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This paper aims to study individuals’ information service satisfaction during the COVID-19 pandemic lockdown in China’s urban communities.

The researchers analyse people’s uncertainties during the pandemic and argue that uncertainties caused by the lockdown can negatively affect people. By reducing people’s uncertainty during the pandemic, community staff members can improve individuals’ information service satisfaction and social order. This study constructs a conceptual model that includes key transparency and self-disclosure constructs and their relationships that can contribute to the trust and satisfaction of the community information service phenomenon. The researchers collected 489 responses to test their hypothesis from an online survey of Chinese residents in areas where the strict lockdown policy was implemented.

The empirical results show that policy and goods information transparency significantly affect information service satisfaction in a positive way, with goods information transparency having the highest impact. Second, self-disclosure of community staff members is also an effective way to increase information service satisfaction. Finally, trust plays a mediating role in the influence of information transparency and self-disclosure on information service satisfaction.

This paper innovatively uses uncertainty reduction theory to examine the effects of information transparency and self-disclosure on satisfaction with community information services. It expands the research in the field of information service satisfaction and extends the scope of the research subjects of self-disclosure.

This study aims to examine how different hospitals utilize social media to communicate risk information about COVID-19 with the communities they serve, and how hospitals' social media messaging (firm-generated content and their local community's responses (user-generated content) evolved with the COVID-19 outbreak progression.

This research proposes a healthcare-specific social media analytics framework and studied 68,136 tweets posted from November 2019 to November 2020 from a geographically diverse set of ten leading hospitals' social media messaging on COVID-19 and the public responses by using social media analytics techniques and the health belief model (HBM).

The study found correlations between some of the HBM variables and COVID-19 outbreak progression. The findings provide actionable insight for hospitals regarding risk communication, decision making, pandemic awareness and education campaigns and social media messaging strategy during a pandemic and help the public to be more prepared for information seeking in the case of future pandemics.

For hospitals, the results provide valuable insights for risk communication practitioners and inform the way hospitals or health agencies manage crisis communication during the pandemic For patients and local community members, they are recommended to check out local hospital's social media sites for updates and advice.

The study demonstrates the role of social media analytics and health behavior models, such as the HBM, in identifying important and useful data and knowledge for public health risk communication, emergency responses and planning during a pandemic.

With the worsening of corporate fraud and consequential loss, the growing importance of truthful disclosure is globally advocated. This study aims to examine corporate governance’s role in accountants’ intention to disclose fraudulent practices honestly. At the same time, this study examines intergender differences concerning the formation of the disclosure intention.

Based on the theory of planned behavior (TPB), data from 256 accountants working in China have been collected via an online survey. This data is subsequently analyzed with the partial least square (PLS) structural equation modeling method.

The results revealed that integrity and corporate governance significantly positively affect employees’ attitudes, subjective norms and perceived behavioral control toward disclosure intention. At the same time, it shows that only subjective norm and perceived behavioral control established a significant positive relationship with disclosure intention. It also shows that males display higher attitudes and perceived behavioral control in developing the intention.

This study helps understand accountants’ disclosure intention of fraud practices, especially during shock events such as the COVID-19 pandemic. To the best of the authors’ knowledge, this study is the first to extend the TPB incorporating corporate governance and integrity as antecedents to disclosure intention. At the same time, this study contributes to the existing literature by being the first attempt to investigate intergender differences. Finally, it advances the body of knowledge on employees’ behavior and contributes methodologically by introducing the PLS approach.

The main purpose of the paper is timing analysis of mixed critical applications on the multicore system to identify an efficient task scheduling mechanism to achieve three main objectives improving schedulability, achieving reliability and minimizing the number of cores used. The rise in transient faults in embedded systems due to the use of low-cost processors has led to the use of fault-tolerant scheduling and mapping techniques.

The paper opted for a simulation-based study. The simulation of mixed critical applications, like air traffic control systems and synthetic workloads, is carried out using a litmus-real time testbed on an Ubuntu machine. The heuristic algorithms for task allocation based on utilization factors and task criticalities are proposed for partitioned approaches with multiple objectives.

Both partitioned earliest deadline first (EDF) with the utilization-based heuristic and EDF-virtual deadline (VD) with a criticality-based heuristic for allocation works well, as it schedules the air traffic system with a 98% success ratio (SR) using only three processor cores with transient faults being handled by the active backup of the tasks. With synthetic task loads, the proposed criticality-based heuristic works well with EDF-VD, as the SR is 94%. The validation of the proposed heuristic is done with a global and partitioned approach of scheduling, considering active backups to make the system reliable. There is an improvement in SR by 11% as compared to the global approach and a 17% improvement in comparison with the partitioned fixed-priority approach with only three processor cores being used.

The simulations of mixed critical tasks are carried out on a real-time kernel based on Linux and are generalizable in Linux-based environments.

The rise in transient faults in embedded systems due to the use of low-cost processors has led to the use of fault-tolerant scheduling and mapping techniques.

This paper fulfills an identified need to have multi-objective task scheduling in a mixed critical system. The timing analysis helps to identify performance risks and assess alternative architectures used to achieve reliability in terms of transient faults.