From soft to hard elicitation

French, Simon

doi:10.1080/01605682.2021.1907244

Cited by 15 publications

(8 citation statements)

References 165 publications

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“…The process of building and quantifying such models with experts, stakeholders, and analysts follows a series of clear steps: building a conceptual model, identifying parameters, formulating data requirements and addressing data gaps. Although a clear distinction between the qualitative and quantitative steps may seem tempting, the modeling process needs to then be treated as a whole [15].…”

Section: Multivariate Probabilistic Modelling For Risk and Decision A...mentioning

confidence: 99%

Editorial: Multivariate Probabilistic Modelling for Risk and Decision Analysis

Hanea

Nane

2022

Front. Appl. Math. Stat.

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Section: Multivariate Probabilistic Modelling For Risk and Decision A...mentioning

confidence: 99%

Editorial: Multivariate Probabilistic Modelling for Risk and Decision Analysis

Hanea

Nane

2022

Front. Appl. Math. Stat.

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“…Moreover, the modeling is not descriptive in the sense that beliefs, values and objectives exist fully and explicitly before the modeling process begins. Rather the process of elicitation helps the participants reflect on what they are truly seeking to achieve and constructs the detailed objectives for the analysis (Keeney, 1992;Lichtenstein and Slovic, 2006;French, 2021). This form of modeling is particularly focused on helping the participants move from System 1 Thinking toward System 2 Thinking as it generally introduces rationality conditions that help their values become more consistent.…”

Section: Modeling and Decision Analysismentioning

confidence: 99%

“…Also there are many cases in which the clarity brought by framing the issues well has obviated the need for formal quantitative analysis. These techniques are useful in all of the Cynefin Spaces, though they come to the fore in the Complex and Chaotic Spaces In which sense really needs to be made (Rosenhead and Mingers, 2001;Checkland, 2013;Steed et al, 2013;Bendoly and Clark, 2016;Pyrko et al, 2019;French, 2021) (See Table 3h for further details).…”

Section: Soft Elicitationmentioning

confidence: 99%

Decision-Making for Managing Climate-Related Risks: Unpacking the Decision Process to Avoid “Trial-and-Error” Responses

Constable¹,

French²,

Karoblyte³

et al. 2022

Front. Clim.

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We provide an overview of decision support tools and methods that are available for managing climate-related risks and for delivering adaptation and resilience options and solutions. The importance of understanding political, socio-economic and cultural contexts and the decision processes that these tools support is emphasized. No tool or method is universally suited to all circumstances. Some decision processes are structured with formal governance requirements; while others are less so. In all cases, discussions and interactions with stakeholders and other players will have formal and informal aspects. We categorize decision support tools in several broad ways with the aim of helping decision makers and their advisors select tools that are appropriate to their culture, resources and other circumstances. The assessment examines the constraints and methodological assumptions that need be considered.

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“…These delegates were engaged in what can be called joint model building or soft elicitation (French, 2021; Wilkerson & Smith, 2021). First they were presented with the UK picture and then asked to express their beliefs about how this related specifically to Warwickshire.…”

Section: Idss: Uk Food Securitymentioning

confidence: 99%

A Decision Support System for Addressing Food Security in the United Kingdom

Barons

Fonseca

Davis

et al. 2021

Journal of the Royal Statistical Society Series A: Statistics in Society

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This paper presents an integrating decision support system (IDSS) for food security in the United Kingdom. In ever‐larger dynamic systems, such as the food system, it is increasingly difficult for decision makers (DMs) to effectively account for all the variables within the system that may influence the outcomes of interest under enactments of various candidate policies. Each of the influencing variables is likely, themselves, to be dynamic subsystems with expert domains supported by sophisticated probabilistic models. Recent increases in food poverty in the United Kingdom have raised the questions about the main drivers of food insecurity, how this may be changing over time and how evidence can be used in evaluating policy for decision support. In this context, an IDSS is proposed for household food security to allow DMs to compare several candidate policies which may affect the outcome of food insecurity at the household level.

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From soft to hard elicitation

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Cited by 15 publications

References 165 publications

Editorial: Multivariate Probabilistic Modelling for Risk and Decision Analysis

Editorial: Multivariate Probabilistic Modelling for Risk and Decision Analysis

Decision-Making for Managing Climate-Related Risks: Unpacking the Decision Process to Avoid “Trial-and-Error” Responses

A Decision Support System for Addressing Food Security in the United Kingdom

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