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

Bibliographic Details
Main Author: Lemke, Claudia.
Format: eBook
Language:English
Published: Wiesbaden : Springer Fachmedien Wiesbaden GmbH, 2021.
Edition:1st ed.
Series:Sustainable Management, Wertschöpfung und Effizienz Series
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Preface
  • Foreword
  • Acknowledgement
  • Table of contents
  • List of abbreviations
  • List of figures
  • List of tables
  • List of equations
  • List of symbols
  • Chapter 1 Introduction
  • 1.1 Background and motivation
  • 1.2 Research question and aim of the dissertation
  • 1.3 Procedure
  • Chapter 2 Conceptual framework of sustainable development
  • 2.1 Definition of sustainable development and sustainability
  • 2.2 The three contentual domains of sustainable development
  • 2.2.1 Environmental protection
  • 2.2.2 Social development
  • 2.2.3 Economic prosperity
  • 2.2.4 Integration of the three contentual domains
  • 2.3 Stakeholders and change agents of sustainable development
  • 2.3.1 The multilevel perspective
  • 2.3.2 Corporate sustainability
  • 2.3.3 Political goal setting: The United Nations's (UN) Sustainable Development Goals (SDGs)
  • 2.3.4 Sustainability science
  • 2.4 Summary
  • Chapter 3 Measuring and assessing contributions to sustainable development
  • 3.1 Principles of sustainable development measurement and assessment methods
  • 3.2 Overview of quantitative sustainable development assessment methods
  • 3.3 Sustainable development indicators
  • 3.3.1 Corporate indicator frameworks
  • 3.3.2 Meso-level indices
  • 3.3.3 Macro-level indices
  • 3.4 Summary
  • Chapter 4 Methodology
  • 4.1 Overview of sustainable development indices' calculation steps and methodological requirements
  • 4.2 Methodological evaluation of sustainable development indices
  • 4.3 Methodology of the Multilevel Sustainable Development Index (MLSDI)
  • 4.3.1 Collection of sustainable development key figures
  • 4.3.2 Preparation of sustainable development key figures
  • 4.3.2.1 Meso-level transformation to macro-economic categories
  • 4.3.2.2 Macro-level transformation of statistical classifications
  • 4.3.3 Imputation of missing values.
  • 4.3.3.1 Characterisation of missing values
  • 4.3.3.2 Single time series imputation: Various methods depending on the missing data pattern
  • 4.3.3.3 Multiple panel data imputation: Amelia II algorithm
  • 4.3.3.4 Statistical tests of model assumptions
  • 4.3.4 Standardisation to sustainable development key indicators
  • 4.3.5 Outlier detection and treatment
  • 4.3.5.1 Characterisation of outliers
  • 4.3.5.2 Univariate Interquartile Range (IQR) method
  • 4.3.6 Scaling
  • 4.3.6.1 Characterisation of scales
  • 4.3.6.2 Rescaling between ten and 100
  • 4.3.7 Weighting
  • 4.3.7.1 Overview of weighting methods
  • 4.3.7.2 Multivariate statistical analysis: Principal Component Analysis (PCA)
  • 4.3.7.3 Multivariate statistical analysis: Partial Triadic Analysis (PTA)
  • 4.3.7.4 Information theory: Maximum Relevance Minimum Redundancy Backward (MRMRB) algorithm
  • 4.3.7.5 Statistical tests of model assumptions
  • 4.3.8 Aggregation
  • 4.3.9 Sensitivity analyses
  • 4.4 Summary and interim conclusion
  • Chapter 5 Empirical findings
  • 5.1 Data base, objects of investigation, and time periods
  • 5.2 Sustainable development key figures
  • 5.2.1 Collection and preparation of sustainable development key figures
  • 5.2.2 Imputation of missing values
  • 5.3 Sustainable development key indicators
  • 5.3.1 Alignment of the Global Reporting Initiative (GRI) and the Sustainable Development Goal (SDG) disclosures
  • 5.3.1.1 Environmental sustainable development key indicators
  • 5.3.1.2 Social sustainable development key indicators
  • 5.3.1.3 Economic sustainable development key indicators
  • 5.3.2 Summary statistics of the sustainable development growth indicators
  • 5.3.3 Outlier detection and treatment
  • 5.3.4 Empirical findings of the cleaned and rescaled sustainable development key indicators
  • 5.3.4.1 Summary statistics.
  • 5.3.4.2 Comparative analysis of the selected branches
  • 5.4 Weighting
  • 5.4.1 The Principal Component (PC) family's eigenvalues and explained cumulative variances
  • 5.4.2 The Maximum Relevance Minimum Redundancy Backward (MRMRB) algorithm's discretisation and backward elimination
  • 5.4.3 Comparative analysis of weights
  • 5.4.4 Statistical tests of the Principal Component (PC) family
  • 5.5 Empirical findings of the four composite sustainable development measures
  • 5.5.1 Summary statistics
  • 5.5.2 Comparative analysis of the selected branches
  • 5.6 Sensitivity analyses
  • 5.7 Summary
  • Chapter 6 Discussion and conclusion
  • 6.1 Implications for research
  • 6.2 Implications for practice
  • 6.3 Limitations and future outlook
  • 6.4 Summary and conclusion
  • Appendix
  • A.1 Statistical classification scheme of economic activities in the European Union (EU)
  • A.2 German health economy's statistical delimitation
  • A.3 Statistical tests of sustainable development key figures
  • A.4 Summary statistics of the sustainable development key indicators
  • A.5 Outlier thresholds of the sustainable development key indicators
  • A.6 Normality tests of z-score scaled sustainable development key indicators
  • A.7 Sensitivities by the four composite sustainable development measures
  • References.

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