xvi
Indicators and Partial Orders – An Introduction
Indicators in Social Sciences
The area of social science is the subject of two chapters, where one chapter focuses
on the main motivations (see M. Fattore and A. Arcagni, p. 219) for applying
partial order theory in the statistical analysis of socio-economic data, whereas the
second chapter demonstrates the use of partial order methodology to an analysis of
subjective well-being data from a European harmonized official statistical survey
based on indicators for life satisfaction, meaning of life and emotional status (See
L.S. Alaimo and P. Conigliaro, p. 243).
Software
One of the most popular software packages for studying partial ordering is the
PyHasse. The package contains today more than 100 specialized modules, many of
which are developed for specific purposes. However, it has been argued that PyHasse
constitutes as a tool for ‘connoisseurs’. Hence, web-based versions of PyHasse were
developed (See R. Bruggemann et al., p. 291). However, they include only a limited
number of modules.
However, other approaches to ranking are available, e.g., the Deep Ranking
Analysis by Power Eigenvectors (DRAPE), which is illustrated in a chapter by a
study of the sustainability of 154 countries based on 21 human, environmental and
economic well-being criteria (See C. Valsecchi and R. Todeschini, p. 267).
Schwandorf, Germany
Rainer Bruggemann
Roskilde, Denmarks
L. Carlsen
References
Agent based modelling. Wikipedia, https://en.wikipedia.org/wiki/Agent-based_model. Assessed
17.05.2020.
Barilla. (2019). Food sustainability Index. A study on global food sustainability. https//
www.barillacfn.com/en/food_sustainability_index
Brans, J. P., & Vincke, P. H. (1985). A preference ranking organisation method (the PROMETHEE
method for multiple criteria decision – Making). Management Science, 31, 647–656.
Bruggemann, R., & Carlsen, L. (2020). The UN Sustainable Development Goal No. 7, Sustainable
energy. Ranking of EU countries in: Simulation in Umwelt- und Geowissenschaften, Workshop
2020, J. Wittmann, ed., ASIM-Mitteilung AM 173, 29–47.
Bruggemann, R., & Drescher-Kaden, U. (2003). Einführung in die modellgestützte Bewertung
von Umweltchemikalien – Datenabschätzung, Ausbreitung, Verhalten, Wirkung und Bewertung.
Berlin: Springer.
Bruggemann, R., & Patil, G. P. (2011). Ranking and prioritization for multi-indicator systems -
introduction to partial order applications. New York: Springer.
Indicators and Partial Orders – An Introduction
Indicators in Social Sciences
The area of social science is the subject of two chapters, where one chapter focuses
on the main motivations (see M. Fattore and A. Arcagni, p. 219) for applying
partial order theory in the statistical analysis of socio-economic data, whereas the
second chapter demonstrates the use of partial order methodology to an analysis of
subjective well-being data from a European harmonized official statistical survey
based on indicators for life satisfaction, meaning of life and emotional status (See
L.S. Alaimo and P. Conigliaro, p. 243).
Software
One of the most popular software packages for studying partial ordering is the
PyHasse. The package contains today more than 100 specialized modules, many of
which are developed for specific purposes. However, it has been argued that PyHasse
constitutes as a tool for ‘connoisseurs’. Hence, web-based versions of PyHasse were
developed (See R. Bruggemann et al., p. 291). However, they include only a limited
number of modules.
However, other approaches to ranking are available, e.g., the Deep Ranking
Analysis by Power Eigenvectors (DRAPE), which is illustrated in a chapter by a
study of the sustainability of 154 countries based on 21 human, environmental and
economic well-being criteria (See C. Valsecchi and R. Todeschini, p. 267).
Schwandorf, Germany
Rainer Bruggemann
Roskilde, Denmarks
L. Carlsen
References
Agent based modelling. Wikipedia, https://en.wikipedia.org/wiki/Agent-based_model. Assessed
17.05.2020.
Barilla. (2019). Food sustainability Index. A study on global food sustainability. https//
www.barillacfn.com/en/food_sustainability_index
Brans, J. P., & Vincke, P. H. (1985). A preference ranking organisation method (the PROMETHEE
method for multiple criteria decision – Making). Management Science, 31, 647–656.
Bruggemann, R., & Carlsen, L. (2020). The UN Sustainable Development Goal No. 7, Sustainable
energy. Ranking of EU countries in: Simulation in Umwelt- und Geowissenschaften, Workshop
2020, J. Wittmann, ed., ASIM-Mitteilung AM 173, 29–47.
Bruggemann, R., & Drescher-Kaden, U. (2003). Einführung in die modellgestützte Bewertung
von Umweltchemikalien – Datenabschätzung, Ausbreitung, Verhalten, Wirkung und Bewertung.
Berlin: Springer.
Bruggemann, R., & Patil, G. P. (2011). Ranking and prioritization for multi-indicator systems -
introduction to partial order applications. New York: Springer.