The Challenge of Scientific Cooperation in Large Complex Research Clusters - Experiences from the Cluster of Excellence "Integrative Production Technology for High-Wage Countries

Claudia Jooß (), Florian Welter (), Anja Richert () and Sabina Jeschke ()
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Claudia Jooß: RWTH Aachen University, IMA/ZLW
Florian Welter: RWTH Aachen University, IMA/ZLW
Anja Richert: RWTH Aachen University, IMA/ZLW
Sabina Jeschke: RWTH Aachen University, IMA/ZLW

A chapter in Automation, Communication and Cybernetics in Science and Engineering 2011/2012, 2013, pp 395-405 from Springer

Abstract: Abstract The initiation of so called Clusters of Excellence constitutes a milestone with regard to Germany's efforts to foster integrative and interdisciplinary research. Clusters of Excellence constitute spatially concentrated research networks including about 20 university institutes, non-university research institutes as well as further selected partners and advisors from industry and science. The heterogeneity of the included actors can lead to structural, cognitive and cultural challenges in coordination and cooperation, because diverse disciplines (e.g. production and material engineering, informatics as well as business sciences) are integrated using different methodologies and technical terms. Therefore, the question arises in how far cross linked, knowledge-intensive and highly complex scientific cooperations can be organized to ensure a high quality of the research cluster output. To cope with the challenge of scientific cooperation, the conceptual framework of the Cross Sectional Processes in the Cluster of Excellence “Integrative Production Technology for High-Wage Countries” at RWTH Aachen University supports effective networking processes and strategic cluster development by means of learning and knowledge management. In order to contribute to the aforementioned research question, a model for the management of Cross Sectional Processes is developed. The model will define specific measures for a promotion of interdisciplinary cooperation and cluster development at respective phases of network development – e.g. from the initiation phase to the steady phase. Following the research approach of the Grounded Theory, the generation of the model bases on a triangulation of quantitative as well as qualitative data, captured through a Balanced-Scorecard-based performance measurement tool, direct evaluations and structured interviews with cluster members. First results of the data triangulation make obvious that e.g. the role of project leaders as cluster-internal knowledge agents is crucial for a successful knowledge transfer in a hierarchical Cluster of Excellence. Moreover, a high rate of staff turnover in the research environment strongly influences the implementation of cross sectional activities. A further transfer of cross sectional measures to other forms of scientific oriented clusters and comparable networks is aspired by the Cross Sectional Processes to support scientific oriented interdisciplinary cooperation in future.

Keywords: Knowledge Management; Cross Sectional Measure; Network Development; Management Board; Balance Scorecard (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/978-3-642-33389-7_31

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