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A flexible elicitation procedure for additive model scale constants

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This paper contributes to the process of eliciting additive model scale constants in order to support choice problems, thereby reducing the effort a decision maker (DM) needs to make since partial information with regard to DM preferences can be used. Procedures related to eliciting weights without a tradeoff interpretation of weights are justified based on assumptions that DM is not able to specify fixed weight values or if DM is able to do so, this would not be reliable information. As long as partial information is provided, the flexible elicitation procedure performs dominance tests based on a linear programming problem to explore the DM’s preferences as a vector space which is built using the DM’s partial information. To provide evidence of the satisfactory performance of the flexible elicitation procedure, an empirical test is presented with results that indicate that this procedure requires less effort from DMs.
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Ann Oper Res (2017) 259:65–83
DOI 10.1007/s10479-017-2519-y
ORIGINAL PAPER
A flexible elicitation procedure for additive model scale
constants
Adiel T. de Almeida-Filho1·Adiel T. de Almeida1·
Ana Paula C. S. Costa1
Published online: 11 May 2017
© Springer Science+Business Media New York 2017
Abstract This paper contributes to the process of eliciting additive model scale constants in
order to support choice problems, thereby reducing the effort a decision maker (DM) needs
to make since partial information with regard to DM preferences can be used. Procedures
related to eliciting weights without a tradeoff interpretation of weights are justified based on
assumptions that DM is not able to specify fixed weight values or if DM is able to do so, this
would not be reliable information. As long as partial information is provided, the flexible
elicitation procedure performs dominance tests based on a linear programming problem
to explore the DM’s preferences as a vector space which is built using the DM’s partial
information. To provide evidence of the satisfactory performance of the flexible elicitation
procedure, an empirical test is presented with results that indicate that this procedure requires
less effort from DMs.
Keywords Flexible elicitation ·Partial information ·MAVT ·Tradeoff ·FITradeoff ·
Additive model
1 Introduction
In multicriteria decision problems, the inter-criteria evaluating parameter is usually called
weights. This is one of the fundamental modeling issues widely discussed in the literature.
The additive model is widely used in the literature (Palha et al. 2016;Pergher and de Almeida
2017), and in such kind of models using weights means using scale constant or tradeoffs,
and declaring which committed relationship the decision maker (DM) is willing to establish
between two criteria. In other methods, weights may be about the relative importance among
the criteria.
BAdiel T. de Almeida-Filho
ataf@cdsid.org.br
1Universidade Federal de Pernambuco, CDSID - Center for Decision Systems and Information
Development, Av. Acadêmico Hélio Ramos, s/n Cidade Universitária, Recife, PE, CEP 50.740-530,
Brazil
123
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... The approach proposes the integration of two methodologies: Balanced Scorecard -a multi-perspective tool for performance evaluation and strategic planning, and FITradeoff for the ranking problematic -an MCDA that features a robust axiomatic structure while improving the elicitation process through the flexibility and interactivity which it depicts in the exploit of partial information required to prioritize key performance indicators (Almeida-Filho et al., 2017). The FITradeoff method arose from the need of having an elicitation process that employs partial information in a more structured and flexible way as the traditional methods entailed many inconsistencies in the process (Almeida et al., 2016). ...
... It was found that FITradeoff decreased questions by almost 42% when compared with the traditional tradeoff method, which means savings in time and effort for DM. This outcome reinforces that FITradeoff overperformes the traditional Tradeoff as to the number of questions matter (Almeida-Filho et al., 2017). ...
... Thus, the model asks him for new relations of preference until a unique solution is found, that is, a situation in which the ideal alternative is found. The solution is found when the subset of potentially optimal alternatives has only one element [69]. Therefore, using the FITradeoff method allows for a more transparent and effective decision-making process [69]. ...
... The solution is found when the subset of potentially optimal alternatives has only one element [69]. Therefore, using the FITradeoff method allows for a more transparent and effective decision-making process [69]. ...
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