Knut Schmidtke

The study aims to cluster countries worldwide by business practices in the agrosector to reveal trends and specifics in applying sustainable methods in agrobusiness management. The analysis covers 26 countries from the OECD database as of 2021. The Word and k-means clustering methods are based on General Services Support Estimate indicators from the OECD: share of agricultural knowledge and innovation system, share of inspection and control, share of development and maintenance of infrastructure, share of cost of public stockholding, which has a determining, statistically significant influence on the formation of clusters. The first cluster included three Asian countries; China is the leader (share of agricultural knowledge and innovation system – 6,529.7 million USD, share of inspection and control – 3177.9 million USD, share of development and maintenance of infrastructure – 12,874.7 million USD, share of cost of public stockholding – 14,668.5 million USD). The second cluster comprised six countries, with the USA as the leader (share of agricultural knowledge and innovation system – 2,908.4 million USD, share of inspection and control – 1,298.0 million USD, share of development and maintenance of infrastructure – 2,392.5 million USD). The third cluster has 17 countries, with Canada being singled out (share of inspection and control – 631.8 million USD and share of agricultural knowledge and innovation system – 683.1 million USD). The results indicate the diversity of countries’ approaches to support and develop their agrosector. Advanced Asian countries and the US invest significant resources in innovation, infrastructure development, and quality control, underscoring their commitment to food security, efficiency, and sustainability.

The development of strategy and tactics for reforms in the energy industry involves the identification of benchmark countries whose experience can form the basis of a quantitative assessment of the main targets of the reforms. The basis for such decisions can be the results of the integrated assessment of energy reforms in the EU countries for 2010–2021. This study aims to cluster these countries according to the integral indicator and determine specific directions in which the respective country needs to make progress in moving to another cluster. Thus, based on a linear model, the Fishburn formula, and variance analysis, 10 energy development indicators were combined into a single indicator that characterizes the effectiveness of energy reforms (for example, in 2021, it was the highest in Austria (0.612), Germany (0.644), and France (0.620); the lowest – in Latvia (0.383) and Croatia (0.369)). Based on this indicator, countries were clustered using the k-means method. Four clusters were formed: representatives of the highest first (Austria, Germany, France, Spain, Sweden, and Luxembourg) are strategic benchmarks for all EU countries, and representatives of other clusters are tactical benchmarks for countries from lower clusters. The average values of all 10 indicators of energy development were calculated. Their low values are a sign that this direction should be a priority when carrying out reforms, and their quantitative estimates can be used as specific targets when setting strategic and tactical tasks (transition to a higher cluster or achieving average values in one’s cluster).

Acknowledgment
The research was funded by a Fellowship agreement for a research fellowship in the framework of the 11th funding round within the Philipp Schwartz Initiative of the Alexander von Humboldt Foundation.