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Published in: Business & Information Systems Engineering 1/2014

01-02-2014 | Research Notes

Model-Based Decision Support in Manufacturing and Service Networks

Authors: Prof. Dr. Andreas Fink, Prof. Dr. Natalia Kliewer, Prof. Dr. Dirk Mattfeld, Prof. Dr. Lars Mönch, Prof. Dr. Franz Rothlauf, Prof. Dr. Guido Schryen, Prof. Dr. Leena Suhl, Prof. Dr. Stefan Voß

Published in: Business & Information Systems Engineering | Issue 1/2014

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Abstract

In this paper, we sketch some of the challenges that should be addressed in future research efforts for model-based decision support in manufacturing and service networks. This includes integration issues, taking into account the autonomy of the decision-making entities in face of information asymmetry, the modeling of preferences of the decision makers, efficiently determining robust solutions, i.e. solutions that are insensitive with respect to changes in the problem data, and a reduction of the time needed for model building and usage. The problem solution cycle includes problem analysis, the design of appropriate algorithms and their performance assessment. We are interested in a prototypical integration of the proposed methods within application systems, which can be followed up with field tests of the extended application systems. We argue that the described research agenda requires the interdisciplinary collaboration of business and information systems engineering researchers with colleagues from management science, computer science, and operations research. In addition, we present some exemplifying, illustrative examples of relevant research results.

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Metadata
Title
Model-Based Decision Support in Manufacturing and Service Networks
Authors
Prof. Dr. Andreas Fink
Prof. Dr. Natalia Kliewer
Prof. Dr. Dirk Mattfeld
Prof. Dr. Lars Mönch
Prof. Dr. Franz Rothlauf
Prof. Dr. Guido Schryen
Prof. Dr. Leena Suhl
Prof. Dr. Stefan Voß
Publication date
01-02-2014
Publisher
Springer Fachmedien Wiesbaden
Published in
Business & Information Systems Engineering / Issue 1/2014
Print ISSN: 2363-7005
Electronic ISSN: 1867-0202
DOI
https://doi.org/10.1007/s12599-013-0310-4

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