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This study aims to evaluate the current situation of education for sustainable development, climate change education and environmental education in a nationwide context. Methodologically, this study calls for more research to go beyond case studies and take a similar approach to examine university curricula and facilitate cross-country comparisons.

This paper examines the status of climate and sustainability curricula in Taiwan’s higher education system. Using the course catalog for the 2020–2021 academic year, the authors constructed a unique data set that includes 1,827 courses at 29 major universities in Taiwan. In each institution, the authors search for course titles that include “climate,” “sustainable/sustainability” and “environment/environmental” as keywords and code the courses according to their disciplines.

The finding highlights the variations across institutional types and subject matters. Public universities have an average of 4.94 related courses per 1,000 students, whereas private universities have only 3.13. In general, the relevant courses are more concentrated in the STEM and bioscience fields. The curricula, however, are seriously constrained by the disciplinary structure and foster few transdisciplinary perspectives.

The authors seek to go beyond case studies and offer one of the most comprehensive curricula samples at the national level. Taiwan adds an important data point, as the current literature focuses heavily on the USA and Europe.

This study adopts a narrative approach to understanding women’s life experiences from a feminist perspective. How Taiwanese women of different generations have lived their lives and what has and has not changed was investigated through a gender lens. The narrators include the author and her grandmother, born in 1975 and 1927, respectively. They each re-experience and reconfirm the markings of their pasts, psychological conditions, and bodies through deep dialogue. The two stories span approximately 50 years and manifest the patriarchal culture in Taiwanese society at different times.

This study finds that although the stories of these two women from different generations appear distinct in their own way, similar ‘dilemmas’ can be observed in their gender experiences: for example, women get married to men’s family; the value system of lineage and succession creates a tendency to expect to have boys; women need to get married to get their status recognition; and through home, women learn gender roles and gender norms.

However, the study shows progress: women’s education brings economic independence and yields a sense of accomplishment from work or school; women of different generations have different perceptions during the awakening of gender consciousness. The current findings contribute to understanding the working principles of gender relations, which reinforce the patriarchal system despite its appearance changing over time.

Social media has become the main venue for users to express their opinions and feelings, generating a vast number of available and valuable data to be scrutinized by researchers and marketers. This paper aims to extend previous studies analyzing social media reviews through text mining and sentiment analysis to provide useful recommendations for management in the restaurant industry.

The Lexalytics, a text mining artificial intelligence tool, is applied to analyze the text of the online reviews of the restaurants in a touristic Dutch village extracted from the most frequently used social media platforms focusing on the four restaurant quality factors, namely, food and beverage, service, atmosphere and value.

The findings of this research are presented by the identified key themes with comparisons of the customers’ review sentiment between a selected restaurant, Zwaantje, vis-à-vis its bench-mark restaurants set by a specific approach under the abovementioned quality dimensions, in which the food and beverage and service are the most commented by customers. Results demonstrate that text mining can generate insights from different aspects and that the proposed approach is valuable to restaurant management.

The paper provides a relatively big scale in numbers and resources of social media reviews to further explore the most important service dimensions in the restaurant industry in a specific tourist area. It also offers a useful framework to apply the text mining business intelligence tool by comparison of peers for local small business restaurant practitioners to improve their management skills beyond manually reading social media reviews.