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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...
|a Accounting and statistical analyses for sustainable development :
|b multiple perspectives and information-theoretic complexity reduction /
|c Claudia Lemke.
|h [recurso electrónico - acceso abierto]
260
|a Berlin :
|b Springer Gabler,
|c 2020
300
|a 1 recurso en línea (294 p.)
490
0
|a Sustainable Management, Wertschöpfung und Effizienz
504
|a Bibliografía: p. 226-263.
505
0
|a Introduction -- Conceptual framework of sustainable development -- Measuring and assessing contributions to sustainable development -- Methodology -- Empirical findings -- Discussion and conclusion.
520
3
|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.
