A design concept of big data analytics model for managers in hospitality industries.

The hospitality and tourism sector has long played a significant role in Australia's economy, especially in regional areas. Due to the onslaught of COVID-19, numerous businesses have experienced lockdowns, restrictions, and closures due to the fact that people's activity in restaurants, shopping centers, and recreational destinations was restricted, and many other places went into hibernation. After about 2 years since the outbreak, businesses in this sector are gradually starting to reopen and revitalize themselves, but in order to have better decision support about the future of this sector, thus being able to plan, businesses are suffering from an effective analytics solution due to the lack of broken data trends. Starting from fresh day-to-day real-time big data, the study aims to develop a new data analytics model, adopting the design science research methodology, which can provide invaluable options and techniques to make prediction easier from immediate past datasets. This study introduces an innovative design artifact as a big data solution for hospitality managers to utilize analytics for predictive strategic decision-making in post-COVID situation. The artifact can also be generalized for other sectors with tailoring aspects which are subject to further studies. The proposed artifact is then compared with other design artifacts related to big data solutions where it outperforms them in terms of comprehensiveness. The proposed artifact also shows promises for primarily available UGC in managers' decision support aids.

Adoption of AI in response to COVID-19-a configurational perspective.

Although the importance of artificial intelligence (AI) has often been highlighted in strategic agility and decision outcomes, whether it helps firms strengthen their competitiveness and the means firms use to achieve such competitiveness are still under-researched. Our research thus joins the recent discussion on digitalization trends and strategic responses to COVID-19 to better understand how firms strengthen their competitiveness during such challenging times. Namely, this study incorporates the strategic responses to COVID-19 into the technology-organization-environment (TOE) framework by investigating the impacts of different configurations of TOE contexts and strategic responses on a firm's competitive advantage. We used fuzzy-set qualitative comparative analysis to investigate how TOE contexts and strategic responses integrate into configurations and impact a firm's competiveness. By applying a configurational approach with data from 514 exporting firms in China, we find a strong indication of the equifinality of different strategies, indicating that multiple strategic paths can be used to respond to crises. The adoption of AI, while important, is not sufficient to enhance a firm's competitiveness. Our results stress the significance of data quality, organizational resources and capabilities, and digital business model innovation for AI adoption. We also identify successful strategic paths of AI adoption aversion and ambidextrous strategies. The findings have practical implications for firms seeking effective strategies to respond to future crises and sustain their competitive advantages.

Adoption of AI in response to COVID-19—a configurational perspective

Although the importance of artificial intelligence (AI) has often been highlighted in strategic agility and decision outcomes, whether it helps firms strengthen their competitiveness and the means firms use to achieve such competitiveness are still under-researched. Our research thus joins the recent discussion on digitalization trends and strategic responses to COVID-19 to better understand how firms strengthen their competitiveness during such challenging times. Namely, this study incorporates the strategic responses to COVID-19 into the technology–organization–environment (TOE) framework by investigating the impacts of different configurations of TOE contexts and strategic responses on a firm's competitive advantage. We used fuzzy-set qualitative comparative analysis to investigate how TOE contexts and strategic responses integrate into configurations and impact a firm's competiveness. By applying a configurational approach with data from 514 exporting firms in China, we find a strong indication of the equifinality of different strategies, indicating that multiple strategic paths can be used to respond to crises. The adoption of AI, while important, is not sufficient to enhance a firm's competitiveness. Our results stress the significance of data quality, organizational resources and capabilities, and digital business model innovation for AI adoption. We also identify successful strategic paths of AI adoption aversion and ambidextrous strategies. The findings have practical implications for firms seeking effective strategies to respond to future crises and sustain their competitive advantages.

A Broad Antiviral Strategy: Inhibitors of Human DHODH Pave the Way for Host-Targeting Antivirals against Emerging and Re-Emerging Viruses.

New strategies to rapidly develop broad-spectrum antiviral therapies are urgently required for emerging and re-emerging viruses. Host-targeting antivirals (HTAs) that target the universal host factors necessary for viral replication are the most promising approach, with broad-spectrum, foresighted function, and low resistance. We and others recently identified that host dihydroorotate dehydrogenase (DHODH) is one of the universal host factors essential for the replication of many acute-infectious viruses. DHODH is a rate-limiting enzyme catalyzing the fourth step in de novo pyrimidine synthesis. Therefore, it has also been developed as a therapeutic target for many diseases relying on cellular pyrimidine resources, such as cancers, autoimmune diseases, and viral or bacterial infections. Significantly, the successful use of DHODH inhibitors (DHODHi) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection further supports the application prospects. This review focuses on the advantages of HTAs and the antiviral effects of DHODHi with clinical applications. The multiple functions of DHODHi in inhibiting viral replication, stimulating ISGs expression, and suppressing cytokine storms make DHODHi a potent strategy against viral infection.

Home Countries Matter for the Internationalisation of Emerging Market Multinational Enterprises

Introduction The past two decades have witnessed the significant growth of emerging markets and the rise of emerging market multinational enterprises (EMNEs) (Luo and Tung 2007). A case study approach has been adopted to explore the rich contextual environments of these two industry clusters, including human capital investment, professional labour, infrastructure, public–private sector cooperation, support for funding and commercialisation, and innovative corporate culture in the national innovation ecosystem. The third article by Sharmelly and Klarin (2021) (Creating Customer Value for the Middle Class in Emerging Markets: Perspectives from Case Studies in India) examines the design of customer value creation frameworks and essential components of product development in emerging markets. [...]this paper uses a framework consisting of actors, networks and the institutional pillars of ecosystems to promote the application of the system concept further.

Three Specific Potential Epitopes That Could Be Recognized by T Cells of Convalescent COVID-19 Patients Were Identified From Spike Protein.

The current coronavirus disease 2019 (COVID-19) vaccines are used to prevent viral infection by inducing neutralizing antibody in the body, but according to the existing experience of severe acute respiratory syndrome coronavirus (SARS) infection, T-cell immunity could provide a longer durable protection period than antibody. The research on SARS-CoV-2-specific T-cell epitope can provide target antigen for the development and evaluation of COVID-19 vaccines, which is conducive to obtain COVID-19 vaccine that can provide long-term protection. For screening specific T-cell epitopes, a SARS-CoV-2 S protein peptide library with a peptide length of 15 amino acids was synthesized. Through flow cytometry to detect percentage of IFN-γ+ T cells after mixed COVID-19 convalescent patients' peripheral blood mononuclear cell with peptide library, seven peptides (P77, P14, P24, P38, P48, P74, and P84) that can be recognized by the T cells of COVID-19 convalescent patients were found. After excluding the nonspecific cross-reactions with unexposed population, three SARS-CoV-2-specific T-cell potential epitopes (P38, P48, and P84) were finally screened with the positive reaction rates between 15.4% and 48.0% in COVID-19 convalescent patients. This study also provided the HLA allele information of peptide-positive-response COVID-19 convalescent patients, thus predicting the population coverage of these three potential epitopes. Some HLA alleles showed higher frequency of occurrence in COVID-19 patients than in total Chinese population but no HLA alleles related to the T-cell peptide response and the severity of COVID-19. This research provides three potential T-cell epitopes that are helpful for the design and efficacy evaluation of COVID-19 vaccines. The HLA information provided by this research supplies reference significance for subsequent research such as finding the relation of HLA genotype with disease susceptibility.

A newly identified linear epitope on non-RBD region of SARS-CoV-2 spike protein improves the serological detection rate of COVID-19 patients.

BACKGROUND: Serological test is helpful in confirming and tracking infectious diseases in large population with the advantage of fast and convenience. Using the specific epitope peptides identified from the whole antigen as the detection antigen is sensitive and relatively economical. The development of epitope peptide-based detection kits for COVID-19 patients requires comprehensive information about epitope peptides. But the data on B cell epitope of SARS-CoV-2 spike protein is still limited. More importantly, there is a lack of serological data on the peptides in the population. In this study, we aimed to identify the B cell epitope peptides of spike protein and detect the reactivity in serum samples, for further providing data support for their subsequent serological applications. RESULTS: Two B cell linear epitopes, P104 and P82, located in non-RBD region of SARS-CoV-2 S protein were identified by indirect ELISA screening of an overlapping peptide library of the S protein with COVID-19 patients' convalescent serum. And the peptides were verified by testing with 165 serum samples. P104 has not been reported previously; P82 is contained in peptide S21P2 reported before. The positive reaction rates of epitope peptides S14P5 and S21P2, the two non-RBD region epitopes identified by Poh et al., and P82 and P104 were 77.0%, 73.9%, 61.2% and 30.3%, respectively, for 165 convalescent sera, including 30 asymptomatic patients. Although P104 had the lowest positive rate for total patients (30.3%), it exhibited slight advantage for detection of asymptomatic infections (36.7%). Combination of epitopes significantly improved the positive reaction rate. Among all combination patterns, (S14P5 + S21P2 + P104) pattern exhibited the highest positive reaction rate for all patients (92.7%), as well as for asymptomatic infections (86.7%), confirming the feasibility of P104 as supplementary antigen for serological detection. In addition, we analyzed the correlation between epitopes with neutralizing antibody, but only S14P5 had a medium positive correlation with neutralizing antibody titre (rs = 0.510, P < 0.01). CONCLUSION: Our research proved that epitopes on non-RBD region are of value in serological detection especially when combination more than one epitope, thus providing serological reaction information about the four epitopes, which has valuable references for their usage.

Risk Management: Exploring Emerging Human Resource Issues during the COVID-19 Pandemic

The unanticipated coronavirus disease 2019 (COVID-19) pandemic has hit global business heavily, disrupting the management of human resources across numerous industries. More than 500 articles (indexed in Scopus and the Web of Science) on the impact of the COVID-19 outbreak on emerging human resources issues and related practices were published from 1 January 2020 to 31 January 2021. In this study, we conduct a systematic literature review on emerging studies in the business and management field to explore what the emerging human resource issues are during the COVID-19 pandemic and propose related practices to solve these issues. The analysis of the published literature identifies nine main human resource issues across 13 industries. The findings of this study suggest that COVID-19 has enormous impact on conventional human resource management and requires the theoretical and empirical attention of researchers. The propositions nominate related human resource practices to deal with emerging human resources issues and identify several research venues for future studies in this field.

Viral RNA level, serum antibody responses, and transmission risk in recovered COVID-19 patients with recurrent positive SARS-CoV-2 RNA test results: a population-based observational cohort study.

Managing recovered COVID-19 patients with recurrent-positive SARS-CoV-2 RNA test results is challenging. We performed a population-based observational study to characterize the viral RNA level and serum antibody responses in recurrent-positive patients and evaluate their viral transmission risk. Of 479 recovered COVID-19 patients, 93 (19%) recurrent-positive patients were identified, characterized by younger age, with a median discharge-to-recurrent-positive length of 8 days. After readmission, recurrent-positive patients exhibited mild (28%) or absent (72%) symptoms, with no disease progression. The viral RNA level in recurrent-positive patients ranged from 1.8 to 5.7 log10 copies/mL (median: 3.2), which was significantly lower than the corresponding values at disease onset. There are generally no significant differences in antibody levels between recurrent-positive and non-recurrent-positive patients, or in recurrent-positive patients over time (before, during, or after recurrent-positive detection). Virus isolation of nine representative specimens returned negative results. Whole genome sequencing of six specimens yielded only genomic fragments. 96 close contacts and 1,200 candidate contacts of 23 recurrent-positive patients showed no clinical symptoms; their viral RNA (1,296/1,296) and antibody (20/20) tests were negative. After full recovery (no longer/never recurrent-positive), 60% (98/162) patients had neutralizing antibody titers of ≥1:32. Our findings suggested that an intermittent, non-stable excretion of low-level viral RNA may result in recurrent-positive occurrence, rather than re-infection. Recurrent-positive patients pose a low transmission risk, a relatively relaxed management of recovered COVID-19 patients is recommended.