A note on “A decision model for ranking suppliers in the presence of cardinal and ordinal data, weight restrictions, and nondiscriminatory factors”

2013 ◽  
Vol 211 (1) ◽  
pp. 49-54 ◽  
Author(s):  
Hossein Azizi
Keyword(s):  
Ordinal Data ◽  
Decision Model ◽  
Weight Restrictions

Supplier Selection by the Pair of AR-NF-IDEA Models

2012 ◽  
pp. 349-367
Author(s):  
Reza Saen ◽  
Mark Gershon
Keyword(s):  
Supply Chain ◽  
Ordinal Data ◽  
Supplier Selection ◽  
Weight Restrictions ◽  
New Model ◽  
Numerical Example ◽  
Nondiscretionary Factors

Supplier selection is the process by which suppliers are reviewed, evaluated, and chosen to become part of a company’s supply chain. To select the best suppliers in the presence of cardinal data, ordinal data, nondiscretionary factors, and weight restrictions, this paper proposes a new model considering all of these assumptions. A numerical example demonstrates the application of the proposed method.

Supplier Selection by the Pair of AR-NF-IDEA Models

2010 ◽  
Vol 3 (4) ◽  
pp. 25-41 ◽  
Author(s):  
Reza Saen ◽  
Mark Gershon
Keyword(s):  
Supply Chain ◽  
Ordinal Data ◽  
Supplier Selection ◽  
Weight Restrictions ◽  
New Model ◽  
Numerical Example ◽  
Nondiscretionary Factors

Supplier selection is the process by which suppliers are reviewed, evaluated, and chosen to become part of a company’s supply chain. To select the best suppliers in the presence of cardinal data, ordinal data, nondiscretionary factors, and weight restrictions, this paper proposes a new model considering all of these assumptions. A numerical example demonstrates the application of the proposed method.

A Fixed Observation Boundary Decision Model for Detection of Change

1974 ◽  
Author(s):  
Graham J. Burkheimer ◽  
William E. Stein ◽  
Amnon Rapoport
Keyword(s):  
Decision Model

A Multivariate Approach to Analyze Ordinal Data Collected in Clinical Trials of Analgesic Agents

1979 ◽  
Vol 18 (03) ◽  
pp. 175-179
Author(s):  
E. Mabubini ◽  
M. Rainisio ◽  
V. Mandelli
Keyword(s):  
Clinical Trials ◽  
Multivariate Analysis ◽  
Analgesic Effect ◽  
Ordinal Data ◽  
Ordinal Scale ◽  
Multivariate Approach ◽  
Controlled Clinical Trials ◽  
Second Stage ◽  
Analgesic Agents ◽  
Relevant Factors

After pointing out the drawbacks of the approach commonly used to analyze the data collected in controlled clinical trials carried out to evaluate the analgesic effect of potential agents, the authors suggest a procedure suitable for analyzing data coded according to an ordinal scale. In the first stage a multivariate analysis is carried out on the codec! data and the projection of each result in the space of the most relevant factors is obtained. In the second stage the whole set of these values is processed by distribution-free tests. The procedure has been applied to data previously published by VENTAITBIDDA et al. [18].

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