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.

This study aims to take Chinese higher vocational colleges professional group leaders as the research subjects to analyze the components of their key competencies, develop the competency model of professional group leaders (PGL), and analyze the main factors influencing the model. It provides a powerful help for improving the scientific level of the construction and management of the teaching staff in higher vocational colleges and filling the gap in the research on the quality and ability of Chinese professional group leaders. A mixed research method is deployed in this study. Data are collected with the help of a self-administrated questionnaire and a semi-structured interview based on grounded theory. Data analysis involves structural equation modeling using AMOS, complemented by qualitative coding in NVivo. It concludes that the competency development model of professional group leaders comprises two main dimensions: explicit competencies and implicit competencies. Explicit competencies include cross-border adaptability (CBA), resource integration ability (RIA), innovation and development practice ability (IDPA), management leadership ability (MLA), and interdisciplinary scientific research ability (ISRA). Implicit competencies include personality attitude (PA), and intrinsic motivation (IM). The study fills a significant gap in the literature by providing a detailed model of competency for professional group leaders in the context of higher vocational education, offering a practical framework for improving the training and management of teaching staff and promoting the development of professional groups effective in vocational colleges.

This research aims to examine the influence of IHRMP, recruitment and selection, training, compensation, and performance appraisal on the productivity of Faculty Members (FM) productivity working in private universities in the UAE. The study also examines the mediating role of Organizational Commitment (OC) and the moderating role of the Entrepreneurial Mind-set (EM). The research adopted the social exchange theory. A survey was conducted comprising 160 FM. The data was analyzed using Structural Equation Modelling, Smart-PLS. The findings indicate a positive relationship between IHRMP and the productivity of the FM. The findings also show that OC mediates the relationship between IHRMP and the productivity of FM. Finally, an EM was found to moderate the relationship between IHRMP and the productivity of FM.

The transportation sector in India, which is a vital engine for economic growth, is progressively facing challenges related to climate change. Increased temperature, extreme weather conditions, and rising seas threaten physical infrastructure, service delivery, and the economy. This research examines efforts towards improving the climate resilience of India’s transport sector through policy interventions. Strategies encompass broadening the focus to cover the integration of sustainability, innovative technology deployment, and adaptive infrastructure planning. Multi-sectoral measures are proposed to guarantee longevity, equity and environmental protection. National transport infrastructure will be secured, people will be enabled to move sustainably, and India will take its position in the world economy as a climate-resilient country. Long-term resource management and promoting inclusive governance are critical to agri-transportation systems that can withstand the changing climate.