Abstract
Purpose: The purpose of the article is to substantiate the necessity and to develop a conceptual model of managing the agricultural machinery market on the basis of AI for infrastructural provision of AIC 4.0 in modern Russia.
Methodology: The authors use the method of plan-fact analysis for comparing the target values of the indicators of agricultural machinery market, announced in the Strategy of development of agricultural machine building in the Russian Federation until 2020, and their factual values. The research is performed based on the 2016 data, as the data for later periods are not yet available in the official statistics. The difference (plan-fact) and the share of deviation of fact from plan (%) are determined.
Results: It is determined that non-optimality of managing the agricultural machinery market is a serious problem in modern Russia, as it does not allow forming the necessary infrastructural provision for transition to AIC 4.0. The reason of non-execution of the strategy of development of the Russian agricultural machinery market consists in high complexity of this management, which cannot reach high effectiveness with the current bureaucratic organization due to slow collection of statistical information, duration of its processing and analysis, and the long process of managerial decision making. This problem could be solved by organization of managing the agricultural machinery market on the basis of AI.
Recommendations: The developed conceptual model of managing the agricultural machinery market on the basis of AI is recommended for practical application in modern Russia, as it has the following advantages: high flexibility of the strategy of development of agricultural machinery market and the plan of its implementation, connection of the strategy of development of agricultural machinery market and the plan of its implementation to the current economic practice, and completeness and high detalization of the strategy of development of agricultural machinery market and the plan of its implementation.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Altukhov, A.I., Bogoviz, A.V., Kuznetsov, I.M.: Creation of an information system – a necessary condition of rational organization of agricultural production. In: Advances in Intelligent Systems and Computing, vol. 726, pp. 800–809 (2019)
Burggräf, P., Wagner, J., Koke, B.: Artificial intelligence in production management: a review of the current state of affairs and research trends in academia. In: International Conference on Information Management and Processing, ICIMP 2018, January 2018 , pp. 82–88. 8325846 (2018)
Butorin, S.N., Bogoviz, A.V.: The innovational and production approach to management of economic subjects of the agrarian sector. In: Advances in Intelligent Systems and Computing, vol. 726, pp. 758–773 (2019)
Huh, J.-H., Kim, K.-Y.: Time-based trend of carbon emissions in the composting process of swine manure in the context of agriculture 4.0. Processes 6(9), 168 (2018)
Kumar Deb, S., Jain, R., Deb, V.: Artificial intelligence creating automated insights for customer relationship management. In: Proceedings of the 8th International Conference Confluence 2018 on Cloud Computing, Data Science and Engineering, Confluence 2018, pp. 758–764. 8442900 (2018)
Litvinova, T.N., Khmeleva, G.A., Ermolina, L.V., Alferova, T.V., Cheryomushkina, I.V.: Scenarios of business development in the agricultural machinery market under conditions of international trade integration. Contemp. Econ. 10(4), 323–332 (2016)
Litvinova, T.N., Kulikova, E.S., Kuznetsov, V.P., Taranov, P.M.: Marketing as a determinant of the agricultural machinery market development. In: Contributions to Economics, pp. 465–471 (2017). ISBN 9783319606958
Litvinova, T.N., Morozova, I.A., Pozdnyakova, U.A.: Criteria of evaluation of effectiveness of Industry 4.0 from the position of stimulating the development of knowledge economy. In: Studies in Systems, Decision and Control, vol. 169, pp. 101–107 (2019)
Litvinova, T.N., Tolmachev, A.V., Saenko, I.I., Iskandaryan, G.O.: Role and Meaning of the ICT Infrastructure for Development of Entrepreneurial Activities in the Russian Agricultural Machinery Market. Advances in Intelligent Systems and Computing, vol. 726, pp. 793–799 (2019)
Matei, O., Anton, C., Bozga, A., Pop, P.: Multi-layered architecture for soil moisture prediction in agriculture 4.0. In: Proceedings of International Conference on Computers and Industrial Engineering, CIE, vol. 2, no. 1, pp. 39–48 (2017)
Partel, V., Charan Kakarla, S., Ampatzidis, Y.: Development and evaluation of a low-cost and smart technology for precision weed management utilizing artificial intelligence. Comput. Electron. Agric. 157, 339–350 (2019)
Troyanskaya, M.A., Ostrovskiy, V.I., Litvinova, T.N., Matkovskaya, Y.S., Bogoviz, A.V.: Possibilities and perspectives for activation of sales in the agricultural machinery market within sectorial development of Russian and European economies. In: Contributions to Economics, pp. 473–480 (2017). ISBN 9783319606958
Weltzien, C.: Digital agriculture - or why agriculture 4.0 still offers only modest returns. Landtechnik 71(2), 66–68 (2016)
Association of participants of the market of the Internet of Things: The explanatory note to the offer on implementation of the new direction of the program “Digital economy of the Russian Federation”: Digital agriculture (2019). https://iotas.ru/files/documents/Пoяcнит.зaпиcкa%20eAGRO%20fin%20000.pdf. Accessed 27 Jan 2019
The Ministry of Industry and Trade of the Russian Federation: Strategies of development of agricultural machine building until 2020, adopted by the Decree dated 22 December, no. 1810, 2011 (2019). http://www.consultant.ru/document/cons_doc_LAW_145647/. Accessed 25 Jan 2019
National Research University “Higher School of Economics”: The market of agricultural machinery – 2017 (2019). https://dcenter.hse.ru/data/2018/02/03/1163430452/Pынoк%20ceльcкoxoзяйcтвeнныx%20мaшин%202017.pdf Accessed 25 Jan 2019
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Litvinova, T.N. (2020). Managing the Development of Infrastructural Provision of AIC 4.0 on the Basis of Artificial Intelligence: Case Study in the Agricultural Machinery Market. In: Popkova, E., Sergi, B. (eds) Digital Economy: Complexity and Variety vs. Rationality. ISC 2019. Lecture Notes in Networks and Systems, vol 87. Springer, Cham. https://doi.org/10.1007/978-3-030-29586-8_37
Download citation
DOI: https://doi.org/10.1007/978-3-030-29586-8_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-29585-1
Online ISBN: 978-3-030-29586-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)