Sven-Volker Rehm

Collaborative innovation in Smart Networks - a methods perspective

Innovation management methods have been subject to extensive research during the last decades, many of which have found their way to application in practice. However, innovation management methods are still predominantly used within company boundaries, although knowledge contributions of external business partners could often boost the benefits of applying these methods. Smart Networks, focusing on Organizational Networking, Knowledge Networking and Information and Communication Technology (ICT) Networking, offer an approach for the collaborative, inter-enterprise implementation of such methods. This paper presents an engineering approach for how innovation management methods can be applied collaboratively within this specific form of enterprise networking. An approach to implement innovation management methods with help of ICT applications is highlighted. Exemplarily, an implementation of the Failure Mode and Effects Analysis (FMEA) method is illustrated.

Using information systems to achieve complementarity in SME innovation networks

Within dynamic innovation networks of small and medium enterprises (SMEs), complementarity between innovation partners is central to extend firm-level resources and capabilities and create synergies at the network level. Few guidelines exist for how information systems (IS) can be used to achieve fit between innovation partners. We conduct qualitative case studies of three innovation networks and investigate information technology (IT) affordances that undergird complementary activities. We provide evidence for three areas of fit and identify IT-based affordances, which foster synergy creation. These areas provide stimulus for developing IS strategies to networked innovation. We offer a conceptual model of how complementarity in SME innovation networks can be supported with the help of interorganizational systems.

Towards self-managing systems inspired by economic organizations

Todays self-managing systems would ideally be able to adapt themselves (their internal structure or behavior), as well as to autonomously participate in larger, self-organizing systems. Analogously, the enterprises or other socio-economic systems autonomously manage themselves — they make decisions on how to adapt their structure and behavior, and how to organize with other entities in the environment. To connect internal self-adaptive with external self-organizational behavior, an enterprise is “aware” of itself and of its environment, and acts according to this awareness. This position paper proposes to address the challenges of a complex distributed self-managing system by making entities in such a system able to adapt themselves similarly to how companies manage themselves in socio-economic systems. To enable the knowledge transfer between these two fields, the paper proposes to utilize symbolic models which will be used by self-managing systems for knowledge representation and reasoning. This will make such systems in a way also self-aware and enable both self-adaptive and self-organizing capabilities. The paper discusses research directions to make this approach possible.

A Cybernetic Approach Towards Knowledge-Based Coordination of Dynamically Networked Enterprises

In the scope of the European Research Framework, at ITV Denkendorf new concepts, methodologies and ICT architectures for cooperation and coordination in multi-stage value added chains have been developed and applied. Starting from a cybernetic approach, methods of knowledge-oriented management have been used that support the cooperative planning of production network resources and their allocation to dynamic business processes for networked organizations.

An Agile Framework for Modeling Smart City Business Ecosystems.

Modeling business ecosystems enables ecosystem stakeholders to take better-informed decisions. In this paper we present an agile framework for modeling a smart city business ecosystem. We follow a design science research approach to conceptualize the agile approach to manage ecosystem models and present the architecture of our framework as design artefact. During the design process, we evaluated ecosystem models that need to adapt with the emerging structures of the business ecosystem. The platform aims at a collaborative modeling process, which empowers end-users to manage the business ecosystem models and underlying data. The evaluation of the platform was conducted with industry partners as part of the presented smart city initative, indicating it usefulness when fulfilling modeling related tasks.

Was kommt danach

Technologische Entwicklungen erlauben, Besucherverhalten automatisiert zu messen und zu beeinflussen. Ein Ansatz ist die Adaption visueller Botschaften auf Veranstaltungen. Diese Anpassung wird von „intelligenten“ Algorithmen gestutzt, die auf das Besucherverhalten reagieren konnen.

ERM in der Praxis

In diesem Kapitel betrachten wir die Erfolgsfaktoren des ERM-Frameworks aus praktischer Perspektive. Insbesondere stellen wir dar, wie sich Erfolgsfaktoren als Kenngrosen der ERM-Prozesse typischerweise verandern. Dies soll dabei helfen einzuschatzen, wie sich Prozesse im eigenen Unternehmen bei Umsetzung eines systematischen ERMs verandern.

Event-Resource-Management

Einige Leser werden viele der vorgenannten Herausforderungen, denen sich Live-Kommunikation stellen muss, aus dem Effeff nachvollziehen konnen. Es ist folglich nur logisch, dass fur einzelne singulare Herausforderungen und/oder Aufgaben in den letzten Jahren digitale Tools sowie Anwendungssoftware entwickelt wurden. Event-Manager profitieren, in B2B und B2C, branchenubergreifend und vielschichtig.

Einsichten und Aussichten

Die Betrachtung aktueller Funktionen von Event-Resource-Management-Systemen in der Praxis (vgl. Kap. 3) und auch der Ausblick auf kunftige Funktionen weisen eine zentrale Gemeinsamkeit auf: Sie zeigen, wie hoch die Bedeutung von Daten ist, was bereits angesprochen wurde, als es um die zunehmende Relevanz quantitativer Ansatze ging (vgl. „Funktion: Event-Controlling“).

Holistic Design of Visual Collaboration Arenas and Intelligent Workspaces

Future industrial and societal projects must be designed for sustainable operations, evolutionary capabilities, and business operations. To exploit the potential of digitalization, we must design practical cases and roles, workspaces and collaboration spaces, creating evolutionary action- and work-sensitive contexts. Intelligent workspaces and operation models will complement, enhance, and replace natural language specifications, coded systems and information flows. Design of visual knowledge models, enabled by Active Knowledge Architectures, will revolutionize industrial computing and collaboration. The MADONE partners have performed industrial and public pilot projects verifying that sector adaptable platforms give actors agile approaches and evolving collaboration capabilities and services. Evolutionary workplaces and collaboration spaces resolve present challenges and open new opportunities, supporting flexibility, adaptability, reusability, traceability, predictability and sustainability. Holistic design of projects and operations is the industry case demonstrator described.