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.

The United Nations General Assembly declared 2023 the “International Year of Millets” in order to promote millet cultivation, consumption, and conservation. Millets play an important role in food security, livelihoods, and biodiversity. Despite its numerous benefits, millet cultivation and consumption in Uttarakhand have declined due to a variety of constraints. This paper examines the effects of regiocentrism and materialism on intention towards Uttarakhand’s regional food products (millets). It employs PLS-SEM to investigate relationships between latent variables and generate results on a sample of 460 participants. This study elucidates the intricate interplay between materialism, regiocentrism, and intention towards regional food products in the Himalayan region, enriching the theory of planned behavior (TPB) with a nuanced understanding of personal values and regional identity. It reveals materialism’s positive association with attitudes towards regional food products, suggesting materialistic individuals may view these products as status symbols, thus affecting behavioral intentions. Additionally, the research highlights regiocentrism’s dual influence—enhancing attitudes yet deterring purchase intentions—underscoring the complexity of regional pride in consumer decision-making. These findings advance TPB by integrating broader value systems and cultural context, offering significant theoretical and practical insights for promoting sustainable consumption patterns.

This paper investigates the evolving clustering and historical progression of “Asian regionalisms” concerning their involvement in multilateral treaties deposited in the United Nations system. We employ criteria such as geographic proximity, historical connections, cultural affinities, and economic interdependencies to identify twenty-eight candidate countries from East Asia, Southeast Asia, South Asia, and Central Asia for this empirical testing. Using a social network analysis approach, we model the network of these twenty-eight Asian state actors alongside 600 major treaties from the United Nations system, identifying clusters among Asian states by assessing similarities in their treaty participation behavior. Specifically, we observe dynamic changes in these clusters across three key historical eras: Post-war reconstruction and transformation (1945–1968), Cold War tensions and global transformations (1969–1989), and post-Cold War era and globalization (1990–present). Employing the Louvain cluster detection algorithm, the results reveal the evolution in cluster numbers and changes in membership status throughout the world timeline. The results also identify the current situation of six distinct Asian clusters based on states’ inclinations to engage or abstain from multilateral treaties across six policy domains. These findings provide a foundation for further research on the trajectories of Asian regionalisms amidst evolving global dynamics and offer insights into potential alliances, cooperation, or conflicts within the region.

The purpose of the study is to create proposals and recommendations to improve the system evaluating the quality of governance and efficient use of budget funds in order to improve public welfare and sustainable development. The research methodology included application of statistical methods to review scientific articles, legislative acts and other documents, study models for evaluating the quality of governance and efficient use of budget funds. Mathematical modeling and forecasting methods were also used to assess aspects of governance and predict the results when changes are made, including building a trend model and determining the forecast values of accrued taxes and mandatory payments for 2024–2026. The conclusions highlight there is a positive correlation between the accrued taxes and mandatory payments to the budget of the Republic of Kazakhstan, and an economic growth and changes in tax legislation. The key factors influencing the quality of governance and efficient use of budget funds were identified. Recommendations were developed to improve the quality assessment system and governance of budget funds in order to increase efficiency and responsibility in financial management. The results of the study can be used by public administration bodies and financial institutions to optimize the governance of budget funds.

Entrepreneurial self-efficacy has a predictive effect on entrepreneurial performance. The lithium-ion battery industry is the cornerstone of the emergency of the four emerging industries of “new energy”, “new materials”, “new technology” and “high-end manufacturing”. In the past, scholars have not considered the characteristics of entrepreneurs in their research on improving Chinese lithium-ion battery new venture growth. The personal characteristics of entrepreneurs have not received widespread attention from scholars. This article will start with the characteristics of entrepreneurs themselves and explore the path that entrepreneurs’ characteristics affect Chinese lithium battery new venture growth. This article builds a structural equation model to empirically analyze the relationship among variables. The data analysis results show that entrepreneurial self-efficacy significantly promotes the growth of new startups and entrepreneurial resilience plays a mediating role between the two. It cannot be concluded that entrepreneurial passion plays a positive moderation role between entrepreneurial self-efficacy and entrepreneurial resilience. Entrepreneurial passion also does not play a positive moderation effect between entrepreneurial self-efficacy and new venture growth. However, entrepreneurial passion plays a positive moderating role in the influence of entrepreneurial resilience on new venture growth. The findings of the study are beneficial for practitioners of Chinese lithium battery enterprises and will allow their strategies to promote sustainable new venture growth.