Making the most of mental models: Advancing the methodology for mental model elicitation and documentation with expert stakeholders. (February 2020)

• Record Type: Journal Article
• Authors: LaMere, Kelsey; Mäntyniemi, Samu; Vanhatalo, Jarno; Haapasaari, Päivi
• Is Part Of: Environmental modelling & software. Volume 124(2020)
• Publication Date: 2020-02
• Subjects: Cognitive maps -- Participatory modeling -- Stakeholder engagement -- Natural resource management -- Environmental modeling -- Transdisciplinary research; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2019.104589
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Eliciting stakeholders' mental models is an important participatory modeling (PM) tool for building systems knowledge, a frequent challenge in natural resource management. Therefore, mental models constitute a valuable source of information, making it imperative to document them in detail, while preserving the integrity of stakeholders' beliefs. We propose a methodology, the Rich Elicitation Approach (REA), which combines direct and indirect elicitation techniques to meet these goals. We describe the approach in the context of the effects of climate change on Baltic salmon. The REA produced holistic depictions of mental models, with more variables and causal relationships per diagram than direct elicitation alone, thus providing a solid knowledge base on which to begin PM studies. The REA was well received by stakeholders and fulfilled the substantive, normative, instrumental, and educational functions of PM. However, motivating stakeholders to confirm the accuracy of their models during the verification stage of the REA was challenging. Highlights: Holistic knowledge is an important first step in modeling and problem-solving. Stakeholder knowledge is often lost or simplified during mental model elicitation. This method combines direct and indirect elicitation to solve this problem. It holds substantive, normative, instrumental, and educational value. Participatory modelling methodologies should be well-documented.