In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

Enhancing the emphasis on incorporating sustainable practices reinforces a linear transition towards a circular economy by organizations. Nevertheless, although studies on circular economy demonstrate an increasing trend, the drivers that support circular economy practices towards sustainable business performance in the Small and Medium-Sized Enterprise (SME) sector, especially in developing nations, demand exploration. Accordingly, the study examines circular economy drivers, i.e., green human resource management, in establishing sustainability performance and environmental dynamism as moderating variables. The study engaged 207 SMEs and 621 respondents who were analyzed utilizing structural equation modeling. The analysis indicated that sustainable business performance was affected by green human resource management and a circular economy. Subsequently, the circular economy mediated the linkage between green human resources management and sustainable business performance. The environmental dynamism moderated the linkage between green human resources management and the circular economy.

Concession agreements (CAs) in the port sector are designed to establish mutually beneficial arrangements for involved parties. They serve as catalysts, enabling ports to attract adept private investors and secure requisite funding to enhance port infrastructure, superstructure, and service quality. Concurrently, the imperative to mitigate negative externalities and promote sustainable practices in port organization and development remains paramount. In this context, the paper explores the nuanced landscape of CAs, specifically focusing on the urgent need for an innovative framework that integrates sustainability within port organization, operations and development. Drawing from existing academic discourse and field evidence, it systematically identifies, examines, and analyzes fundamental requirements and key factors that should be considered in CAs, in line with sustainable development and proposes a reference framework for an ideal Concession Agreement model. Despite evident strengthening of sustainability implications in port concessions, significant room for improvement persists. Nevertheless, dynamics in the field create a certain optimism for the future.

The focus of the article is the evaluation of the interaction between regional state bodies and business structures in Kazakhstan, specifically in terms of the development of public-private partnerships. The purpose of the research is to enhance the understanding of the theoretical and practical aspects of the mechanism of interaction between the state and business structures. Through an examination of the various structural components of the partnership development strategy, the study aims to identify the elements of the mechanism for the implementation of the state and business development strategy. Additionally, the research seeks to establish the correlation between the outcomes of the joint entrepreneurship mechanism and the criteria used to evaluate the performance of regional state bodies. To assess the effectiveness of the interaction between business and government at the regional level in Kazakhstan, a survey-based evaluation was conducted to measure the satisfaction levels of public utilities, entrepreneurs, and businesses with the activities of local authorities. The survey also evaluated the degree of corruption among local authorities. A matrix of interaction between business and government was created, and various models and algorithms for the interaction between government representatives and business structures were studied. The research findings highlight the importance of enhancing the collaboration between the state and the business sector, promoting the implementation of public-private partnerships, and establishing social partnerships to cultivate mutually beneficial relationships.

In order to further alleviate the problems of large assessment deviations, low efficiency of trading organisation and difficulties in system optimisation in medium- and long-term market trading, the article proposes an optimisation model for continuous intra-month bidding trading in the electricity market that takes into account risk hedging. Firstly, the current situation of market players’ participation in medium and long-term trading is analysed; secondly, the impact of contract trading on reducing operational risks is analysed based on the application of hedging theory in the primary and secondary markets; finally, the continuous bidding trading mechanism is designed and its optimisation effect is verified. The proposed model helps to improve the efficiency of contract trading in the secondary market, maintain the stability of market players’ returns and accelerate the formation of a unified, open, competitive and well-governed electricity market system.