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The victim’s rights movement and restorative justice (RJ) have gained momentum around the world. More laws and policies have focused on crime victims and their families. Western literature suggests that the victim’s family suffers physical, emotional, and financial tolls and that the power of the victim’s family in pursuing justice for their loved ones remains limited. This is particularly concerning within the political and legal context of the abolitionist movement, innocence project, and human rights groups’ campaigns against police torture. Grounded in the perspectives of RJ and Chinese legal culture, this study examines the victim’s family, represented by Ding and senior Yu, of the Nian Bin capital murder case. Drawing on published reports and using the thematic content analysis method, this study examines the following aspects of victim’s family in a death penalty case: 1) victim family’s physical, emotional, and financial tolls; 2) victims’ family and the criminal justice system; 3) victims’ family and the media; and 4) the relationship between the victims’ and the accused’s families. This study concludes with discussions of the competing goals of families impacted by a crime and RJ practices that would help mitigate the loss of the victim’s family and enhance their confidence in the criminal justice system.

Many experts agree with the opinion that blockchain technology will bring about a revolution and create a new system of living, relating and doing business. What so far seems to be an experimental phenomenon, which is already producing results and creating high-value communities, may soon become a real social transformation. The case study presented here sheds some light on the blockchain reality, the importance of digital entrepreneurial talent, which seeks to take advantage of a situation in the country to develop a commercial project attractive to foreign investors. The authors analyze the key elements of the success of a Paraguayan company focused on high-tech operations. The authors venture to present an exploratory model of management in the blockchain world, in order to collaborate, cooperate and encourage the success of many future digital ventures.

The need for an efficient enterprise risk management (ERM) has never been greater than today when organisations face complex and interconnected risks targeting their business models. Macroeconomics and geopolitical uncertainties, digital transformations of industries and sectors, cybersecurity, and climate change, among other trends, present significant uncertainties. This article aims to analyse the scientific papers on research specific to ERM and review the links between the researched area and market or corporate governance topics. Risk management is underdeveloped in many organisations; the current standard for risk management is a reactive approach. It is usually treated in isolation rather than as a core competency and a strategic asset. As a result, risk management processes are ineffective and seen as adding value to decision-making and responding to uncertainties. Based on the literature, the scope is to set up the framework for future research on ERM by building a bibliometric analysis and examining articles collected from the Web of Science Core Collection database. The study identified the essential research on this topic based on the citations of the papers and the author’s countries with the highest number of publications and citations. VOSviewer software analysed the ERM system based on keywords, citations, geographical distribution, and authorships. The research proves a strong connection between the ERM and corporate governance topics considering the stage where most countries are regarding this subject.

The COVID-19 pandemic has substantially affected China’s tourism industry. Tourism small- and medium-sized enterprises (SMEs), with limited crisis response ability, might be difficult to recover after the pandemic. Regarding the impacts of the pandemic on rural tourism, income for rural attraction sites was almost zero; sightseeing, agri-tourism activities were ceased; and large amount of rural bed-and-breakfasts (B&Bs) faced business closure. However, through three cases, our study found that through either content innovation or process innovation, some B&Bs are able to recover speedily from the pandemic and develop sustainably. These innovations are important for their business strategy adjustment. Innovation creates more value for tourists and stakeholders by developing new service products or adjusting existing products. This chapter discusses the linkages between innovation and leadership. Through the investigation and analysis of three cases, the researchers found that the advantages of transformational leadership were reflected in the post-crisis management in different ways and effectively improved the innovation ability and sustainable development of post-crisis organizations. This study has enriched the literature on transformational leadership and post-crisis recovery of small tourism enterprises and has practical reference value for managers of small rural tourism companies.

In this chapter, rephrasing Spivak's question into ‘can subaltern children speak?’, I reorient the research on China's gigantic population of children and youths in rural migrant families towards a critical interpretative approach. Based on life history and longitudinal ethnographic interview gathered with three cases, I unpack the multiple meanings migrants' children attach to mobility in their childhood experiences. First, despite emotional difficulties, children see their parents' out-migration more as a ‘mobility imperative’ than their abandonment of parental responsibilities, which should be contextualized in China's long-term urban-biased social policies and the resultant development gaps in rural and urban societies. Second, the seemingly ‘unstable’ and ‘flexible’ mobility patterns observed in migrant families should be understood in relation to a long-term family social mobility strategy to promote children's educational achievement and future attainment. The combination of absent class politics in an illiberal society with an enduring ideology of education-based meritocracy in Confucianism makes this strategy a culturally legitimate channel of social struggle for recognition and respect for the subaltern. Last, children in migrant families are active contributors to their families' everyday organization amidst mobilities through sharing care and household responsibilities, and developing temporal and mobility strategies to keep alive intergenerational exchanges and family togetherness. The study uncovers coexisting resilience and vulnerabilities of migrants' children in their ‘doing class’ in contemporary China. It also contributes insights into our understanding of the diversity of childhoods in Asian societies at the intersection of familyhood, class dynamics and cultural politics.

Machine learning (ML) has recently gained momentum as a method for measurement in strategy research. Yet, little guidance exists regarding how to appropriately apply the method for this purpose in our discipline. We address this by offering a guide to the application of ML in strategy research, with a particular emphasis on data handling practices that should improve our ability to accurately measure our constructs of interest using ML techniques. We offer a brief overview of ML methodologies that can be used for measurement before describing key challenges that exist when applying those methods for this purpose in strategy research (i.e., sample sizes, data noise, and construct complexity). We then outline a theory-driven approach to help scholars overcome these challenges and improve data handling and the subsequent application of ML techniques in strategy research. We demonstrate the efficacy of our approach by applying it to create a linguistic measure of CEOs' motivational needs in a sample of S&P 500 firms. We conclude by describing steps scholars can take after creating ML-based measures to continue to improve the application of ML in strategy research.

This chapter summarizes the literature on mindfulness and its impact of postdisaster response. Although the use of mindfulness is still in its infancy in Southeast Asia (SEA), initial studies suggest it has potential as a means to address survivors’ posttrauma symptoms. Given cultural nuances such as a discomfort in emotional expression and shame, mindfulness is non-intrusive and encourages non-judgmental acceptance. Mindfulness has been used in group settings which is congruent with the region’s collectivist orientation. In addition, given the importance of spirituality, we suggest that mindfulness may be an inclusive approach that is familiar and acceptable to SEA survivors.

Carbon emission is one of the most important issues threatening the existence of the world. Mostly carbon emission induced climate change disrupts human and nature balance. Carbon emission occurs as a result of practices that are dependent on human activities or not. One of the actors causing carbon emissions is production companies. The companies are working toward reducing carbon emissions. However, although these efforts reduce carbon emissions in the short term, carbon emissions continue in the long term. Therefore, the present study aims to determine the importance of carbon emission in terms of sustainable economic development. Depending on this purpose, production companies in Chile were included in the scope of research for 1990–2019. Based on these data, the study has been tested by Toda Yamamoto causality analysis. Result shows that carbon emissions are not the primary cause of sustainable economic development. In this context, governments need to focus on other issues that have a stronger causal relationship with sustainable economic development. However, studies should be conducted to determine the importance of other activities of companies for sustainable economic development. Hereby, the amount of carbon emission will be reduced and deficiencies in factors affecting sustainable economic development will be identified.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.

Introduction: Human resource management (HRM) is going through a transformation phase due to the pandemic. The COVID-19 crisis compelled the employees to work virtually. To mitigate the effects of COVID-19, several organisations heavily invested in artificial intelligence (AI) in the realm of HRM.

Purpose: With limited studies on the paradigm shift in HRM post-pandemic and the role of AI, the study investigates and proposes a conceptual framework for the paradigm shift in HRM practices post-COVID-19 pandemic and the significance of AI. Furthermore, the study investigates the outcomes of the use of AI in HRM for organisations and employees.

Methodology: A comprehensive review of the literature based on the guidelines of Tranfield, Denyer, and Smart (2003) and Crossan and Apaydin (2010) has been followed. A systematic literature review assisted in critically analysing, synthesising, and mapping the extant literature by identifying the broad themes involved.

Findings: COVID-19-related economic disruption has led to a paradigm shift in HRM practices. AI-enabled HRM practices are now centred around remote and contingent workforce management, mindfulness, social capital, increasing employee engagement, reskilling and upskilling towards new competencies, etc. AI is making remote work seamless through smooth recruitment and selection process, onboarding, career and development, tracking and managing the performance, facilitating learning, and talent management. Post-pandemic, AI-powered tools based on data mining (DM), predictive analytics, big data analytics, natural language processing (NLP), intelligent robots, machine learning (ML), virtual (VR)/augmented reality (AR), etc., have paved the way for managing the HRM practices effectively, thereby leading to enhanced organisational performance, employee well-being, automation, and reduced cost.