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Big data are collected along the entire food industry value chain, but remain mostly unused. Data sharing in data ecosystems could lead to efficiency gains and new revenue streams. We investigate data sharing within food industry and derive challenges and opportunities for data sharing in this context. We conducted interviews with ten qualified experts from the German food industry. The results reveal that mainly trust, usefulness and value influence users’ attitude towards data sharing. Our results confirm social exchange theory in conjunction with technology acceptance model as relevant underlying IS theories of data sharing.
This chapter presents key challenges of digital pricing: selling value propositions, data-driven quantification of value, the design of value-driven pricing models, and the definition of subscription-based price metrics. To structure the pricing for smart-product-service offerings promisingly, a framework with four specific elements has been developed. To address the value propositions properly, this chapter presents four archetypes for offering smart-product-service systems. The chapter concludes by presenting an approach to quantify customer value for digital products and services.