Digital twinning in smart agribusiness: Towards a conceptual and methodological framework for organizational digital modelling
Abstract
At the present stage, the achievement of the set strategic goals of ensuring Russia’s economic independence and technological leadership is associated with the development and implementation of domestic information and cognitive technologies. The country’s agro-industrial complex, which is undergoing a complex process of digital transformation with the expansion of the use of robotic technology and intelligent systems, plays a special role in solving the basic tasks of maintaining state sovereignty. The development of platform solutions in agricultural production faces serious limitations and constraints on the effective application of the “digital twin” concept, due to unresolved issues regarding the conceptual and institutional justification for their construction for organizational systems. In this regard, the aim of this study is to substantiate proposals for defining the concept of a digital model of an agricultural enterprise and the formation of a possible option for describing the economic system and basic business processes for conducting full-cycle smart agriculture. The application of content and logical analysis methods, and reengineering technology, allowed us to appropriately define a reference digital model of an enterprise in the agricultural sector and present a possible design for a digital model of the economic system of a smart agricultural enterprise. Definitions of the concepts of “digital model” and “digital twin” for organizational systems are proposed, clarifying existing definitions in terms of reflecting the variability of the description of the organization’s business model when displaying the entities of “business architecture” and “business processes” as separate structural elements and the contour of subjective perception of information when making decisions. The structure of a digital model of an agricultural enterprise’s economic system in a networked precision farming environment is substantiated, taking into account changes in the composition and role of production factors in a data economy. We demonstrate the need to reflect in this model elements and relationships that address the requirements of ensuring environmental neutrality and social responsibility in full-cycle agricultural production. We recommend using the information image of a digital twin of an agricultural enterprise to design the structure and fill the model of the economic system with data based on regulated forms of planning and reporting documentation when building a digital platform to support management decision-making. The digital twin ontology description scheme expands our understanding of the theoretical foundations of the methodology and tools for designing and developing information models of objects and processes for business systems.
Downloads
References
Pisareva, O. M., Belousova, M. N., & Stefanovsky, D. V. (2024). Modern trends in digital transformation of Russian full-cycle agricultural enterprises. Russian Management Journal, 22(3), 541–572 (in Russian). https://doi.org/10.21638/spbu18.2024.308
Sosfenov, D. A. (2023). The digital twin: The history of its origin and development prospects. Intelligence. Innovation. Investment, 4, 35–43 (in Russian). https://doi.org/10.25198/2077-7175-2023-4-35
Singh, M., Fuenmayor, E., Hinchy, E., Qiao, Y., Murray, N., & Devine, D. (2021). Digital twin: Origin to future. Applied System Innovation, 4(2), 36. https://doi.org/10.3390/asi4020036
Kamanina, A. N. (2023) Prospects of technological development of agriculture: digital platform solutions. Innovation and investment, 10, 463–467 (in Russian). https://cyberleninka.ru/article/n/perspektivy-tehnologicheskogo-razvitiya-selskogo-hozyaystva-tsifrovye-platformennye-resheniya/pdf
Vasiliev, N., Protopopova, L., Dayanova, G., Krylova, A., & Nikitina, N. (2024). Formation of a unified digital platform for the region’s agriculture. International Agricultural Journal, 67(1), 53–56 (in Russian). https://doi.org/10.55186/25876740_2024_67_1_53
Monakhov, S. V., & Ukolova, N. V (2022). Digital transformation of technology transfer in agriculture: creation and use digital platforms. Agroindustrial complex: economics, management, 6, 25–32 (in Russian). https://doi.org/10.33305/226-23
Motorin O. A., & Stukalin A. V. (2023). Issues of classification of platform solutions in the context of the study of digital platforms for agriculture. Technical and technological support for innovations in the agro-industrial complex. Materials of the II International scientific and practical conference, Melitopol, 28–29 November 2023. Melitopol State University, 292–296 (in Russian). https://elibrary.ru/download/elibrary_58638908_89068276.pdf
Kulba, V. V., Medennikov, V. V., & Mikulets, Yu. I. (2020). Evolution of information systems design: From synthesis at individual enterprises to the synthesis of optimal industry digital platforms. Herald of MHEI, 1, 132–148 (in Russian).
Zhukova, M. A., & Ulez’ko, A. V. (2020). Conceptual approach to creating a digital platform for the agro-food complex. Vestnik of Voronezh state agrarian university, 4(67), 238–250 (in Russian). https://doi.org/10.17238/issn2071-2243.2020.4.238
Raikov, A. N. (2021). Concept of the digital platform for Russian agriculture providing convergence to goals. Informatization and Communication, 1, 64–73 (in Russian). https://doi.org/10.34219/2078-8320-2021-12-1-64-73
Zatsarinny, A. A., Medennikov, V. I., & Raikov, A. N. (2023). Integration of agricultural artificial intelligence applications into a single digital platform. Information Society, 1, 127–138 (in Russian). https://doi.org/10.52605/16059921_2023_01_127
Sosfenov, D. A. (2023). Digital twin: history of origin and development prospects. Intellect. Innovations. Investments, 4, 35–43 (in Russian). https://doi.org/10.25198/2077-7175-2023-4-35
Kurganova, N. V., Filin, M. A., Chernyaev, D. S., Shaklein, A. G., & Namiot, D. E. (2019). Implementation of digital twins as one of the key areas of digitalization of production. International Journal of Open Information Technologies, 7(5), 105–115 (in Russian). https://elibrary.ru/download/elibrary_38215110_78228890.pdf
Vasiliev, A. N., Tarkhov, D. A., & Malykhina, G. F. (2018). Methods of creating digital twins based on neural network modeling. Modern information technologies and IT education, 14(3), 521–532 (in Russian). https://doi.org/10.25559/SITITO.14.201803.521-532
Petrov, A. (2018). Simulation as the basis of digital twin technology. Proceedings of Irkutsk State Technical University, 22(10), 56–66 (in Russian). https://doi.org/10.21285/1814-3520-2018-10-56-66
Makarov, V. L., Bakhtizin, A. R., & Beklaryan, G. L. (2019). Developing digital twins for production enterprises. Business Informatics, 13(4), 7–16 (in Russian). https://doi.org/10.17323/1998-0663.2019.4.7.16
Samosudov, M. (2019). Resource footprint of activities as an element of the digital twin of the enterprise. E-Management, 2(3), 38–47 (in Russian). https://doi.org/10.26425/2658-3445-2019-3-38-47
Alves, R. G., Souza, G., Maia, R. F., Tran, A. L. H., Kamienski, C., Soininen, J.-P., Aquino, P. T., & Lima, F. (2019). A digital twin for smart farming. 2019 IEEE Global Humanitarian Technology Conference (GHTC), 1–4. https://doi.org/10.1109/ghtc46095.2019.9033075
Verdouw, C., Tekinerdogan, B., Beulens, A., & Wolfert, S. (2021). Digital twins in smart farming. Agricultural Systems, 189, 103046. https://doi.org/10.1016/j.agsy.2020.103046
Peladarinos, N., Piromalis, D., Cheimaras, V., Tserepas, E., Munteanu, R. A., & Papageorgas, P. (2023). Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review. Sensors, 23(16), 7128. https://doi.org/10.3390/s23167128
Soussi, A., Zero, E., Herrera, C. D. C., Zahmoun, S., Bozzi, A., & Sacile, R. (2025). Integrating Digital Twins and MPC for Sustainable Greenhouse Management in Smart Agriculture. IEEE Transactions on AgriFood Electronics, 1–17. https://doi.org/10.1109/tafe.2025.3572808
Pisareva, O. M. (2011). Methods of analytics as an innovative potential for the development of management theory and practice. Analytical Bulletin: Models and methods in analytical work. 27, 16–31 (in Russian). http://council.gov.ru/activity/analytics/analytical_bulletins/25903/
Pisareva, O. M. (2013). Predictive and analytical activity in managing the development of multilevel organizational systems. Publishing House of the State University of Management (in Russian).
Grieves, M. W. (2005). Product lifecycle management: The new paradigm for enterprises. International Journal of Product Development, 2(1/2), 71–84. https://doi.org/10.1504/IJPD.2005.006669
Gelernter D. (1991). Mirror worlds: Or: The day software puts the universe in a shoebox...How it will happen and what it will mean. Oxford University Press. https://doi.org/10.1093/oso/9780195068122.001.0001
GOST 24.104-85. (1985). Unified system of standards for automated control systems. Automated control systems. General requirements. Moscow: Rosstandart (in Russian).
NIST Special Publication 500-167. (1987). Information Management Directions: The Integration Challenge. Gaithersburg, MD, USA.
ISO/IEC 15288. (2002). “System engineering – System life cycle processes”. Geneva: International Organization for Standardization.
ISO/TS 12911. (2012). Framework for building information modelling (BIM). guidance. Geneva: International Organization for Standardization.
IEC PAS 63088:2017. (2017). Smart manufacturing – Reference architecture model industry 4.0 (RAMI4.0). Geneva: International Organization for Standardization.
GOST R 57700.37-2021. (2021). Computer models and modeling. Digital twins of products. General provisions. Moscow: Russian Standardization Institute (in Russian).
ISO 23247-1:2021. (2021). Automation systems and integration. Digital twin framework for manufacturing. Part 1: Overview and general principles. Geneva: International Organization for Standardization.
GOST R 58439.1-2019. (2019). Organization of information on construction objects. Information management in construction using information modeling technology. Part 1: Concepts and principles. Moscow: Rosstandart (in Russian).
ISO 19650-1:2018. (2018). Organization of information about construction works. Information management using building information modelling. Part 1: Concepts and principles. Geneva: International Organization for Standardization.
GOST R 59799-2021. (2021). Smart manufacturing. Model of the reference architecture of industry 4.0 (RAMI 4.0). Moscow: Russian Standardization Institute (in Russian).
Lu, Y., Xu, X., & Wang, L. (2020). Smart manufacturing process and system automation – A critical review of the standards and envisioned scenarios. Journal of Manufacturing Systems, 56, 312–325. https://doi.org/10.1016/j.jmsy.2020.06.010
Coallier, F. Standardization strategy on IoT and Digital Twin – ISO/IEC JTC 1/SC 41. IoT and DTw Workshop, 2024, Helsinki, Finland. https://sesko.fi/wp-content/uploads/2024/06/10-2024-ISO-IEC-Standardization-strategy-on-IoT-and-Digital-Twin-v1.0.pdf
Kondratiev, V. V. (2015). Constructor of regular management. Moscow: Infra-M (in Russian).
Isaev, R. A. (2023). Management of the OT architecture of an organization: design, analysis, optimization and transformation, in 2 volumes. Moscow: Infra-M (in Russian).
Kovzunova, E. S., Ruyga, I. R., Zhirnova, I. S., & Shelevaya, V. S. (2024). Digital services in the agro-industrial complex: content analysis of functionality, problems and development perspectives. Food policy and security, 11(2), 265–286 (in Russian). https://doi.org/10.18334/ppib.11.2.120784
Sibiryaev, A. S. (2024). Possibilities of using digital platforms in agriculture. Methodological approach to the process of their implementation. Bulletin NGIEI, 7, 123–133 (in Russian).
Matyash, A. V., Bagrin, P. P., Andreeva, V. A., Mironova, M. P., & Samosudov, M. V. (2022). The term "digital twin" as applied to a social system. Economics: Yesterday, Today and Tomorrow, 12(10А), 428–440 (in Russian).
GOST-R-MEK-622641-2014. (2014). Integration of enterprise management systems. Moscow: Rosstandart (in Russian).
Oborin, M. S. (2024). Specific features of cluster-network integration in enterprises of agro-industrial complex. Lomonosov Economics Journal, 5, 114–131 (in Russian). https://doi.org/10.55959/msu0130-0105-6-59-5-6
Zvorykina, Y. V., Usov, V. G., Karelina, M. Y., Pisareva, O. M., Belousova, M. N., & Alexeev, V. A. (2025). Modernization of the North and the Arctic agro-industrial complex under digital transformation: conceptual foundations and design solutions. Arctic: Ecology and Economy, 15(1), 48–58 (in Russian). https://doi.org/10.25283/2223-4594-2025-1-48-58
Copyright (c) 2026 National Research University Higher School of Economics (HSE University)
This work is licensed under a Creative Commons Attribution 4.0 International License.
