Modeling and Simulation as a Bridge to Advance Practical and Theoretical Insights About Forced Migration Studies

Abstract

Modeling and Simulation (M&S) is a relatively unused research approach in forced migration studies. In most of its application areas, M&S is applied in several broad thematic policy-oriented topics: predicting human movement, humanitarian logistics, communicable diseases, healthcare, policing, and economics. More recently, there has been increased use of M&S in predicting human movement and health impacts resulting from climate change. Computer modeling has benefits for both policy and theoretical advancements in the field. M&S is often associated as a predictive tool that appeals to policymakers and planners. But M&S has many other significant benefits. For policymakers and planners, M&S provides a simulated environment to explore “what-if” scenarios. These scenarios can be adjusted to reflect different assumptions and conditions in the field. M&S can provide a means for translating interpretivist research findings—themselves rich in descriptions of actors, relationships, and dynamics—into visual artifacts that can communicate results to policymakers. It also can help to test the assumptions of theoretical findings, explore generalizability to other cases and conditions, and inform future data collection efforts. On the other hand, because models can take a long time to construct and test, they cannot provide rapid insights about evolving situations to inform decision-making at the onset of a new emergency. Data dashboards, the staple of modern humanitarian operations, are better for identifying emergent needs and tracking efforts. However, modeling what we know from one situation allows us to use those insights in systematic and strategic ways to improve operations for the future. M&S can also provide researchers with an additional tool that allows improved integration of multiple data types and sources. These data, assumptions, and theoretical constructs can be linked together in a complex, nonlinear, dynamic system that can then be set in motion to see if the simulated world reveals phenomena that are witnessed in the real world. But interdisciplinary communication and collaboration is hard and finding modelers who value interpretivist research can be even harder. M&S is not a silver bullet but provides a unique approach that incorporates dynamics and is becoming increasingly accessible to policymakers, practitioners, and academics, including those without computer programing experience. For policy, it is important to invest the time and resources to develop simulation models—from simple to complex—that help when planning for the evolution of events, or for the next event. Models of current refugee situations should inform where to concentrate efforts to advance durable solutions and how to plan for potential scenarios of return to countries of origin. Policymakers must recognize the long-term value of modeling what we know now to use later. Researchers of migration should become familiar with M&S paradigms so they can become part of the model design, development, and testing phases—at least part of the conversation. Better integration of migration scholars in design and development has the potential to strengthen models for policymaking, but perhaps more importantly, to strengthen the field by serving as an extra tool for testing theories, assumptions, and generalizability of findings to other locations and situations.

Venezuelan migration in Northern Brazil: a system dynamics approach for the internalization program

“…Policymakers normally see displacement as a one-off, short-term humanitarian problem, but it is a long-term situation that must be assessed holistically. Frydenlund (2021) suggested that modeling and simulation tools can incorporate the dynamic characteristics of migration and forced displacement and are an accessible way of integrating academia, practitioners and policymakers. Nevertheless, a gap remains between simulation techniques and migratory operations.…”

“…Frydenlund (2021) suggested that modeling and simulation tools can incorporate the dynamic characteristics of migration and forced displacement and are an accessible way of integrating academia, practitioners and policymakers. Nevertheless, a gap remains between simulation techniques and migratory operations.…”

“…We find SD suitable for analyzing complex systems, such as migration crises since it considers the relationships between a large number of variables and simulates the delays between cause and effect. Many studies have expanded the SD application field to the humanitarian sector (Besiou et al , 2011; Gonçalves, 2008) and find that it can offer important outcomes when applied to migration and forced displacement (Frydenlund, 2021). To the best of our knowledge, this study is the first to apply SD to a large migratory operation providing organizations and authorities with policies that improve the reception and relocation of migrants and refugees.…”

Analysing the effect of a dynamic physical environment network on the travel dynamics of forcibly displaced persons in Mali

“…For instance, the modelling of environment-migration linkages [15]. In addition, ABM can be used in circumstances (where there is limited or no training data) to complement machine learning approaches (e.g., [16,17]) in regards to forecasting efficacy. Examples of ABM models in forced migration include models of events in refugee settlements (e.g.…”

A Structured Narrative Prompt for Prompting Narratives from Large Language Models: Sentiment Assessment of ChatGPT-Generated Narratives and Real Tweets

“…As a possible avenue to mitigate these concerns, researchers and policy makers can lean on simulations to reflect systems of interest populated with simulated agents. The information created in these simulations can allow for a better understanding of the context of the system and its occupants, and help guide towards more informed participatory simulation designs [3]. Large language models (LLMs) can play a promising role in the ability to create useful narrative messaging that reflects both the emotional state of the individual that a narrative is based on and the context of the environment.…”