Evaluation index system and methodology for actively responding to ageing population

Si-bo Yang, Ai-hua Li, Guijun Li
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引用次数: 1

Abstract

Ageing population is a challenge faced by the global community. According to international standards for measuring ageing society, China has entered the ageing society since 2000. Currently, actively responding to ageing population has become one of China's national strategies. Increasingly, actively responding to ageing population is gaining greater attention, but there lacks a comprehensive evaluation index system and model. Based on China's real situations, we scientifically and comprehensively construct an evaluation index system for actively responding to ageing population, using source statistical surveys, social tracking surveys and other multi-source heterogeneous data. Best-Worst Method (BWM) and K-means clustering algorithm are used here to evaluate ageing population measuring nationwide with a scientific and comprehensive index system. This paper also analyses and evaluates the measurement taken by 31 districts in China, thus carrying both theoretical and practical implications. With the emergence of big data for government administration, the rigor of the evaluation outcome will enhance.
积极应对人口老龄化的评价指标体系与方法
人口老龄化是全球社会共同面临的挑战。按照国际老龄化社会的衡量标准,中国从2000年开始进入老龄化社会。当前,积极应对人口老龄化已成为中国的国家战略之一。积极应对人口老龄化日益受到重视,但缺乏全面的评价指标体系和模型。结合中国实际,运用源统计调查、社会跟踪调查等多源异构数据,科学、全面地构建积极应对人口老龄化的评价指标体系。本文采用Best-Worst Method (BWM)和K-means聚类算法对全国人口老龄化测度进行评价,建立科学、全面的指标体系。本文还对中国31个地区所采取的措施进行了分析和评价,从而具有理论和实践意义。随着政府管理大数据的出现,评估结果的严谨性将会提高。
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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