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This study aims to investigate the impact of brain drain on government AI readiness in EU member countries, considering the distinctive governance characteristics, macroeconomic conditions and varying levels of ICT specialists.

The research employs a dynamic panel data model using the System Generalized Method of Moments (GMM) to analyze the relationship between brain drain and government AI readiness from 2018 to 2022. The study incorporates various control variables such as GDP per capita growth, government expenditure growth, employed ICT specialists and several governance indicators.

The results indicate that brain drain negatively affects government AI readiness. Additionally, the presence of ICT specialists, robust governance structures and positive macroeconomic indicators such as GDP per capita growth and government expenditure growth positively influence AI readiness.

Major limitations include the focus on a specific region of countries and the relatively short period analyzed. Future research could extend the analysis with more comprehensive datasets and consider additional variables that might influence AI readiness, such as the integration of AI with emerging quantum computing technologies and the impact of governance reforms and international collaborations on AI readiness.

The theoretical value of this study lies in providing a nuanced understanding of how brain drain impacts government AI readiness, emphasizing the critical roles of skilled human capital, effective governance and macroeconomic factors in enhancing AI capabilities, thereby filling a significant gap in the existing literature.

This research fills a significant gap in the existing literature by providing a comprehensive analysis of the interaction between brain drain and government AI readiness. It uses control variables such as ICT specialists, governance structures and macroeconomic factors within the context of the European Union. It offers novel insights for policymakers to enhance AI readiness through targeted interventions addressing brain drain and fostering a supportive environment for AI innovation.

This chapter shows the prevalence, trends and heterogeneity in maternal smoking around birth in the United Kingdom (UK), focussing on the war and post-war reconstruction period in which there exists surprisingly little systematic data on (maternal) smoking behaviours. Within this context, the authors highlight relevant events, the release of new information about the harms of smoking and changes in (government) policy aimed at reducing smoking prevalence. The authors show stark changes in smoking prevalence over a 30-year period, highlight the onset of the social gradient in smoking as well as genetic heterogeneities in smoking trends.

Despite recent efforts to link religion with job satisfaction, the current state of research lacks the knowledge of why there may be a positive relationship between the two variables. This study tries to fill this gap by testing the notion that Christians are more likely to exhibit a higher level of distributive justice perception, which leads to a higher level of job satisfaction. The study also tries to identify Christianity as the moderator in the relationship between distributive justice and job satisfaction.

This study uses secondary data. The study analyzes 13,289 employees in 27 countries in the 2010 European Social Survey, which contains information on the levels of distributive justice perceptions and job satisfaction, as well as the religious affiliations of the respondents. The country fixed effect regression analysis was conducted.

The analyses first reveal that Protestants, compared to non-Protestants, exhibit a higher level of distributive justice perception, which leads to a higher level of job satisfaction. The analyses also demonstrate that the positive relationship between distributive justice perception and job satisfaction is weaker for Protestants than non-Protestants. These relationships, however, were not evident for people affiliated with other denominations of Christianity.

Protestant employees are likely to maintain a higher level of distributive justice perception, and distributive justice perception matters less in shaping their job satisfaction. As a result, organizations may want to focus more on the other aspects of organizational justice, such as procedural and interactional justices in managing protestant employees, if maintaining job satisfaction level is a concern. With many “Christian-based” companies operating and being supported in today’s economy, the findings in this study can be useful to these organizations that are more likely to attract and have Christians as their employees.

The current study provides evidence that employees’ religious affiliation (i.e. Protestantism in this case) can be a predictor of job satisfaction through the mediation of distributive justice perception. It also offers a basis for future studies on employee morale (e.g. job satisfaction and justice perceptions) to consider religious factors. Finally, the findings also identify Protestant affiliation as a moderator in the distributive justice–job satisfaction relationship.

The purpose of this study is to explore the incorporation of the sustainable development goals (SDGs) at the National University of Moreno (Universidad Nacional de Moreno, UNM, in Spanish), focusing on teaching and research activities, encountering difficulties from primary and secondary information sources, to integrate the SDGs, and contribute with actions for their incorporation into teaching and learning processes and research, in a newly established university.

To describe the implementation of the SDGs, an empirical study was conducted using a mixed methodology for data collection. Data collected from the survey were combined with information from the UNM project database for the period 2017–2022. Non-parametric methods were used to analyse both sets of data.

This study provides an initial overview of SDG implementation at UNM, allowing the identification of constraints and challenges to scale up contributions to the SDGs at UNM, as well as the generation of relevant action lines in the interaction with university's authorities.

Conducting studies through questionnaires has limitations, similar to other cases analysed. To increase the validity of the data, prior consultations were carried out. In addition, the database of research projects was used to identify the application of the SDGs in research. However, an approximation of the current situation could be obtained.

Particular importance was given to the challenges encountered during the data analysis phase in relation to capacity building needs. This enabled a set of actions to be defined to bring the SDGs closer to the UNM.

Although the paper used methodologies already proposed by other authors, such as survey collection, its value lies in demonstrating the possibility of using them to analyse whether the SDGs are integrated into teaching and research activities in a recently founded university, where the SDGs are integrated into its principles. The analysis also complements the survey results with information from project databases, which has not yet been analysed in the literature. Based on the results, activities are designed so that the SDGs could begin to guide teaching and research activities.

This study aims to bring together the available scattered knowledge about teaching and learning in Living Labs within higher education, and to explore their potential for supporting students’ sustainability-oriented transformative learning.

A literature review was conducted, applying a realist approach. A sample of 35 articles was analyzed qualitatively, mapping the data according to the realist constructs “context,” “intervention,” “mechanism” and “outcome” and using the constant comparison method for data analysis.

This study identified multiple characteristics of teaching and learning in sustainability-oriented Living Labs, namely, two socio-physical teaching and learning contexts, two pedagogical approaches as interventions therein, four learning processes as (potential) mechanisms and six sustainability-related learning outcomes. Two main challenges were also identified.

To the best of the authors’ knowledge, this is the first study that brings together the scattered results from previous studies into a comprehensive description of characteristics and challenges of teaching and learning in Living Labs as sustainability-oriented learning spaces in higher education. The findings can support educators in making scientifically grounded informed choices for teaching and learning in Living Labs and inform future empirical studies to examine when, how and why certain characteristics of teaching and learning in Living Labs, as identified in this study, can support sustainability-oriented transformative learning in higher education.

This study aims to explore the structural changes in food consumption expenditure in Indonesia before and during the COVID-19 pandemic using data from the 2020 and 2021 National Socioeconomic Survey by Statistics Indonesia.

The quadratic almost-ideal demand system analysis model is used to estimate changes in the share of food consumption and the demand and price elasticity of food commodities in Indonesia. A total of 15 food items are analyzed to determine changes in food consumption expenditure during the COVID-19 pandemic.

The results of this study show that during the COVID-19 pandemic, there was an increase in the proportion of household expenditure related to the consumption of home-cooked food. Simultaneously, the proportion of expenditure on prepared food significantly decreased.

The pandemic has changed household food consumption in Indonesia. This study recommends that the government ensure the availability of supplies and stability of food prices and provide financial subsidies to maintain food consumption, especially for lower-income communities.

There has yet to be a study on the changes in household food consumption during the COVID-19 pandemic in Indonesia. Therefore, this research provides empirical evidence that there were changes in household food expenditure during the pandemic.

This article discusses the underlying teaching framework of relational cultural theory (RCT), as well as additional teaching practices used within a doctoral-level, interdisciplinary social studies course on critical social justice. Areas for future development are identified.

A research-engaged, conceptual report on practice was used to identify and integrate relevant scholarship for the purpose of formulating and analyzing teaching practices for this type of course, and to iteratively identify possible directions for future development.

RCT is a generative, underlying teaching framework for the interdisciplinary social study of critical social justice. Additional teaching practices including a community agreement to guide challenging discussions; participant-led presencing activities at the outset of classes; and, co-creation by participants of the content topics can be fruitfully embedded within RCT. Potential future development could include team-based, community-engaged, experiential term projects aimed at further deepening interdisciplinarity and civic engagement skills.

Practical guidance is provided on the use of RCT, community agreements, co-creation, presencing activities and Indigenous land acknowledgments or contemplations on Indigenous works.

RCT can be used across different educational levels or contexts. Practices of co-creation, presencing and contemplation of Indigenous works are receiving increased consideration in diverse contexts. However, conventional grading procedures can be inconsistent with critical social justice, suggesting the need for research-engaged policy review.

This article responds to recent scholarly calls for discussion of teaching practices in the interdisciplinary, social study of critical social justice in post-secondary education.

This study combines the TAM and UGT frameworks to investigate how Vietnamese students' views of ChatGPT and intrinsic needs affect their intentions to use it for education (via variables including perceived ease of use, perceived usefulness, novelty, information seeking and academic content creation). We will employ TAM theory (Davis, 1989) and UGT theory to elucidate university students' motivations for utilising ChatGPT in Vietnam. Simultaneously, we aim to address the limitation stemming from data uniformity. Our research will make a substantial contribution to the understanding of researchers regarding the use of ChatGPT and its varied consequences as it grows and develops.

This study was conducted at a private university in Vietnam with an estimated population of 15,000 students. One of Vietnam’s top private information technology institutions requires its students to use a variety of information and communication technologies (ICTs) on a regular basis to facilitate and enjoy their academic pursuits (Ngo, 2024; Nguyen). Students who are familiar with ChatGPT and have access to it for educational purposes are the ones that were chosen. This research is a quantitative study that utilises primary data through a survey method. Participants answered a questionnaire online through the Google Form platform sharing via social media platforms from October to December 2023. The questionnaire was divided into two sections: the first contained screening questions and demographic information and the second had five-point Likert-scale questions that measured the study’s components. Two screening questions are used to separate out the intended responders. (i.e. “I have heard the name ChatGPT” and “I know about ChatGPT”) were set to find whether the participants had any knowledge of ChatGPT. If participants were unaware of ChatGPT, their responses were not included in the study. A total of 283 responses were received. The participant’s demographic information is shown in Table 1. It is believed that a sample size of more than 200 provides adequate statistical power for data analysis in structural equation modelling. It is evident that the 283-sample size in this study is adequate to evaluate the research hypothesis and the fitting model. 42.9% of the 283 research samples were made up of men, while 57.1% were women. Business administration accounted for 40.1% of survey respondents, followed by information technology (25.2%) and English language (14.5%). The average ChatGPT usage time of respondents was 56 min in a single use. The study sample’s average age is 20–72 years old.

The present study contributes to the existing AI chatbot literature in the educational industry in several ways. First, this study addresses a gap in the literature by investigating the factors that influence students’ ITU ChatGPT for educational purposes in Vietnam. Using the extended model, we investigated factors influencing students’ intentions to use ChatGPT. It integrates three motive factors of the UGT (ACT, IS and N) with the core factors of TAM (PeoU and PU). The integrated framework’s findings indicate that in a Vietnamese educational setting, ChatGPT is a novel technology that should be considered in conjunction with PU and PEoU.

First, only Vietnamese students make up the research sample. To increase the relevance of the findings, it is advised that future research look at the study model in various geographic regions. Second, the present investigation’s constraints arise from the lack of clarity about the Chat GPT version utilised by the respondents, specifically whether it was the free or premium edition. Furthermore, the limited duration of the survey presents an obstacle to gathering thorough data. Due to their reliance on the particular features and functionalities of the Chat GPT version used, these restrictions may have an effect on the researcher’s objectivity. Furthermore, the limited survey time may curtail the coverage of the collected answers, particularly considering that our survey predominantly focuses on business administration students, thus limiting the diversity and richness of the gathered data. We recommend that future studies should conduct comparative research between different versions of GPT Chat, including free and paid variants that can provide valuable insights into potential differences in performance and results. Such analysis can provide a deeper understanding of the strengths and limitations of different GPT Chat versions. Third, because the study focused on behavioural intention, actual usage and post-usage behaviour may not be covered by the findings. To gain a deeper understanding of users' actual behaviour, we suggest doing research on their usage and post-usage behaviours.

The findings will assist service providers and legislators in determining critical variables and influencing students' incentives to use ChatGPT in educational settings that use constructivist teaching methods. As a result, the information will assist service providers in creating AI chatbots that are more user-friendly, visually appealing, efficient, safe and convenient for education. Governments, in conjunction with service providers, have the potential to significantly accelerate the adoption of AI-based chatbots by highlighting their ethical and sustainable use. The findings demonstrate that students' ITU towards ChatGPT is substantially impacted by PU and PEoU. It is recommended that service providers emphasize the advantages and ease of use of AI chatbots in order to draw new clients. Additionally, in order to promote ChatGPT or related technologies, marketers should concentrate on raising the technology’s perceived novelty value. This is because people are open to new technologies as long as they believe they are interesting and innovative.

ChatGPT is an advanced AI-powered chatbot that has the potential to advance and revolutionize the learning and teaching process. This study attempted to look at the elements that lead students to want to use ChatGPT from an academic standpoint by combining the UGT and TAM. For practitioners, academics and educators, the findings provide a solid knowledge of and encouragement for the sustainable use of such AI tools. Despite having important practical consequences, the study contains a number of limitations that indicate possible research gaps that should be filled by further investigation.

Complementary feeding practices was more difficult during the COVID-19 pandemic due to economic instability, especially for animal source foods (ASFs) consumption. According to the problem, the purpose of this study was to determine the economic impact of COVID-19 pandemic on ASFs consumption and ASFs consumption related factors on complementary feeding in Indonesia.

This cross-sectional study was targeted at mothers of children aged 6–23 months during pandemic. A total of 574 respondents were obtained through online questionnaire.

This study found that flesh food, including fish/seafood, organ meat, meat, poultry and processed meat, were associated with all economic impact of COVID-19 pandemic; in contrast, those economic impacts did not affect the dairy product and egg consumption. Multivariate analysis showed children with older age (AOR: 1.13, 95%CI: 1.04–3.26), meet minimum dietary diversity (AOR: 2.17, 95%CI: 1.56–5.44) and are from high income level household (AOR: 1.14, 95%CI: 1.09–2.10) contributed to ASFs consumption.

Other strategies aimed at enhancing food security to increase ASFs consumption on complementary feeding. The government may consider short-term emergency purchasing subsidies and macro-control of the ASFs market. Nutrition education is also required to improve knowledge related to importance of ASFs consumption for children.

This study reveals the association between each food group of ASFs consumption on complementary feeding and the economic impact of COVID-19 pandemic.

This paper primarily aims to identify the multilevel learning processes emerging from abrupt telework implementation in a public knowledge-intensive organization (KIO) amid the COVID-19 crisis.

This single-case process research was guided by interpretivist epistemology. Empirical data from documentary research and 41 interviewed managers were processed by inductive qualitative analysis using the multilevel learning theoretical model.

Eight types and three modes of learning processes during the COVID-19 pandemic were identified in a public KIO, iteratively emerging in multilevel learning dynamics during the compulsory adoption of telework and replacing the face-to-face work mode conducted since its foundation.

As insider researchers, while daily and privileged access to the field was obtained, it also demanded their continuous effort to maintain transparency and scientific distancing; conceptual results are restricted to process theorisation studies, specifically the 4Is theoretical model in the scope of crisis learning process studies concerning KIOs.

This study provides evidence for managers to adopt interactive dynamics among eight multilevel types and three learning modes of emergent learning, developed during the COVID-19 pandemic, and support learning practices’ implementation and routinisation across three organizational levels in crisis situations. In addition, evidencing emergent types of learning enables organizational learning (OL) researchers to examine how organizational structures and work practices either promote or inhibit different learning types and impact multilevel learning when adopting teleworking during a crisis.

This research has theoretical value in two ways: (i) Providing empirically supported knowledge: This involves understanding multilevel learning processes resulting from emergent learning in a public KIO that abruptly adopted teleworking during a crisis context; (ii) deepening process theorization studies on OL: To achieve this, we enhance the 4I model by incorporating eight types and two modes of learning processes. These processes iteratively emerge from the individual and group levels towards the institutional level in a public KIO.