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This study aims to test the relationship between emotional labor and service quality of the frontline employees of Chinese restaurants during the coronavirus disease pandemic (COVID-19). This study further investigated the mediating role of work fatigue (WF) and the moderating role of supervisor–subordinate Guanxi (SSG).

The authors used a time-lag approach to gather data from a sample of 365 frontline staff members working in Chinese restaurants. All hypotheses were tested using SPSS and AMOS.

First, restaurant frontline employees’ deep acting was associated with higher service quality, whereas surface acting leads to lower service quality. Second, WF mediated the relationship between emotional labor and service quality. Third, SSG moderated the impact of emotional labor on WF during COVID-19.

All variables measured in this study were self-reported by restaurant frontline employees, which may increase the risk of common-method bias. However, this study enriches the literature on emotional labor, WF and SSG during COVID-19.

COVID-19 has severely affected the hotel, restaurant and catering sector and especially the psychological state and the work performance of frontline employees. Restaurant managers should implement some measures to improve employees’ service quality during COVID-19.

The present findings show that restaurant frontline employees adopted various emotional labor strategies when they were faced with higher than usual job demands and the risk of infection during COVID-19.

This study aimed to propose a performance-oriented approach of automatically generative design and optimization of hospital building layouts in consideration of public health emergency, which intended to conduct reasonable layout design of hospital building to meet different performance requirements for both high efficiency during normal periods and low risk in the pandemic.

The research design follows a sequential mixed methodology. First, key points and parameters of hospital building layout design (HBLD) are analyzed. Then, to meet the requirements of high efficiency and low risk, adjacent preference score and infection risk coefficient are constructed as constraints. On this basis, automatic generative design is conducted to generate building layout schemes. Finally, multi-objective deviation analysis is carried out to obtain the optimal scheme of hospital building layouts.

Automatic generative design of building layouts that integrates adjacent preferences and infection risks enables hospitals to achieve rapid transitions between normal (high efficiency) and pandemic (low risk) periods, which can effectively respond to public health emergencies. The proposed approach has been verified in an actual project, which can help systematically explore the solution for better decision-making.

The form of building layouts is limited to rectangles, and future work can explore conducting irregular layouts into optimization for the framework of generative design.

The contribution of this paper is the developed approach that can quickly and effectively generate more hospital layout alternatives satisfying high operational efficiency and low infection risk by formulating space design rules, which is of great significance in response to public health emergency.

This case study paper aims to explore the complexities and challenges of epidemic response and public health surveillance in Native American and Indigenous American communities in the United States and find viable solutions. This paper explores these topics through the emergence and impact of the hantavirus pulmonary syndrome (HPS) within the Navajo Nation in the United States using critical incident analysis and best practices.

This project is a case study paper based on a topical review of the literature. A topical review of the literature is a comprehensive exploration of the current body of knowledge within a particular research field. It is an important tool used by scholars and practitioners to further the development of existing knowledge as well as to identify potential directions for future research (Fourie, 2020). Such a paper can provide a useful insight into the various aspects of the process that the researcher may have overlooked, as well as highlighting potential areas of improvement (Gall et al., 2020). It can also provide a useful source of ideas and inspiration for the researcher as it can provide an overview of the various approaches used by other researchers in the field (Göpferich, 2009). Case study papers using a topical review of the literature have been used to help frame and inform research topics, problems and best practices for some time. They are typically used to explore a topic in greater depth and to provide an overview of the literature to improve the world of practice to provide a foundation for future comprehensive empirical research. Case study papers can provide research value by helping to identify gaps in the literature and by providing a general direction for further research. They can also be used to provide a starting point for research questions and hypotheses and to help identify potential areas of inquiry.

This study explores best practices in public health surveillance and epidemic response that can help strengthen public health infrastructure by informing the development of effective surveillance systems and emergency response plans, as well as improving data collection and analysis capabilities within Native American and Indigenous American communities in the United States that also have the option to include new technologies like artificial intelligence (AI) with similar outbreaks in the future.

The literature review did not include any primary data collection, so the existing available research may have limited the findings. The scope of the study was limited to published literature, which may not have reported all relevant findings. For example, unpublished studies, field studies and industry reports may have provided additional insights not included in the literature review. This research has significant value based on the limited amount of studies on how infectious diseases can severely impact Native American communities in the United States, leading to unnecessary and preventable suffering and death. As a result, research on viable best practices is needed on the best practices in public health surveillance and epidemic response in Native American and Indigenous American communities through historical events and critical incident analysis.

Research on public health surveillance and epidemic response in Native American communities can provide insights into the challenges faced by these communities and help identify potential solutions to improve their capacity to detect, respond to and prevent infectious diseases using innovative approaches and new technologies like AI.

More research on public health surveillance and epidemic response can inform policies and interventions to improve access to healthcare for Native American populations, such as increasing availability of healthcare services, providing culturally appropriate health education and improving communication between providers and patients. By providing better public health surveillance and response capacity, research can help reduce the burden of infectious diseases in Native American communities and ultimately lead to improved public health outcomes.

The aim of this study is to investigate the role of Corporate Social Responsibility (CSR) in assisting firms in their response to public emergency crises under the integrated view of government emergency response.

Using event study and survival analysis method, the authors examine whether CSR can act as a stock price stabilizer for companies from China by splitting the stock price fluctuations into two phases – CSR price insurance, which decrease the shock on stock prices during the emergency crisis, and CSR price recovery, which helps stock prices rebound faster during the postcrisis phase.

The authors’ empirical results confirm the stabilizer role of CSR during crisis and that effective government response can strengthen such effect. Furthermore, the authors examine the different aspects of the government’s response and the impact of multiple waves of public emergency.

This study provides empirical evidence on the topic of CSR and the government’s response to public emergency under the emerging context.

China is the only major economy in the world that has achieved positive gross domestic product (GDP) growth in 2020. The paper aims to explore the effect of China's public policy restarting supply and consumption after coronavirus disease-2019 (COVID-19).

Affected by the epidemic, global economic growth slowed down. Using the stock price data of Chinese A-share listed company, combining natural experiment and event study method, the paper examines the policy effects of work resumption and consumer vouchers.

Compared with demand capacity, the work resumption has a more significant role in promoting the supply industry. Issuing consumer vouchers can effectively promote local demand recovery, and the effect is mainly concentrated in the industries involved in consumption vouchers. At the same time, public management capacity and the income level of residents play an important role in restarting supply and demand.

Understanding China's public policies and effects are of positive significance to the restoration of economic development in other countries.

The study contributes to knowledge by empirically examining the effect of China's public policies against the COVID-19 pandemic. The paper also expands the scope of policy-oriented research based on the perspective of supply and demand capacity building.

Forecasting demand of emergency supplies under major epidemics plays a vital role in improving rescue efficiency. Few studies have combined intuitionistic fuzzy set with grey-Markov method and applied it to the prediction of emergency supplies demand. Therefore, this article aims to establish a novel method for emergency supplies demand forecasting under major epidemics.

Emergency supplies demand is correlated with the number of infected cases in need of relief services. First, a novel method called the Intuitionistic Fuzzy TPGM(1,1)-Markov Method (IFTPGMM) is proposed, and it is utilized for the purpose of forecasting the number of people. Then, the prediction of demand for emergency supplies is calculated using a method based on the safety inventory theory, according to numbers predicted by IFTPGMM. Finally, to demonstrate the effectiveness of the proposed method, a comparative analysis is conducted between IFTPGMM and four other methods.

The results show that IFTPGMM demonstrates superior predictive performance compared to four other methods. The integration of the grey method and intuitionistic fuzzy set has been shown to effectively handle uncertain information and enhance the accuracy of predictions.

The main contribution of this article is to propose a novel method for emergency supplies demand forecasting under major epidemics. The benefits of utilizing the grey method for handling small sample sizes and intuitionistic fuzzy set for handling uncertain information are considered in this proposed method. This method not only enhances existing grey method but also expands the methodologies used for forecasting demand for emergency supplies.

1. An intuitionistic fuzzy TPGM(1,1)-Markov method (IFTPGMM) is proposed.

2. The safety inventory theory is combined with IFTPGMM to construct a prediction method.

3. Asymptomatic infected cases are taken to forecast the demand for emergency supplies.

An intuitionistic fuzzy TPGM(1,1)-Markov method (IFTPGMM) is proposed.

The safety inventory theory is combined with IFTPGMM to construct a prediction method.

Asymptomatic infected cases are taken to forecast the demand for emergency supplies.

This paper aims to straighten out the research progress in the field of maker education, summarize the research hotspots and frontiers of maker education at home and abroad and provide path optimization suggestions for the research and development of this field.

In total, 751 pieces of domestic and the foreign maker education research literature from 2014 to 2021 are retrieved and screened, and literature analysis methods such as keyword analysis and clustering map analysis are used to quantitatively analyze the quantity distribution, published journals, core authors, research institutions and subject keywords of the maker education literature.

It is found that research in this field is still in the development stage, but the pandemic has severely inhibited maker education and related research. Frontiers at home and abroad have begun to pay attention to the impact of humanistic care on maker education. Strengthening the dialog between multidisciplinary theories requires cross-disciplinary research. Regional and cross-field cooperation and fully grasping the actual situation and constraints of the development of maker education are the cornerstones of bold innovation in maker education research.

This paper uses bibliometric analysis to reveal the severe challenges to the development of maker education due to the normalization of the epidemic. By excavating the research hotspots and research frontiers in this field, it fills the gap that the current research in the field of maker education has not yet formed a complete theoretical framework and evaluation system.

This study analyzes the evolution of topics related to COVID-19 on Chinese social media platforms with the aim of identifying changes in netizens' concerns during the different stages of the pandemic.

In total, 793,947 posts were collected from Zhihu, a Chinese Question and Answer website, and Dingxiangyuan, a Chinese online healthcare community, from 31 December, 2019, to 4 August, 2021. Topics were extracted during the prodromal and outbreak stages, and in the abatement–resurgence cycle.

Netizens' concerns varied in different stages. During the prodromal and outbreak stages, netizens showed greater concern about COVID-19 news, the impact of COVID-19 and the prevention and control of COVID-19. During the first round of the abatement and resurgence stage, netizens remained concerned about COVID-19 news and the prevention and control of the pandemic, however, less attention was paid to the impact of COVID-19. During later stages, popularity grew in topics concerning the impact of COVID-19, while netizens engaged more in discussions about international events and the raising of spirits to fight the global pandemic.

This study contributes to the practice by providing a way for the government and policy makers to retrospect the pandemic and thereby make a good preparation to take proper measures to communicate with citizens and address their demands in similar situations in the future.

This study contributes to the literature by applying an adapted version of Fink's (1986) crisis life cycle to create a five-stage evolution model to understand the repeated resurgence of COVID-19 in Mainland China.

This study aims to explore the efficacy of government policy directions in mitigating the effects of the COVID-19 pandemic by employing a panel of 22 countries throughout the 2020-second quarter of 2022.

The panel autoregressive distributed lag (ARDL) model is employed to examine this phenomenon and to investigate the long-run effects of government policy decisions on infection and mortality rates from the pandemic.

The study reveals the following key findings: (1) Income support and debt relief facilities and stringent standards of governments are associated with reduced infection and death rates. (2) The response of governments has resulted in decreased mortality rates while simultaneously leading to an unexpected increase in infection rates. (3) Containment and healthcare practices have led to a decrease in infection rates but an increase in mortality rates, presenting another counterintuitive outcome. Despite the expectation that robust government responses would decrease infection rates and that healthcare containment practices would reduce mortality, these results highlight a lack of health equity and the challenge of achieving high vaccination rates across countries.

To effectively combat the spread of COVID-19, it is crucial to implement containment health practices in conjunction with tracing and individual-level quarantine. Simply implementing containment health measures without these interconnected strategies would be ineffective. Therefore, policy implications derived from containment health measures should be accompanied by targeted, aggressive, and rapid containment strategies aimed at significantly reducing the number of individuals infected with COVID-19.

This study concludes by suggesting the importance of implementing economic support in terms of income, and debt relief has played a crucial role in mitigating the spread of COVID-19 infections and reducing fatality rates.

To effectively combat the spread of COVID-19, it is crucial to implement containment health practices in conjunction with tracing and individual-level quarantine. Simply implementing containment health measures without these interconnected strategies would be ineffective. Therefore, policy implications derived from containment health measures should be accompanied by targeted, aggressive, and rapid containment strategies aimed at significantly reducing the number of individuals infected with COVID-19.

This research makes a unique contribution to the existing literature by investigating the impact of government responses on reducing COVID-19 infections and fatalities, specifically focusing on the period before COVID-19 vaccinations became available.

According to the Government Response tracker (oxCGRT) index, the overall government response, stringency, economic support, containment and health policies to COVID-19 from January 2020 to December 2022. The main objective of this paper is to explore how stock market performance is affected by these polices, respectively.

The authors employ EGARCH and autoregressive distributional lag (ARDL) models to test the impact of epidemic prevention policy implementation on stock market returns, volatility and liquidity and make cross-country comparisons for six important world economies.

Firstly, the implementation of various preventive policies hurts stock market returns and increases volatility, but there are a few indicators that have no effect or have an easing effect in some countries. Secondly, health policies exacerbate market volatility and have a stronger effect than other policy indicators. Thirdly, In China and the USA, anti-epidemic policies have been shown to worsen liquidity, while in Japan they have been shown to improve liquidity.

First, enrich the growing body of COVID-19 research by comprehensively examining whether and how government prevention policies affect stock market returns, volatility and liquidity. Second, explore the impact of different types of intervention policies on stock market performance, separately.