Research
“What we observe is not nature in itself but nature exposed to our method of questioning.”
— Werner Heisenberg, Physics and Philosophy (1958), Chapter III.
Understanding Intelligence, Organization & Societal Change
My research explores how intelligence, communication, and organization emerge and evolve in complex socio-technical systems. A central concern throughout my work has been how people, organizations, and technologies interact to create knowledge, coordinate activities, and develop new capabilities for collective action.
Over more than two decades, this inquiry has evolved from the study of networked value creation and digitally enabled innovation to questions of collective intelligence, human–AI collaboration, and the dynamics of organizational and societal communication. Across these changing contexts, a recurring theme has been the role of information systems in shaping the conditions under which collective action becomes possible.
My theoretical perspective draws on cybernetics, systems sciences, information systems, and organizational research. Rather than treating technologies or organizations as isolated entities, I seek to understand their mutual constitution through communication, interpretation, and evolving patterns of interaction. This perspective also informs my interest in the design and governance of systems whose behaviour cannot be adequately understood through their individual components alone.
The following research programmes illustrate the development of these interests and their current directions.
Selected Research Programmes
1. Networked Innovation & Digital Infrastructures
Inter-organizational collaboration · Network resources · Digital infrastructures
My early research investigated how information and communication technologies enable organizations to collaborate across institutional and industrial boundaries. A particular focus was the development of digital infrastructures and organizational arrangements supporting knowledge creation, innovation, and networked value creation.
This work originated in European research programmes including AVALON, a major FP6 initiative developing cross-sectoral innovation networks, and later SmartNets, an FP7 project investigating the transformation of collaborative knowledge networks into integrated value-creation systems.
Within AVALON, I served as Scientific-Technical Coordinator, contributing to the design and implementation of digitally supported collaboration across industrial sectors. The project demonstrated how technological infrastructures and organizational coordination mechanisms could support distributed innovation among otherwise independent firms. It was subsequently recognized as a finalist for the European Commission's 2012 Best Project Award in Industrial Technologies.
The SmartNets programme provided the empirical basis for a series of theoretical and applied contributions. These included research on boundary clusters, complementarities in inter-organizational collaboration, and the concept of IS-embedded network resources.
The latter conceptualizes how information systems become constitutive elements of network resources, enabling new forms of coordination, organizing, and collective value creation.
An enduring insight from this work is that digital infrastructures do more than connect existing actors: they can reshape the resources, relationships, and possibilities for collective action that emerge within a network.
Selected research: Journal of the Association for Information Systems (2017) · MIS Quarterly Executive (2015)
Research Illustration
Networked Value Creation in Business Ecosystems
Business process model of networked value creation in one of more than 70 networks within an Italian industrial ecosystem. The illustration shows how organizational units, business processes, and coordination mechanisms are integrated across organizational boundaries.
Adapted from Rehm (2007).
2. Business Ecosystems & Collaborative Modelling
Digital ecosystems · Collective sensemaking · Design research
Building on the study of innovation networks, my subsequent research examined the emergence, development, and governance of digital business ecosystems.
In collaboration with colleagues at the Technical University of Munich, particularly the research group of Prof. Florian Matthes, I investigated how complex business ecosystems can be represented, collaboratively modelled, and analysed to support organizational decision-making.
A central outcome was the Business Ecosystem Explorer (BEEx), developed in the context of research on urban mobility ecosystems. The work combined Action Design Research with visual analytical approaches to support a shared understanding of ecosystem structures, relationships, and emerging dynamics.
This research addressed both the design of analytical instruments and the organizational processes through which stakeholders construct and negotiate their understanding of complex ecosystems. It contributed methods and design principles for collaborative modelling and visualization, together with insights into the governance and evolution of digitally enabled ecosystems.
Several publications arising from this collaboration received international Best Paper distinctions.
The programme also established connections to my subsequent research on urban sustainability and governance. In particular, it raised broader questions about how digital infrastructures can enable collective experimentation, learning, and adaptive policymaking across organizational and institutional boundaries.
Selected research: Australasian Journal of Information Systems (2020)
Research Illustration
Open Digital Platforms for Urban Governance
Conceptual model illustrating how open digital platforms can facilitate collective intelligence in urban ecosystems by connecting stakeholders, enabling knowledge exchange, and supporting collaborative experimentation, decision-making, and governance.
Source:
Rehm et al. (2021), Smart Cities.
3. Collective Inferencing & Hybrid Intelligence
Collective intelligence · Communication · AI-supported reasoning
A more recent direction of my research concerns the processes through which groups and organizations construct shared understanding, interpret complex situations, and develop coordinated decisions.
I approach collective intelligence as an emergent phenomenon grounded in communication and inferential coordination. From this perspective, collective intelligence is not simply the aggregation of individual knowledge or capabilities. It develops through interactions in which actors articulate interpretations, establish distinctions, negotiate meanings, and adapt their understanding of a shared problem.
This research builds on earlier conceptual work concerning communication, knowledge, and the dynamic organization of socio-technical systems. It also draws on our investigation of digitalized work arrangements using the Laws of Form, which explored how different ways of drawing distinctions influence what researchers can observe and conceptualize.
My current work develops Collective Inferencing as a conceptual and methodological approach to investigating these dynamics. It explores how AI-supported qualitative analysis can help reconstruct inferential relationships, feedback structures, and otherwise implicit assumptions from distributed knowledge and organizational dialogue.
A central question is how artificial intelligence can complement human interpretive capabilities without replacing human judgment. This creates important connections to Hybrid Intelligence, particularly the interaction of human and artificial agents in collective reasoning, decision-making, and adaptive governance.
The research also motivates the development of experimental analytical approaches, including Stratify and related work within DeepDynamIQ, as instruments for exploring complex problem landscapes and the dynamics of collective reasoning.
Selected research: MIS Quarterly Executive (2025) · Information and Organization (2022)
Research Illustration
Managing Complexity in Digital Platforms
Analytical ideogram illustrating the distinction between complexity captured within predefined functional categories and complexity arising from inter-functional dependencies. It highlights the importance of coordination across organizational functions when addressing complex challenges in digital platform management.
Related research:
Rehm (2025),
MIS Quarterly Executive
4. Organizational & Societal Dynamics
System dynamics · Governance · Societal communication
A fourth research programme extends these interests to the governance of complex organizations and broader socio-technical systems.
One strand examines cyber-resilience and governance in corporate boards. In collaboration with colleagues, I investigate how directors interpret cybersecurity challenges, how their discussions reveal or obscure underlying organizational dynamics, and how these processes influence collective decision-making. The research combines qualitative investigation with systems-oriented modelling to explore feedback mechanisms, governance tensions, and conditions for organizational resilience.
Another strand addresses urban sustainability and adaptive governance. Research on urban experimentation platforms has examined how digital infrastructures support collective learning and policy innovation among public authorities, businesses, and civil society. Subsequent work has explored the potential of System Dynamics to improve the understanding of interconnected urban challenges and support adaptive policymaking.
These studies share an interest in the dynamics of communication, collective sensemaking, and governance under conditions of uncertainty and complexity.
An emerging extension concerns societal communication in increasingly AI-mediated environments. As artificial intelligence becomes integrated into communication processes, new questions arise about how public interpretations, collective expectations, and social norms are shaped through interactions among human and artificial agents.
This direction connects organizational cybernetics and collective intelligence with broader questions of public discourse, autonomy, and the governance of human–AI ecologies.
Selected research: Smart Cities (2021)
Research Illustration
Simulating Governance Dynamics
Scenario visualization generated through Discrete Semantic Inferencing Simulation (DSIS), illustrating how selected Functional Modules evolve under alternative conditions. The simulation supports comparison of dynamic trajectories, identification of emerging hotspots, and assessment of potential governance interventions.
Illustration from ongoing research on platform ecosystem governance dynamics.
Research Approaches & Methods
My research combines conceptual theorizing, qualitative empirical investigation, and design-oriented approaches. The choice of methods follows the nature of the problem rather than a single disciplinary tradition.
Across different research programmes, I have employed qualitative case studies, Action Design Research, collaborative modelling, systems-oriented analysis, and simulation. More recently, these approaches have been complemented by computational and AI-supported methods for analysing communication, knowledge structures, and inferential dynamics.
A particular methodological interest lies in connecting qualitative interpretation with the modelling of dynamic relationships and feedback structures. This involves exploring how observations and interpretations can be translated into analytical representations that make complex interdependencies accessible to further inquiry and critical examination.
Research artefacts, prototypes, and visual modelling environments play an important role in this process. They serve not only as potential practical applications, but also as instruments for investigating how people understand, communicate about, and interact with complex socio-technical systems.
Current Research Agenda
Intelligence, Communication & Governance in Human–AI Systems
My current research brings together these longstanding interests around a central question:
How do human and artificial agents jointly shape the emergence, coordination, and governance of intelligence in organizations and society?
Three interconnected lines of inquiry guide this agenda:
• Collective reasoning and hybrid intelligence • How can the interaction of human and artificial intelligence enhance collective sensemaking, learning, and decision-making? What new forms of coordination emerge, and under what conditions do they support—or undermine—collective agency?
• Dynamic governance and socio-technical design • How can the dynamics of complex organizational systems be made more visible and comprehensible? How can conceptual and computational approaches support the design of more adaptive, responsible, and resilient governance arrangements?
• AI-mediated societal communication • How do interacting human–AI ecologies influence public communication, norm formation, and collective expectations? What are the consequences for autonomy, institutional governance, and society's capacity for collective reasoning?
These questions motivate ongoing theoretical and methodological development, interdisciplinary collaborations, and empirical research in organizational and societal contexts.
The broader ambition is to advance a systemic understanding of intelligence that connects technological development with communication, organizational design, and societal governance.