图书情报工作 ›› 2020, Vol. 64 ›› Issue (8): 13-23.DOI: 10.13266/j.issn.0252-3116.2020.08.002

• 理论研究 • 上一篇    下一篇

大数据驱动的图书馆风险治理:内涵及框架

赵发珍1,2   

  1. 1 兰州大学管理学院 兰州 730000;
    2 兰州大学图书馆 兰州 730000
  • 收稿日期:2019-05-28 修回日期:2019-10-29 出版日期:2020-04-20 发布日期:2020-04-20
  • 作者简介:赵发珍(ORCID:0000-0002-2108-0674),馆员,博士研究生,E-mail:zhaofzh@lzu.edu.cn。
  • 基金资助:
    本文系2017年教育部哲学社会科学研究重大课题攻关项目"大数据驱动的城市公共安全风险研究"(项目编号:16JZD023)研究成果之一。

Big Data Driven Library Risk Governance: Connotation and Framework

Zhao Fazhen1,2   

  1. 1 School of Management, Lanzhou University, Lanzhou 730000;
    2 Library of Lanzhou University, Lanzhou 730000
  • Received:2019-05-28 Revised:2019-10-29 Online:2020-04-20 Published:2020-04-20

摘要: [目的/意义] 现代风险社会对图书馆行业发展及其管理带来了严峻的挑战,传统的图书馆风险管理模式已不适应当前图书馆的发展,亟需探索新的风险治理框架。[方法/过程] 分析图书馆风险治理研究与实践过程中存在的概念界定不清晰、研究方法滞后、管理主体单一等不足。在风险社会理论及治理理论与方法的指导下,以大数据驱动为视角,提出图书馆风险治理的内涵,并分析图书馆风险治理的大数据应用需求、治理框架构建以及在此治理框架下图书馆风险治理内容、治理流程。[结果/结论] 针对图书馆领域存在的实体性风险(建筑、公共场所、自然灾害)、具体业务发展中的风险(资源建设、服务创新、技术应用与管理)以及外界环境(社会、技术、政策等的发展)所带来的行业风险,大数据分析能够有效地识别、预测、治理所面临的风险,为图书馆风险治理提供有效的技术工具。

关键词: 大数据, 图书馆风险, 风险治理, 数据驱动

Abstract: [Purpose/significance] Modern risk society has brought severe challenges to the development and management of the library industry. The traditional risk management model of the library has not adapted to the development of the current library, and it is urgent to explore a new risk governance framework. [Method/process] It analyzed the shortcomings in the research and practice of library risk governance. Under the guidance of risk society theory and governance theory and method, this paper put forward the connotation of library risk management from the perspective of big data drive, and analyzed the big data application requirements, governance framework construction and under the governance framework of library risk governance. Library risk management content, governance process. [Result/conclusion] For the physical risks (buildings, public places, natural disasters) in the library field, risks in specific business development (resource construction, service innovation, technology application and management) and the external environment (social, technology, The industry risks brought about by the development of policies, etc), big data analysis can effectively identify, predict and manage the risks faced, and provide effective technical tools for library risk management.

Key words: big data, library risk, risk governance, data driven

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