The Role of Solution Business Model Patterns in Digital Agriculture: Linking Business Model Components and Sustainable Outcomes From a Startup Business Perspective

Digital agriculture is expanding rapidly, yet research has only begun to examine how AgTech startups design and adapt their business models, through digital technologies, in response to technological change and rising sustainability expectations. Although business model innovation (BMI) has gained prominence, existing research remains fragmented and offers limited guidance for entrepreneurs operating in uncertain, sustainability‐driven environments. This article examines how solution business model patterns (SBMPs) in digital agriculture relate firm‐level business model configurations to economic and environmental sustainability outcomes. Based on an explorative pattern qualitative analysis of 170 AgTech startups identified from Crunchbase, combining hybrid thematic coding and co‐occurrence analysis, this study identifies 19 SBMPs across value creation, value proposition and value capture. Among these, nine patterns extend existing pattern‐based literature by capturing configurations specific to digital agriculture. The identified SBMPs include data‐driven value creation (e.g., sensors‐as‐a‐service), integrated solution‐oriented value propositions (e.g., smart business in a box) and flexible pricing configurations (e.g., pay‐per‐use). The findings show that these patterns are associated with specific economic outcomes, particularly productivity and strategic decision‐making, and environmental outcomes, most prominently sustainable resource use and, to a lesser extent, ecosystem protection. By systematically linking business model components to differentiated sustainability dimensions, this study advances BMI scholarship in digital agriculture and provides a structured understanding of how specific business model configurations relate to sustainability‐oriented value creation. These insights offer a more precise analytical basis for examining BMI in sustainability‐intensive and technology‐driven contexts.