be prioritised for improvement. This study argues that start-ups can appropriately challenge their risk management strategies to meet potential risk management needs based on their own circumstances.

Predicting the climate impact of aviation for en-route emissions: the algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53

Using climate-optimized flight trajectories is one essential measure to reduce aviation's climate impact. Detailed knowledge of temporal and spatial climate sensitivity for aviation emissions in the atmosphere is required to realize such a climate mitigation measure. The algorithmic Climate Change Functions (aCCFs) represent the basis for such purposes. This paper presents the first version of the Algorithmic Climate Change Function submodel (ACCF 1.0) within the European Centre HAMburg general circulation model (ECHAM) and Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model framework. In the ACCF 1.0, we implement a set of aCCFs (version 1.0) to estimate the average temperature response over 20 years (ATR20) resulting from aviation CO2 emissions and non-CO2 impacts, such as NOx emissions (via ozone production and methane destruction), water vapour emissions, and contrail cirrus. While the aCCF concept has been introduced in previous research, here, we publish a consistent set of aCCF formulas in terms of fuel scenario, metric, and efficacy for the first time. In particular, this paper elaborates on contrail aCCF development, which has not been published before. ACCF 1.0 uses the simulated atmospheric conditions at the emission location as input to calculate the ATR20 per unit of fuel burned, per NOx emitted, or per flown kilometre.In this research, we perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by ACCF 1.0 to previous studies. The comparison confirms that in the Northern Hemisphere between 150–300 hPa altitude (flight corridor), the vertical and latitudinal structure of NOx-induced ozone and H2O effects are well represented by the ACCF model output. The NOx-induced methane effects increase towards lower altitudes and higher latitudes, which behaves differently from the existing literature. For contrail cirrus, the climatological pattern of the ACCF model output corresponds with the literature, except that contrail-cirrus aCCF generates values at low altitudes near polar regions, which is caused by the conditions set up for contrail formation. Secondly, we evaluate the reduction of NOx-induced ozone effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). The simulation results show that climate-optimized trajectories reduce the radiative forcing contribution from aviation NOx-induced ozone compared to cost-optimized trajectories. Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effects is considered. Based on the 1 d simulation results of a subset of European flights, the total ATR20 of the climate-optimized flights is significantly lower (roughly 50 % less) than that of the cost-optimized flights, with the most considerable contribution from contrail cirrus. The CO2 contribution observed in this study is low compared with the non-CO2 effects, which requires further diagnosis.

Preparation and Properties of an Efficient Purification Material for Personal Protection

At present, the filtration of virus and other small particles in the air by meltblown cloth produced by electret treatment mainly depends on its electrostatic adsorption mechanism. However, because the surface charge of melt blown fabric can not be maintained for a long time, it can not maintain high efficiency filtration for a long time. Therefore, there is no guarantee for the medical staffs to not be infected by COVID-19. Therefore, it is necessary to improve the mechanical filtration efficiency of melt blown fabric in the situation of an electric charge loss. In this paper, nylon 6 (PA6) nanofibers were electrospun on melt blown cloth by electrospinning technology, and a sandwich material with melt blown cloth as surface layer and PA6 nanofibers as middle layer was made by hot- pressing technology;the surface morphology, thermal and mechanical properties of the sandwich material were characterized, and its filtration performance was tested. The experimental results show that the surface integrity of the sandwich material is high, and the diameter of nanofibers can reach about 67 nm;without the electret treatment, the filtration efficiency of the sandwich material for particles in an size of 0.2 μm is more than 95%,while the filtration efficiency of non-woven fabric is zero;the filtration resistance of the material is about 284 Pa, which is suitable for personal protection. © 2023 Chengdu University of Science and Technology. All rights reserved.

GPU libraries speed performance analysis for RCWA simulation matrix operations

Rigorous Coupled Wave Analysis (RCWA) method is highly efficient for the simulation of diffraction efficiency and field distribution patterns in periodic structures and textured optoelectronic devices. GPU has been increasingly used in complex scientific problems such as climate simulation and the latest Covid-19 spread model. In this paper, we break down the RCWA simulation problem to key computational steps (eigensystem solution, matrix inversion/multiplication) and investigate speed performance provided by optimized linear algebra GPU libraries in comparison to multithreaded Intel MKL CPU library running on IRIDIS 5 supercomputer (1 NVIDIA v100 GPU and 40 Intel Xeon Gold 6138 cores CPU). Our work shows that GPU outperforms CPU significantly for all required steps. Eigensystem solution becomes 60% faster, Matrix inversion improves with size achieving 8x faster for large matrixes. Most significantly, matrix multiplication becomes 40x faster for small and 5x faster for large matrix sizes. © 2023 SPIE.

The Relationship between Movement Control Order Impact Factors and Construction Project Performance

The Malaysian government's pursuit of the Movement Control Order (MCO) had a severe impact on the performance of the construction project, which was hampered as a result of their actions. It becomes even more difficult when the region around construction projects is defined as a "red zone". This situation affects the performance of construction projects, which is related to project delays, increase in construction costs, waste of construction materials, labourers who have not received any salary, lack of labour, and etc. This paper attempts to investigate the relationship between MCO impact factors and the performance of construction projects in Malaysia. The quantitative technique was applied in this study. The contractors registered under the Construction Development Board (CIDB) in the state of Selangor were chosen as the respondents. In total, 100 respondents participated and gave full support for this study. This relationship was investigated using a correlation analysis technique. The highest impact is the construction cost. The construction costs increased due to the increase in the prices of construction materials and machinery, lack of labours, and additional expenses for COVID-19 precautions. The findings found that the larger the negative impact of MCO's actions during the COVID-19 outbreak on time, cost, and resources, the worse the performance of Malaysian projects will be in general. These factors should be considered by the government before a decision is made. For future research, it is suggested to look at how the regulation can assist the construction stakeholders to ensure the MCO does not have a big impact on the construction projects.

Non-Hodgkin's lymphoma complicated with human coronavirus HKU1 pneumonia: A case report and literature review.

Objective: To analyze the clinical manifestations, diagnostic methods and treatment process of the patients with non-Hodgkin's lymphoma complicated with human coronavirus(HCoV)-HKU1 pneumonia and improve the clinical medical staff's awareness of the disease, and to reduce the occurrence of clinical adverse events. Method(s): The clinical data of a patient with non-Hodgkin's lymphoma complicated with HCoV-HKU1 pneumonia with hot flashes and night sweats, dry cough and dry throat as the main clinical features who were hospitalized in the hospital in January 2021 were analyzed, and the relevant literatures were reviewed and the clinical manifestations and diagnosis of HCoV-HKU1 were analyzed. Result(s): The female patient was admitted to the hospital due to diagnosed non-Hodgkin's lymphoma for more than 2 months. The physical examination results showed Karnofsky score was 90 points;there was no palpable enlargement of systemic superfical lymph nodes;mild tenderness in the right lower abdomen, no rebound tenderness, and slightly thicker breath sounds in both lungs were found, and a few moist rales were heard in both lower lungs. The chest CT results showed diffuse exudative foci in both lungs, and the number of white blood cells in the urine analysis was 158 muL-1;next generation sequencing technique(NGS) was used the detect the bronchoalveolar lavage fluid, and HCoV-HKU1 pneumonia was diagnosed. At admission, the patient had symptoms such as dull pain in the right lower abdomen, nighttime cough, and night sweats;antiviral treatment with oseltamivir was ineffective. After treatment with Compound Sulfamethoxazole Tablets and Lianhua Qingwen Granules, the respiratory symptoms of the patient disappeared. The re-examination chest CT results showed the exudation was absorbed. Conclusion(s): The clinical symptoms of the patients with non-Hodgkin's lymphoma complicated with HCoV-HKU1 pneumonia are non-specific. When the diffuse shadow changes in the lungs are found in clinic, and the new coronavirus nucleic acid test is negative, attention should still be paid to the possibility of other HCoV infections. The NGS can efficiently screen the infectious pathogens, which is beneficial to guide the diagnosis and treatment of pulmonary infectious diseases more accurately.Copyright © 2023 Jilin University Press. All rights reserved.

Long-term support of COVID-19 patients with veno-venous extracorporeal membrane oxygenation: Complications, predictors of mortality and long-term outcome

Objectives: Treatment of severe respiratory distress syndrome (ARDS) due to COVID-19 by veno-venous extracorporeal membrane oxygenation (VV-ECMO) had a mortality of up to 70% in Germany. Many patients with COVID-19 need VV-ECMO support longer than 28 days (long-term VV-ECMO). Evidence on mortality, complications during intensive care, functional status after discharge and mortality-predictors for patients supported with long-term VV-ECMO is lacking. Method(s): Retrospective study of 137 consecutive patients treated with VV-ECMO for ARDS due to COVID-19 at University Hospital Regensburg from March 2020 to March 2022. Result(s): 38% (n=52;87% male) of patients needed longterm VV-ECMO support. In these, SOFA score (median [IQR]) at ECMO initiation was 9 [8-11], age 58.2 [50.6- 62.5] years, PaO2/FiO2-ratio 67 [52-88] mmHg, pCO262 [52-74] mmHg, Murray-Score 3.3 [3.0-3.6] and PEEP 15 [13 - 16] cmH2O. Duration of long-term support was 45 [35-65] days. 26 (50%) patients were discharged from the ICU. Only one patient died after hospital discharge. At VVECMO initiation, baseline characteristics did not differ between deceased and survivors. Complications were frequent (acute kidney injury: 31/52, renal replacement therapy: 14/52, pulmonary embolism: 21/52, intracranial hemorrhage 8/52, major bleeding 34/52 and secondary sclerosing cholangitis: 5/52) and more frequent in the deceased. Karnofsky index (normal 100) after rehabilitation was 70 [57.5-82.5]. Twelve of the 18 patients discharged from rehabilitation had a satisfactory quality of life according to their own subjective assessment. Four patients required nursing support. Mortality-predictors within the first 30 days on VV-ECMO only observed in those who deceased later, were: Bilirubin >5mg/dl for > 7 days, pulmonary compliance <10ml/mbar for >14 days, and repeated serum concentrations of interleukin 8 >150ng/L. Conclusion(s): Long-term extracorporeal lung support in patients with COVID-19 resulted in 50 % survival and subsequently lead to a satisfactory quality of life and functionality in the majority of patients. It should preferably be performed in experienced centers because of a high incidence of complications. Several findings during the early course were associated with late mortality but need validation in large prospective studies.

Port strategy and performance: empirical evidence from major container ports and implications for role of data analytics

Container ports operate in more challenging and volatile environments at present times. Events such as US-China trade tensions and the COVID-19 pandemic severely affect numerous container ports at various levels. Strategies pursued by container ports are key to port development and management amidst these challenges. Drawing on configuration theory, this research employs Fuzzy-set Qualitative Comparative Analysis to investigate the relation between port strategies and container throughput. The research contributes to the literature by proposing an approach to account for complexity of the port sector and offers insights into strategies adopted by major container ports. The research further identifies 10 port strategies and proposed indicators that can represent the essence of these strategies. Being able to represent strategies in a quantitative format is important for strategy analysis and performance evaluation. Results reveal that major container ports employ a combination of strategies which address both the supply and demand-side aspects of the port business. Growing digitalization and digitization coupled with advancements in information capture, diagnostics capabilities and predictive abilities means a greater role for data analytics to influence container port strategy and performance. Implications for port managers, policy makers and researchers from the perspective of port policy and management are proposed.

The effect of the emergency shift to virtual instruction on student team dynamics

In spite of the sudden onset of the COVID-19 pandemic, many instructors who used team-based pedagogies shifted them online rather than suspending them entirely, but with limited time and resources. To examine the difference in team dynamics and outcomes for courses in Spring 2019 and Spring 2020 of over 1500 first-year engineering students per semester, Wilcoxon signed-rank tests and random forests method were used. Results show that students reported less improvement in team-member effectiveness, lower psychological safety, and less satisfaction in the semester with the emergency transition. However, students also reported lower conflict. The most important factor predicting project grades shifted from 'Interacting with teammates' to 'Having relevant knowledge, skills, and abilities' amid the emergency shift, accompanied by a reduction in team interdependence. In spite of the collection of data during an emergency transition, the foundation of face-to-face interaction before moving to virtual cooperation represents a useful contribution to research that has focused exclusively on virtual learning circumstances.

Insights into entrepreneurship: impact of entrepreneur psychological capital and employee well-being on business sustainable performance during and post-Covid-19 era

Since Covid-19 is an enduring disease that pushed the world to reshape business strategies to overcome the unprecedented situations in all sectors such as the sports industry. Although substantial research has been carried out to inspect this phenomenon globally. Nevertheless, how entrepreneurial initiatives can contribute to tackling the situation is still lacking. This study attempts to uncover the relationships between entrepreneur psychological capital (EPC) and business sustainable performance (BSF). Second, this study strives to reveal the relationships between employee wellbeing (EWb) and BSP. In addition, education is treated as a moderating factor to unfold the relationships among factors, i.e., EPC, EWb, and BSF. Data were collected from eight hundred (n = 800) participants who were associated with the Chinese sports industry from March to July 2022. The results demonstrated interesting and fruitful findings based on SEM statistical model. First, a positive connection was found between EPC and BSF. Second, it found a positive link between EWb and BSF. Finally, the study highlighted a significant moderating impact of education among implicit relationships, i.e., EPC, EWb, and BSF. This study provides insights into entrepreneurship, entrepreneur psychological capital, and employee wellbeing on how it can optimize the performance of a business during and post-Covid-19 era. Besides, certain shortcomings along with future potential lines are reported for future researchers. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Market development strategy and process performance of knowledge-intensive SMEs in the epidemic era: a process-oriented perspective

PurposeThis study analyzes in-depth how knowledge-intensive small and medium-sized enterprises (SMEs) can achieve higher new product development (NPD) process performance in the epidemic era and examine the internal development mechanism of knowledge-intensive SMEs in the process of continuous digital transformation.Design/methodology/approachThis issue is tested with partial least squares on data collected via a survey conducted from November 2021 to February 2022. The sample comprises 487 knowledge-intensive SMEs operating in China.FindingsThe results indicate that one form of cross-functional ambidexterity, market development strategy (MDS), plays an important role in process performance from an inside-out financial perspective and an outside-in customer perspective. Simultaneously, product innovation efficiency (PIE) mediates the relationship between MDS and the above results. Big data analytics capabilities (BDACs) positively regulate the relationship between MDS and PIE.Research limitations/implicationsThe authors do not consider other contingency factors. Future research should introduce influential factors such as leadership and competitive intensity to further distinguish the effects of MDS on NPD process performance.Practical implicationsThe study findings offer suggestions to help knowledge-intensive SME managers better manage their NPD process by making better use of their limited resources in developing countries such as China.Originality/valueThis study is one of only a few to adopt a process-oriented perspective to specifically examine how one form of cross-functional ambidexterity, MDS, impacts knowledge-intensive SME process performance in the epidemic era. This study also extends the theoretical framework of cross-functional ambidexterity to BDAC research.

Task-Technology Fit and ICT Use in Remote Work Practice During the COVID-19 Pandemic

This study examines the use of information and communications technology (ICT) in remote work practice during the COVID-19 pandemic by integrating task-technology fit theory and the post-acceptance model of IS continuance into a research framework. In addition, it operationalizes the technological characteristics of TTF (task-technology fit) with the technology acceptance model (TAM) and the diffusion of innovation (DOI) theory. The methodology to test the research model takes support from the partial least squares structural equation modeling (PLS-SEM) method using a sample of 320 employees. The results show that TAM significantly explains TTF. Furthermore, there is a positive impact of ICT use on individual and organizational performance. User satisfaction has the most significant effect on individual performance, organizational performance, and IS continuance intention. The authors provide some managerial implications for addressing the challenges of remote work related to ICT disruptions for the post-COVID-19 period.

Control System for Indoor Safety Measures Using a Faster R-CNN Architecture

This paper presents a control system for indoor safety measures using a Faster R-CNN (Region-based Convolutional Neural Network) architecture. The proposed system aims to ensure the safety of occupants in indoor environments by detecting and recognizing potential safety hazards in real time, such as capacity control, social distancing, or mask use. Using deep learning techniques, the system detects these situations to be controlled, notifying the person in charge of the company if any of these are violated. The proposed system was tested in a real teaching environment at Rey Juan Carlos University, using Raspberry Pi 4 as a hardware platform together with an Intel Neural Stick board and a pair of PiCamera RGB (Red Green Blue) cameras to capture images of the environment and a Faster R-CNN architecture to detect and classify objects within the images. To evaluate the performance of the system, a dataset of indoor images was collected and annotated for object detection and classification. The system was trained using this dataset, and its performance was evaluated based on precision, recall, and F1 score. The results show that the proposed system achieved a high level of accuracy in detecting and classifying potential safety hazards in indoor environments. The proposed system includes an efficiently implemented software infrastructure to be launched on a low-cost hardware platform, which is affordable for any company, regardless of size or revenue, and it has the potential to be integrated into existing safety systems in indoor environments such as hospitals, warehouses, and factories, to provide real-time monitoring and alerts for safety hazards. Future work will focus on enhancing the system's robustness and scalability to larger indoor environments with more complex safety hazards.

Does ESG Disclosure Transparency Mitigate the COVID-19 Pandemic Shock? An Empirical Analysis of Listed Firms in the UK

This paper examines whether the ESG reporting transparency of listed firms in the UK can play a role in mitigating the impact of the COVID-19 pandemic. We investigate 350 UK firms in the FTSE350 index from 2016 to 2021 with daily data on stock performance and annual data on financial performance. The empirical results show that firms with a high ESG disclosure score have a lower volatility of stock performance during the COVID-19 pandemic. For these firms, the negative relationship between stock performance, as well as financial performance, and their main driving factors, is lower during the COVID-19 pandemic. Among these factors, we identify the lockdown announcement, quantitative easing announcement, and the intensity of news media coverage of the company. These results tend to indicate that the quantity of ESG data reported by firms can contribute to mitigating the impact of the COVID-19 pandemic on stock performance volatility and financial performance. © 2023 Journal of Innovation Economics and Management. All rights reserved.

Modelling COVID-19 effect on the performance of MENA Health-care sector

PurposeThis study models the effects of the COVID-19 pandemic on the performance of the private health-care sector in the Middle East and North Africa (MENA) countries. This paper aims to address the economic, societal and sustainability of the health-care sector.Design/methodology/approachData were collected from Bloomberg and the sample consists of 534 firm-year observations from 55 firms listed over 2010–2020. The authors apply panel data and control for the country and governance effects.FindingsThe authors found heterogeneous results regarding the three sub-sectors. The pandemic has a negative effect on the accounting and market performances of the "Pharmaceutical companies” and an insignificant impact on "Healthcare Management and Facilities Services.” Moreover, the impact of COVID-19 on health-care firms' performance depends on the country's economic classification and the degree of regulatory and governance frameworks.Research limitations/implicationsFurther studies may consider a larger sample and other regions. It is recommended to address the health-care sector's challenges to invest in new technologies such as "digital twin” and predictive and personalized medicine. It is worth testing model development theory and its effects on speeding up and designing models to ensure the proper functioning and developing mathematics to determine uncertainties in patient data and model predictions.Originality/valueTo the best of the authors' knowledge, this paper is novel as it is unique in modeling the impact of COVID-19 on the health-care public companies in the MENA region. The findings pinpoint firms' and countries' heterogeneous impacts on financial and market performances.