A new method for elicitation of criteria weights in additive models: Flexible and interactive tradeoff

Highlights

• FITradeoff (Flexible and Interactive Tradeoff) is a new elicitation MCDM method.

• FITradeoff uses the tradeoff procedure for eliciting weights of an additive model.

• FITradeoff uses the concept of flexible elicitation and has been built into a DSS.

• The nature of information required is cognitively easier for the DM to grasp.

• FITradeoff also reduces the amount of information required from the DM.

Abstract

This paper proposes the Flexible and Interactive Tradeoff (FITradeoff) method, for eliciting scaling constants or weights of criteria. The FITradeoff uses partial information about decision maker (DM) preferences to determine the most preferred in a specified set of alternatives, according to an additive model in MAVT (Multi-Attribute Value Theory) scope. This method uses the concept of flexible elicitation for improving the applicability of the traditional tradeoff elicitation procedure. FITradeoff offers two main benefits: the information required from the DM is reduced and the DM does not have to make adjustments for the indifference between two consequences (trade-off), which is a critical issue on the traditional tradeoff procedure. It is easier for the DM to make comparisons of consequences (or outcomes) based on strict preference rather than on indifference. The method is built into a decision support system and applied to two cases on supplier selection, already published in the literature.

Introduction

One of the most relevant issues in using a multicriteria decision model is probably that of evaluating the weights of criteria (or attributes) in the aggregation procedure. This is particularly relevant for aggregation using an additive model. In practice, this aggregation procedure is the most commonly found in a multicriteria decision model (Spliet & Tervonen, 2014), for instance when selecting suppliers (Xia & Wu, 2007), or planning of metro extension lines (Hurson & Siskos, 2014). The additive model can be applied under some basic assumptions covered by many earlier studies (Fishburn, 1967, Keeney, 1972, Keeney, 1992, Keeney and Raiffa, 1976). Stewart´s survey on multicriteria methods shows some useful characteristics for an additive model (Stewart, 1992). A more recent survey considers eliciting the weights of criteria as a central issue (Riabacke, Danielson, & Ekenberg, 2012). Eisenführ, Weber, and Langer (2010) give a broad overview on weights elicitation procedures for additive models.

Previous studies on experimental analysis (Borcherding et al., 1991, Weber and Borcherding, 1993) on the main elicitation procedures for additive models have identified some major difficulties and challenges. The results of these studies prompted our research and led to the original achievement proposals to overcome those issues that this article sets out. First of all, it has long been held that the tradeoff elicitation procedure (Keeney, 1992, Keeney and Raiffa, 1976) has a strong axiomatic foundation (Weber & Borcherding, 1993). Nevertheless, experimental studies have shown that inconsistencies have been found when applying this procedure (Weber & Borcherding, 1993).

The method proposed in this paper contributes to overcoming some of these inconsistencies. This paper proposes a flexible elicitation procedure, which collects information from the DM, and evaluates this information. The main difference from previous studies is related to the elicitation process. In flexible elicitation, incomplete or imprecise information, a priori, is not assumed. Whether the DM is or is not able to give complete information, this is evaluated in the elicitation process itself, in a flexible way. For this reason, right from the start, the flexible process seeks complete information, based on the tradeoff elicitation procedure. However, at any point further on, it may consider incomplete information in either of the following two situations: when a unique solution is found or when the DM is not able to give additional information.

The method is built into a DSS (decision support system), which uses a flexible elicitation concept that requires less effort from the DM (Decision Maker). Before presenting the method proposed and its DSS, a brief review of the related literature is presented. In order to illustrate how the method named FITradeoff (Flexible and Interactive Tradeoff) works, the DSS is used on two applications dealing with supplier selection problems (Barla, 2003, Xia and Wu, 2007).