Data Envelopment Analysis (DEA) is one of the fastest growing approaches to solving management problems for the multi-criteria evaluation of the efficiency of homogeneous production systems. The general trend in recent years has been the development of network DEA (NDEA) models, which can consider the complicated structure of Decision Making Units (DMUs) and, therefore, can be more informative from the point of view of management science than traditional DEA models. The aim of this study is the systematization and clarification of general trends in the development of NDEA applications over the past 6 years (2017–2022). This study uses the methodology of a systematic literature review, which includes the analysis of the dynamics of the development of the topic, the selection of the main clusters of publications according to formal (citation, branches of knowledge, individual researchers) and informal (topics) criteria, and the analysis of their content. This review reveals that, most frequently, network structures are used for bank models, supply chain models, models of eco-efficiency of complex production systems, models of innovation processes, and models of universities or their departments and healthcare systems. Two-stage models, where the outputs of the first stage are the inputs of the second (intermediate outputs), are the most commonly used. However, in recent years, there has been a noticeable tendency to complicate DEA models and introduce hierarchical structures into them.

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Subject. The article considers a methodology for assessing the comparative effectiveness of the activity of homogeneous economic agents, i.e. Data Envelopment Analysis. Objectives. The focus is on systematization and classification of modern practical applications of network Data Envelopment Analysis, identification of types of additional information that can be extracted from solving problems of network DEA for the strategic management of companies/organizations. Methods. The study rests on systematic literature review. Results. At present, multi-stage DEA models are most actively used to model and evaluate the performance of banks, supply chains consisting of a “supplier-manufacturer-distributor” link, innovative and high-tech companies (or territories), and companies whose activities are regulated by strict environmental standards. Least of all, multi-stage DEA models are so far used to model consumer behavior as a sequential process consisting of many stages, which is explained by the underdevelopment of approaches to measuring consumer behavior factors. Conclusions. The main difference between the types of multi-stage network models is the absence or presence of common inputs for several stages, which are divided in a certain proportion between the stages (subsystems). This factor significantly affects the type of optimization model and approaches to its solution. The presence of common inputs gives rise to the need to solve an additional optimization problem for the distribution of resources between subsystems.

Subject. The article addresses the issue of forecasting changes in consumer behavior patterns in the medium and long term. Objectives. The focus is on consumer behavior prediction to identify potential growth points for small and medium-sized businesses in the field of trade and services. Methods. The methodological basis of the study is behavioral economics. The information base draws on analytical reports of Cerulli Associates, Profi Online Research, PricewaterhouseCoopers, Euromonitor International, and Ipsos research company, which developed and uses in its analysis a calculation methodology for the Global Consumer Confidence Index. Results. We analyzed the main trends of consumer behavior in 2022 in Russia in the context of tougher sanctions, global supply disruptions, and other crisis phenomena, from the perspective of existing knowledge about sustainable forms of Russian consumers’ reaction to crisis events in the economy. The paper highlights a decrease in loyalty to brands, expansion of online commerce to people over the age of 60, reduced demand for eco-products, and enhanced financial literacy, which is accompanied by an increase in demands for a fair price-quality ratio, as the key changes in consumer behavior that determine opportunities for businesses. Conclusions. Crises seriously affect the time frames of consumer planning. During the crisis, the time frames are reduced and blurred, and now consumers proceed from even greater uncertainty.