Abstract

The selection of indicators and criteria for the intellectual level of the Electronic logistics-information systems

Highlights

  • 1.1 Selection of Indicators What necessitates such a requirement is the preliminary structuring of the technical levels of the system

  • The purpose of the present paper is to advance a different approach to the selection of indicators and criteria so that they would be consistent with the intellectual level of the electronic logistics-information systems (E-LIS) in their evaluation and classification of the logistics objects according to their significance

  • The type and number of the criteria involved in the selection of E-LIS object is normally specified by the particular methods and principles applied in the evaluation of the technical level of the related logistics system

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Summary

INTRODUCTION

1.1 Selection of Indicators What necessitates such a requirement is the preliminary structuring of the technical levels of the system. The primary objective of the research is to specify the information and technical parameters of the objects under study according to requirements for their future development. To that effect, their technical level ought to be determined at a given point of time, and in the dynamics over the years to come. The type and number of the criteria involved in the selection of E-LIS object is normally specified by the particular methods and principles applied in the evaluation of the technical level of the related logistics system. With respect to the primary selection, the criteria have to fulfill the “necessity” and “acceptability” conditions restricting the selection of objects considered adequate for the introduction of digital intelligence. As for the significance of the criteria that relate to the condition of “acceptability” in the selection of objects, it is determined by the following inequality: where: - calculated coefficient of efficiency; - normative coefficient of efficiency; - calculated period of time for return on investment; - normative period of time for return on investment

Calculation of Criteria
Artificial Intelligence Functionality
CONCLUSIONS

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