The use of multi-criteria decision analysis to tackle waste management problems: a literature review

2013 ◽  
Vol 31 (2) ◽  
pp. 115-129 ◽  
Author(s):  
Charisios Achillas ◽  
Nicolas Moussiopoulos ◽  
Avraam Karagiannidis ◽  
Georgias Banias ◽  
George Perkoulidis
Keyword(s):  
Literature Review ◽  
Waste Management ◽  
Decision Analysis ◽  
Multi Criteria Decision Analysis ◽  
Management Problems

Life Cycle Assessment and Multi-criteria Decision Analysis: Selection of a strategy for domestic food waste management in Rio de Janeiro

2017 ◽  
Vol 143 ◽  
pp. 744-756 ◽  
Author(s):  
Ana Carolina Maia Angelo ◽  
Anna Bernstad Saraiva ◽  
João Carlos Namorado Clímaco ◽  
Carlos Eduardo Infante ◽  
Rogerio Valle
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Waste Management ◽  
Decision Analysis ◽  
Food Waste ◽  
Rio De Janeiro ◽  
Multi Criteria Decision Analysis ◽  
Selection Of ◽  
Domestic Food

scholarly journals APPLICATION OF MULTICRITERIA DECISION ANALYSIS (MCDA) IN THE AREA OF SUSTAINABILITY: A LITERATURE REVIEW

2020 ◽  
Vol 12 (3) ◽  
Author(s):  
Praveen Goyal ◽  
Divesh Kumar ◽  
Vinod Kumar
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Literature Review ◽  
Decision Analysis ◽  
Citation Analysis ◽  
Multicriteria Decision Analysis ◽  
Research Papers ◽  
Multicriteria Decision ◽  
Multi Criteria Decision Analysis ◽  
Scopus Database

Multi-Criteria Decision Analysis is a decision-making technique that is used by practitioners and frequently discussed and applied by researchers. This present study attempts to review the literature of applications of MCDA techniques in the area of sustainability using citation analysis. For the data collection, the Scopus database was used. With the help of related keywords, 701 research papers were identified and found suitable for analysis. These papers were then analyzed based on country, author, citation, year, and other criteria to demonstrate the pattern of research applying MCDA in sustainability. The CiteSpace tool was also used to present the clusters, citation analysis, and keywords as bursts. The findings of the present study will help future researchers better explore the field.

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