One of the conditions for the future development of companies is the identification and use of digital capabilities. In recent years, the environment in which we live and work has changed radically. If the emergence of the Internet was revolutionary in the way we communicate and obtain information, currently the availability and mobility of technologies affects consumers' habits and promotes the transformation of classic business models. Aim of the study: to explore and learn about the development trends of digital marketing. Applied research methods: monographic descriptive method, analysis, synthesis, statistical method. The study based on scientific publications, statistics and other sources of information. The results of the study show that in 2019 digital marketing tools are most actively used: artificial intelligence / augmented reality / machine learning; video marketing; chatbots, virtual assistants.

ASSESSMENT OF FINANCIAL INDICATORS FOR EVALUATION OF BUSINESS PERFORMANCE

NON-FINANCIAL INDICATORS FOR EVALUATION OF BUSINESS ACTIVITY

Food waste is a global problem, which becomes apparent at various stages of the food supply chain. The present research study focuses on the optimization of food consumption in schools and effective food management through data-driven decision making within the trends: zero food waste and digital transformation. The paper presents a plate waste forecasting system based on mathematical modeling and simulation using the Monte Carlo method, which showed an RMSE equal to ±3% and a MAPE of 10.15%. The solution based on the simulator provides a possibility to better understand the relationship between the parameters investigated through data visualization and apply this knowledge to train managers to make decisions that are more effective. The developed system has multi-disciplinary application: forecasting, education and decision making targeted to reduce food waste and improve public health and food management in schools.

This research was conducted within the framework of a research project aimed at detecting patterns of plate waste and developing recommendations for improving catering in seven schools in Rezekne city (Latvia) by a combination of observation, physical weighing, semi-structured interview approaches and statistical analysis of variance (ANOVA). We identified plate waste (including wasted beverages), which remains after the lunch of schoolchildren in grades 1–7, examining a total of 7064 lunch samples. The originality of the research is due to the fact that a unified menu was designed for the field study, which ensured the same field study conditions in all the schools. The results of the research revealed that the average weight of plate waste per schoolchild reached 178 g, and the total weight of plate waste accounted for 28.75% of the total weight of food served. No significant differences in plate waste weight between various age groups and grades of schoolchildren were found, which was also confirmed by a one-way ANOVA test. An analysis of plate waste by food category showed that beverages accounted for the largest share of total plate waste (42.24%), followed by staple food (28.38%) and meat (11.77%). An analysis of plate waste shares of food served (%) by food category revealed a similar situation: the largest share of food served was made up of beverages (37.56%), followed by staple food (36.48%) and meat (28.77%). An analysis of the monetary value of food waste showed that the average cost of plate waste (excluding beverage) per schoolchild was EUR 0.236, which represented 16.6% of the national and municipal funding of EUR 1.42 per portion. Given the research results, the authors have concluded that in order to reduce the amount of plate waste generated by Rezekne city schools, school menus should be based not only on the requirements prescribed by relevant legal acts but also on cooking processes that meet the requirements of modern consumers (learners), e.g., by following trends in cooking practices in society to make the learners interested in consuming school food.