Digital twinning in smart agribusiness: Towards a conceptual and methodological framework for organizational digital modelling

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.