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Titlebook: Innovating in a Learning Community; Emergence of an Open Kai Reimers,Xunhua Guo,Tiantian Zhang Book 2014 The Author(s) 2014 Government acti

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发表于 2025-3-21 20:08:50 | 显示全部楼层 |阅读模式
书目名称Innovating in a Learning Community
副标题Emergence of an Open
编辑Kai Reimers,Xunhua Guo,Tiantian Zhang
视频videohttp://file.papertrans.cn/467/466674/466674.mp4
概述Shows how open information infrastructures can emerge under adversarial conditions.Provides an inside view into a rarely studied industry.Provides a detailed account of government action in China.Incl
丛书名称SpringerBriefs in Digital Spaces
图书封面Titlebook: Innovating in a Learning Community; Emergence of an Open Kai Reimers,Xunhua Guo,Tiantian Zhang Book 2014 The Author(s) 2014 Government acti
描述How do firms jointly develop open information infrastructures? To answer this question, this book draws on the results of a longitudinal research project covering the development of the pharmaceutical distribution industry in China from 2004 to 2012, focusing on the emergence and subsequent evolution of industry-wide information infrastructures. How do firms delimit areas of proprietary innovation in open innovation projects? How do firms coordinate, initiate, negotiate and implement the development of innovative infrastructures? How do processes and practices within firms enable and constrain such collective efforts? - This book provides answers to these questions and draws conclusions regarding the challenges and new capabilities that firms will need in a world in which participation in the building of open information infrastructures becomes a necessary task for commercial organizations.
出版日期Book 2014
关键词Government action; Industry-wide information infrastructures; Information technology; Innovation manage
版次1
doihttps://doi.org/10.1007/978-3-319-05098-0
isbn_softcover978-3-319-05097-3
isbn_ebook978-3-319-05098-0Series ISSN 2193-5890 Series E-ISSN 2193-5904
issn_series 2193-5890
copyrightThe Author(s) 2014
The information of publication is updating

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Kai Reimers,Xunhua Guo,Mingzhi Li,Bin Xie,Tiantian Zhangirements of the state-of-the-art process discovery techniques. Secondly, we show how to move the computation of intermediate data structures to the database engine, to reduce the time required during process discovery. The work presented in this paper is implemented in ProM tool, and a range of expe
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Kai Reimers,Xunhua Guo,Mingzhi Li,Bin Xie,Tiantian Zhanglated behaviors in processes, and apply our technique to other perspectives present in event logs. We have developed a ProM plug-in that exploits efficient algorithms for the discovery of frequent episodes and episode rules. Experimental results based on real-life event logs demonstrate the feasibil
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