Infrastructural Sovereignty over Agreement and Transaction Data (‘Metadata’) in an Open Network-Model for Multilateral Sharing of Sensitive Data

Organizations are becoming ever more aware that their data is a valuable asset requiring protection against mis-use. Therefore, being in control over the usage conditions (i.e. data sovereignty) is a prerequisite for sharing sensitive data in (increasingly complex) supply chains. Maintaining sovereignty applies to both the primary shared data and to the ‘metadata’ stemming from the data sharing support processes. However, maintaining sovereignty over this metadata creates an area of tension. Data providers must balance operational efficiency through outsourcing the data sharing support processes and the associated metadata to external, trusted, organizations against the added risk of transferring control over the metadata. At the same time, lock-in by community providers and major integration efforts due to multiple data sharing relationships need to be avoided. To address these issues, this paper elaborates an open network-model approach for maintaining sovereignty over metadata

Trust in a multi-tenant, logistics, data sharing infrastructure:Opportunities for blockchain technology

In support of the trend towards ever more complex supply chain collaboration for the physical Internet, a trusted, multi-tenant (and interoperable) data sharing infrastructure has to be enabled. Trust is a condition sine qua non organizations may not be prepared to share potentially competitive sensitive information. As such, trust has to be an essential design aspect for any multi-tenant data sharing infrastructure for the data sharing stakeholders To overcome the challenges for trusted data sharing, various reference architectures for a trusted, multi-tenant, data sharing infrastructure are being developed. As such, the Industrial Data Space (IDS) initiative is currently gaining attention. It’s based on the architectural principles of keeping the data owner in control over his data and keeping data, data processing and data distribution at the source. Its reference architecture is strongly grounded on a role / stakeholder model for the intermediary trusted roles to enable peer-to-peer data sharing over a controlled and trusted connector infrastructure. The intermediary trusted roles may contain and process meta-data on the data sources, the data transactions and/or on the identities of the parties involved in the data sharing. This paper focuses on the role of blockchain technology for improving trust levels for such intermediary trusted roles

Beheer- en OntwikkelModel Open Standaarden: BOMOS

Semantische standaarden zijn van groot belang bij elektronische gegevensuitwisseling: ze definiëren de uitgewisselde informatie en de betekenis daarvan. Het ontwikkel- en beheerproces van dergelijke standaarden biedt veelal mogelijkheden tot verbetering. Het Beheer- en OntwikkelModel Open Standaarden ondersteunt bij het maken van keuzes om ontwikkeling en beheer van deze standaarden te verbeteren

Implementing Industry 4.0: assessing the current state

Purpose: The purpose of this paper is to introduce, summarize and combine the results of 11 articles in a special issue on the implementation of Industry 4.0. Industry 4.0 emerged as a phenomenon about a decade ago. That is why, it is interesting now to explore the implementation of the concept. In doing so, four research questions are addressed: (1) What is Industry 4.0? (2) How to implement Industry 4.0? (3) How to assess the implementation status of Industry 4.0? (4) What is the current implementation status of Industry 4.0? Design/methodology/approach: Subgroups of articles are formed, around one or more research questions involving the implementation of Industry 4.0. The articles are carefully analyzed to provide comprehensive answers. Findings: By comparing definitions systematically, the authors show important aspects for defining Industry 4.0. The articles in the special issue explore several cases of manufacturing companies that implemented Industry 4.0. In addition, systematic approaches to aid implementation are described: an approach to combine case-study results to solve new implementation problems, approaches to assess readiness or maturity of companies regarding Industry 4.0 and surveys showing the status of implementation in larger samples of companies as well as showing relationships between company characteristics and type of implementation. Small and large firms differ considerably in their process of implementing Industry 4.0, for example. Research limitations/implications: This special issue discusses implementation of Industry 4.0. The issue is limited to 11 articles, each of which with its own strengths and limitations. Practical implications: The practical relevance of the issue is that it focuses on the implementation of Industry 4.0. Cases showing successful implementation, measurement instruments to assess degree of implementation and advice how to build a database with cases together with large-scale studies on the state of implementation do provide a wealth of information with a large managerial relevance. Originality/value: The paper introduces an original take on Industry 4.0 by focusing on implementation. The special issue contains both literature reviews, articles describing case studies of implementation, articles developing systematic measurement instruments to assess degree of implementation and some articles reporting large-scale studies on the state of implementation of Industry 4.0 and thereby combine several perspectives on implementation of Industry 4.0.Economics of Technology and Innovatio

Configurations of digital platforms for manufacturing: An analysis of seven cases according to platform functions and types

We analyze organizational configurations of digital platforms for manufacturing according to two dimensions: platform functions and platform types. Platform functions refer to the organizational functions of platforms: manufacturing, data sharing, market making, and innovation. Platform types refer to a typology of how platforms are organized: as internal, supply chain, or industry type. We combine those dimensions into a framework and use that to analyze seven cases of digital platforms from the manufacturing sector. Our research answers calls for conceptual clarity and scoping of the digital platform concept and mends relative lack of attention toward digital platforms for the manufacturing sector. We find that digital platforms for manufacturing come in different, partly unexpected, configurations: (1) not all functions are necessarily organizationally part of the platform, (2) not all functions are necessarily organized according to the same platform type, but (3) also not all random configurations of platform types and functions seem to be possible. This complexity highlights the importance of the innovation function for exploring effective configurations of digital platforms for manufacturing.Economics of Technology and Innovatio