Climate change risk management: a Mental Modeling application

Barriers to innovation in USACE

“…Interviewees were stratified across four cohorts according to the agency or organization they represent: USACE (n = 7); other government (n = 4); nongovernment organization (NGO, n = 5); and contractors (n = 7). These cohort sample sizes are consistent with those in the literature (Bridges et al 2013;Wood et al 2017) and are intended to develop an understanding of the variety of points of view related to innovation in the navigation program rather than to provide a high-resolution quantitative measure of the degree or intensity of specific perceptions or beliefs. We used recommendations from unstructured interview participants and the project sponsor to identify potential interviewees to solicit.…”

“…In order to understand opportunities and barriers for dredging innovations across USACE and its partners, we conducted mental model interviews (Morgan et al 2002). Expert modeling is a well-accepted method for formulating problems, developing an understanding of variations in expertise, and analyzing that expertise as a function of the amount or different types available for a policy or engineering challenge (Jones et al 2011;Bridges et al 2013;Gray et al 2014;Halbrendt et al 2014;Wood et al 2017). Expert modeling was initially developed to expedite the creation of risk communication plans, under the assumption that laypersons could reach expert understanding on a risk issue if the deficits in layperson knowledge could be identified in terms of expert understanding (Woods et al 2017).…”

“…Mental models bridge the gap between physical and social sciences by facilitating researchers' understanding of how experts and laypersons perceive some subject matter (Morgan et al 2002). Mental models lend understanding to a variety of engineering and organizational change problems for USACE, such as understanding perception of flood risk management processes , 1350 and the ability to adapt in the face of climate change (Bridges et al 2013) or identifying opportunities for business development and growth (Collier, Trump, et al 2016;Wood et al 2017). Outside of USACE, mental models have helped develop effective risk communications (Atman et al 1994) and risk management (Stewart and Butte 2017;Wagner 2007), effective decision support systems for hazardous material exposure (Kovacs, Thorne, and Butte 2017), effective natural resource management strategies (Jones et al 2011;, and effective development and evaluation frameworks for a wide range of policies (Wood et al 2017;Kane and Trochim 2007).…”

Supporting decision-making for sustainable nanotechnology

“…Jones et al (2011) review its applications to natural resource management and list the following goals of applying mental models in that context: (a) to explore similarities and differences between stakeholders' understanding of an issue to improve communication between stakeholders, (b) to integrate different perspectives, including expert and local, to improve overall understanding of a system, (c) to create a collective representation of a system to improve decision-making processes, (d) to support social learning processes, (e) to identify and overcome stakeholders' knowledge limitations and misconceptions associated with a given resource and (f) to develop more socially robust knowledge to support negotiations over unstructured problems in complex, multifunctional systems. The ''Carnegie Mellon'' mental model approach (Wood et al 2012a;Morgan et al 2002) has been applied to environmental management case studies like climate change (Bridges et al 2013;Roncoli 2006;Sterman and Sweeney 2007), water use (Stone-Jovicich et al 2011) and flood management (Eisenman et al 2007;McDaniels et al 2008;Wood et al 2012b).…”

Multi-scale decision making: challenges in engineering and environmental systems

“…Notions of risk also can be difficult to incorporate into multi-scale decision making, particularly for the wicked problem space (see, e.g., Seager et al 2013). In this issue, Bridges et al (2013) propose mental modeling as a tool for identifying gaps and formulating strategies for such problems. Collins et al (2013) also study methods for assisting decision makers, but at entirely different scale.…”