Scientific Performance Indicators – Empirical Results from Collaborative Research Centers and Clusters of Excellence in Germany

Welter, Florian; Schröder, Stefan; Leisten, Ingo; Richert, Anja; Jeschke, Sabina

doi:10.1007/978-3-319-08816-7_17

Cited by 4 publications

(5 citation statements)

References 6 publications

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“…These outputs introduced and reported by the Iran Ministry of Health as the main indicators of measuring knowledge production of health research centers. These outputs also have been used in previous studies for measuring knowledge production of research centers ( 15 , 16 ). Using the average five years (2010–2014) of inputs and outputs data was because the result of some research activities appear in the long-run (five year).…”

Section: Methodsmentioning

confidence: 99%

“…Nowadays, due to the rapid progress of research systems, the regular collection and reporting information about the performance of research centers are common practices. Research center information and reports can provide a general overview about their performance ( 15 , 16 ), and the next logical step is to begin comparison of the efficiency of research centers. Through such comparisons, the most efficient research units can be identified and considered as benchmarks for improving the efficiency and effectiveness of others ( 17 ).…”

Section: Introductionmentioning

confidence: 99%

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Measuring Efficiency of Knowledge Production in Health Research Centers Using Data Envelopment Analysis (DEA): A Case Study in Iran

et al. 2016

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IntroductionEfficiency analysis is necessary in order to avoid waste of materials, energy, effort, money, and time during scientific research. Therefore, analyzing efficiency of knowledge production in health areas is necessary, especially for developing and in-transition countries. As the first step in this field, the aim of this study was the analysis of selected health research center efficiency using data envelopment analysis (DEA).MethodsThis retrospective and applied study was conducted in 2015 using input and output data of 16 health research centers affiliated with a health sciences university in Iran during 2010–2014. The technical efficiency of health research centers was evaluated based on three basic data envelopment analysis (DEA) models: input-oriented, output-oriented, and hyperbolic-oriented. The input and output data of each health research center for years 2010–2014 were collected from the Iran Ministry of Health and Medical Education (MOHE) profile and analyzed by R software.ResultsThe mean efficiency score in input-oriented, output-oriented, and hyperbolic-oriented models was 0.781, 0.671, and 0.798, respectively. Based on results of the study, half of the health research centers are operating below full efficiency, and about one-third of them are operating under the average efficiency level. There is also a large gap between health research center efficiency relative to each other.ConclusionIt is necessary for health research centers to improve their efficiency in knowledge production through better management of available resources. The higher level of efficiency in a significant number of health research centers is achievable through more efficient management of human resources and capital. Further research is needed to measure and follow the efficiency of knowledge production by health research centers around the world and over a period of time.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Measuring Efficiency of Knowledge Production in Health Research Centers Using Data Envelopment Analysis (DEA): A Case Study in Iran

et al. 2016

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“…To foster interdisciplinary cooperation with the objective of increasing effectiveness of interdisciplinary research consortia, measurement approaches are necessarily implemented and adapted to the needs of interdisciplinary consortia as examples for publicly funded, non-profit organizations [27,28]. Thereby the measurement of interdisciplinarity is essential, e.g.…”

Section: How To Measure Interdisciplinary Integrationmentioning

confidence: 99%

Fostering interdisciplinary integration in engineering management

Vaegs

Zimmer

Schröder

et al. 2013

2013 IEEE International Conference on Industrial Engineering and Engineering Management

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Research in the challenging field of industrial engineering and engineering management often needs the expertise from more than one discipline. Various disciplinary competences have to be combined to answer research questions and to solve specific (engineering) problems at the interfaces of different professional disciplines. The disciplines being part of the research and problem solving process have to be consequently integrated to form an efficiently performing interdisciplinary consortium.Current research states that this interdisciplinary integration process has to include various dimensions. This paper introduces three sets of interdisciplinary integration methods. Together they cover all of the dimensions explained before and lead to an enhanced interdisciplinary integration. Having just implemented a set of integration methods, measurement methods are adjusted to evaluate and optimize them continually. Keywords -Interdisciplinary integration, KnowledgeManagement, Terminology, Virtual and physical cross linkage 1 http://www.dfg.de/en/index.jsp 2 http://www.wissenschaftsrat.de/en/home.html 3 The excellence initiative was started in 2005 by the government and federal states. It is divided into three funding lines: graduate schools, clusters of excellence and future concepts for top-level research. In 2012 its second funding period started.

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“…All procedures are currently investigated in the processes of three dissertations. Further publications are listed in the references section [21,17,18,19,31]. The research works are results from the accompanying research of the depicted clusters of excellence.…”

Section: Concerning the Clusters Of Excellence Integrative Productionmentioning

confidence: 99%

“…• internal perspective/ research cooperation • perspective on learning and development • output/ client perspective 21 The four perspectives constitute a f whom the superior vision of the cluster of broken down in strategic (sub-) goals [20]. 22 Initially, the adapted design of Kapla intended as a communication, information With this in mind, the cluster-specific adapt the four perspectives in alignment with cont consortium agreement as well as the integra online-based evaluation.…”

Section: Prototype 1: Cluster-specific Balanced Scorecardmentioning

confidence: 99%

Knowledge engineering in interdisciplinary research clusters

Joos

Vossen

Leisten

et al. 2012

2012 IEEE International Conference on Industrial Engineering and Engineering Management

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This paper proposes an innovative knowledge engineering approach for interdisciplinary research clusters. In science, different competences, knowledge, scientific experience and cultures converge. To cope with this challenge it is necessary to combine several dimensions of human, organization and technology within a holistic knowledge engineering approach. Cooperation structures have to be adapted accordingly. The authors present prototypes of an application oriented research to promote interdisciplinary knowledge production.

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Scientific Performance Indicators – Empirical Results from Collaborative Research Centers and Clusters of Excellence in Germany

Cited by 4 publications

References 6 publications

Measuring Efficiency of Knowledge Production in Health Research Centers Using Data Envelopment Analysis (DEA): A Case Study in Iran

Measuring Efficiency of Knowledge Production in Health Research Centers Using Data Envelopment Analysis (DEA): A Case Study in Iran

Fostering interdisciplinary integration in engineering management

Knowledge engineering in interdisciplinary research clusters

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