Title: Data structures, logical-probabilistic models and digital management of the safety and quality of systems in the economics

Authors: Eugene Solozhentsev; Ekaterina Karaseva

Addresses: Institute of Business Technologies, Department of Information Technologies in Business, Saint-Petersburg State University of Aerospace Instrumentation, Saint-Petersburg, ul. Bolshaya Morskaya, 67, 190000, Russia; Laboratory of Intelligent Integrated Systems of Computer-Aided Design, Institute of Problems on Mechanical Engineering, Russian Academy of Sciences, Bolshoi 61, V.O., Saint-Petersburg, 199178, Russia ' Institute of Business Technologies, Department of Information Technologies in Business, Saint-Petersburg State University of Aerospace Instrumentation, Saint-Petersburg, ul. Bolshaya Morskaya, 67, 190000, Russia

Abstract: In this paper we are considering data structures in economic systems. These structures can be used to construct logical-probabilistic risk models intended for digital management of safety and quality of systems. Transformation of any database into a system of logical equations is described, which is the basis for constructing logical-probabilistic models of safety or quality. We give examples how the database is used to construct models of the credit risk in banks and the risk and efficiency of restaurants. Also we present examples of using complex structure data to construct a model for management of a country's innovation system quality and simple structure data for construction of a model for assessment of the failure risk for one innovation. The special software 'Arbiter' and 'Expa' for management in economics are described. The term 'digital management' is defined and computer network components for digital management of systems in economics are given.

Keywords: data structure; social and economic systems; logical-probabilistic risk models; safety; quality; efficiency.

DOI: 10.1504/IJRAM.2020.106162

International Journal of Risk Assessment and Management, 2020 Vol.23 No.1, pp.27 - 53

Received: 08 Oct 2018
Accepted: 30 Mar 2019
Published online: 01 Apr 2020 *

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