| 钟元贵 陈 峰.贵州省大数据资源开发利用的竞争情报解决方略[J].中国科技资源导刊,2017,(2):68~74 |
| 贵州省大数据资源开发利用的竞争情报解决方略 |
| On the Strategy Oriented Competitive Intelligence for Big Data Resources Development andUtilization in Guizhou Province |
| 投稿时间：2016-11-18 |
| DOI： |
| 中文关键词: 竞争情报；竞争情报应用研究；竞争情报服务；大数据；资源开发利用；竞争情报用户需求；解决方略；
贵州省 |
| 英文关键词: competitive intelligence, applied research on competitive intelligence, competitive intelligence
service, big data, resources development and utilization, competitive intelligence user demand, strategy,
Guizhou province |
| 基金项目: |
| 作者 | 单位 | | 钟元贵 陈 峰 | 1. 中国科学技术信息研究所，北京 100038；2. 中共贵州省委政策研究室，贵州贵阳 550002 |
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| 全文下载次数: 1867 |
| 中文摘要: |
| 本文旨在从贵州战略全局顶层设计和提出具有可操作性举措的双重角度，思考求解推动贵州发展竞争情报与
促进大数据产业应用交互促进、实现可持续发展的战略和举措问题，这既是已有竞争情报和大数据资源开发利用领域研
究的拓展深化，也是基于求解现实工作问题的思考研究。通过文献资料研究、专家组讨论、专项调研、代表性竞争情报
用户需求访谈相结合的方法，研究贵州大数据资源开发利用的竞争情报解决方略的主要问题。提出竞争情报解决方略：
在确立正确认知基础上，从系统工程顶层设计和竞争情报系统构建视角，确定指导思想和总体目标，进行组织 |
| 英文摘要: |
| From the angle of both global strategy and top-level design of Guizhou province of China, studies on
strategy and methods about promoting both competitive intelligence work and big data resources development and
utilization interactively, will extend the new research field both in competitive intelligence and big data resources
development and utilization domain ,and is significant for both academic research domain and practical work.
Four kinds of research methods including literature research, expert group discussion, special investigation and
interview on typical users in competitive intelligence were using in the studies. The main points of conclusion about
the strategy oriented competitive intelligence for big data resources development and utilization are: setting up the
correct cognition, guiding ideology, and overall goal; establishing a special organization that play multiple roles
including pilot, research institute, professional personnel training institution, model, demonstrator and propagandist;
promoting more and more competitive intelligence best practice units emerging, and promoting sustainablely both
competitive intelligence work and big data resources development and utilization interactively in Guizhou province. |
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