The proposed model for optimizing the logistics system of an enterprise using information technology. The motivation to build the model emphasizes the critical role that new information technologies play in significantly increasing the availability of data of a wide variety of types related to the transportation process and servicing logistics tasks. | Optimization model of the enterprise logistics system using information technologies International Journal of Management IJM Volume 11 Issue 5 May 2020 pp. 54-64 Article ID IJM_11_05_006 Available online at http ijm JType IJM amp VType 11 amp IType 5 Journal Impact Factor 2020 Calculated by GISI ISSN Print 0976-6502 and ISSN Online 0976-6510 DOI IAEME Publication Scopus Indexed OPTIMIZATION MODEL OF THE ENTERPRISE LOGISTICS SYSTEM USING INFORMATION TECHNOLOGIES Mariya Naumenko Department of Management and Military Economy National Academy of the National Guard of Ukraine Kharkiv Ukraine Nataliia Valiavska Department of Business Logistics and Transportation Technology State University of Infrastructure and Technologies Kyiv Ukraine Mariia Saiensus Department of Marketing Odessa National Economics University Odessa Ukraine Olena Ptashchenko Department of International Business and Economic Analysis Simon Kuznets Kharkiv National University of Economics Kharkiv Ukraine Vitalii Nikitiuk Department of Economics Kremenchuk Mykhailo Ostrohradskiy National University Kremenchuk Ukraine Anton Saliuk Department of Marketing and Corporate Communications Department Simon Kuznets Kharkiv National University of Economics Kharkiv Ukraine ABSTRACT The proposed model for optimizing the logistics system of an enterprise using information technology. The motivation to build the model emphasizes the critical role that new information technologies play in significantly increasing the availability of data of a wide variety of types related to the transportation process and servicing logistics tasks. In particular the ability to operate in real-time with a significant amount of detailed data collected locally can potentially improve the accuracy of information about critical unobserved characteristics of the production process. Among such unobservable values one can indicate various kinds of attributes of the
