networks

In the past ecological (and social) aspects were often dealt with by the legal or compliance department. Ever more often ecological issues are linked with eco-innovations. This almost paradigmatic change of perspective entails that ecological topics are not just seen as cost drivers but as a management area relevant to increase competitiveness and to create business cases for sustainability. Although this view is increasingly adopted it remains fuzzy what really constitutes processes of sustainability innovations. Large companies often have R&D and sustainability departments driving eco-innovations in a professional manner. Small and medium sized enterprises (SMEs), however, depend on other means such as public-private partnerships (PPPs) which can play an important role for the diffusion of eco-innovations in SMEs.

The increasing turbulence in enterprises environment becomes apparent by rising variant diversity and continuously reducing product life cycles. These results cause immense and not resolvable adaption necessities for producing companies. The approach of network factories combines system immanent and network bounded potentials to increase adaption alternatives, reduce adaption risks, and optimize agility.

This article describes an opportunity to model actors and systems in various business processes into an overall model by using the technique of networking. To achieve this goal, an algorithm is introduced. Next, different metrics based on social network analysis, are described. These metrics are able to expose parts of the network which have a huge utilization and therefore the underlying process itself. With this technique it is possible for project leaders, managers and decision makers to analyze the processes for flaws, finding out capacities and to build new project teams together (staffing).

In the past the dynamics of the markets in interaction with an increasing globalization led to the fact that industries concentrated more and more on their core competences. By the reduction of the companies vertical integration value-added processes were outsourced in the same measure as supporting activities. In order to be able to meet the so developing complexity, production and logistics networks were formed to enhance the co-operation between the enterprises in a long-term and stable form. In these networks beside products and semi-finished materials also knowledge and information are produced and transferred. The protection and division of knowledge, experience and behaviours are of a special relevance if e.g. a participant leaves the network. In such a case the question arises whether and how the knowledge of the separating participant can be particularly retained for the network and a possible advancing producer, in order to not disturb the efficiency of the network. For the ...

Production and logistics networks are characterized by an increasing dynamic and structural complexity, which makes an efficient planning more difficult. Observed non-linear dynamic effects, which in case of similar causes can lead to different results, contribute additionally to this problem. As a consequence strong inventory fluctuations can appear among others, which represent a strong economically load for network participants. The simulation-supported analysis of these connections is the main focus of this article. Moreover as a result of the analysis ways and means are pointed out, which will help to react more adequately to the given problems.

The adoption of the internet to support electronic business processes is currently done by a transformation of traditional processes. However, the direct transfer does not make use of the network capabilities and of the resulting possibility of direct communication between the business partners. Furthermore, actual systems do not support the dynamics and flexibility required by emerging business models. The article analyses actual interaction patterns and presents a technical concept based on Peer-to-Peer network architecture to support these new types of decentralized economic interactions.