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Background: This paper examines the impact of coronavirus COVID-19 outbreak on employees’ mental health, specifically psychological distress and depression. It aims at identifying the main stressors during and post COVID-19, examining the main moderating factors which may mitigate or aggravate the impact of COVID-19 on employees’ mental health and finally to suggest recommendations from a human resource management perspective to mitigate COVID-19’s impact on employees’ mental health.

Methods: This paper is a literature review. The search for articles was made in Google scholar, Web of Science and Semantic scholar. We used a combination of terms related to coronavirus OR COVID-19, workplace and mental health. Due to the paucity of studies on the COVID-19 impact on employees’ mental health, we had to draw on studies on recent epidemics.

Results: The identified literature reports a negative impact of COVID-19 on individual’s mental health. Stressors include perception of safety, threat and risk of contagion, infobesity versus the unknown, quarantine and confinement, stigma and social exclusion as well as financial loss and job insecurity. Furthermore, three dimensions of moderating factors have been identified: organizational, institutional and individual factors. In addition, a list of recommendations has been presented to mitigate the impact of COVID-19 on the employee’s mental health, during and after the outbreak, from a human resource management perspective.

Conclusions: Coronavirus is new and is in a rapid progress while writing this paper. Most of current research are biomedical focusing on individuals’ physical health. In this context, mental health issues seem overlooked. This paper helps to broaden the scope of research on workplace mental health, by examining the impact of a complex new pandemic: COVID-19 on employees’ mental health, from social sciences perceptive, mobilizing psychology and human resource management.

This study aims to provide a cutting-edge evaluation of the sharing economy's impact within the realm of tourism and hospitality. The primary objectives guiding this research are as follows: to uncover the prevalent discussions and debates within the tourism and hospitality sector concerning the implications and effects of the sharing economy on urban destinations; and to analyse how scholarly inquiries and empirical investigations have contributed to a comprehensive comprehension of the intricate theoretical foundations and practical intricacies inherent in the sharing economy. This exploration takes place within the extensive expanse of existing literature.

The study used the non-conventional method for data mining. An artificial intelligence (AI) tool called www.dimensions.ai was used to mine data between the year 2002 and 2021. After which the data was analysed, using Citespace software that assisted in building themes for answering the research questions.

The sharing economy has multifaceted implications for rural and urban destinations. For instance, the findings demonstrated that emotional solidarity fosters community bonds between tourists and residents, enhancing authenticity. While, management firms optimise short-term rentals, boosting revenue and occupancy rates despite capped at 20%. It further demonstrated that the sharing economy disrupts traditional accommodations, especially hotels, impacting rural and urban destinations differently based on location and regulatory flexibility. Technological advancements would shape the digital future, transforming the resource in sharing and connectivity in urban settings.

Management firms or agents significantly enhance property facilities, revenue and occupancy rates. Properties managed by professionals perform better in terms of revenue and occupancy; furthermore, traditional accommodations need innovative strategies to compete with sharing economy platforms. Policymakers must consider location-specific regulations to balance sharing economy impacts. Embracing technological advancements ensures urban destinations stay relevant and competitive.

Emotional solidarity fosters bonds between residents and tourists, contributing to a sense of community. Management firms contribute to local economies and stability. However, Airbnb's impact on traditional accommodations raises concerns about the effect on residents and communities.

The study incorporates classical sociology theory to understand emotional solidarity and extends the concept of moral economy to guide economic behaviour in the sharing economy. The analysis also underscores the influence of technological trends such as mobile technology, Internet of Things, AI and blockchain on sharing practices in reshaping existing theoretical frameworks in the sharing atmosphere. Furthermore, the co-creation of value theory highlights collaborative interactions between hosts and guests, shaping the sharing economy experience. Consumer segmentation and choice theories shed light on sharing economy dynamics. Institutional and location-based theories provide insights into regulatory and location-specific impacts.

This research contributes by comprehensively exploring the multifaceted implications of the sharing economy on a tourist destination. It delves into emotional solidarity, management firm roles and location-specific impacts, enriching the understanding of the sharing economy's effects. The application of co-creation of value theory and examination of platform technologies offer fresh perspectives on value creation and user engagement. The study's focus on practical dimensions guides stakeholders in optimising the benefits and addressing challenges posed by the sharing economy in urban contexts. The exploration of moral economy and its relevance to the sharing economy provides a novel perspective, while the examination of technological influences on sharing practices contributes to understanding the digital future of the sharing economy.

The aim of this paper is reviewing the discipline development course of the history of socialist political economy with Chinese characteristics and recognising the changes of its development and its historic mission in the new stage will be beneficial to the construction of socialist political economy with Chinese characteristics from the perspective of doctrinal history.

In this paper from the aspect of discipline formation and development, the history of China’s socialist political economy has experienced two stages: emergence and formation (the first stage) and steady development (the second stage). It has explored new research fields and improved the quality of research levels. However, the role of studying the history of socialist political economy with Chinese characteristics has not been fully played regarding satisfying the needs of constructing socialist political economy with Chinese characteristics.

In this study when the construction of socialist political economy with Chinese characteristics entered a new era, the study of the history of socialist political economy also entered a new stage, showing new features in terms of research objectives, principles, scale and methods.

Therefore, the research on the history of socialist political economy with Chinese characteristics should be highly emphasised, and the focus on serving the construction of socialist political economy with Chinese characteristics should be its historic mission and core task. Also, researchers should pay attention to changing ideas, laying a good foundation, highlighting key points, building platforms and broadening horizons.

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

It has been a tremendous challenge for organisations to navigate and survive the COVID-19 pandemic. This paper proposes a novel multi-level conceptual model, based on the resource-based view (RBV), to address the pandemic crisis and highlight the importance of strategic human resource management (SHRM) in promoting employee motivation and organisational resilience. The paper aims to provide insights and practical guidance for organisations to leverage their internal resources and capabilities to thrive in the post-pandemic landscape.

This paper conducted a comprehensive literature review of the existing research on the impact of the COVID-19 pandemic, SHRM, RBV, job satisfaction, turnover intentions and organisational resilience, covering the main contributors to this research stream and their findings.

The conceptual model presented in this paper offers five testable propositions to examine the impact of the COVID-19 pandemic on employee motivation and organisational resilience and how organisations can navigate challenging times through SHRM, which enables RBV. It highlights the foundational role of RBV and identifies the resources employed by SHRM as intervening constructs that significantly enhance employee outcomes, including motivation, job satisfaction, turnover intention and organisational resilience.

The proposed model counsels that organisations need to look beyond the straightforward application of SHRM and should enable the RBV climate to protect and uphold employee motivation and organisational resilience. Finally, measurement and analysis implications are presented for future research opportunities and managerial interventions to mitigate the impact of difficult times such as the COVID-19 pandemic.

Currently, there is a lack of research regarding the conceptualisation of the COVID-19 pandemic and its impact on employee and organisational resilience. Therefore, the proposed model discusses the significance of the alignment of SHRM and RBV as a moderator of the relationships between the impact of COVID-19 pandemic, employee motivation and organisational resilience.

Every day thousands of academic institutes suspend their classes and students are staying in their home maintaining social distancing due to the fear of COVID-19 pandemic and Nepal is no exception. Realizing these facts, this study aims to explore the factors for the effectiveness of online mode of classes to on-class course-based students and analyzes the perception of faculties and students toward online mode during the COVID-19 pandemic.

It is based on exploratory research design, following mixed methods of qualitative and quantitative procedure. To build a rich understanding of the phenomenon, three-stage data collection procedure: preliminary interview, structural survey and validation were used.

This study revealed triplet factors: infrastructure, student and teacher as antecedents of effectiveness of online classes during a pandemic. Technological support, infrastructure availability, faculty and students' perception have a significant relationship for the effectiveness of the online mode of the teaching-learning process. Students faced anxiety during the COVID-19 pandemic, but a higher willingness to learn reduces the level of anxiety.

This study significantly contributes to the future management of higher education and digs the future path of online and on-class teaching-learning practices.

There is a significant decrease in students' attendance in Zoom classes compared to traditional classes. This paper investigates the factors that affect students' attitudes, behavioral intentions and actual use of Zoom for online classes at higher educational institutions (HEIs) in Sri Lanka.

This research uses the technology acceptance model (TAM) as a theoretical model. The data are collected from HEI students via an online survey form. The hypotheses between constructs in the model are tested using partial least squared–structural equation model.

The analysis shows that computer self-efficacy (CSE) affects perceived usefulness (PU) and perceived ease of use (PEU), which affects attitude (ATT) and behavioral intention (BI) and actual use (AU) of Zoom in a chain reaction. Further, PEU affects PU, which, in turn, affects BI. Furthermore, the effect size of PU to BI is larger than ATT to BI.

Students' attendance for Zoom classes mainly depends on CSE, PU and PEU. Therefore, HEIs should promote Zoom with interactive training before teaching online. Further, officials should revise the curriculum in schools to upsurge the CSE of students.

During coronavirus-19, no research was published on students' use of Zoom for online classes in the Sri Lankan context. Moreover, the TAM model has been modified by including CSE as an external variable.