A multicriteria approach to ranking Latin-American universities based on region-specific criteria

IF 12.9 1区 管理学 Q1 BUSINESS
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引用次数: 0

Abstract

University rankings have become a widespread tool for assessing and comparing the performance of higher education institutions worldwide. Over time, these rankings have evolved into crucial references for both students and academic institutions when making decisions. Several well-established university rankings, such as the QS and Scimago Ranking, utilize various evaluation criteria to classify universities. However, these criteria may adversely affect universities in different regions, including Latin America. In this study, we aim to address the unique reality of Latin American universities, considering their specific characteristics and challenges. Our focus will be on a comprehensive review of the evaluation criteria used in these two renowned rankings and their impact on the region, including how they influence the performance of universities. We propose a novel ranking model using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to counter these potential biases and regional disparities. This multicriteria optimization approach enables us to evaluate and compare universities based on multiple criteria, considering their similarities to the ideal solution and differences from the anti-ideal solution. By adopting the TOPSIS method, we aim to create a more robust and balanced approach incorporating carefully selected criteria. It allows us to include economic and inclusion criteria often overlooked in conventional rankings. Our study seeks to establish a fairer, more relevant university ranking system tailored to Latin America's needs and aspirations. Our proposed TOPSIS-based model aims to contribute significantly to the ongoing discussions on higher education excellence in Latin America by providing a comprehensive evaluation considering the region's specific circumstances.

基于地区特定标准的拉丁美洲大学排名多标准方法
大学排名已成为评估和比较全球高等教育机构表现的广泛工具。随着时间的推移,这些排名已发展成为学生和学术机构决策时的重要参考。一些成熟的大学排名,如 QS 和 Scimago 排名,利用各种评估标准对大学进行分类。然而,这些标准可能会对包括拉丁美洲在内的不同地区的大学产生不利影响。在本研究中,我们将考虑到拉丁美洲大学的具体特点和挑战,旨在解决其独特的现实问题。我们的重点是全面回顾这两个著名排名所使用的评价标准及其对该地区的影响,包括它们如何影响大学的表现。我们提出了一个新颖的排名模型,利用与理想解相似度排序偏好技术(TOPSIS)来消除这些潜在的偏差和地区差异。这种多标准优化方法使我们能够根据多个标准对大学进行评估和比较,同时考虑它们与理想解决方案的相似性以及与反理想解决方案的差异。通过采用 TOPSIS 方法,我们旨在创建一种更稳健、更平衡的方法,将精心挑选的标准纳入其中。它允许我们纳入传统排名中经常忽略的经济性和包容性标准。我们的研究旨在建立一个更公平、更切合拉丁美洲需求和愿望的大学排名系统。我们提出的基于 TOPSIS 的模型旨在通过提供考虑到该地区具体情况的综合评估,为正在进行的有关拉丁美洲高等教育卓越性的讨论做出重要贡献。
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来源期刊
CiteScore
21.30
自引率
10.80%
发文量
813
期刊介绍: Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.
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