通过标准间关联(CRITIC)法了解标准重要性的研究趋势:使用 Tableau 软件对书目数据进行可视化分析

IF 2.1 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE Information Discovery and Delivery Pub Date : 2024-07-10 DOI:10.1108/idd-02-2024-0030
Anath Rau Krishnan
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引用次数: 0

摘要

目的 通过标准间相关性确定标准重要性(CRITIC)是一种多标准决策方法,它通过考虑每条标准固有的对比强度和冲突关系来帮助计算决策标准的权重。本研究旨在进行文献计量分析,以提供有关 CRITIC 方法研究趋势的定量见解。随后,使用 Tableau 软件对收集到的数据进行处理,并使用软件中的特定功能对数据进行格式化,以满足分析要求。数据准备工作完成后,我们根据可描述 CRITIC 研究演变特征的五个参数进行了可视化分析。这些参数包括跨年度研究生产率、主要国家、主要研究人员、主要出版渠道和热门研究课题。研究发现,近年来 CRITIC 的研究呈现出蓬勃发展的趋势,尤其是从 2019 年开始。COVID-19 大流行出乎意料地推动了这一上升趋势,促使研究人员之间开展了出色的合作,他们使用 CRITIC 等多种决策方法,为应对 COVID-19 的挑战提供了数据驱动的解决方案。此外,研究还发现中国和伊朗是 CRITIC 研究的领先国家,彭新东和 Mehdi Keshavarz-Ghorabaee 等著名研究人员主要隶属于这两个国家的机构。关键词分析表明,CRITIC 应用于各种趋势性主题,包括工业 4.0 和环境可持续性。原创性/价值 自 1995 年 CRITIC 方法诞生以来,文献中从未对其进行过文献计量分析,因此科学界对其研究趋势一无所知。据作者所知,本研究是第一项文献计量分析,提供了与 CRITIC 方法相关的研究趋势的定量证据。通过揭示这些趋势,本研究使科学界(包括研究人员和资助机构)能够对涉及 CRITIC 方法的未来研究工作做出明智的决策。
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Research trends in criteria importance through intercriteria correlation (CRITIC) method: a visual analysis of bibliographic data using the Tableau software
Purpose Criteria importance through intercriteria correlation (CRITIC) is a multicriteria decision-making method that helps compute the weights of decision criteria by considering the contrast intensity and conflicting relationships inherent in each criterion. This study aims to conduct a bibliometric analysis to provide quantitative insights into the research trends concerning the CRITIC method. Design/methodology/approach The study assembled bibliographic data from 220 CRITIC-based publications retrieved from the Scopus database. Subsequently, the gathered data were processed using Tableau software, using specific functions within the software to format them to suit the analysis requirements. Following data preparation, a visual analysis was then conducted based on five parameters that can characterize the research evolutions in CRITIC. These parameters include research productivity across years, dominant countries, dominant researchers, dominant publication outlets and popular research topics. Various visualization techniques, such as combined charts, geographical maps and word clouds, were used to draw conclusions for each parameter. Findings The study discovered a burgeoning trend in CRITIC research in recent years, particularly from 2019 onwards. The COVID-19 pandemic unexpectedly contributed to this upward trend, prompting remarkable collaboration among researchers who used diverse decision-making methods, such as CRITIC, to provide data-driven solutions for addressing COVID-19 challenges. Additionally, the study identified China and Iran as the leading countries in CRITIC research, with notable researchers such as Xindong Peng and Mehdi Keshavarz-Ghorabaee predominantly affiliated with institutions in these countries. Keyword analysis indicated the application of CRITIC across various trending topics, including Industry 4.0 and environmental sustainability. Originality/value No bibliometric analyses have been conducted on the CRITIC method in the literature since its inception in 1995, leaving the scientific community clueless about its research trends. To the best of the author’s knowledge, this study serves as the first bibliometric analysis, providing quantitative evidence on the research trends associated with the CRITIC method. By shedding light on these trends, this study enables the scientific community, including researchers and funding agencies, to make informed decisions regarding future research endeavors involving the CRITIC method.
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来源期刊
Information Discovery and Delivery
Information Discovery and Delivery INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
5.40
自引率
4.80%
发文量
21
期刊介绍: Information Discovery and Delivery covers information discovery and access for digital information researchers. This includes educators, knowledge professionals in education and cultural organisations, knowledge managers in media, health care and government, as well as librarians. The journal publishes research and practice which explores the digital information supply chain ie transport, flows, tracking, exchange and sharing, including within and between libraries. It is also interested in digital information capture, packaging and storage by ‘collectors’ of all kinds. Information is widely defined, including but not limited to: Records, Documents, Learning objects, Visual and sound files, Data and metadata and , User-generated content.
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