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The COVID-19 pandemic has caused severe challenges to ethnic minorities in the UK. While the experiences of migrants are both complex and varied depending on individuals' social class, race, cultural proximity to the host country and acculturation levels, more in-depth studies are necessary to fully understand how COVID-19 affects specific migrant groups and their health. Taiwanese migrants were selected because they are an understudied group. Also, there were widespread differences in pandemic management between the UK and Taiwan, making this group an ideal case for understanding how their acculturation journey can be disrupted by a crisis.

Qualitative data were collected at two different time points, at the start of the UK pandemic (March/April 2020) and six months on (October/November 2020), to explore migrant coping experiences over time. Theoretically, the authors apply acculturation theory through the lens of coping, while discussing health-consumption practices, as empirical evidence.

Before the outbreak of the pandemic, participants worked hard to achieve high levels of integration in the UK. The pandemic changed this; participants faced unexpected changes in the UK’s sociocultural structures. They were forced to exercise the layered and complex “coping with coping” in a hostile host environment that signalled their new marginalised status. They faced impossible choices, from catching a life-threatening disease to being seen as overly cautious. Such experience, over time, challenged their integration to the host country, resulting in a loss of faith in the UK’s health system, consequently increasing separation from the host culture and society.

It is important to note that the Taiwanese sample recruited through Facebook community groups is biased and has a high level of homogeneity. These participants were well-integrated, middle-class migrants who were highly educated, relatively resourceful and active on social media. More studies are needed to fully understand the impact on well-being and acculturation of migrants from different cultural, contextual and social backgrounds. This being the case, the authors can speculate that migrants with less resource are likely to have found the pandemic experience even more challenging. More studies are needed to fully understand migrant experience from different backgrounds.

Public health policymakers are advised to dedicate more resources to understand migrants' experiences in the host country. In particular, this paper has shown how separation, especially if embraced temporarily, is not necessarily a negative outcome to be corrected with specific policies. It can be strategically adopted by migrants as a way of defending their health and well-being from an increasingly hostile environment. Migrants' home country experience provides vicarious learning opportunities to acquire good practices. Their voices should be encouraged rather than in favour of a surprising orthodox and rather singular approach in the discussion of public health management.

The paper has clear public health policy implications. Firstly, public health policymakers are advised to dedicate more resources to understand migrants' experiences in the host country. Acknowledging migrants' voice is a critical first step to contribute to the development of a fair and inclusive society. Secondly, to retain skilful migrants and avoid a future brain-drain, policymakers are advised to advance existing infrastructure to provide more incentives to support and retain migrant talents in the post-pandemic recovery phase.

This paper reveals how a group of previously well-integrated migrants had to exercise “coping with coping” during the COVID crisis. This experience, over time, challenged their integration to the host country, resulting in a loss of faith in the UK’s health system, consequently increasing separation from the host culture and society. It contributes to the understanding of acculturation by showing how a such crisis can significantly disrupt migrants' acculturation journey, challenging them to re-acculturate and reconsider their identity stance. It shows how separation was indeed a good option for migrants for protecting their well-being from a newly hostile host environment.

This paper aims to propose a novel control scheme and offer a control parameter optimizer to achieve better automatic carrier landing. Carrier landing is a challenging work because of the severe sea conditions, high demand for accuracy and non-linearity and maneuvering coupling of the aircraft. Consequently, the automatic carrier landing system raises the need for a control scheme that combines high robustness, rapidity and accuracy. In addition, to exploit the capability of the proposed control scheme and alleviate the difficulty of manual parameter tuning, a control parameter optimizer is constructed.

A novel reference model is constructed by considering the desired state and the actual state as constrained generalized relative motion, which works as a virtual terminal spring-damper system. An improved particle swarm optimization algorithm with dynamic boundary adjustment and Pareto set analysis is introduced to optimize the control parameters.

The control parameter optimizer makes it efficient and effective to obtain well-tuned control parameters. Furthermore, the proposed control scheme with the optimized parameters can achieve safe carrier landings under various severe sea conditions.

The proposed control scheme shows stronger robustness, accuracy and rapidity than sliding-mode control and Proportion-integration-differentiation (PID). Also, the small number and efficiency of control parameters make this paper realize the first simultaneous optimization of all control parameters in the field of flight control.

This paper aims to empirically investigate the impact of the carbon intensity constraint policy (CICP) on green innovation.

This study takes the implementation of the CICP as a quasi-natural experiment and uses a quasi–difference-in-difference method to investigate the impact of the CICP on firm green innovation from a microeconomic perspective.

The CICP significantly limits the quality of firms’ green innovation. Among the range of green patents, the CICP distorts only patents related to CO₂ emissions. The inhibitory effect is more pronounced in non-state-owned enterprises and heavily polluting firms. R&D investment and green investor are identified as the main mechanism.

These findings provide evidence for the influence of the CICP on firm green innovation, which can guide policymakers in China and other emerging economies that prioritize carbon intensity constraint targets and the improvement of relevant auxiliary measures.

Governments and firms should have a comprehensive understanding of environmental policies and corporate behavior and need to mitigate the negative impact through a combination of measures.

This study contributes to the literature by providing additional empirical evidence regarding the two opposing sides of the ongoing debate on the positive or negative effects of CICP. It also provides new evidence on the policy effect of the CICP on firm green innovation, together with its mechanisms and heterogeneous influences.

In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.

To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.

The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.

The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.

Purpose: The study aims to analyse and discuss the effect of COVID-19 on businesses. The chapter discusses the various machine learning (ML) tools and techniques, which can help in better decision making by businesses in the present world.

Need for the Study: COVID-19 has increased the role of VUCA elements in the business environment, and there is a need to address the challenges faced by businesses in such environment. ML and artificial learning can help businesses in facing such challenges.

Methodology: The focus and approach of the chapter are in the context of using artificial intelligence (AI) and ML techniques for decision making during the COVID-19 pandemic in a VUCA business environment.

Findings: The key findings and their implications emphasise the importance of understanding and implementing AI and ML techniques in business strategies during times of crisis.

Practical Implications: The chapter’s content is in the context of using AI and ML techniques during the COVID-19 pandemic and in a VUCA business environment.

This study aims to examine the relationship between contextual factors and career exploration. Career adaptability mediates the relationship between social support, sense of belonging and career exploration.

This quantitative study involved 291 undergraduates recruited from two universities in China. Data were analyzed using structural equation modeling.

The results indicated that social support and sense of belonging were positively related to career adaptability. Career adaptability was found to be a mediator between relational predictors and career exploration. Contrary to our hypothesis, the direct path from sense of belonging to career exploration was insignificant.

This study highlights the importance of career adaptability in connecting contextual indicators and career exploration in the Chinese context.

Given the important role of change capability for organizational development and competitive advantage, the purpose of this study is to clarify the influences of transformational leadership (TL) on organizational change capability (OCC) via mediating roles of two specific aspects of trust in leadership namely disclosure-based trust and reliance-based trust.

Structural equation modeling is applied to test the degree of influences of TL and employee trust on OCC via empirical data collected from 376 participants in 115 small and medium firms in China.

The results show the positive and significant impacts of TL and aspects of employee trust in leadership on OCC. It indicated that disclosure-based trust in leadership has a greater influence on change capability in comparison with the effect of reliance-based trust in leadership. Especially, the findings have shown the evidence supporting the mediating mechanism of aspects of employee trust in leadership between TL and OCC.

This study provides the practical initiatives that highlight the importance of applying TL style to build and improve the trust of employees in their leadership for fostering OCC.

The paper has significantly advanced and deepened insight of how transformational leaders nurture employee’s specific shades of trust in leadership for fostering OCC. The valuable findings of this study contribute to enriching the theoretical basis of organizational behavior and change management, and can be used to analyze and explain the relationships between TL, employee’s trust in leadership and organizational capability for change.

The main purpose of this paper is to examine the adoption of big data analytics (BDA) in the Tanzania banking industry by investigating the influence of technological, environmental and organizational (TOE) factors while exploring the moderating role of perceived risk (PR).

The study employed a qualitative research design, and the research instrument was developed using per-defined measurement items adopted from prior studies; the items were slightly adjusted to fit the current context. The questionnaires were distributed to top and middle managers in selected banks in Tanzania using the snowball sampling technique. Out of 360 received responses, 302 were considered complete and valid for data analysis. The study employed partial least squares structural equation modeling (PLS-SEM) to examine the developed conceptual framework.

Top management support and financial resources emerged as influential organizational factors, as did competition intensity for the environmental factors. Notably, bank size and perceived trends showed no significant impacts on BDA adoption. The study's novelty lies in revealing PR as a moderating factor, weakening the link between technological readiness, perceived usefulness and the intent to adopt BDA.

This study extends literature by extending the TOE model, through examining the moderating roles of PR on technological factors. Furthermore, the study provides useful managerial support for the adoption of BDA in banking in emerging economies.

The study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative assessments for OB.

The study applied exploratory factor analysis (EFA) to 764 respondents to explore dimensions of OB. These were validated with formative assessments on 489 respondents by the partial least square path modeling (PLS-PM) approach in SmartPLS 4.0 software.

The major findings of EFA explored four dimensions for OB, i.e. accuracy, perceived control, positive illusions and past investment success. The formative assessments revealed that positive illusions followed by past investment success among retail investors played an instrumental role in orchestrating the OBs that affect investment decisions in financial markets.

The formative index of OB has several practical implications for registered financial and investment advisors, bank advisors, business media companies and portfolio managers, besides individual investors in the domain of behavioral finance.

This research provides a novel approach to provide a formative index of OB with four dimensions. This formative index can acts as an overview for upcoming researchers to investigate the OB of retail individual investors.

1. Overconfidence bias is an important predictor of retail investors' behavior

2. Formative dimensions of the overconfidence bias index.

3. Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

4. Modern portfolio theory and illusion of control theory support this study.

Overconfidence bias is an important predictor of retail investors' behavior

Formative dimensions of the overconfidence bias index.

Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

Modern portfolio theory and illusion of control theory support this study.

Collaborative projects require overlapping skills and capabilities to facilitate knowledge transfer. However, not all kinds of learning are virtuous and some may lead to leakage of commercially valuable knowledge. The purpose of this paper is to explain and restrain leakage of organizational competitive knowledge in collaborative projects.

A total of 398 survey questionnaires are collected from project-based firms in Pakistan. We gathered data from horizontal and vertical collaborations. Analysis is conducted with transaction cost economics lens through Process Macro 3.0.

Findings suggest that partner’s learning intent (PLI) and distrust positively affect knowledge leakage, whereas human resource management (HRM) practices have negative effect on knowledge leakage. Furthermore, HRM practices negatively moderate the relationship between PLI and knowledge leakage and distrust positively mediates it.

This study integrates HRM with knowledge management to restrain knowledge leakage and contributes to knowledge management and strategic management. This study examines knowledge leakage in the presence of passive opportunism.

This study explains how passive opportunism translates into opportunistic behavior. Besides, effectiveness of HRM practices are least surveyed to restrain passive and active opportunisms.