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Economic Analysis: Theory and Practice
 

Prospects for applying the artificial neural networks to solve business problems under sourcing conditions

Vol. 18, Iss. 8, AUGUST 2019

Received: 12 February 2019

Received in revised form: 8 April 2019

Accepted: 13 May 2019

Available online: 30 August 2019

Subject Heading: MATHEMATICAL METHODS AND MODELS

JEL Classification: C45

Pages: 1565–1580

https://doi.org/10.24891/ea.18.8.1565

Farkhutdinov I.I. Branch of Kazan (Volga Region) Federal University in Naberezhnye Chelny, Naberezhnye Chelny, Republic of Tatarstan, Russian Federation
ilnour1986@inbox.ru

ORCID id: not available

Isavnin A.G. Branch of Kazan (Volga Region) Federal University in Naberezhnye Chelny, Naberezhnye Chelny, Republic of Tatarstan, Russian Federation
isavnin@mail.ru

ORCID id: not available

Subject The article addresses the issue of improving the competitiveness of a company through the use of sourcing models.
Objectives The study aims to check the applicability of artificial neural networks to solve economic problems within the framework of sourcing, in particular, to solve the make-or- buy problem.
Methods In the study, we employ our own matrix and a standard model of artificial neuron.
Results We prove the applicability of artificial neural networks to solve economic problems within the framework of sourcing. The findings may serve as a basis for creating the tools to assess the feasibility of sourcing models by building artificial neural networks.
Conclusions Creating the tools to assess the applicability of sourcing models that are based on artificial neural networks is a promising area in developing the resource utilization theory.

Keywords: outsourcing, insourcing, make-or-buy decision, artificial neural network

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