Application of Mass Service Theory to Economic Systems Optimization Problems—A Review

• Published in: Mathematics (Basel) 2024-01, Vol.12 (3), p.403
• Main Authors: Galimulina, Farida F., Barsegyan, Naira V.
• Format: Article
• Language: English
• Subjects: complex networks; Context; Customer services; Economic aspects; Markov chains; Markov processes; mass service theory; Mathematical optimization; modeling; Modelling; Optimization; Organizational structure; Probability; Production management; productivity and efficiency of economic systems; Resource management; resource supply
• ISSN: 2227-7390; 2227-7390
• DOI: 10.3390/math12030403

An interdisciplinary approach to management allows for the integration of knowledge and tools of different fields of science into a unified methodology in order to improve the efficiency of resource management of different kinds of systems. In the conditions of global transformations, it is economic systems that have been significantly affected by external destabilizing factors. This determines the focus of attention on the need to develop tools for the modeling and optimization of economic systems, both in terms of organizational structure and in the context of resource management. The purpose of this review study is to identify the current gaps (shortcomings) in the scientific literature devoted to the issues of the modeling and optimization of economic systems using the tools of mass service theory. This article presents a critical analysis of approaches for the formulation of provisions on mass service systems in the context of resource management. On the one hand, modern works are characterized by the inclusion of an extensive number of random factors that determine the performance and efficiency of economic systems: the probability of delays and interruptions in mobile networks; the integration of order, inventory, and production management processes; the cost estimation of multi-server system operation; and randomness factors, customer activity, and resource constraints, among others. On the other hand, controversial points are identified. The analytical study carried out allows us to state that the prevailing majority of mass service models applied in relation to economic systems and resource supply optimization are devoted to Markov chain modeling. In terms of the chronology of the problems studied, there is a marked transition from modeling simple systems to complex mass service networks. In addition, we conclude that the complex architecture of modern economic systems opens up a wide research field for finding a methodology for assessing the dependence of the enterprise performance on the effect of optimization provided by using the provisions of mass service theory. This statement can be the basis for future research.