A common framework for deriving preference values from pairwise comparison matrices

By E. Choo, W. Wedley. Computers & Operations Research, 2004

331 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management of Technology and Innovation, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/abb0a24c4b0b6b7233be08d0839c385701f431bc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Rafael Pérez-García
2. Xitlali Delgado-Galván
3. Chao Gao
4. Joaquín Izquierdo
5. Ashraf Labib
6. Matteo Brunelli
7. Julio Benítez
8. Pinhan Chen

In Management of Technology and Innovation

1. Alessio Ishizaka
2. Ashraf Labib
3. Rafael Pérez-García
4. Xitlali Delgado-Galván
5. Joaquín Izquierdo
6. Matteo Brunelli
7. Julio Benítez
8. Ramakrishnan Ramanathan

In Management Science and Operations Research

1. Alessio Ishizaka
2. Matteo Brunelli
3. Ashraf Labib
4. Rafael Pérez-García
5. Xitlali Delgado-Galván
6. Chao Gao
7. Joaquín Izquierdo
8. Julio Benítez

Citations in the corpus

• Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process (2006, methodology): “As DEA is based on linear programming, DEAHP may be compared and contrasted with other linear programming based techniques suggested for deriving weights from judgment matrices, such as goal programming [25,26].”
• Achieving matrix consistency in AHP through linearization (2011, methodology): “There are different techniques to extract priority vectors from these comparison matrices [6, 7, 8].”
• Optimal full ranking from pairwise comparisons (2021, background): “This highdimensional statistical estimation problem has important applications in many areas such as recommendation systems [1, 7], sports and gaming [2, 17, 23, 40, 41, 49], web search [16, 19], social choices [33, 36, 38, 39, 47], psychology [13, 34, 52], information retrieval [8, 32], etc.”
• Analytic Hierarchy Process and Expert Choice: Benefits and limitations (2009, methodology): “Cho and Wedley (2004) have enumerated 18 different methods, which are effectively 15 because three are equivalent to others (Lin, 2007).”
• Review of the main developments in the analytic hierarchy process (2011, background): “Cho and Wedley (2004) have enumerated 18 different methods, which are effectively 15 because three are equivalent to others (C.”
• Introduction to the Analytic Hierarchy Process (2014, methodology): “Choo and Wedley [39] listed 18 different methods and proposed a numerical and comparative study.”