A neural network model for the assessment of partners’ performance in virtual enterprises |
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Authors: | Burak Sari Saleh Amaitik S Engin Kilic |
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Affiliation: | (1) Mechanical Engineering Department, Middle East Technical University, 06531 Ankara, Turkey;(2) Manufacturing Engineering Department, Atilim University, 06836 Ankara, Turkey |
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Abstract: | In response to increasing international competition, enterprises have been investigating new ways of cooperating with each
other to cope with today’s unpredictable market behaviour. Advanced developments in information & communication technology
(ICT) enabled reliable and fast cooperation to support real-time alliances. In this context, the virtual enterprise (VE) represents
an appropriate cooperation alternative and competitive advantage for the enterprises. VE is a temporary network of independent
companies or enterprises that can quickly bring together a set of core competencies to take advantage of market opportunity.
In this emerging business model of VE, the key to enhancing the quality of decision making in the partner companies’ performance
evaluation function is to take advantage of the powerful computer-related concepts, tools and technique that have become available
in the last few years. This paper attempts to introduce a neural network model, which is able to contribute to the extrapolation
of the probable outcomes based on available pattern of events in a virtual enterprise. Quality, delivery and progress were
selected as determinant factors effecting the performance assessment. Considering the features of partner performance assessment
and neural network models, a back-propagation neural network that includes a two hidden layers was used to evaluate the partner
performance. |
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Keywords: | Virtual enterprise Neural networks Partners performance Back propagation |
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