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Resources 2017, 6(4), 66; doi:10.3390/resources6040066

Developing Composite Indicators for Agricultural Sustainability Assessment: Effect of Normalization and Aggregation Techniques

1
McGill Centre for the Convergence of Health and Economics (MCCHE), McGill University, Montreal, QC H3A 1X9, Canada
2
Department of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 4B6, Canada
3
Centre for International Governance Innovation and the Balsillie School of International Affairs, Waterloo, ON N2L 6C2, Canada
4
School of Environmental Studies, Queen’s University, Kingston, ON K7L 3N6, Canada
*
Author to whom correspondence should be addressed.
Received: 26 August 2017 / Revised: 18 November 2017 / Accepted: 19 November 2017 / Published: 24 November 2017
(This article belongs to the Special Issue Sustainability Indicators for Environment Management)
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Abstract

The assessment of the sustainability of agricultural systems is multidimensional in nature and requires holistic measures using indicators with different measurements and units reflecting social, economic, and environmental aspects. To simplify the assessment process, various indicators have different units, and measurements are grouped under broad indicator heads, and normalization and/or transformation processes are carried out in order to aggregate them. In this study, a total of 50 indicators from agricultural sustainability categories of productivity, stability, efficiency, durability, compatibility, and equity are employed to investigate which normalization technique is the most suitable for further mathematical analysis for developing a final composite indicator. To understand the consistency and quality of normalization measurement techniques and compare the benefits and drawbacks of the various selected normalization processes, the indicators of agricultural sustainability are considered. Each of the different techniques for normalization has advantages and drawbacks. This study shows that the proportionate normalization and hybrid aggregation rules of the arithmetic mean and the geometric mean are appropriate for the selected data set, and that this technique has a wider applicability for developing composite indicators for agricultural sustainability assessment. View Full-Text
Keywords: composite indicators; normalization; aggregation; agricultural sustainability; coastal agriculture of Bangladesh composite indicators; normalization; aggregation; agricultural sustainability; coastal agriculture of Bangladesh
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Talukder, B.; W. Hipel, K.; W. vanLoon, G. Developing Composite Indicators for Agricultural Sustainability Assessment: Effect of Normalization and Aggregation Techniques. Resources 2017, 6, 66.

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