图书情报工作 ›› 2021, Vol. 65 ›› Issue (20): 13-22.DOI: 10.13266/j.issn.0252-3116.2021.20.002

• 理论研究 • 上一篇    下一篇

网络信息资源著作权创新生态系统构建及其可靠性研究

李珊1, 张文德2, 曾金晶3   

  1. 1. 福州大学经济与管理学院, 福州 350108;
    2. 福州大学信息管理研究所, 福州 350108;
    3. 福建农林大学图书馆, 福州 350002
  • 收稿日期:2021-04-05 修回日期:2021-07-26 出版日期:2021-10-20 发布日期:2021-10-22
  • 通讯作者: 曾金晶(ORCID:0000-0001-6078-1708),馆员,博士,通讯作者,E-mail:765621957@qq.com
  • 作者简介:李珊(ORCID:0000-0002-7843-3303),博士研究生;张文德(ORCID:0000-0002-3017-9211),教授,博士,博士生导师。
  • 基金资助:
    本文系福建省中青年教师科研课题项目"高校专利信息化的驱动机制及其模式研究"(项目编号:JAT170208)研究成果之一。

Research on the Construction and Reliability of Network Information Resource Copyright Innovation Ecosystem

Li Shan1, Zhang Wende2, Zeng Jinjing3   

  1. 1. School of Economics & Management, Fuzhou University, Fuzhou 350108;
    2. Institute of Information Management, Fuzhou University, Fuzhou 350108;
    3. Fujian Agriculture and Forestry University Library, Fuzhou 350002
  • Received:2021-04-05 Revised:2021-07-26 Online:2021-10-20 Published:2021-10-22

摘要: [目的/意义] 新形势下推进网络信息资源著作权创新生态系统建设并评估其可靠性,有利于激活著作权活动的创新活力,引导网络版权产业的可持续发展。[方法/过程] 首先,构建网络信息资源著作权创新生态统演化模型,并提出一种基于Markov过程的系统可靠性评估方法并给出相应的解析方程式。然后,利用贝叶斯网络模型计算运行状态转移率的基础数据,求解系统的瞬态可用度,同时通过研究稳态可用度探索影响网络信息资源版权业态发展的关键因素。最后,以网络视频资源著作权创新生态系统为例验证模型的适用性。[结果/结论] 网络视频资源著作权创新生态系统运行过程中,在254h达到演化的稳定值0.758 0。其中,创新投入风险对网络信息资源版权业态发展潜在危害最为严重,创新环境风险、著作权侵权风险次之,技术风险、融合创新风险、网络信息资源风险再次之,中止调整率和定期调整率对恢复系统的稳定性具有明显的修正作用。基于此仿真结果,提出促进网络视频版权产业发展的几点策略。

关键词: 网络信息资源, 著作权, 创新生态系统, 创新风险, Markov过程, 贝叶斯网络

Abstract: [Purpose/significance] In the new situation, advancing the construction of an innovation ecosystem for network information resource copyright and evaluating its reliability is conducive to promoting the creative vitality of copyright activities and guiding the sustainable development of network copyright industry. [Method/process] Firstly, this paper constructed the evolution model of network information resource copyright innovation ecosystem, proposed a system reliability evaluation method based on Markov process, and gave the corresponding analytical equations. After that, the Bayesian network model was used to calculate the basic data of the transition rate of each operating state, and the transient availability of the system was solved. Meanwhile, studying the steady availability was to explore the key factors of affecting the development of the copyright industry of network information resources. Finally, the applicability of the model was verified by an example which was the network video resource copyright innovation ecosystem. [Result/conclusion] During the operational process of the network video resource copyright innovation ecosystem, it reaches a stable value of 0.7580 at 254 hours. Among them, the innovation investment risk has the most serious potential harm to the development of network information resource copyright industry, followed by innovation environment risk and copyright infringement risk, followed by technology risk, integration innovation risk and network information resource risk, and the suspension adjustment rate and the periodic adjustment rate have obvious corrective effects on the stability of restoring system. Based on the simulation result, several strategies to promote the development of network video copyright industry are put forward.

Key words: network information resources, copyright, innovation ecosystem, innovation risk, Markov process, Bayesian network

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