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作 者:朱明 苏晗 Zhu Ming;Su Han(School of History and Archives,Yunnan University,Kunming 650091)
出 处:《图书情报工作》2023年第23期28-37,共10页Library and Information Service
摘 要:[目的/意义]通过深入调查图书馆仪式活动,有效识别其影响馆员组织认同的路径和因素,为图书馆仪式活动及组织管理研究与实践提供参考依据。[方法/过程]从云南省内选择10所在仪式活动实践方面较为突出的公共图书馆和高校图书馆,并从中选择30位馆员作为本研究的样本数据,通过深度访谈收集资料,采用扎根理论方法分析样本数据,构建新的理论解释框架。[结果/结论 ]研究从仪式实践视角深入考察图书馆仪式活动如何影响馆员组织认同,研究发现:图书馆仪式活动构成要素包括仪式展演、仪式景观和仪式程序。仪式展演会受到群体共识的调节并在身份识别的作用下共同影响馆员的自我认同,仪式景观会受到记忆图式的调节并在场景互动的作用下共同影响馆员的图书馆认同,仪式程序会受到程序理性的调节并在情感凝聚的作用下共同影响馆员的价值认同。馆员的自我认同、图书馆认同、价值认同会共同影响馆员对图书馆的组织认同。[Purpose/Significance]Literature analysis and social network analysis are important ways of knowledge discovery.Based on the dynamic and hierarchical features of knowledge evolution,this paper proposes a knowledge deconstruction and migration path identification method based on dynamic multilayer networks.[Method/Process]Firstly,the hierarchical network deconstruction was determined through equal time segmentation,knowledge element extraction,knowledge network construction and layering.Then,the knowledge migration span was calculated by the common node percentage in single-layer network and Jaccard coefficient,the importance of knowledge elements was determined by Simpson’s diversity index,and the main paths of knowledge migration were filtered.On this basis,the knowledge network was reconstructed to clarify the internal logic among the knowledge elements.In this paper,22,049 papers from 24 journals in information management from 2001 to 2021,were divided into four stages with a three-year interval.CiteSpace software was used for keyword extraction and preliminary statistics,and Pajek software for network stratification and reconstruction on the important paths.[Result/Conclusion]The results show that,in recent years,the information management field has been characterized by subfields centered on the enterprise,e-commerce and user behavior,and information technology and innovation,with information technology being an important connection between the enterprise and the user.Comparing with cluster analysis and time expanded network method,the proposed approach can not only better demonstrate the importance of knowledge elements,but also the reconstructed network shows a more specific and clear logic of knowledge element modules and their internal relationships.
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