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With China’s economic growth slowing down and the growth rate of fiscal revenue decreasing, the pressure on local government debts is further increasing. Under this background, it is of great significance to clarify the relation between local government debts and China’s economic growth in order to give full play to the positive role of local debts in stabling growth. The paper aims to discuss this issue.

Therefore, this paper explores the impact of Chinese local government debt on economic growth from theoretical and empirical aspects, respectively, and compares the regional differences between different debts and economic growth dynamics.

In the theoretical model part, this paper constructs a three-sector dynamic game model, under the two circumstances of whether local government is subject to debt constraints, and examines the relation between local government debt and economic growth and other variables through numerical simulation. Research shows that when the government is not constrained by debt, there is an inverted “U” relation between government debt and economic growth. When the government is constrained by debt, the economic growth rate gradually decreases as the government debt increases.

In the theoretical analysis part, this paper tries to estimate the amount of local debts under different calibers and examines the impact of different types of local government debts on China’s economic growth and their regional differences. The results show that excessive accumulation of government hidden debts in the eastern region is not conducive to economic growth, while explicit debts in the central and western regions significantly contribute to local economic growth. The results of empirical analysis are basically consistent with the predictions of the theoretical model.

Emergency logistics is an important means to deal with disasters and public crises. Since the outbreak of the severe acute respiratory syndrome (SARS) virus in 2003, China has established and developed an emergency logistics management system. With the outbreak of coronavirus disease (COVID-19) in China, its emergency logistics system is facing unfolded challenges. The main purposes of this study are to explore the development of China’s emergency logistics system in this context and identify the critical success factors for such systems. A series of focus groups are organized to collect the opinions of 24 interviewees from three Chinese cities, namely Wuhan, Shanghai, and Xi’an. Through the analysis, a framework of the critical success factors for emergency logistics in China is recreated. The key elements are demand forecasting and planning, inventory management, distribution network, and systematic information management. Findings suggest critical points on the design and imple-mentation of the emergency logistics operations during a chaotic period.

The purpose of this study is to explore educational policy directions in the Maldives to continue learning in public schools during the coronavirus disease 2019 (COVID-19) pandemic and identify policy changes that could improve the preparedness of the schools for future pandemics.

This qualitative study is descriptive in nature with an analytical methodology of document and interview data analysis. The purposively selected participants for the interviews included senior officials of the Ministry of Education, school leaders and teachers of public schools in the Maldives.

This study identified significant policy changes for public schools in the Maldives during the COVID-19 pandemic. These were early response and timely policy directions to continue education during the COVID-19 pandemic. Another finding was the effective change communication of the educational policies for its implementation. Following the policy changes, the teachers were trained for online teaching, hence increasing their competency in information and communications technology. As a result, this led to resilient teachers who were determined to provide education through the challenging times of the pandemic. Hence, it is evident that the school system of the Maldives will emerge stronger beyond COVID-19.

The education policy changes for public schools in the Maldives during the global COVID-19 pandemic have merits for education practices beyond the pandemic.

The purpose of this paper is to investigate the potential integration of deep learning (DL) and digital twins (DT), referred to as (DDT), to facilitate Construction 4.0 through an exploratory analysis.

A mixed approach involving qualitative and quantitative analysis was applied to collect data from global industry experts via interviews, focus groups and a questionnaire survey, with an emphasis on the practicality and interoperability of DDT with decision-support capabilities for process optimization.

Based on the analysis of results, a conceptual model of the framework has been developed. The research findings validate that DL integrated DT model facilitating Construction 4.0 will incorporate cognitive abilities to detect complex and unpredictable actions and reasoning about dynamic process optimization strategies to support decision-making.

The DL integrated DT model will establish an interoperable functionality and develop typologies of models described for autonomous real-time interpretation and decision-making support of complex building systems development based on cognitive capabilities of DT.

The research explores how the technologies work collaboratively to integrate data from different environments in real-time through the interplay of the optimization and simulation during planning and construction. The framework model is a step for the next level of DT involving process automation and control towards Construction 4.0 to be implemented for different phases of the project lifecycle (design–planning–construction).

The study focuses on the negative implications that an organizational crisis can have for individual employees. Specifically, it considers job-related uncertainty, negative emotions (anxiety and frustration) and job disengagement. Through the lens of the social exchange theory, it is argued that internal crisis communication needs to provide sufficient socioemotional resources to their employees in order to mitigate these negative outcomes. In particular, the study argues for internal crisis communication that fosters organizational transparency and organizational support to achieve these mitigating effects.

An online survey among employees in Austria was administered one year after the outbreak of the COVID-19 pandemic – this specific crisis context particularly evoked job-related uncertainty and negative emotions which are considered relevant drivers of job disengagement. The hypotheses were tested using structural equation modeling based on a sample of N = 410.

Results show that employees' perceptions of job-related uncertainty are strongly linked to job-related anxiety and frustration; job-related frustration, in turn, strongly influences job disengagement. Overall, employees' perceptions of organizational transparency and organizational support contribute both to prevent the risk of job disengagement; however, the processes how these effects evolve differ. Whereas organizational transparency works on the cognitive level via a reduction of employees' perceptions of uncertainty, organizational support shows its effect on the emotional level through a reduction of job frustration.

The study contributes to the scarce research on how internal crisis communication can address employees' uncertainty, negative emotions and job disengagement during a crisis. Moreover, despite the lack of organizational responsibility for creating the crisis, the study emphasizes organizational accountability to respond to the needs of its employees to mitigate negative effects.