高校图书馆大数据智慧墙评价指标体系构建研究  

Research on the Construction of Evaluation Index System for Big Data Smart Wall in University Libraries

作　　者：吴芳 牛麟 Wu Fang;Niu Lin(Library of University of South China,Hengyang,421001)

机构地区：[1]南华大学图书馆,衡阳421001

出　　处：《高校图书馆工作》2024年第2期49-57,共9页Library Work in Colleges and Universities

基　　金：湖南省衡阳市社会科学基金一般项目“衡阳高校图书馆参与衡阳市公共文化服务对策研究”(项目编号:2022C011)的研究成果之一。

摘　　要：大数据智慧墙作为智慧图书馆的重要智慧场景,在实现文化体验中发挥着积极作用。构建一个完整、科学、有效的大数据智慧墙评价指标体系,有助于提升高校图书馆智慧化服务水平。从用户满意度视角出发,以Lib QUAL+TM模型为基础,分析同类产品服务质量的评价指标,结合高校图书馆大数据智慧墙的特点,总结初始评价指标;利用专家调查法、李克特量表法、数学问题的非传统解法,对初始指标进行筛选和验证;最后基于层次分析法计算高校图书馆大数据智慧墙评价指标权重。构建了由4个一级指标与22个二级指标组成的高校图书馆大数据智慧墙评价指标体系,得出在高校图书馆大数据智慧墙建设过程中,需要优先考虑智慧墙的内容,始终坚持为用户提供更为优质的资源与服务的结论。The big data smart wall,as an important intelligent scenario in smart libraries,plays an active role in achieving cultural experiences.Constructing a complete,scientific,and effective evaluation index system for big data smart walls is conducive to advance the level of intelligent services in university libraries.From the perspective of user satisfaction,this study uses the LibQUAL+TM model as a foundation to analyze evaluation indicators of service quality in similar products and summarizes initial evaluation indicators specific to big data smart walls in university libraries.The initial indicators are then screened and validated by using the Delphi method,Likert scales,and unconventional mathematical problem-solving methods.Finally,the weights of the evaluation indicators are calculated using the Analytic Hierarchy Process(AHP).The constructed evaluation index system for big data smart walls in university libraries consists of 4 first-level indicators and 22 second-level indicators.The study concludes that in the construction of big data smart walls in university libraries,priority should be given to the content of the smart wall,consistently providing users with higher-quality resources and services.

关 键 词：高校图书馆 大数据 智慧墙 指标体系 层次分析法 

分 类 号：G250[文化科学—图书馆学]