This paper addresses the critical challenges faced by organizations in designing and managing digital ecosystems within the ongoing digital transformation. Previous research has made notable progress in tackling technical and infrastructural concerns yet practical implementation, value creation, the integration of diverse partners remain underexplored and difficult to operationalize. Existing design-oriented research methods, such as Action Design Research (ADR), provide a strong foundation but lack a stepwise, process-oriented approach that fully recognizes the active roles of researchers as facilitators, knowledge providers, and trust anchors in the context of digital ecosystems. Moreover, current methods do not sufficiently accommodate the heterogeneity of ecosystem partners and the emergence of scientific artifacts during ecosystem formation. To bridge these gaps, we propose the Testbed Research approach, an adaptation of ADR specifically tailored for the complex realities of digital ecosystem development. Drawing on empirical evidence from 30 ecosystem initiatives conducted between 2016 and 2026, we demonstrate the methodological innovations and practical benefits of Testbed Research. Our findings contribute to both theory and practice by offering a robust framework that supports sustainable value creation and the effective orchestration of digital ecosystems, ultimately bridging the divide between academic insight and organizational practice.

Sharing and collaborating on data across organizational boundaries is increasingly important for building a comprehensive data foundation for a variety of relevant analytical models and reports. We argue that a formalized set of rules and responsibilities-data governance-is needed to guide such data sharing activities and thus provide the foundation for an institutionalized data ecosystem. To this end, we propose a set of design principles. Based on three case studies from different application domains, we derive the design principles using Service-Dominant Logic as our theoretical lens. We distinguish between dynamic and static design principles. Our approach supports the delineation and specification of data governance structures for data ecosystems.

The transition of our economy towards more sustainability is accompanied with various challenges and a need for collaborative solutions. Digital technologies have the potential to address these challenges and to contribute to the achievement of global sustainability goals. Business models that drive the prevailing economic system are characterized by the consumption of natural resources and the generation of waste. The Internet-of-things (IoT) enables business cooperations and networks to foster new principles of value creation. They are able to create an opportunity to incorporate sustainability measures and enhance environmental impact. In order to remain competitive, companies are faced with the need for sustainable and digital transformation at the same time. Aligning the two concepts could help address the urgency to act. This literature review portrays specific approaches for integrating sustainability into IoT ecosystems as a starting point to enhance the practicability of abstract concepts in this field.

Purpose The initial observation of this study is the gap of research in the economic application of data spaces in wholesale. With the lowering threshold in using digital technology in innovative services wholesale is confronted with new competition in their main business – the purchase and sale of products in large numbers. Wholesale must advance in their own business creating new digital services for their customers to stay relevant competitors in their markets. Design/methodology/approach The design follows an explorative, heuristic and interdisciplinary approach (social sciences and in-formation systems) of a multiple case study combining semi-structured, open and participating observation in three case studies. The cases were set in tourism, construction, as well as manufacturing and were each scientifically accompanied for more than one year during the identification of implementation of strategies for data spaces as digital entrepreneurial path. Findings The study shows four strategies in the implementation of data spaces in traditional wholesale. These data spaces have their focus in (1) the traded commodity with two specificities (1a and 1b), (2) the customer and (3) the cooperation of an ecosystem of companies. Each have their own challenges, chances and specifications like the data sovereignty. These strategies are embedded in the behavior of digital entrepreneurship. Originality/value This study accompanied and observed the entrepreneurial strategies of three wholesalers discovering new opportunities enabled via data spaces. These three strategies follow different approaches offering potentials for other wholesalers.

Traditional enterprise information systems have been around for more than 40 years. They are designed to support business processes and deliver information to the people within a company who require it for their work. However, there are blind spots that these systems are unable to address. In this article, we investigate how digital twins, which are based on the technology and architecture of the Industrial Internet of Things, as well as the principles of cyber-physical systems, can be used to fill such gaps and elucidate how their application will affect the prospective relationship between internal information systems and digital twins. The insights are based on a single case study within the logistics department of an industrial company and its service provider. From the case study, properties of both system types were identified that provided a basis for comparison and stimulated discussion about their future dependencies.

Managers have at least two social roles in their job position: One is to keep the business running while the other role searches for entrepreneurial opportunities to exploit. Both roles have one aspect in common: the security of the organization’s existence, in short term as manager and in long term as entrepreneur. Our paper compares entrepreneurial intentions - the mental preparation to follow entrepreneurial goals – as well as the realization of these intentions in crises. The research question is: how do global crises affect the realization of entrepreneurial intentions? The approach is explorative, describes four directions of entrepreneurial intentions and what happened during their realization. We conducted two qualitative interview series, partly structured with two sequentially partly standardized guidelines, one in 2018/19 with 13 participants, the follow-up series in 2022/23 with 10 of the 13. The intentions of the interviews from 2018/19 were assigned to four directions: four of the wholesaling managers intended no to low collaboration in the familiar markets (direction I), four sought high collaboration in the familiar markets (II), two wanted no to low collaboration but to engage in unfamiliar markets (III), and three were looking for high collaboration in unfamiliar markets (IV). During the second interview series we confronted the participants with their intentions. The responses of 2022/23 show that global crises influenced the entrepreneurial intentions in different ways. Despite several crises between the two interview series, three wholesalers followed their intentions. All others changed directions. While some managers struggled with the situation and postponed or even discarded the intentions others saw new opportunities and exploited them. Consequently, it can be stated that crises can nevertheless maintain intentions and/or lead to new ideas. In times of a crisis, it is advisable to continue to keep both roles: the manager role must guide the company through the crisis, while at the same time ensuring its existence by exploiting opportunities as entrepreneur. For this purpose, we derived entrepreneurial paths from the results: (1) focus on existing business in familiar market, (2) expansion of the business segment in familiar market, (3) entering unfamiliar markets.

Das Internet of Things (IoT) und kooperative Datenräume bereiten den Weg für neue datengetriebene Services, die oftmals auch die Grundlage für neue digitale Geschäftsmodelle bilden. Damit einher gehen vielfältige Herausforderungen, insbesondere für kleine und mittelständische Unternehmen (KMU). Diese kommen zunehmend in digitalen Ökosystemen zusammen – Verbünde von Organisationen, die in kooperativer wie kompetitiver Weise miteinander in Verbindung stehen und ihre Aktivitäten und Ressourcen an einem zentralen Wertversprechen ausrichten. In diesem Beitrag wird anhand einer Case Study im produzierenden Kontext untersucht, ob und wie mit der Rechtsform der Genossenschaft ein Governance-Rahmen für solche digitalen Ökosysteme geschaffen werden kann. Die mitwirkenden Praxispartner aus dem produzierenden Kontext teilen Zustandsdaten IoT-fähiger Objekte über Unternehmensgrenzen hinweg miteinander, um einen kooperativ genutzten Datenraum aufzubauen. Dieser bildet die Grundlage für die Ausgestaltung datengetriebener Services und Geschäftsmodelle. Der Beitrag beleuchtet, wie der verbreitete rechtliche Rahmen einer Genossenschaft genutzt werden kann, um kooperative Datenräume zu etablieren und deren Betrieb dauerhaft zu verstetigen.

The Internet-of-Things enables enterprises to collaborate in IoT-Ecosystems. These ecosystems make it possible to create new value scenarios that individual enterprises are unable to offer on their own. Turning IoT-Ecosystems from concept to reality is a challenge, especially for small and medium sized enterprises. We conducted a case study in the early stages of an IoT-Ecosystem. Seven enterprises from diverse backgrounds were forming the observed ecosystem in the German hospitality industry. The case study consists of a series of workshops with business executives and a Proof-of-Concept. Our research focuses on the Proof-of-Concept steps within the process of forming an IoT-Ecosystem. Researchers took an active role in these steps. We condensed our observations into six key factors and structured them along the creation process of IoT-Ecosystems. We show that the Proof-of-Concept is not only dependent on technical but also on business and human factors. The identified key factors help practitioners to implement a Proof-of-Concept in their IoT-Ecosystem. Researchers may use them as a base for further research into the steps of IoT-Ecosystems.

There is a variety of reasons that sharing data among Small and Medium-Sized Enterprises (SMEs) carries business potential, particularly for analytical applications.But outside a few niche domains, the number of success stories for data sharing is rather modest.Based on a qualitative study and first experiences from a research project with pilot implementations, we argue that this is mainly due to a lack of an institutionalized governance structure: Founding a separate legal entity for data sharing and analysis can address core concerns regarding sharing valuable data assets.However, this requires a well-calibrated set of defined roles for the involved partners.Based on our results we propose a first concept on delineating and mapping out those roles.

The collection and analysis of industrial Internet of Things (IIoT) data offer numerous opportunities for value creation, particularly in manufacturing industries. For small and medium-sized enterprises (SMEs), many of those opportunities are inaccessible without cooperation across enterprise borders and the sharing of data, personnel, finances, and IT resources. In this study, we suggest so-called data cooperatives as a novel approach to such settings. A data cooperative is understood as a legal unit owned by an ecosystem of cooperating SMEs and founded for supporting the members of the cooperative. In a series of 22 interviews, we developed a concept for cooperative IIoT ecosystems that we evaluated in four workshops, and we are currently implementing an IIoT ecosystem for the coolant management of a manufacturing environment. We discuss our findings and compare our approach with alternatives and its suitability for the manufacturing domain.

By exchanging data from various assets the Internet of Things (IoT) enables new forms of cooperation between companies from different domains. These collaborations of companies are known as IoT ecosystems. Through the interrelations between the partners within the IoT ecosystem the companies are able to realize additional business potentials. In our paper we identify business potentials and ecosystem requirements based on the interrelations between the partners in an IoT ecosystem. The basis for our work is a case study in the industrial domain with seven different companies. Within the scope of the case study an IoT ecosystem was created based on a pay per part production of turntables for excavators. The ecosystem was implemented under real life conditions.