Accounting and Statistical Analyses for Sustainable Development : Multiple Perspectives and Information-Theoretic Complexity Reduction
Accounting and Statistical Analyses for Sustainable Development : Multiple Perspectives and Information-Theoretic Complexity Reduction
- Springer Nature 2021
- 1 electronic resource (31 p.)
Open Access
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.
Creative Commons
978-3-658-33246-4
10.1007/978-3-658-33246-4
Environmental Economics
Open Access
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.
Creative Commons
978-3-658-33246-4
10.1007/978-3-658-33246-4
Environmental Economics