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将层次分析法研究映射到可持续发展目标:文献计量学与社会网络分析。

Mapping analytical hierarchy process research to sustainable development goals: Bibliometric and social network analysis.

作者信息

Sreenivasan Aswathy, Suresh M, Nedungadi Prema, R Raghu Raman

机构信息

Amrita School of Business, Amrita Vishwa Vidyapeetham, Coimbatore, 641112, India.

Amrita School of Computing, Amritapuri, Amrita Vishwa Vidyapeetham, Kollam, Kerala, India.

出版信息

Heliyon. 2023 Aug 10;9(8):e19077. doi: 10.1016/j.heliyon.2023.e19077. eCollection 2023 Aug.

Abstract

The drive to achieve the Sustainable Development Goals (SDGs) becomes more urgent as the 2030 deadline draws near, increasing research in various sectors. Nevertheless, studies that systematically map Analytical Hierarchy Process (AHP) publications with the SDGs need to be more conspicuously lacking. Our study adds a new perspective to the field by creatively bridging this knowledge gap using the Elsevier SDG Mapping Initiative. To find research clusters, trends, and themes linked to SDGs and their connection to environmental sustainability, we thoroughly analyzed 29,897 publications from 2012 to 2022. The analysis showed that SDG 15, SDG 7, SDG 12, SDG 13, and SDG 11 were the top five SDGs, with an environmental focus among the 17 SDGs. These top SDGs had many clusters connected to them, illustrating various sustainability-related problems. The study also looked at connections between SDGs, the nations with the highest rates of productivity, the top contributors, and the journals with the highest citation counts. We discovered three separate SDG clusters using co-occurrence network analysis, each representing a different SDG. We discovered relevant SDGs using Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis and centrality indicators like eigenvector and betweenness. This novel method for publishing analysis combines an AHP focus that aligns with the SDGs with social network analysis and centrality metrics. Our research advances knowledge of how the AHP technique can assess initiatives supporting the SDGs. We offer essential insights into prioritizing sustainable development measures by identifying research clusters, trends, and issues related to environmental sustainability. This study highlights the subject's most important SDGs, productive nations, helpful organizations, and significant journals.

摘要

随着2030年期限临近,实现可持续发展目标(SDGs)的紧迫性日益增加,各领域的研究也在增多。然而,系统梳理与可持续发展目标相关的层次分析法(AHP)出版物的研究却明显不足。我们的研究通过爱思唯尔可持续发展目标映射计划创造性地弥合这一知识差距,为该领域增添了新视角。为了找到与可持续发展目标相关的研究集群、趋势和主题及其与环境可持续性的联系,我们全面分析了2012年至2022年的29,897篇出版物。分析表明,可持续发展目标15、可持续发展目标7、可持续发展目标12、可持续发展目标13和可持续发展目标11是17个可持续发展目标中排名前五的目标,且都聚焦于环境。这些首要的可持续发展目标有许多与之相关的集群,说明了各种与可持续性相关的问题。该研究还考察了可持续发展目标、生产率最高的国家、主要贡献者以及被引频次最高的期刊之间的联系。我们使用共现网络分析发现了三个不同的可持续发展目标集群,每个集群代表一个不同的可持续发展目标。我们使用交叉影响矩阵乘法应用于分类分析(MICMAC)以及特征向量和中介中心性等中心性指标发现了相关的可持续发展目标。这种新颖的出版分析方法将与可持续发展目标一致的层次分析法重点与社会网络分析和中心性指标相结合。我们的研究推进了关于层次分析法技术如何评估支持可持续发展目标的举措的知识。我们通过识别与环境可持续性相关的研究集群、趋势和问题,为优先考虑可持续发展措施提供了重要见解。这项研究突出了该主题中最重要的可持续发展目标、有生产力的国家、有帮助的组织和重要的期刊。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/938c/10457455/a35cd64c37c4/gr1.jpg

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