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Related Concept Videos

Weighted Mean00:57

Weighted Mean

While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
Sustainable Development01:43

Sustainable Development

As the human population continues to grow and use resources, we must be mindful of our planet’s natural limits. Sustainable development provides a pathway to maintain and improve human life now while also ensuring that future generations will have the resources that they need. The long-term success of sustainability efforts rests on understanding the interplay between human actions and ecological systems.
Design Example: Sustainability in Concrete Building01:26

Design Example: Sustainability in Concrete Building

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Methods to Assess Microbial Communities01:19

Methods to Assess Microbial Communities

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Unsoundness of Aggregate due to Volume Change01:26

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Summation Notation01:25

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Aggregating sustainability indicators: beyond the weighted sum.

Hazel V Rowley1, Gregory M Peters, Sven Lundie

  • 1UNSW Water Research Centre, The University of New South Wales, UNSW Sydney, NSW 2052, Australia. h.rowley@unsw.edu.au

Journal of Environmental Management
|July 21, 2012
PubMed
Summary

This study clarifies multi-criteria decision analysis (MCDA) methods for sustainability analysts. It provides guidance on selecting MCDA approaches to reduce subjectivity and uncertainty in environmental decision-making.

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Area of Science:

  • Environmental Science
  • Decision Science

Background:

  • Environmental decision-making often relies on multi-criteria decision analysis (MCDA) to interpret complex environmental data.
  • Subjectivity and uncertainty arise from the diverse MCDA methods for weighting and aggregation.

Purpose of the Study:

  • To clarify the theoretical implications of choosing different MCDA methods.
  • To provide practical guidance for environmental managers on selecting appropriate MCDA approaches.

Main Methods:

  • Systematic examination of methodological decisions in the MCDA process.
  • Analysis of the relationship between MCDA theory and practical application.

Main Results:

  • Improved understanding of how MCDA choices impact results.
  • Framework for aligning MCDA methods with decision-maker needs.

Conclusions:

  • Analysts can better understand MCDA theory-practice links.
  • Enables selection of MCDA methods consistent with specific environmental decision contexts.