BIBLIOTECA MANUEL BELGRANO - Facultad de Ciencias Económicas - UNC

Imagen de Google Jackets

Accounting and statistical analyses for sustainable development : multiple perspectives and information-theoretic complexity reduction / Claudia Lemke. [recurso electrónico - acceso abierto]

Por: Tipo de material: TextoTextoSeries Sustainable Management, Wertschöpfung und EffizienzDetalles de publicación: Berlin : Springer Gabler, 2020Descripción: 1 recurso en línea (294 p.)ISBN:
  • 9783658332464
Tema(s): Recursos en línea:
Contenidos:
Introduction -- Conceptual framework of sustainable development -- Measuring and assessing contributions to sustainable development -- Methodology -- Empirical findings -- Discussion and conclusion.
Resumen: 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.
Existencias
Tipo de ítem Biblioteca actual Signatura topográfica Estado Fecha de vencimiento Código de barras
Libro electrónico Libro electrónico Biblioteca Manuel Belgrano Recurso en línea (Navegar estantería(Abre debajo)) Disponible

Bibliografía: p. 226-263.

Introduction -- Conceptual framework of sustainable development -- Measuring and assessing contributions to sustainable development -- Methodology -- Empirical findings -- Discussion and conclusion.

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.

No hay comentarios en este titulo.

para colocar un comentario.

Bv. Enrique Barros s/n - Ciudad Universitaria. X5000HRV-Córdoba, Argentina - Tel. 00-54-351-4437300, Interno 48505
Horario de Atención: Lunes a Viernes de 8 a 18

Contacto sobre Información bibliográfica: proinfo.bmb@eco.uncor.edu