Common Weight DEA-Based Methodology for Ranking APEC Countries by Considering Sustainable Development Goals Including Decent Work, Income Inequalities, and Gender Equality

2019 3rd International Conference on Data Science and Business Analytics (ICDSBA) Pub Date : 2019-10-01 DOI:10.1109/ICDSBA48748.2019.00028

E. Karsak, Nazli Goker

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引用次数: 1

Abstract

Strategic plan that aims to obtain equality and universality around the world is provided by Agenda for Sustainable Development that is announced by United Nations Development Program. Gender equality and women empowerment are included in 17 sustainable development goals that are determined in 2015 and aimed to be achieved by 2030. This study develops a decision aid that is based on common weight data envelopment analysis (DEA). The proposed decision methodology is employed to conduct performance assessment of Asia-Pacific Economic Cooperation countries considering decent work, gender equality, and reduced income inequalities criteria. The developed model does not need a discriminating parameter for efficiency ranking, guarantees to identify the best performing country in a computationally efficient manner, and provides a realistic dispersion for input and output weights. Ranking results of the developed common weight MCDM-DEA model are compared with basic DEA, and super efficiency DEA models along with the common weight DEA approaches proposed by earlier studies.

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基于共同权重dea的APEC国家排名方法，考虑可持续发展目标，包括体面工作、收入不平等和性别平等

联合国开发计划署宣布的可持续发展议程提供了旨在在世界范围内实现平等和普遍性的战略计划。性别平等和妇女赋权被纳入2015年确定的17项可持续发展目标，这些目标旨在到2030年实现。本研究开发了一种基于通用权重数据包络分析(DEA)的决策辅助工具。所提出的决策方法被用来对亚太经合组织国家进行绩效评估，考虑体面工作、性别平等和减少收入不平等的标准。所开发的模型不需要判别参数来进行效率排序，保证以计算效率的方式识别表现最佳的国家，并提供了一个真实的输入和输出权重的分散。将所建立的通用权重MCDM-DEA模型与基本DEA、超效率DEA模型以及前人提出的通用权重DEA方法的排序结果进行了比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 3rd International Conference on Data Science and Business Analytics (ICDSBA)

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