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The purpose of this paper is to investigate the medical incident responses from two public hospitals in Hong Kong, namely, Kowloon Hospital and Caritas Medical Centre, in order to improve the strategic preparation for crisis management in hospitals.

The paper analyses two medical incidents using Situational Crisis Communication Theory by Coombs (2007). The two case studies presented herein demonstrate the importance of consistency in terms of crisis responses.

For the first case, the crisis responses from different parties after the incident, including Hospital Authority, the doctor and the nurses from Kowloon Hospital, are contradicting to each other. First, Hospital Authority confirmed that the incident is solely an accident which is a denial response. Second, the doctor passed the responsibility to the nurses which is a scapegoating response. Third, the nurses tend to reduce the responsibility for the death of patient by excusing strategy. As a whole, their responses are inconsistent to each other. For the second case, Caritas had initially denied the responsibilities, but finally had given partial apology under public pressure. That makes people think that Caritas does not really regret.

Rebuilding posture should be used instead of denial and diminishment posture. However, public organization and civil servants are reluctant to use a full apology due to possible legal consequences. The apology ordinance would ease the pressure to express regret and sympathy.

Scientific knowledge is usually regarded as the basis for the management of natural environment and wildlife in ecotourism. However, recently, social construction approaches challenge the domination of natural science. This study aims to examine the effectiveness of the social construction paradigm in ecotourism management, through conducting a content analysis of social media comments on an accident caused by a monkey in a Chinese ecotourism area. The results show that people commented on the accident from five aspects. First, the public expressed their compassion and mourning for the deceased. Second, people thought that the death was casual and absurd, yet life is full of uncertainty and people should cherish the present. Third, people commented much on the deceased tourist’s company, which is a famous sugar brand well entrenched in many Chinese people’s childhood memories. Fourth, people constructed the monkey as Monkey King, Golden Monkey (another famous sugar brand in China) and as a criminal. Fifth, people also gave their opinions about possible causes of the accident, namely, it was caused by “the mandate of heaven,” company competition, conspiracies or poor management. This study only seriously considers the comments about the mandate of heaven. This explanation is consistent with the Chinese traditional construction of nature as “heaven,” which is believed to dominate the natural and human worlds. Most people, including the managers, accepted the accident and did not explore further about the reasons for the accident. In this case, such a social construction of nature does not aid effective ecotourism management.

Bolted joint is the most important connection method in aircraft composite/metal stacked connections due to its large load transfer capacity and high manufacturing reliability. Aircraft components are subjected to complex hybrid variable loads during service, and the mechanical properties of composite/metal bolted joint directly affect the overall safety of aircraft structures. Research on composite/metal bolted joint and their mechanical properties has also become a topic of general interests. This article reviews the current research status of aeronautical composite/metal bolted joint and its mechanical properties and looks forward to future research directions.

This article reviews the research progress on static strength failure and fatigue failure of composite/metal bolted joint, focusing on exploring failure analysis and prediction methods from the perspective of the theoretical models. At the same time, the influence and correlation mechanism of hole-making quality and assembly accuracy on the mechanical properties of their connections are summarized from the hole-making processes and damage of composite/metal stacked structures.

The progressive damage analysis method can accurately analyze and predict the static strength failure of composite/metal stacked bolted joint structures by establishing a stress analysis model combined with composite material performance degradation schemes and failure criteria. The use of mature metal material fatigue cumulative damage models and composite material fatigue progressive damage analysis methods can effectively predict the fatigue of composite/metal bolted joints. The geometric errors such as aperture accuracy and holes perpendicularity have the most significant impact on the connection performance, and their mechanical responses mainly include ultimate strength, bearing stiffness, secondary bending effect and fatigue life.

Current research on the theoretical prediction of the mechanical properties of composite/metal bolted joints is mainly based on ideal fits with no gaps or uniform gaps in the thickness direction, without considering the hole shape characteristics generated by stacked drilling. At the same time, the service performance evaluation of composite/metal stacked bolted joints structures is currently limited to static strength and fatigue failure tests of the sample-level components and needs to be improved and verified in higher complexity structures. At the same time, it also needs to be extended to the mechanical performance research under more complex forms of the external loads in more environments.

The mechanical performance of the connection structure directly affects the overall structural safety of the aircraft. Many scholars actively explore the theoretical prediction methods for static strength and fatigue failure of composite/metal bolted joints as well as the impact of hole-making accuracy on their mechanical properties. This article provides an original overview of the current research status of aeronautical composite/metal bolted joint and its mechanical properties, with a focus on exploring the failure analysis and prediction methods from the perspective of theoretical models for static strength and fatigue failure of composite/metal bolt joints and looks forward to future research directions.

Presentation of the different industrial carbon linkages of India. The purpose of this paper is to understand the direct and indirect impact of these industrial linkages.

This study uses a hypothetical extraction method with its various extensions. Under this method, different carbon linkages of a block are removed from the economy, and the effects of carbon linkages are determined by the difference between the original and the post-removal values. Energy and non-energy carbon linkages are also estimated.

“Electricity, gas and water supply (EGW)” at 655.61 Mt and 648.74 Mt had the highest total and forward linkages. “manufacturing and recycling” at 231.48 Mt had the highest backward linkage. High carbon-intensive blocks of “EGW” plus “mining and quarrying” were net emitters, while others were net absorbers. “Fuel and chemicals” at 0.08 Mt had almost neutral status. Hard coal was the main source of direct and indirect emissions.

Net emitting and key net forward blocks should reduce direct emission intensities. India should use its huge geographical potential for industrial accessibility to cheaper alternative energy. This alongside with technology/process improvements catalyzed by policy tools can help in mitigation efforts. Next, key net-backward blocks such as construction through intermediate purchases significantly stimulate emissions from other blocks. Tailored mitigation policies are needed in this regard.

By developing an understanding of India’s industrial carbon links, this study can guide policymakers. In addition, the paper lays out the framework for estimating energy and non-energy-based industrial carbon links.

In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.

By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.

The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.

Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.

This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.

This paper examines the pedagogical features of massive open online courses (MOOCs) for language learning–known as language MOOCs. The mainstream pedagogy of MOOCs typically involves the provision of short videos and reading materials for self-study; discussion forums, mostly for peer-to-peer interaction on course content; and machine-graded quizzes for self-assessment. For language learning, which has been conventionally understood as skill development, the pedagogical features of relevant MOOCs have yet to be comprehensively surveyed.

This study surveyed a total of 123 language MOOCs from the major MOOC platforms. The pedagogical features shown in these courses were identified and categorised according to the types of course materials and learning activities as well as the participation of learners and instructors.

English was the most common language taught in the courses. Over 80% of the courses took not more than six hours to complete. Most of these courses followed the typical approach of xMOOC delivery, with video watching, reading and auto-graded assessment being the most common learning activities. Less than half of the courses included discussion as part of learning, and instructors were involved in less than 30% of the discussion.

The findings show that, despite the technological advances in course delivery, current language MOOCs do not differ substantially from conventional distance language learning. Yet, the utilisation of computer-assisted language learning technology and the massive student base of MOOCs for creating a virtual social community are opportunities for developing learners' language proficiency on this learning environment.

During rush hours, many passengers find it difficult to board the first train due to the insufficient capacity of metro vehicles, namely, left behind phenomenon. In this paper, a data-driven approach is presented to estimate left-behind patterns using automatic fare collection (AFC) data and train timetable data.

First, a data preprocessing method is introduced to obtain the waiting time of passengers at the target station. Second, a hierarchical Bayesian (HB) model is proposed to describe the left behind phenomenon, in which the waiting time is expressed as a Gaussian mixture model. Then a sampling algorithm based on Markov Chain Monte Carlo (MCMC) is developed to estimate the parameters in the model. Third, a case of Beijing metro system is taken as an application of the proposed method.

The comparison result shows that the proposed method performs better in estimating left behind patterns than the existing Maximum Likelihood Estimation. Finally, three main reasons for left behind phenomenon are summarized to make relevant strategies for metro managers.

First, an HB model is constructed to describe the left behind phenomenon in a target station and in the target direction on the basis of AFC data and train timetable data. Second, a MCMC-based sampling method Metropolis–Hasting algorithm is proposed to estimate the model parameters and obtain the quantitative results of left behind patterns. Third, a case of Beijing metro is presented as an application to test the applicability and accuracy of the proposed method.

As climate change impacts residential life, people typically use heating or cooling appliances to deal with varying outside temperatures, bringing extra electricity demand and living costs. Water is more cost-effective than electricity and could provide the same body utility, which may be an alternative choice to smooth electricity consumption fluctuation and provide living cost incentives. Therefore, this study aims to identify the substitute effect of water on the relationship between climate change and residential electricity consumption.

This study identifies the substitute effect of water and potential heterogeneity using panel data from 295 cities in China over the period 2004–2019. The quantile regression and the partially linear functional coefficient model in this study could reduce the risks of model misspecification and enable detailed identification of the substitution mechanism, which is in line with reality and precisely determines the heterogeneity at different consumption levels.

The results indicate that residential water consumption can weaken the impact of cooling demand on residential electricity consumption, especially in low-income regions. Moreover, residents exhibited adaptive asymmetric behaviors. As the electricity consumption level increased, the substitute effects gradually get strong. The substitute effects gradually strengthened when residential water consumption per capita exceeds 16.44 tons as the meeting of the basic life guarantee.

This study identifies the substitution role of water and heterogeneous behaviors in the residential sector in China. These findings augment the existing literature and could aid policymakers, investors and residents regarding climate issues, risk management and budget management.

In this paper, the authors use the balance sheet data to investigate the interconnectedness and risk contagion effects in China's banking sector. They firstly study the network structure and centrality of the interbank network. Then, they investigate how and to what extent the credit shock and liquidity shock can lead to the risk propagation in the banking network.

Referring to the theoretical framework by Haldane and May (2011), this paper uses the network topology theory to analyze the contagion mechanism of credit shock and liquidity shock. Centrality measures and log-log plot are used to evaluate the interconnectedness of China's banking network.

The network topology has shown clustering effects of large banks in China's financial network. If the Industrial and Commercial Bank of China (ICBC) is in distress, the credit shock has little impact on the Chinese banking sector. However, the liquidity shock has shown more substantial effects than that of the credit shock. The discount rate and the rollover ratio play significant roles in determining the contagion effects. If the credit shock and liquidity shock coincide, the contagion effects will be amplified.

The results of this paper reveal the network structure of China's interbank market and the resilience of banking system to the adverse shock. The findings are valuable for regulators to make policies and supervise the systemic important banks.

The balance sheet data of different types of banks are used to construct a bilateral exposure matrix. Based on the matrix, this paper investigates the knock-on effects of credit shock triggered by the debt default in the interbank market, the knock-on effects of liquidity effects, which is featured by “fire sale” of bank assets, and the contagion effects of combined shocks.