Due to the lack of clear regulation of management accounting at the state level in Russia, the authors conducted a study based on an analysis of information sources, an expert survey on their reliability, and a case method, which resulted in a reporting form compiled for the production process of an agro-industrial enterprise (grain products) as part of inter-organizational company cooperation. The developed management reporting system (composed of eight consecutive stages: standard reports, specialized reports, itemized query reports, notification reports, statistical reports, prognostic reports, modeling results reports, and process optimization reports), on one hand, allows solving a set of tasks to increase the competitiveness of Russian agro-industrial enterprises within the framework of inter-organizational management accounting. On the other hand, the introduction of ESG principles into the management reporting system (calculation of the environmental (E) index, which assesses the company’s impact on the natural ecosystem and covers emissions and efficient use of natural resources in the agricultural production process) increases the level of control and minimizes the risks of an unfair approach of individual partners to environmental issues.

Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.

The importance of improving industrial transformation processes for more efficient ones is part of the current challenges. Specifically, the development of more efficient processes in the production of biofuels, where the reaction and separation processes can be intensified, is of great interest to reduce the energy consumption associated with the process. In the case of Biodiesel, the process is defined by a chemical reaction and by the components associated to the process, where the thermochemical study seeks to develop calculations for the subsequent understanding of the reaction and purification process. Thus, the analysis of the mixture of the components using the process simulator Aspen Plus V9^® unravels the thermochemical study. The UNIFAC-DMD thermodynamic method was used to estimate the binary equilibrium parameters of the reagents using the simulator. The analyzed aspects present the behavior of the components in different temperature conditions, the azeotropic behavior and the determined thermochemical conditions.