情报研究

结构嵌入影响企业竞争情报绩效的机理及实证研究

  • 仝丽娟 ,
  • 仝若贝 ,
  • 张建林 ,
  • 李环
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  • 1 首都师范大学管理学院 北京 100048;
    2 河南科技学院经济管理学院 新乡 453003
仝丽娟(ORCID:000-0002-2298-3584),副研究员,博士;仝若贝(ORCID:0000-0001-9327-3144),副研究员,硕士,E-mail:tongruobei@hist.edu.cn;张建林(ORCID:0000-0001-7910-5099),副教授,硕士;李环(ORCID:0000-0002-7743-9869),高级工程师,学士。

收稿日期: 2019-08-30

  修回日期: 2019-11-26

  网络出版日期: 2020-06-05

基金资助

本文系北京市教委项目"基于社会媒体大数据的谣言传播行为研究"(项目编号:KM201810028021)研究成果之一。

Research on the Mechanism of Structural Embeddedness Influcence on Enterprise Competitive Intelligence Performance

  • Tong Lijuan ,
  • Tong Ruobei ,
  • Zhang Jianlin ,
  • Li Huan
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  • 1 School of Management, Capital Normal University, Beijing 100048;
    2 School of Economic Management, Henan Institute of Science and Technology, Xinxiang 453003

Received date: 2019-08-30

  Revised date: 2019-11-26

  Online published: 2020-06-05

摘要

[目的/意义] 企业的竞争情报活动离不开社会网络。通过探究结构嵌入的形成及其对情报绩效的影响,构建结构嵌入作用情报绩效的机理模型,为丰富竞争情报理论,提升企业的情报战略能力提供支撑。[方法/过程] 以了解和开展竞争情报工作的企业为研究对象,采用调查问卷和结构方程模型拟合等方法,分析结构嵌入维度:网络规模、网络地位和网络密度影响情报绩效的作用机理。[结果/结论] 结果发现,竞争情报工作需要结构嵌入。并且,网络规模扩张对识别、筛选和过滤出所需情报尤为有利。

本文引用格式

仝丽娟 , 仝若贝 , 张建林 , 李环 . 结构嵌入影响企业竞争情报绩效的机理及实证研究[J]. 图书情报工作, 2020 , 64(11) : 57 -66 . DOI: 10.13266/j.issn.0252-3116.2020.11.007

Abstract

[Purpose/significance] Social network is inseparable from enterprise competitive intelligence activity. By exploring the formation of structural embeddedness and its impact on intelligence performance, the mechanism model of structural embeddedness affects intelligence performance is constructed to provide support for enriching competitive intelligence theory and enhancing the intelligence capability of enterprises. [Method/process] This paper took the enterprise that understand and engage in intelligence work as the research object, and used the questionnaire and structural equation model fitting method to analyze the mechanism of network scale,network status and network density affecting intelligence performance. [Result/conclusion] It was found that competitive intelligence work requires structural embeddness. Moreover, network scale expansion is particularly beneficial for identifying, screening and filtering out the needded intelligence.

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