Inter-Organizational Data Sharing: Foundations, Tensions and Value Constellations

Inter-organizational data sharing has become a pressing issue due to rising legal regulations (e. g., Data Governance Act or Supply Chain Act) and global competition. To meet these challenges as a company, more and more data must be shared across several stages of their supply chains. Therefore, companies are obligated to act, and they need to be shown clear ways to benefit from sharing their data. Consequently, companies need to build internal competencies for handling data and understand what needs to be considered when sharing data with other participants in different value constellations in data ecosystems. Inter-organizational data sharing itself is not a new phenomenon, as data has been shared in supply chains for decades, often in direct bilateral exchange relationships. Due to the growing challenges of having to share increasingly more data types with an increasing number of actors, building these bilateral exchange relationships is no longer appropriate, and standardized value constellations are needed so that data can be shared with many actors, for example, via data marketplaces or data spaces. To address these issues, this dissertation examines inter-organizational data sharing from an organizational, cross-company perspective. The studies in this dissertation are organized into three areas: First, it explicates the foundations of inter-organizational data sharing by distinguishing and defining the terms data sharing and data exchange and to what extent does it fit into the overarching research context of data ecosystems and data spaces. Second, it explores tensions, particularly from data providers' perspectives, and their influence on their willingness to share data. Thirdly, this dissertation shows which value constellations data providers should consider for planning and implementation, depending on the use case, and which values arise for the involved actors. In-depth consideration of these three research areas was based on an analysis of the existing literature to capture existing knowledge in research, a total of 36 interviews with experts from the field, and seven workshops with 42 experts from the field and research to develop and evaluate the results in the context of this dissertation. This approach achieved the following overarching research objective: Development of decision support for data providers in inter-organizational data sharing. This dissertation contributes to both research and practice. Firstly, from a research perspective, this dissertation aims to strengthen and position the importance of inter-organizational data sharing in the overarching developments of the data economy. Secondly, this dissertation provides an overview of what inter-organizational data sharing encompasses and, more importantly, what tensions exist, thus offering numerous starting points for future research. From a practical point of view, the contributions are threefold. They provide an overview, offer recommendations, and point out solutions. The results of this dissertation address both companies that already practice data sharing and companies that want to do so in the future. The specific target group of this dissertation are managers from business development or data management, such as chief data officer, enterprise data strategy lead, and chief data steward, who are responsible for promoting data sharing with other companies. For this target group, the results of this dissertation are intended, first, to provide an overview of what needs to be considered in the context of inter-organizational data sharing (e. g., what incentives exist for data sharing), second, to make recommendations (e. g., what services a data intermediary can provide to support), or third, to show possible solutions, such as how value constellations can be used for different use cases.