Accounting and Statistical Analyses for Sustainable Development Multiple Perspectives and Information-Theoretic Complexity Reduction

In this Open Access publication Claudia Lemke develops a comprehensive Multi-Level Sustainable Development Index (MLSDI) that is applicable to micro, meso, and macro objects by conducting methodological and empirical research. Multi-level comparability is crucial because the Sustainable Development...

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Bibliographic Details
Main Author: Lemke, Claudia
Format: eBook
Language:English
Published: Springer Nature 2021
Series:Sustainable Management, Wertschöpfung und Effizienz
Subjects:
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
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520 |a In this Open Access publication Claudia Lemke develops a comprehensive Multi-Level Sustainable Development Index (MLSDI) that is applicable to micro, meso, and macro objects by conducting methodological and empirical research. Multi-level comparability is crucial because the Sustainable Development Goals (SDGs) at macro level can only be achieved if micro and meso objects contribute. The author shows that a novel information-theoretic algorithm outperforms established multivariate statistical weighting methods such as the principal component analysis (PCA). Overcoming further methodological shortcomings of previous sustainable development indices, the MLSDI avoids misled managerial and political decision making.