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Individuals who spend a large percentage of their incomes on consumption are perceived to prefer risks. Since entrepreneurs are well recognized as risk-takers, this chapter investigates whether consumption propensity is associated with entrepreneurship. Using micro-level data from Chinese Household Income Project, we find that households with a higher income–consumption ratio on average have a higher preference for risk-seeking, while they have a lower probability to be entrepreneurs. However, households who have higher consumption–income ratio and are in the top 10% of the wealth distribution are more likely to embark on entrepreneurship. In addition, we find that in-system connection (relationship with government-related units) decreases the likelihood of starting new business, while out-system connection (relationship with market units) increases it. These findings suggest that in an imperfect financial market, start-up finance and connections play important roles for entrepreneurship.

COVID-19 impacted the tourism sector, and its ripple effect is equally evident in tourism academia at all levels. Since innovation in tourism pedagogy is considered an epicentre of quality education, this study proposes an integrated model to identify the degree of pedagogical innovation adapted by tourism educators. The model is an amalgamation of innovation indicators in teaching practices developed by Sigala (2021), a futurist model developed by Wassler and Fan (2021) and a model of innovation developed by Brooker and Joppe (2014).

The study is exploratory, and an online qualitative survey was used to collect data. Data were analysed using the Nvivo 12 software and three themes were drawn: Painters, Artists and Artisans.

The study found that the majority of the tourism educators are painters as they adopted minor changes in their pedagogy. They follow the conventional methods of teaching by incorporating ICT into their pedagogy. Whereas a smaller group of tourism educators introduced innovative tools to encourage and equip students with professional skills (artists/artisans).

The study suggests practical implications for tourism educators to embrace and innovate their pedagogy to become ‘artists/artisans’. The support of Higher Education Institutions (HEIs) and industry professionals are equally crucial for bringing innovation in tourism pedagogy and academia, in general, artisans.

Given that tourism education has scantly been discussed following the breakout of COVID-19 (Sigala, 2020), the study addresses that resurrection of tourism pedagogy through an integrated model.

This chapter examines China’s corporate governance and accounting environment that shapes the adoption of internationally acceptable principles and standards. Specifically, it examines international influences, including supranational organizations; foreign investors and international accounting firms; domestic institutional influences, including the political system, economic system, legal system, and cultural system; and accounting infrastructure. China’s convergence is driven by desired efficiency of the corporate sector and legitimacy of participating in the global market. Influenced heavily by international forces in the context of globalization, corporate governance and accounting practices are increasingly becoming in line with internationally acceptable standards and codes. While convergence assists China in obtaining legitimacy, improving efficiency is likely to be adversely affected given that corporate governance and accounting in China operate in an environment that differs considerably from those of Anglo-American countries. An examination of the corporate governance and accounting environment in China suggests heavy government involvement within underdeveloped institutions. While the Chinese government has made impressive progress in developing the corporate governance and accounting environment for the market economy, China’s unique institutional setting is likely to affect how the imported concepts are interpreted and implemented.

The visibility and impact of young activists is evident in 2020 more than ever, most clearly in the Black Lives Matter movement, but also among climate strikers, water protectors, March for Our Lives organizers, and even TikTok users and K-pop music fans. The ambivalence with which adults have responded – from pride to dismissal to demonization – has its roots in implicit yet pervasive assumptions about young people stretching back to the early nineteenth century. Through a brief historical sketch, I demonstrate that the contemporary concept of the “American teenager” is the product of a series of social, economic, and political changes in the United States and that this concept undermines youth activism and gives license to adults to dismiss young peoples' justified anger at injustice. This essay contends that adultism, and specifically ephebiphobia – the fear and loathing of young people – dominates today's cultural perceptions of youth in the United States and contributes to policies in education and law enforcement that have domesticated and criminalized young people, undermining their political power. Understanding of the historical factors that shape adults' attitudes toward young peoples' capabilities as activists is a first step to improving and sustaining collaboration between youth and adults in social movements.

This chapter uses an application to explore the utility of Bayesian quantile regression (BQR) methods in producing density nowcasts. Our quantile regression modeling strategy is designed to reflect important nowcasting features, namely the use of mixed-frequency data, the ragged-edge, and large numbers of indicators (big data). An unrestricted mixed data sampling strategy within a BQR is used to accommodate a large mixed-frequency data set when nowcasting; the authors consider various shrinkage priors to avoid parameter proliferation. In an application to euro area GDP growth, using over 100 mixed-frequency indicators, the authors find that the quantile regression approach produces accurate density nowcasts including over recessionary periods when global-local shrinkage priors are used.

Given the rapid growth of the Chinese cruise market, several Chinese cities are attempting to become a hub for cruise ships. The aim of this study is to evaluate the competitiveness of those cities with regard to hosting cruises. It employs a cloud model that transforms the qualitative description of competitive indicators into quantitative measurement and assesses the competitive advantage and specialization of the top homeports in China. Questionnaires are delivered to experts from eight cruise ports in China and the cloud model based on 14 evaluation factors is used to analyze the competitiveness of the ports under investigation. The result shows that the city’s scale, population, and development have been the main factors for assessing the competitiveness of port cities. The research provides insight about the Chinese cruise port cities’ competitiveness, which is particularly useful for future development decision and marketing strategies of ports and prospective destinations.

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.