Cognitive Mapping Tools: Review and Risk Management Needs

Wood, M.; Bostrom, Ann; Bridges, Todd S.; Linkov, Igor

doi:10.1111/j.1539-6924.2011.01767.x

Cited by 77 publications

(74 citation statements)

References 63 publications

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“…Follow-up surveys with larger samples are recommended for examining the prevalence of interviewees' beliefs and drivers of decisions. Both the expert decision model of step 1 and the lay decision model of step 2 can be formally represented in an influence diagram (14,23).…”

Section: Mental Models Approachmentioning

confidence: 99%

Assessing what to address in science communication

Bruin

Bostrom

2013

Proc. Natl. Acad. Sci. U.S.A.

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224

160

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As members of a democratic society, individuals face complex decisions about whether to support climate change mitigation, vaccinations, genetically modified food, nanotechnology, geoengineering, and so on. To inform people's decisions and public debate, scientific experts at government agencies, nongovernmental organizations, and other organizations aim to provide understandable and scientifically accurate communication materials. Such communications aim to improve people's understanding of the decision-relevant issues, and if needed, promote behavior change. Unfortunately, existing communications sometimes fail when scientific experts lack information about what people need to know to make more informed decisions or what wording people use to describe relevant concepts. We provide an introduction for scientific experts about how to use mental models research with intended audience members to inform their communication efforts. Specifically, we describe how to conduct interviews to characterize people's decision-relevant beliefs or mental models of the topic under consideration, identify gaps and misconceptions in their knowledge, and reveal their preferred wording. We also describe methods for designing follow-up surveys with larger samples to examine the prevalence of beliefs as well as the relationships of beliefs with behaviors. Finally, we discuss how findings from these interviews and surveys can be used to design communications that effectively address gaps and misconceptions in people's mental models in wording that they understand. We present applications to different scientific domains, showing that this approach leads to communications that improve recipients' understanding and ability to make informed decisions.

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Section: Mental Models Approachmentioning

confidence: 99%

Assessing what to address in science communication

Bruin

Bostrom

2013

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

224

160

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“…Cognitive maps can help to focus on one part while not losing track of the context and the bigger picture. They provide a useful method for facilitating understanding and communication about complex problems (Wood et al 2012).…”

Section: Resultsmentioning

confidence: 99%

Dynamic simulation of sustainable farm development scenarios using cognitive modeling

Tuzhyk¹,

Hewelke²,

Hewelke³

2017

Annals of Warsaw University of Life Sciences – SGGW. Land Reclamation

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Dynamic simulation of sustainable farm development scenarios using cognitive modeling. The paper presents a dynamic simulation system of sustainable development scenarios on farms using cognitive modeling. The system incorporates relevant variables which affect the sustainable development of farms. Its user provides answers to strategic issues connected with the level of farm sustainability over a long-term perspective of dynamic development. The work contains a description of the model structure as well as the results of simulations carried out on 16 farms in northern Ukraine. The results show that the process of sustainability is based mainly on the potential for innovation in agricultural production and biodiversity. The user is able to simulate various scenarios for the sustainable development of a farm and visualize the infl uence of factors on the economic and social situation, as well as on environmental aspects. Upon carrying out a series of simulations, it was determined that the development of farms characterized by sustainable development is based on additional profi t, which serves as the main motivation for transforming a conventional farm into a sustainable one. Nevertheless, additional profi t is not the only driving force in the system of sustainable development. The standard of living, market condition, and legal regulations as well as government support also play a signifi cant motivational role.

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“…MCDA is a structured approach to decision-making that quantitatively evaluates alternatives, in this case, metrics, based on defined project criteria, expert opinions, and stakeholder preferences (Linkov and Moberg, 2011;Wood et al, 2012). It integrates a wide variety of information to evaluate project alternatives and rank them based on their aggregated value with respect to a set of criteria (Linkov and Moberg, 2011).…”

Section: Multi-criteria Decision Analysis (Mcda)mentioning

confidence: 99%

“…We consider stakeholders to be all the people that have a stake in the environmental problem considered as suggested in Wood et al (2012).…”

Section: Multi-criteria Decision Analysis (Mcda)mentioning

confidence: 99%

Multi-criteria decision analysis to select metrics for design and monitoring of sustainable ecosystem restorations

Convertino

Baker

Vogel

et al. 2013

Ecological Indicators

104

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Convertino, M.; Baker, K.M.; Vogel, J.T.; Lu, C.; Suedel, B.; and Linkov, I., "Multi-criteria decision analysis to select metrics for design and monitoring of sustainable ecosystem restorations" (2013). US Army Research. 190 The selection of metrics for ecosystem restoration programs is critical for improving the quality and utility of design and monitoring programs, informing adaptive management actions, and characterizing project success. The metrics selection process, that in practice is left to the subjective judgment of stakeholders, is often complex and should simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. With limited funding, it is often very difficult to balance the importance of multiple metrics, often competing, intended to measure different environmental, social, and economic aspects of the system. To help restoration planners and practitioners develop the most useful and informative design and monitoring programs, we propose the use of multi-criteria decision analysis (MCDA) methods, broadly defined, to select optimal ecosystem restoration metric sets. In this paper, we apply and compare two MCDA methods, multi-attribute utility theory (MAUT), and probabilistic multi-criteria acceptability analysis (ProMAA), for a hypothetical river restoration case study involving multiple stakeholders with competing interests. Overall, the MCDA results in a systematic, quantitative, and transparent evaluation and comparison of potential metrics that provides planners and practitioners with a clear basis for selecting the optimal set of metrics to evaluate restoration alternatives and to inform restoration design and monitoring. In our case study, the two MCDA methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criterion, it is most likely the best option for projects with highly uncertain data and significant stakeholder involvement. Despite the increase in complexity in the metrics selection process, MCDA improves upon the current, commonlyused ad-hoc decision practice based on consultations with stakeholders by applying and presenting quantitative aggregation of data and judgment, thereby increasing the effectiveness of environmental design and monitoring and the transparency of decision making in restoration projects.

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Cognitive Mapping Tools: Review and Risk Management Needs

Cited by 77 publications

References 63 publications

Assessing what to address in science communication

Assessing what to address in science communication

Dynamic simulation of sustainable farm development scenarios using cognitive modeling

Multi-criteria decision analysis to select metrics for design and monitoring of sustainable ecosystem restorations

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