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Building on my earlier work (Dang, 2007, 2008), this chapter provides an updated review of the private tutoring phenomenon in Vietnam including the reasons, scale, intensity, form, cost, and legality of these classes. In particular, this chapter offers a comparative analysis of the trends in private tutoring between 1998 and 2006 using all available data.

This chapter analyzes data from different sources, including (i) the 2006 Vietnam Household Living Standards Measurement Survey (VHLSS), (ii) the 1997–1998 Vietnam Living Standards Measurement Survey (VLSS), (iii) the 2008 Vietnam Household Testing Survey (VHTS), and (iv) local press in Vietnam. Quantitative methods are used.

Several (micro-)correlates are examined that are found to be strongly correlated with student attendance at tutoring, including household income, household heads’ education and residence areas, student current grade level, ethnicity, and household sizes. In particular, I focus on the last three variables that received little attention in the previous literature on the determinants of tutoring.

This chapter provides an updated and systematic review of the private tutoring phenomenon in Vietnam. Findings are highly relevant to the ongoing debates on private tutoring among all stakeholders in Vietnam, as well as policymakers/researchers in other countries. Suggestions are proposed on current gaps in the literature for future research.

Vietnam is an emerging economy in the South East Asia region. Its Generation Z is gradually taking the lead in the country. But rather than breaking away from the previous generations, this generation also shows a strong preference towards local values and solid commitment to social issues. Thus, traditional culture elements are increasingly integrated in every aspect of Generation Z’s life, such as advertising and fashion. Instead of hanging out at coffee places, they go for bubble tea. They still appreciate the traditional values but integrate them within a modern context. Brands chase after these young people by adapting their values into their products and services. In the work place, the Vietnamese Generation Z is less confident. They are partially lost in career development with poor career counselling in the education system. They desire new experience and new learning opportunities. Generation Z, who were born beginning in 1995, emerges in Vietnam as a fresh and promising force.

The chapter describes the research objectives and different steps of the systematic literature review of existing studies on greenwashing. Both academics and practitioners may find this literature review useful, as it identifies the key features of the greenwashing research in a wide range of disciplines (management, marketing, accounting, corporate communication, etc.). The systematic literature review sheds light on the greenwashing types (and research gaps) in which the phenomenon takes shape. Time horizon (1990–mid 2021), keywords selection for queries on academic search engines, data collection, filtering criteria, etc., are explained and discussed in detail before presenting the main results in terms of frequency of publications over years, leading outlets in greenwashing research, trending articles, levels of analysis, geographical affiliation of first authors, theoretical approaches and methods used in this field of research. The chapter concludes by summarising the main types of greenwashing and possible avenues of research.

The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.

To address the grand challenge of refugee workforce integration, a multistakeholder approach which incorporates contributions from governmental organizations, nongovernmental organizations, media, educational institutions, researchers, and the corporate sector, is vital. This chapter provides an overarching understanding of how various stakeholders influence refugee integration and how they can assist employers in promoting the cause.