Order logistics based on collaborative filtering

¹ Plekhanov Russian University of Economics (Voronezh branch) 67a, Karl marks str., Voronezh, 394030, Russia
² Yuri Gagarin State Technical University of Saratov 77, Politehnicheskaja str., Saratov, 410054, Russia

^* Corresponding author: ea_makarov@mail.ru

Abstract

Modern approaches to the organization and management of logistics operators include issues directly related to the forecasting of the dynamics of the processes of the company under study, as well as the development of recommendations for further functioning in the market of goods and services. Services integrated into the order and delivery logistics system are an integral part of it and accompany the flow processes throughout the supply chain. Nowadays, the complex of information technologies, communications and technological solutions allows implementing the most daring offers of logistics companies. Innovative solutions developed using information technologies develop the complex “design-practical implementation” in logistics systems and form a digital space for managing material flows. The calculation of the forecast values of the indicators that characterize the order requires research from the point of view of taking into account the already known preferences of customers. We are talking about recommendation systems that offer to form a package of services in the delivery and assembly of a batch of orders based on the established preferences of other customers and users of the services. The well-known preferences of customers when accessing logistics services form the basis for developing recommendations that are close to them. The obtained data of forecasts of the state of the system under study should provide an opportunity to develop an individual package of solutions, based on the already known preferences of other users. The key value is the information that is used in this model to build forecasts. The practice of finding solutions in the management of order procedures in logistics is an analysis of the key problems and “problem points” that affect the overall performance indicator, taking into account the geography of transport systems, established trade practice, the characteristics of the markets studied and the location of each, specifically selected company.