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Titlebook: Innovation in Manufacturing Networks; Eighth IFIP Internat Américo Azevedo Conference proceedings 2008 IFIP International Federation for In

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21#
發(fā)表于 2025-3-25 03:33:07 | 只看該作者
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發(fā)表于 2025-3-25 11:06:23 | 只看該作者
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發(fā)表于 2025-3-25 14:30:25 | 只看該作者
Process Management In Collaborative Networked Organizations: A Perspective Under The Scope Of Organiprocess management as being an element of Organizational Memory under the scope of Collaborative Networked Organizations (CNOs). The authors argue that the transformations occurring in processes executed by Virtual Organizations are elements of Organizational Memory and shall be stored for future us
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發(fā)表于 2025-3-25 16:04:53 | 只看該作者
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發(fā)表于 2025-3-25 22:35:37 | 只看該作者
A Model For Dynamic Generation Of Collaborative Decision Protocols For Managing The Evolution Of Virer, the VE nature imposes tougher requirements as decisions shall be taken in a distributed and decentralized manner, regarding that members are autonomous and independent. Besides agility, quality is extremely important. This means that such decision-making should be somehow assisted in order to pr
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發(fā)表于 2025-3-26 01:05:17 | 只看該作者
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發(fā)表于 2025-3-26 07:39:27 | 只看該作者
EBXML – Overview, Initiatives and Applications of the standards? modules as well as initiatives concerning its development and adoption. Other frameworks’ efforts on convergence with ebXML are discussed as well as expectations on its place in the future for electronic business.
28#
發(fā)表于 2025-3-26 10:23:26 | 只看該作者
29#
發(fā)表于 2025-3-26 16:22:09 | 只看該作者
Support of Knowledge Creation Process in a Computer-Based COllaborative Systeme key task in trialogical learning is to understand how the “weaker” forms of knowledge are used and made explicit in a meaningful way in collaborative processes. Trialogical learning provides mechanism by which tacit knowledge is conceptualized in collaborative systems. Within the “Knowledge-Practi
30#
發(fā)表于 2025-3-26 19:15:26 | 只看該作者
Efficient Event Handling In Supply Networks Using Q-Learning And K-Means Clusteringnd control processes become more complex. Events in supply networks and their consequences to the partners in the supply network will be hardly to overlook without using computer based decision support systems. This paper describes such a decision support system, learning the rules used to control t
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