Constructing Composite Indicators with Collective Choice and Interval-Valued TOPSIS: The Case of Value Measure
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Constructing Composite Indicators with Collective Choice and Interval‑Valued TOPSIS: The Case of Value Measure Yelin Fu1,2 · Xiongtianrui Kong3 · Hao Luo3 · Lean Yu4 Accepted: 22 June 2020 © Springer Nature B.V. 2020
Abstract This paper is concerned with proposing a new mechanism to re-construct the published composite indicators that are conventionally aggregated in terms of equal weighting scheme, by means of taking all possible preferences among the indicators into account. Regarding to each preference, we apply a sophisticated mathematical transformation to formulate an interval metric. Inspired by the collective choice theory that integrates individual preference into social preference, an interval decision matrix is therefore formulated with preference as column. An interval-valued TOPSIS procedure in conjunction with Shannon entropy objective weights is applied to re-build composite indicators. The proposed methodology is illustrated by modifying the value measure of health systems. The Spearman’s rank correlation coefficients between Access, Satisfaction, Efficiency and two versions of value measure are calculated to perform the comparisons and demonstrate the superiority of our methodology. Keywords Composite indicators · Collective choice · Interval-valued TOPSIS · Shannon entropy weights · Value measure
* Xiongtianrui Kong [email protected] Yelin Fu [email protected] Hao Luo [email protected] Lean Yu [email protected] 1
School of Intelligent Systems Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai, China
2
Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
3
Collaborative Research Centre for Supply Chain Innovation, Department of Transportation Economy and Logistics Management, College of Economics, Shenzhen University, Shenzhen, China
4
School of Economics and Management, Beijing University of Chemical Technology, Beijing, China
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Y. Fu et al.
1 Introduction A composite indicator is typically constructed when individual indicators are compiled into a single index, based upon an underlying model of the multidimensional concept that is being measured (Nardo et al. 2005). Arisen in economy, society, globalization, environment, innovation and technology areas, composite indicators are becoming increasingly acknowledged as an efficacious instrument for aggregating complicated and multidimensional concepts like human development, well-being, welfare, environmental sustainability, technology and others. Because of the prominent feature of providing a comprehensive viewpoint on a phenomenon that cannot be captured by only a single indicator, composite indicator has been widely recognized as a mechanism for performance assessment, benchmarking, ranking, policy monitoring and public communication (Zhou et al. 2007; Becker et al. 2017). By doing so, composite indicator is often simpler to implement and interpret by policy makers, the media and the general public. As noted in previ
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