A Typology for Characterizing Human Action in MultiSector Dynamics Models

Abstract

The role of individual and collective human action is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short‐term (hourly to daily) to long‐term (annually to centennial) timescales, and from the local to the global, pushing systems toward either desirable or undesirable outcomes. However, the effort to represent human systems in multisector models has been fragmented across philosophical, methodological, and disciplinary lines. To cohere insights across diverse modeling approaches, we present a new typology for classifying how human actors are represented in the broad suite of coupled human‐natural system models that are applied in MultiSector Dynamics (MSD) research. The typology conceptualizes a “sector” as a system‐of‐systems that includes a diverse group of human actors, defined across individual to collective social levels, involved in governing, provisioning, and utilizing products, goods, or services toward some human end. We trace the salient features of modeled representations of human systems by organizing the typology around two key questions: (a) Who are the actors in MSD systems and what are their actions? (b) How and for what purpose are these actors and actions operationalized in a computational model? We use this typology to critically examine existing models and chart the frontier of human systems modeling for MSD research.

Uncovering the Dynamics of Multi‐Sector Impacts of Hydrological Extremes: A Methods Overview

“…Systems dynamics and multi‐sector dynamic models focus on studying the complexity of a system through understanding causal relationships and feedback patterns (Yoon et al., 2022). Gaining such understanding is beneficial for predicting future system behavior, identifying detrimental or supportive system components, and evaluating the likely impact of policy strategies.…”

Institutional Dynamics Impact the Response of Urban Socio‐Hydrologic Systems to Supply Challenges

“…Nodes in a CIS are actors, resource users or PIPs, and infrastructures of multiple types, including natural infrastructure (e.g., a watershed), and public infrastructures (hard/built and soft/institutional). With Yoon et al.’s (2022) typology, PIPs are governing actors, users are utilizing actors, and public infrastructure (PI) agents are provisioning actors. The PI agents implement directives from PIPs and operate the infrastructure system (Anderies, Barreteau, & Brady, 2019).…”

Knowledge co-production for decision-making in human-natural systems under uncertainty

“…Within the context of human-natural systems, a major source of uncertainty is related to their multiactor settings (14,15), i.e., diverse societal actors (including individual citizens, local/Indigenous communities, technical experts, NGOs and advocacy groups, industry/business partners, financial sector/markets, and government/decision-makers (16,17)) involved who create a plurality of human interests, conflicting policy objectives, and behavioural and institutional ambiguity (18). Making decisions under the uncertainty of multi-actor settings increasingly requires deeper integration with different world-views (e.g., people's cultural values, human preferences) and diverse policy experience (e.g., decision-maker's conflicting objectives, power relationships) (19,20) through approaches that support interactive arrangements among all (academic and nonacademic) actors for defining the issues, researching them, and delivering impacts to the society, commonly known as co-production (21).…”

“…Co-production promises to improve decision quality through deliberation and collaborative management in a way that can lead to viable, fair, and inclusive solutions (22,23). It also recognises the role of actors in shaping behaviour and empower their actions as the paramount drivers of systems change (15).…”

“…To realise the compelling promise of co-production, different endeavours are emerging across disciplines that provide empirical guidance for engaging with societal actors in scientific work (1,15,21,(24)(25)(26)(27). Studies have used different theories and terminologies (e.g., co-creation (3,28), co-design (29), co-production (30), co-engineering (31), governance partnership (10), actionoriented knowledge (32,33), transdisciplinary and participatory research (34), post-normal science (35)) and employed various qualitative and quantitative approaches that combine computational and human capabilities interactively (24,36).…”