This study is considered one of the few studies that attempted to explore the relationship between exports and foreign direct investment in the Kingdom of Saudi Arabia. The study aims to determine the nature of the relationship between exports and foreign direct investment in the Kingdom of Saudi Arabia during the period between (1990–2023). Employing Ender’s methodology using cointegration and error correction model. The study also relies on data on Saudi exports and foreign direct investment inflows from the World Bank databases. The results indicate the existence of Cointegration between foreign direct investment (FDI) inflows and the Saudi exports in the period (1990–2023), as for the causal relationship between the two variables, the results showed the causal relation between exports and FDI inflows from the direction of exports only, which means that Saudi exports cause FDI inflows in Saudi Arabia, and the study recommends giving more incentives to attract foreign investors in different sector rather than oil sector, besides improving the logistical services which is vital to any investment attraction strategy.

As International Atomic Energy Agency has stated in its Handbook on Nuclear Law, “Even in situations for which the highest standard of safety has been achieved, the occurrence of nuclear accidents cannot be completely excluded.” Therefore, the international legal framework for nuclear damage compensation liability has been evolving since the establishment of Nuclear Energy Agency of Organization for Economic Co-operation and Development (OECD NEA) and International Atomic Energy Agency (IAEA). Over the years, various international treaties have been enacted to address the compensation of nuclear damage and to establish liability regimes for nuclear incidents. To date, these treaties have established a series of legal principles of nuclear damage liability, such as the sole liability principle, the strict liability principle, the financial guarantee principle etc., which have been developing since establishment. This paper offers an overview of the historical development of the principles of these international treaties for nuclear damage liability and thus draws upon both primary and secondary sources, including treaties, official documents, academic literature, and reports by international organizations. Including the legislation study methodology, comparative methodology is also adopted in this paper to analyze the changes and trend of these principles. The paper reveals that the Paris Convention, which was established in 1960, was the first attempt to establish a comprehensive legal regime for nuclear damage liability. Most of the principles of this Convention have been inherited by subsequent international treaties and domestic legislations. With the awareness of protecting public’s rights having been significantly strengthened, the range of compensation has been broader, the matters of immunity from liability for operators of nuclear power plants have been reduced, the limitation of the compensation amount has been higher etc. In conclusion, the international legal regime for nuclear damage liability has been showing a shift from protecting the development of the nuclear industry to a joint protection of both public health and rights and the nuclear industry, which should be paid attention to and deeply learnt by domestic legislators of all states for the establishment and perfection of their domestic legislation in this field.

This study explores the determinants of control loss in eating behaviors, employing decision tree regression analysis on a sample of 558 participants. Guided by Self-Determination Theory, the findings highlight amotivation (β = 0.48, p < 0.001) and external regulation (β = 0.36, p < 0.01) as primary predictors of control loss, with introjected regulation also playing a significant role (β = 0.24, p < 0.05). Consistent with Self-Determination Theory, the results emphasize the critical role of autonomous motivation and its deficits in shaping self-regulation. Physical characteristics, such as age and weight, exhibited limited predictive power (β = 0.12, p = 0.08). The decision tree model demonstrated reliability in explaining eating behavior patterns, achieving an R² value of 0.39, with a standard deviation of 0.11. These results underline the importance of addressing motivational deficits in designing interventions aimed at improving self-regulation and promoting healthier eating behaviors.

This study investigates the impact of entrepreneurial orientation and green innovation on the performance of SMEs. This research explores the wood waste industry in Ngawi, an area that has never been studied before, thus providing a new perspective and unique local relevance. These findings underscore the critical role of entrepreneurial orientation and green innovation in driving sustainable business growth and improving SME performance. The results show that both entrepreneurial orientation and green innovation having a positive and significant link with SMEs performance. Further, the study reveals that the relationship between entrepreneurial orientation and green innovation having a positive and significant link with SMEs performance mediated by knowledge-sahring. The study also highlights the importance of larger sample sizes, and external factors to provide more comprehensive insights for practitioners and policymakers.

The aim of this paper is to introduce a research project dedicated to identifying gaps in green skills by using the labor market intelligence. Labor Market Intelligence (LMI). The method is primarily descriptive and conceptual, as the authors of this paper intend to develop a theoretical background and justify the planned research using Natural Language Processing (NLP) techniques. This research highlights the role of LMI as a tool for analysis of the green skills gaps and related imbalances. Due to the growing demand for eco-friendly solutions, there arises a need for the identification of green skills. As societies shift towards eco-friendly economic models, changes lead to emerging skill gaps. This study provides an alternative approach for identification of these gaps based on analysis of online job vacancies and online profiles of job seekers. These gaps are contextualized within roles that businesses find difficult to fill due to a lack of requisite green skills. The idea of skill intelligence is to blend various sources of information in order to overcome the information gap related to the identification of supply side factors, demand side factors and their interactions. The outcomes emphasize the urgency of policy interventions, especially in anticipating roles emerging from the green transition, necessitating educational reforms. As the green movement redefines the economy, proactive strategies to bridge green skill gaps are essential. This research offers a blueprint for policymakers and educators to bolster the workforce in readiness for a sustainable future. This article proposes a solution to the quantitative and qualitative mismatches in the green labor market.

Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.