The article examines the issues of application and improvement of the methodology for evaluating industrial enterprises as recipients of state support within the framework of the implementation of industrial policy. The authors considered approaches to the content of industrial policy, investigated the factors influencing its efficiency, identified aspects of its imperfections that arise when applying an incomplete list of important parameters of economic development and ambiguity in the interpretation of previously applied estimates. The article presents proposals to improve the methodology for assessing potential recipients of state support based on the development of a comprehensive indicator for assessing enterprises (recipients of support), taking into account not only the classical parameters of the economic efficiency of industrial enterprises applying for state financial assistance, but also such aspects as the development of budgetary funds, belonging to priority sectors of the economy, characteristics of sustainable development and export and innovation potential. Combining the results of a comprehensive assessment of the recipient of state support with a map of the business demography of the territory allows making a decision not only about the fact of support and its efficiency, but also to predict the assessment of the life cycle of the enterprise and its subsequent development.

Support through the corporate tax system is a very specific form of funding to promote the functioning of team sports. The basic idea of the mechanism is that profit-oriented companies can donate a larger part of their corporate tax to sports organisations. The scheme has been in operation in Hungary since 2011. Its introduction and fine-tuning required several legislative changes and EU approval. Its importance is reflected in the increase in the number of sports organisations in the respective sports. While funding is available to many sports organisations, in some cases it is quite concentrated. In our empirical research we sought to find out how the degree of concentration has changed over time. The degree of concentration has an impact on how balanced the competition is. One of the key values for sports services is the requirement of an uncertain output. The data reveal that over time the distribution has become more evenly balanced across all sport operators. The amount of funding for sports organisations has started to converge. According to these figures, there are several sports organisations with equivalent subsidies participating in the competition system. However, the majority of clubs with the highest subsidies tend to be the same from year to year. The allocation of grants is determined by the sports federation of the given sport according to the submitted applications. Decision-makers should pay particular attention to maintaining the balance of competition over a long period of time. To this end, the list of sporting organisations with the highest subsidies should be continuously assessed and revised.

This study examines the effectiveness of Kazakhstan’s grant funding system in supporting research institutions and universities, focusing on the relationship between funding levels, expert evaluations, and research outputs. We analyzed 317 projects awarded grants in 2021, using parametric methods to assess publication outcomes in Scopus and Web of Science databases. Descriptive statistics for 1606 grants awarded between 2021 and 2023 provide additional insights into the broader funding landscape. The results highlight key correlations between funding, evaluation scores, and journal publication percentiles, with a notable negative correlation observed between international and national expert evaluations in specific scientific fields. A productivity analysis at the organizational level was conducted using non-parametric methods to evaluate institutional efficiency in converting funding into research output. Data were manually collected from the National Center of Science and Technology Evaluation and supplemented with publication data from Scopus and Web of Science, using unique grant numbers and principal investigators’ profiles. This comprehensive analysis contributes to the development of an analytical framework for improving research funding policies in Kazakhstan.

Energy systems face serious difficulties due to economic policy uncertainty, which affects consumption trends and makes the shift to sustainability more difficult. While adjusting for economic growth and carbon emissions, this study examines the dynamic relationship between economic policy uncertainty and energy consumption (including renewable and nonrenewable) in China from 1985Q1 to 2023Q4. The research reveals the frequency-specific and time-varying relationships between these variables by employing sophisticated techniques such as Wavelet Cross-Quantile Correlation (WCQC) and Partial WCQC (PWCQC). Economic policy uncertainty and energy consumption do not significantly correlate in the short term; however, over the long term, economic policy uncertainty positively correlates with renewable energy consumption at medium-to-upper quantiles, indicating that it may play a role in encouraging investments in sustainable energy. On the other hand, EPU has a negative correlation with nonrenewable energy usage at lower quantiles, indicating a slow move away from fossil fuels. These results are confirmed by robustness testing with Spearman-based WCQC techniques. The study ends with policy recommendations to maximize economic policy uncertainty’s long-term impacts on renewable energy, reduce dependency on fossil fuels, and attain environmental and energy sustainability in China.

This research explores the dynamic intersection of sustainable design, cultural heritage, and community enterprise, focusing on the innovative utilization of post-harvest sugar cane leaves in bamboo basketry production from various provinces in Thailand. This study aims to investigate how design anthropology principles can enhance community enterprises’ resilience and sustainability by employing a qualitative case study approach. Findings reveal that while traditional bamboo basketry reflects the region’s rich cultural heritage, a shift towards sustainable practices offers environmental benefits and economic opportunities. Design anthropology informs the development of culturally relevant products, fostering market competitiveness and preserving traditional craftsmanship. Moreover, government policies play a pivotal role in supporting or hindering the growth of community enterprises, with soft power initiatives holding promise for promoting cultural heritage and sustainability. Collaboration between policymakers, design anthropologists, and local stakeholders is essential for developing inclusive policies that empower communities and foster sustainable development. Overall, integrating sustainable design practices and cultural insights holds significant potential for enhancing the resilience and effectiveness of community enterprises, ensuring a prosperous and sustainable future for both the industry and the communities it serves. This study is a testament that design anthropology provides a powerful framework for addressing complex social and environmental issues through the lenses of culture and design.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.