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In the food industry, a very large potential of data ecosystems is seen, in which data is understood, exchanged and monetized as an economic asset. However, despite the enormous economic potential, companies in the food industry continue to rely on traditional, product-oriented business models. Existing data in the value chain of industrial food production, e.g., in harvesting, logistics, and production processes, is primarily used for internal optimization and is not monetized in the form of data products. Especially the pricing of data products is a key challenge for data-based business models due to their special characteristics compared to conventional, analog offerings and multiple design options. The goal of this work is therefore to solve this issue by developing a framework that allows the identification of pricing models for data products in the industrial food production. For this purpose, following the procedure of typology formation, essential design parameters and the respective characteristics are derived. Furthermore, three types for pricing models of data products are shown. The results will serve not only stakeholders in the food industry but also manufacturing companies in general as input for an orientation of their databased business models.
The rapid developments in information and communication technology enable new bus iness models that are based on digital platforms. Marketplaces such as Amazon or Airbnb have already adapted this business model to connect previously unconnected supply-side and demand-side to conduct a business transaction via a digital platform. Due to Industrie 4.0 and the rapid technological development that comes with it, digital platforms have entered the market within the area of the mechanical engineering. Different platform types exist, such as marketplaces for machine equipment or digital data platforms for connected machines. Although numerous companies claim to offer platform-based bus iness models, they often lack knowledge on individual business model components. To close this gap, this paper structures a variety of existing platforms based on their detail characteristics. Within this paper, existing typologies of digital platforms from other industry areas are analyzed. Case study research ofplatforms within the mechanical engineering is used to adjust these typologies and create a new one for digital platforms within the mechanical engineering.