کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
387371 660901 2010 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Data aggregation in constructing composite indicators: A perspective of information loss
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Data aggregation in constructing composite indicators: A perspective of information loss
چکیده انگلیسی

Composite indicators (CIs) have been widely accepted as a useful tool for performance comparisons, public communication and decision support in a wide spectrum of fields, e.g. economy, environment and knowledge/information/innovation. The quality and reliability of a CI depend heavily on the underlying construction scheme where data aggregation is a major step. This paper analyzes the data aggregation problem in CI construction from the point of view of information loss. Based on the “minimum information loss” principle, the distance-based and entropy-based aggregation models for constructing CIs are presented. The entropy-based aggregation model has also been extended to deal with qualitative data. It is shown that the proposed aggregation models have close relationships with several popular MCDA aggregation methods in CI construction, although our proposed models seem to be more flexible while more complex in application. Two case studies are presented to illustrate the use of the proposed aggregation models.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 37, Issue 1, January 2010, Pages 360–365
نویسندگان
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