Transparency and Reproducibility in Participatory Systems Modelling: the Case of Fuzzy Cognitive Mapping

Abstract

By aggregating semi‐quantitative mind maps from multiple agents, fuzzy cognitive mapping (FCM) allows developing an integrated, cross‐sectoral understanding of complex systems. However, and especially for FCM based on individual interviews, the map‐building process presents potential pitfalls. These are mainly related to the different understandings of the interviewees about the FCM semantics as well as the biases of the analyst during the elicitation and treatment of data. This paper introduces a set of good practice measures to increase transparency and reproducibility of map‐building processes in order to improve credibility of results from FCM applications. The case study used to illustrate the proposed good practices assesses heatwave impacts and adaptation options in an urban environment. Agents from different urban sectors were interviewed to obtain individual cognitive maps. Using this set of data, we suggest good practices to collect, digitalize, interpret, pre‐process and aggregate the individual maps in a traceable and coherent way. © 2018 The Authors Systems Research and Behavioral Science published by International Federation for Systems Research and John Wiley & Sons Ltd

Multi-faceted impact and outcome of COVID-19 on smallholder agricultural systems: Integrating qualitative research and fuzzy cognitive mapping to explore resilient strategies

“…The NGO staffs worked closely with the farmers and experts and drew on both the worlds, while experts worked closely with the farmers during the implementation of their projects and developed an understanding of their knowledge system, a prerequisite for adaptive system management ( Tran and Rodela, 2019 ). Literature suggests that the aggregation of semi-quantitative cognitive maps is possible ( Kosko, 1993 ) from which multiple stakeholders can develop a holistic understanding of complex systems ( Olazabal et al, 2018 ). Our shared mental model suggested the centrality of current household income, expenditure in farming (in the next crop cycle), and future crop production.…”

“…FCM is recently used in the management of agricultural systems through the development of mental models ( Halbrendt et al, 2018 ; Gray et al, 2015 ). However, the issue of collecting and analyzing data, especially the aggregation of individual mental models, has been debated ( Gray et al, 2012 ; Olazabal et al, 2018 ). Majority of the studies have employed workshops ( Gray et al, 2015 ) or interviews ( Targetti et al, 2019 ) for developing mental models.…”

Climate change in the context of whole-farming systems: opportunities for improved outreach

“…To understand how climate change fits within farmer and outreach professional understanding of whole-farming systems (research question 1) and explore differences in perspectives between these groups (research question 2), we conducted mental modeling interviews with farmers and outreach professionals in Northern New England, USA. Mental models were first conceptualized by Craik (1943) and offer an established framework for understanding stakeholder perceptions and decision-making in complex social-ecological systems (Gray et al 2012;Halbrendt et al 2014;Jones et al 2011;Kosko 1986;Olazabal et al 2018;Özesmi and Özesmi 2004), including farming systems (Findlater et al 2018a;Findlater et al 2018b;Halbrendt et al 2014;Jabbour et al 2014;Schoell and Binder 2009a;Schoell and Binder 2009b). Through elicitive interviews, facilitators guide participants in identifying concepts in a system and causal relationships between them (Kosko 1986), which can be represented both mathematically and through intuitive visual models (Özesmi and Özesmi 2004; see Fig.…”

Volatility in Air Traffic Management—How Changes in Traffic Patterns Affect Efficiency in Service Provision

“…FCM is a participatory, semi-quantitative method in which the experience, knowledge, and perceptions of the system of different experts on the topic (in our case, three air traffic controllers, two engineers specialized in performance management, one engineer with a focus on operational performance and two economists with specific knowledge of the European aviation sector) give rise to the construction of a graph structure that can be later used to simulate scenarios according to which policymakers may analyze how the system may behave under certain impacts [20]. In this way, these maps encourage systematic causal propagation (forward and backward chaining), helping to identify cascading effects and interdependencies across elements (including unexpected trade-offs and synergies) that otherwise would be difficult to analyze.…”