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In this chapter, the authors provide a historical overview of the development of comparative and international education societies throughout the earth. In most cases, these societies have gradually grown and continue to thrive; in other cases, some comparative education societies have become dormant and a few no longer exist. A historical analysis that outlines the rise and fall of comparative education societies is provided. An overview of the World Council of Comparative Education Societies is also discussed, including its lead organizational role in serving as a historical hub to help comparative education societies preserve and disseminate their respective histories. The chapter concludes with suggestions on how anyone can get involved to help contribute to the history preservation of comparative education at the individual, national, regional, and global levels.

This chapter reviews three main issues in the interactions between air transport and high-speed rail (HSR) in China, namely the interaction between low-cost carriers (LCCs) and HSR, HSR speed effect on airlines, and airline–HSR integration. Studies on these three aspects of airline–HSR interactions have yet been well reviewed, and our chapter aims to fill in this gap. In this chapter, we comprehensively survey literature on the topics, especially studies on Chinese markets that have recently witnessed major HSR developments (and have planned further large-scale HSR expansion in the coming years). Our review shows that, first, compared to full-service carriers, LCCs face fiercer competition from HSR. However, the expansion of HSR network in China can be better coordinated with LCC development. Second, HSR speed exerts two countervailing effects on airline demand and price (the “travel-time” effect and “safety” effect, respectively). Specifically, an HSR speed reduction can have a positive effect on airlines due to longer HSR travel time, but a negative effect on airlines due to improved perception on HSR safety. Third, airline–HSR integration can be implemented through cooperation between airlines and HSR operators and through co-location of airports and HSR stations and can have important implications for intermodal transport and social welfare.

Due to climate change and an increasing concentration of the world’s population in vulnerable areas, how to manage catastrophe risk efficiently and cover disaster losses fairly is still a universal dilemma.

This paper applies a law and economic approach.

China’s mechanism for managing catastrophic disaster risk is in many ways unique. It emphasizes government responsibilities and works well in many respects, especially in disaster emergency relief. Nonetheless, China’s mechanism which has the vestige of a centrally planned economy needs reform.

I propose a catastrophe insurance market-enhancing framework which marries the merits of both the market and government to manage catastrophe risks. There are three pillars of the framework: (i) sustaining a strong and capable government; (ii) government enhancement of the market, neither supplanting nor retarding it; (iii) legalizing the relationship between government and market to prevent government from undermining well-functioning market operations. A catastrophe insurance market-enhancing framework may provide insights for developing catastrophe insurance in China and other transitional nations.

First, this paper analyzes China’s mechanism for managing catastrophic disaster risks and China’s approach which emphasizes government responsibilities will shed light on solving how to manage catastrophe risk efficiently and cover disaster losses fairly. Second, this paper starts a broader discussion about government stimulation of developing catastrophe insurance and this framework can stimulate attention to solve the universal dilemma.

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.

This paper provides evidence on the impact of regulatory environment on financial reporting quality of transitional economies. This study compares the financial reporting quality of Hong Kong firms which are cross-listed in mainland China with those of Hong Kong firms cross-listed in China using specific earnings management metrics (earnings smoothing, timely loss recognition, value relevance and managing towards earnings targets) under pre- and post-IFRS regimes.

The financial reporting quality of Chinese A-share companies and Hong Kong listed companies are examined using earnings management measures. Using 2007 as base year, the study used a cumulative of −5 and +5 years of convergence experience which provide a total of 3,000 firm-year observations. In addition to regression analyses, we used the difference-in-difference analysis to check for the impact of regulatory environments on earnings management.

Through the lens of contingency theory, our results indicate that the adoption of the new substantially IFRS-convergent accounting standards in China results in better financial reporting quality evidenced by less earning management. The empirical results further shows that accounting data are more value relevant for Hong Kong listed firms, and that firms listed in China are more likely to engage in accrual-based earnings management than in real earnings management activities. We established that different earnings management practices that are seemingly tolerable in one country may not be tolerable in another due to level of differences in the regulatory environments.

The findings show that Hong Kong listed companies’ exhibit higher level of financial reporting quality than Chinese listed companies, which implies that the financial reporting quality under IFRS can be significantly different in regions with different institutional, economic and regulatory environments. The results imply that contingent factors such as country’s institutional structures, its extent of regulation and the strength of its investor protection environments impact on financial reporting quality particularly in transitional and emerging economies. As such, these factors need to be given appropriate considerations by financial reporting regulators and policy-makers interested in controlling earnings management practices among their corporations.

This study is a high impact study considering that China plays a significant role in today’s globalised economy. This study is unique as it the first, that we are aware of, to compare real earnings activities against accrual-based earnings management in pre- and post-IFRS adoption periods within the Chinese and Hong Kong financial reporting environments, distinguishing between cross-listed and non-cross-listed firms.

The newsvendor problem is fundamental to many operations management models. The problem focuses on the trade-off between the gains from satisfying demand and losses from unsold products. The newsvendor model and its extensions have been applied to various areas, such as production plan and supply chain management. This chapter examines the study about newsvendor problem. In this research, there is a review of the contributions for the multiproduct newsvendor problem. It focuses on the current literature concerning the mathematical models and the solution methods for the multiitem newsvendor problems with single or multiple constraints, as well as with the risks. The objective of this research is to go over the newsvendor problem and bring into comparison different newsvendor models applied to the flower industry. A few case studies are described addressing topics related to the newsvendor problem such as discounting and replenishment policies, inventory inaccuracies, or demand estimation. Three newsvendor models are put into practice in the field of flower selling. A full database of the flowers sold by an anonymous retailer is available for the study. Computational experiments for practical example have been conducted with use of the CPLEX solver with AMPL programming language. Models are solved, and an analysis of different circumstances and cases is accomplished.

Due to its contribution to poverty reduction, which is one of the United Nations’ Sustainable Development Goals, inclusive finance is an issue of discussion. By using a bibliometric analysis approach, this study conducts performance analysis and keyword co-occurrences analysis under VOS viewer to synthesize the characteristics and essential dimensions of financial inclusion in Asia. This research studies 1,072 articles contributed by 1,928 authors, during the years 2005–2022. Numerous figures and networks are provided in order to comprehend publication trends, influential authors and their affiliations and countries, influential publications, and keyword occurrences. Six clusters were discovered, and financial inclusion is in the same cluster as financial literacy and financial service. This research will provide valuable insights for governments, regional authorities, and academic researchers, enabling them to enhance their comprehension of Asian financial inclusion and identify prospective avenues for future research. Ahead of this research, a comprehensive bibliometric analysis of financial inclusion in Asian countries has not been conducted, as far as the authors’ knowledge goes. The study offers a comprehensive overview of financial inclusion in Asia and reveals insights into the field’s crucial messages. Future researchers can use this knowledge to obtain a deeper understanding of the field.

Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.