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Trends, Impacts, and Prospects for Implementing Artificial Intelligence Technologies in the Energy Industry: The Implication of Open Innovation

Authors :
Olesya Dudnik
Marina Vasiljeva
Nikolay Kuznetsov
Marina Podzorova
Irina Nikolaeva
Larisa Vatutina
Ekaterina Khomenko
Marina Ivleva
Source :
Journal of Open Innovation: Technology, Market and Complexity, Vol 7, Iss 155, p 155 (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

This research aims to substantiate the impact of using open innovation (OI) in the energy sector in readiness to implement artificial intelligence (AI) technologies and their effectiveness. The empirical method was proposed to determine the readiness level of OI for the implementation of AI technologies by comparing Russian and French energy companies. Readiness level indicators of companies for AI implementation using the Fibonacci sequence, Student’s t-test, and the method of fuzzy sets were empirically determined. The integrated readiness indicator for AI implementation by companies was calculated using the method of fuzzy sets and expressed through variance, allowing for these significant factors. Russian companies are at a low level of developmental readiness to implement AI, which is in contrast to companies operating in a developed market where the determining factor is the AI technology cost. The example of the innovative business model “Energy-as-a-Service” shows the synergistic effects of OI use and AI technology introduction. This paper is novel because it seeks to contribute to the current debate in the literature, justifying the position that energy companies that have in the past actively applied the concept of open innovation in business, are the most competitive and most efficient in implementing AI technologies.

Details

Language :
English
ISSN :
21998531
Volume :
7
Issue :
155
Database :
Directory of Open Access Journals
Journal :
Journal of Open Innovation: Technology, Market and Complexity
Publication Type :
Academic Journal
Accession number :
edsdoj.96ce2ff5b0c746a29ebd3af131cf32b2
Document Type :
article
Full Text :
https://doi.org/10.3390/joitmc7020155