Software-Defined Value Networks: Motivation, Approaches, and Research Activities

Globalization has led to cost efficient but highly fragile value chains in industrial manufacturing, as demonstrated by the corona pandemic. This paper proposes a rethinking of value chains towards software-defined value networks (SDVN) to achieve resilience advantages in a VUCA world. To unveil these advantages, a holistic view of the causes of global value chain disruptions was set up. In a novel approach, an initial set of causes was extracted from ChatGPT and combined, structured, and expanded with an automated analysis of news and research literature. On this basis, levels of SDVN adaptivity and their corresponding application-oriented requirements are deduced. From this, current barriers in digitalization at the value-added level are derived. To reflect the contribution made by current developments, these are assigned to the barriers. Finally, open research questions towards the transition to SDVN are identified. The result holistically shows how the flexibility, redundancy, scalability, and data efficiency of SDVNs lead to success.