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Since the 2000s, digital ecosystems have been affecting markets—Facebook and Uber being prominent examples. Looking at the agrisector, however, there is not yet a winner-takes-all solution in place. Instead, numerous digital agriplatforms have emerged, many of which have already failed. In the context of this study, it was revealed that reasons for such failures can be manifold, with one key challenge being the orchestration of platform content. Because, however, publicly available knowledge on this regard is limited, we decided to introduce a methodology for the evaluation of digital agriecosystem services, enabling providers to optimize their existing offering and to prioritize new services prior to implementation. By deploying our methodology to digital agriecosystems with two different application focuses (DairyChainEnergy—data agriecosystem on energy management for dairy farmers, and NEVONEX—IoT agriecosystem comprising digital services for agrimachinery), its applicability was proven. Providers of digital agriecosystems will benefit from applying this new methodology because they receive a structured decision-making process, which takes the most relevant success criteria (e.g., customer benefit, technical feasibility, and resilience) into account. Hence, a resulting prioritization of digital agriservices will guide providers in making the right implementation choices in order to successfully generate network effects on their digital agriecosystems.

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The adoption of farm management information systems (FMIS) is on the rise at German dairy farms given their benefits in supporting and automating decision-making processes. However, the offering scope of FMIS for dairy farmers is limited, with digital services mostly focusing on animal-related data and overall economic insights. By contrast, digital energy management services (DEMS) are not yet established as an integral part of FMIS despite their expected positive contribution to a dairy farm’s ecological sustainability and profitability. Against this background, the aim of this study was to find out if there is a hitherto undetected market opportunity for FMIS providers offering DEMS to German dairy farmers. To achieve this aim, the as-is market offering was screened looking at seven pre-defined DEMS, and customer preferences were investigated based on online survey responses from 74 German dairy farmers. Results of the survey indicate a high relevance of DEMS, which especially applies for optimization-oriented energy data analyses. The market coverage of such digital services, on the other hand, is not yet adequate. Hence, for providers of FMIS, we see a promising market opportunity to expand their offering by starting to deploy selected DEMS to German dairy farmers.