Dynamic and flexible business relationships are expected to become more important in the future to accommodate specialized change requests or small-batch production. Today, buyers and sellers must disclose sensitive information on products upfront before the actual manufacturing. However, without a trust relation, this situation is precarious for the involved companies as they fear for their competitiveness. Related work overlooks this issue so far: existing approaches protect the information of a single party only, hindering dynamic and on-demand business relationships. To account for the corresponding research gap of inadequately privacy-protected information and to deal with companies without an established trust relation, we pursue the direction of innovative privacy-preserving purchase inquiries that seamlessly integrate into today’s established supplier management and procurement processes. Utilizing well-established building blocks from private computing, such as private set intersection and homomorphic encryption, we propose two designs with slightly different privacy and performance implications to securely realize purchase inquiries over the Internet. In particular, we allow buyers to consider more potential sellers without sharing sensitive information and relieve sellers of the burden of repeatedly preparing elaborate yet discarded offers. We demonstrate our approaches’ scalability using two real-world use cases from the domain of production technology. Overall, we present deployable designs that offer two-way privacy for purchase inquiries and, in turn, fill a gap that currently hinders establishing dynamic and flexible business relationships. In the future, we expect significantly increasing research activity in this overlooked area to address the needs of an evolving production landscape.

This paper addresses the industrial adoption gap of 5G/6G by presenting a verti-cal-agnostic Methodological Assessment Framework (MAF) that bridges network KPI with user-centric User-KPI and User-KVI to quantify techno-economic and societal value propositions from an end-user perspective. First, a detailed description of the MAF and its underlying principles is given, explaining how a use case’s value proposi-tion can be captured. Second, the MAF is applied to three different use cases from the verticals manufacturing, construction, and automotive utilizing the individual User-KPI and User-KVI for the quantification of the individual value propositions. The results show that the use of 5G can lead to enhanced process capability and reproducibility as well as increased insights into different processes. In addition, it is shown that the MAF objectively quantifies user value across diverse verticals, strengthens inter-disciplinary alignment, and can be employed to support investment decisions, based on the calcu-lated value propositions.

This paper addresses the industrial adoption gap of 5G/6G by presenting a novel, vertical-agnostic Methodological Assessment Framework (MAF). The MAF bridges the Network Key Performance Indicators (KPI) of 5G networks with user-centric User-KPIs and User-KVIs (Key Value Indicators) to quantify the techno-economic and societal value propositions of industrial 5G use cases from an end-user perspective. First, a detailed description of the MAF and its underlying principles is given, explaining how a use case’s value proposition can be captured. Second, the MAF is applied to three different industrial use cases from the verticals manufacturing, construction, and automotive utilizing the individual User-KPI and User-KVI for the quantification of the individual value propositions. The results show that the use of 5G can lead to enhanced process capability and reproducibility as well as increased insights into different processes. In addition, it is shown that the MAF objectively quantifies user value across diverse verticals and is able to strengthen interdisciplinary alignment over different verticals.