University of Life Sciences in Poznań

Scholars and academicians today aimed to develop measures for better management of natural resources and how the contribution of green finance can enhance economic development. The current research assesses the intricate link between natural resources, green finance and economic growth of the provinces of China over the period 2000–2017. This research also addresses the significance of institutional quality and technological innovations. The use of a novel moment quantile regression technique is enabled by the non-linear distributional properties of panel data. The empirical findings suggested that green financing has a negative effect on the regional economy. On the contrary, the positive influence of natural resources confirms the resource-blessings hypothesis in the region. Moreover, the quality of institutions and technological innovation are the main factors that affect economic wellbeing. The empirical results of this study are verified using non-parametric and parametric methods, which includes bootstrap quantile regression, the mean group, fixed effect and random effect. Nevertheless, the effect of green finance is noted asymmetric in these estimators. The findings of this study propose formulation of effective policies, that includes improved investments in research and development and technology sectors, and strengthening of institutional quality to improve economic performance in China.

The Anna Karenina principle posits that beneficial conditions produce both higher average well-being and lower well-being inequality. This study provides the first comprehensive macro-level test of the Anna Karenina principle across economic, political, and social dimensions simultaneously, combining regression and ordinal pattern-coherence methods on data from 63 countries in the World Values Survey Wave 7. We combine regression analysis with the Longest Common Subsequence method, validated through permutation testing, to identify which indicators satisfy this dual condition. Results reveal that unemployment is the only indicator among those examined that predicts both higher mean happiness and lower happiness inequality. These findings are exploratory and threshold-dependent: both unemployment indicators satisfy the complete Anna Karenina pattern only at the p < 0.10 level, and the inequality associations do not survive Benjamini–Hochberg correction, showing that unemployment as a strong candidate among the indicators assessed is not definitive but suggestive.

Sustainable development of territorial units and the standard of living of inhabitants have recently become the subject of economic analysis and scientific research, as well as public debate. The research aimed to assess the position of European Union (EU) countries and changes in terms of sustainable development and the standard of living of inhabitants. In this paper, we applied a hybrid multi-criteria decision-making procedure for assessing the level of sustainable development and standard of living of residents in EU countries. This procedure is based on the modified positional technique for order of preference by similarity to the ideal solution (MP-TOPSIS). The research utilized data from the Eurostat database from 2015–2021. The standard of living of inhabitants of EU countries was assessed, as well as the level of their sustainable development. The results of the research made it possible to determine the relationship between the standard of living of the population and the level of sustainable development in EU countries. The conducted research revealed that the level of sustainable development of EU countries and the standard of living of inhabitants was strongly differentiated but increasing throughout analysed period.

This study investigates the adoption of precision agriculture technologies (PATs) in the Czech Republic. Using unbalanced panel data from the Czech Farm Accountancy Data Network (FADN) survey spanning the period from 2017 to 2021, it aims to identify the drivers and barriers to the adoption of PATs in Czech field crop production. The estimation of a probit binary choice model with a within-between random effects (WBRE) specification – a novel approach to addressing heterogeneity in panel data choice models – reveals that PATs adoption is significantly influenced by socio-economic factors such as labor intensity, indebtedness, manager education, and farm economic size, as well as environmental factors such as localization and land quality. Furthermore, the adoption of PATs is associated with temporal dynamics in labor intensity, production efficiency, specialization, and land ownership. The findings underscore the need for targeted policy measures to promote the adoption of technology and enhance agricultural efficiency. The contribution of this study lies in deepening the understanding of the determinants and barriers to precision agriculture adoption in the EU context, where empirical research remains relatively scarce.

This review examines natural plant resins, wood tars and pitches in heritage science, focusing on their historical uses, chemical composition and analytical characterisation. Particular attention is given to diterpenoid and triterpenoid resins and to chemical transformations induced by ageing, degradation and thermal processing. The identification of diagnostic molecular markers supports the determination of botanical origins and technological practices, while an overview of complementary analytical methods highlights current challenges and perspectives.