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工程化视角下的企业共享服务中心的情报机能研究
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  • 英文篇名:Research on Intelligence Enginery of Enterprise Shared Service Center under the Engineering Thinking Style
  • 作者:王娟
  • 英文作者:Wang Juan;School of Information Management,Wuhan University;
  • 关键词:情报工程 ; 共享服务中心 ; 情报机能 ; 情报服务 ; 竞争情报
  • 英文关键词:enterprise;;intelligence engineering;;shared service center;;intelligence enginery;;intelligence service;;competitive intelligence
  • 中文刊名:XDQB
  • 英文刊名:Journal of Modern Information
  • 机构:武汉大学信息管理学院;
  • 出版日期:2019-05-01
  • 出版单位:现代情报
  • 年:2019
  • 期:v.39;No.335
  • 语种:中文;
  • 页:XDQB201905017
  • 页数:8
  • CN:05
  • ISSN:22-1182/G3
  • 分类号:125-132
摘要
[目的/意义]情报服务是大数据时代企业共享服务中心增值服务的重要内容,工程化思维下的共享服务中心的情报机能研究,不仅拓展了现代企业共享服务中心理论研究领域和实践创新视野,对共享服务模式下的企业竞争情报理论与实践的发展也具有重要意义。[方法/过程]以"数据资源+工具方法+专家智慧"的情报研究方法论为导向,对企业共享服务中心情报机能问题进行了系统性研究,包括企业共享服务中心情报机能的工程化流程要素分析,基于情报流的企业共享服务中心运行机制模型与工程化要素协同情报机能模型构建。[结果/结论]在大数据时代,企业共享服务中心情报机能的发挥依赖于多源数据融合支持、先进方法工具协同支撑、专家智慧的汇集参与。目前企业共享服务中心情报服务研究不足,应从工程化视角强化企业共享服务中心情报机能,助力企业管理和战略决策,促进共享服务中心的转型升级。
        [Purpose/Significance]Intelligence service is an important part of the value-added service of the enterprise shared service center in the big data era.The research on the intelligence enginery of enterprise shared service center under the engineering thinking style can extend the theoretical research field and practice innovation vision of the modern enterprise shared service center.At the same time,it also has important significance for the development of corporate competitive intelligence theory and practice under the shared service mode.[Methods/Procedures]The paper presented a systematic study on the intelligence enginery of enterprise shared service center with the intelligence engineering-oriented paradigm which contained three parts of data resources,tools and methods,and expert wisdom.The main contents included a factor analysis of enterprise shared service center intelligence enginery and the model construction of operation mechanism of enterprise shared service center and collaborative intelligence enginery model based on the intelligence flow.[Results/Conclusion]In big data era,the intelligence enginery of enterprise shared service center relied on multi-source data fusion support,collaborative support of advanced method tools,and the participation of expert wisdom.At present,the research on intelligence service of enterprise shared service center was insufficient.It is necessary to strengthen their intelligence enginery from an engineering perspective in order to assist enterprise strategic decision-making and promote the transformation and upgrading of shared service center.
引文
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