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作 者:苏玲 娄策群[1,2] 莫富传[1,2] SU Ling;LOU Ce-qun;MO Fu-chuan(School of Information Management,Central China Normal University,Wuhan 430019,China;E-Commerce Research Center of Hubei Province,Central China Normal University,Wuhan 430079,China)
机构地区:[1]华中师范大学信息管理学院,湖北武汉430079 [2]华中师范大学湖北省电子商务研究中心,湖北武汉430079
出 处:《情报科学》2020年第4期17-22,共6页Information Science
摘 要:【目的/意义】构建信息生态环境能力体系,剖析信息生态环境因子之间关系及其协调变化所引起的环境和社会效应,为后续的信息生态环境研究开发新的研究思路,提供环境质量与管理的新框架,从而推动信息生态环境的健康和可持续发展。【方法/过程】从系统论的角度,基于自然生态环境与信息生态环境之间的共性,明确信息生态环境在社会环境中的定位与特征,从能力与系统论的视角凝练出信息生态环境的能力体系,并分析彼此之间的关联互动。【结果/结论】信息生态环境能力体系由承载力与影响力构成,二者之间相互关联,承载力为基础,影响力为外在表现,而信息人对承载力与影响力起着重要的调节作用。信息生态环境的质量标准与监管、动态演进视角的环境动态评价、优化路径以及相关实证研究是信息生态研究的重要方向。【Purpose/significance】The ability system of information ecological environment is constructed to analyze the relationship between information ecological environment factors and the environmental and social effects caused by their coordinated changes, so as to develop new research ideas for the information ecological environment research and provide a new framework for environmental quality and management, promote the healthy and sustainable development of information ecological environment.【Method/process】From the perspective of system theory, and based on the commonality between natural ecological environment and information ecological environment, this paper refines the characteristics of information ecological environment in social environment,and then constructs the capability system of information ecological environment,analyzes the interactions between each capability.【Result/conclusion】The capability system of information ecological environment consists of bearing capacity and influence. Bearing capacity and influence are related to each other, the bearing capacity is the basis, the influence is the performance,and the information people play an important role in regulating bearing capacity and influence.The quality standard and supervision of information ecological environment, dynamic evaluation of environment from the perspective of dynamic evolution, optimization path and relevant empirical research are feasible directions in future information ecological research.
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