Measuring Conflicts Using Cardinal Ranking: An Application to Decision Analytic Conflict Evaluations

Abstract

One of the core complexities involved in evaluating decision alternatives in the area of public decision-making is to deal with conflicts. The stakeholders affected by and involved in the decision often have conflicting preferences regarding the actions under consideration. For an executive authority, these differences of opinion can be problematic, during both implementation and communication, even though the decision is rational with respect to an attribute set perceived to represent social welfare. It is therefore important to involve the stakeholders in the process and to get an understanding of their preferences. Otherwise, the stakeholder disagreement can lead to costly conflicts. One way of approaching this problem is to provide means for comprehensive, yet effective stakeholder preference elicitation methods, where the stakeholders can state their preferences with respect to actions part of the current agenda of a government. In this paper we contribute two supporting methods: (i) an application of the cardinal ranking (CAR) method for preference elicitation for conflict evaluations and (ii) two conflict indices for measuring stakeholder conflicts. The application of the CAR method utilizes a do nothing alternative to differentiate between positive and negative actions. The elicited preferences can then be used as input to the two conflict indices indicating the level of conflict within a stakeholder group or between two stakeholder groups. The contributed methods are demonstrated in a real-life example carried out in the municipality of Upplands Väsby, Sweden. We show how a questionnaire can be used to elicit preferences with CAR and how the indices can be used to semantically describe the level of consensus and conflict regarding a certain attribute. As such, we show how the methods can provide decision aid in the clarification of controversies.

Portfolio Decision Analysis for Evaluating Stakeholder Conflicts in Land Use Planning

“…A drawback of ordinal ranking is that it disregards more precise information about preferences, even if it exists (Jia et al 1998). However, this aspect is taken into account in the elicitation methods used in the proposed framework: cardinal ranking (CAR) (Danielson et al 2014;Danielson and Ekenberg 2016) and the application CAR for conflict evaluations (CAR-CE) (Fasth et al 2018). In CAR, the ordinal ranking is refined by adding cardinal information regarding the strength of preference between each pair of elements in the ranking.…”

“…In this paper, we present a decision analytic framework for evaluating conflicts in urban planning between two stakeholder groups. The framework ties together multi-attribute value theory with previous research consisting of methods for eliciting stakeholder preferences (Danielson et al 2014;Danielson and Ekenberg 2016;Fasth et al 2018) and measuring conflict related to an action within one stakeholder…”

“…Portfolio Decision Analysis for Evaluating Stakeholder… group and between two stakeholder groups (Fasth et al 2018). The framework also contains a revised method for generating conflict constrained portfolios based on Lourenço et al (2012); Fasth et al (2016), and a method for sensitivity analysis which draws on the concept of core index (Liesiö et al 2007(Liesiö et al , 2008.…”

A web‐based visualization tool for exploring stakeholder conflicts in land‐use planning

“…The CAR‐CE method (Fasth, Larsson, Ekenberg, & Danielson, ) is an application of CAR in which a do nothing action is added to the ranking. This enables a decision‐maker to state whether the performance of an action is negative or positive relative to the do nothing action.…”

“…Our framework implements two methods for analyzing conflicts. First, it utilizes two conflict indices: (1) a within‐group conflict index for measuring conflict within a stakeholder group; and (2) a between‐group conflict index for measuring conflict between two stakeholder groups (Fasth et al., ). Second, it solves a portfolio optimization problem multiple times with different levels of the conflict index as the constraining resource in order to analyze how a change in conflict affects the portfolio composition.…”