A capability maturity model for assessing digital integration in smart farming

• Developed a capability maturity model for digital integration in smart agriculture • In-depth assessment of both technical and organisational capability dimensions • Defines five levels: ad hoc, managed, integrated, predictable, and innovative • Validated in a multiple-case study of three smart farms in the Netherlands • Provides tailored guidance to improve the maturity of smart farming The advancements of smart farming are noteworthy, largely driven by rapid developments in digital technologies such as the Internet of Things, Big Data, and AI. However, the mere availability of these technologies does not guarantee their effective integration into agricultural systems. Aligning the different digital components, such as sensors, platforms, data analytics, and decision-support tools, remains a complex task. This often prevents smart farming systems from reaching their full potential. Limited integration results in isolated data flows, interoperability problems, and inefficiencies across farm operations. This study presents a comprehensive Capability Maturity Model (CMM) for assessing the level of digital integration in smart farming from both technical and organisational perspectives. The model defines five maturity levels ranging from fragmented manual operations to a fully integrated and optimized level (Ad hoc, Managed, Integrated, Predictable, Innovative). It assesses the maturity of capabilities across five key dimensions: business processes, people and culture, strategy, technology, digital governance and data and analytics. A multi-case study of three smart farms in the Netherlands was conducted to validate the model. The findings indicate that the proposed model provides a holistic and practical framework for assessing digital integration maturity across different contexts. It not only supports strategic planning for interoperability but also identifies critical integration challenges and promotes a whole-farm approach to smart agriculture literature. As a decision-support tool, it provides agri-food practitioners with concrete and tailored guidance on which specific capabilities need to be improved to advance the maturity of smart farming.