Poster: SOC Poster Session (In-person) on Monday, July 20, 2026, 11:00 AM
Room: Entresol 2
Thread: Learning and Teaching
Duration: 60 minutes
Chairs: Paula Goetz, Ellen O'Neill
Support: Özgün Çetinkaya
Modelling Interdependencies Between Fast and Luxury Fashion: Implications for Sustainability
Presenters: Melika Modarres Vahid, Elvan Gokalp, Selim Cakir
Keywords: Business and Strategy
The fashion industry has been criticized for its substantial environmental pressure. Despite increasing regulations, consumer awareness, and industry initiatives, progress towards sustainability remains limited. Existing literature has generated important insights into sustainable fashion, but it often tends to examine either demand-side drivers or supply-side and operational responses in isolation. Moreover, even within the supply-side literature, fast fashion and luxury fashion are treated as separate isolated empirical contexts. This segmentation has led to limited theorisation of how these two segments interact and jointly shape consumer demand and operational choices. To address the need for systemic understanding of the dynamics within the industry, we develop a casual loop diagram of the operational decisions of fast and luxury fashion and their interdependencies. Preliminary findings reveal that competition between the segments has increased speed and waste across the fashion system. Fast fashion’s business model, built on speed, pressures luxury brands to shorten lead times and increase collection frequency, which further intensifies fast fashion responses. The resulting escalation raises forecasting error, excess inventory, material waste, and reinforces a disposability culture among consumers.
From Market Tug-of-War to Grid Supply Trap: Electric Motorcycles Adoption and Distribution Grid Readiness in Indonesia
Presenters: Vertic Eridani Budi Darmawan, Paul Pfaffenbichler, Yusak Octavius Susilo
Keywords: Transport and Mobility
The rapid growth of battery electric vehicle (BEV) adoption is driving transport electrification as a key direction in the global energy transition. This transition is framed as a market tug-of-war between ICE and BEV, following a chicken-and-egg adoption problem. However, this transition presents challenges where local grid capacity for charging infrastructure is limited. These challenges emerge from dynamic interactions among multiple stakeholders within this complex sociotechnical system. This research applies a systems-thinking lens to dynamically couple two subsystems that existing models treat in isolation: BEV adoption and grid infrastructure. We make the local grid endogenous, treating it as the supply constraint underpinning charging infrastructure. The dynamic hypothesis is that readiness is a race between adoption speed and grid reinforcement lead time. We select Indonesia as the case study: it has the world's third-largest motorcycle market, an archipelagic and unevenly developed distribution grid, and strong policy-driven adoption. A causal loop diagram maps the transition in two phases. In Phase 1, the Market Tug-of-War, a Success-to-the-Successful loop lets BEV out-compete ICE. That success then triggers Phase 2, the Grid Supply Trap: rising charging load eats into available grid headroom (Limits-to-Growth), while grid investment lags behind demand (Growth-and-Underinvestment). As headroom collapses, the binding constraint shifts from the market to the grid. This causal structure, together with ongoing semi-structured expert interviews to validate and refine it, forms the basis for the stock-and-flow simulation model we will build next. This work supports long-term, grid-aware planning for electric motorcycles in Indonesia
Repurposing Farmland to Solar Farm: A Strategy to Reduce Groundwater Extraction
Presenters: Samaneh Saeidinaeini, Saeed Langarudi, Ali Bagheri
Keywords: Environment and Resources
Many aquifers worldwide are experiencing long-term declines because groundwater withdrawals exceed their natural recharge capacity. Excessive water extraction not only increases the vulnerability of the aquifer system but also threatens irrigated agriculture in arid regions such as Rafsanjan, Iran. Analysis of annual groundwater extraction and declining groundwater level trends in Rafsanjan reveals increasing vulnerability of this aquifer. In addition, declining water availability has led to the loss of pistachio orchards and economic vulnerability among farmers in this region. This study aims to investigate the potential of solar energy development to facilitate farmland retirement and reduce groundwater extraction as part of a water demand management strategy. The financial feasibility assessment indicates that solar energy generation can be more profitable than pistachio farming. However, the high initial investment and limited transmission grid capacity remain major barriers to this repurposing. Field visits and many interviews with different stakeholders were conducted to understand the socio-economic context of this strategy, which led to the development of a conceptual water–energy–agriculture nexus model. The next phase of this research will focus on developing a system dynamics model that integrates hydrological, economic, and behavioral factors to evaluate the potential of repurposing farmland for solar energy generation as a strategy to reduce groundwater extraction while offsetting economic losses associated with farmland retirement.
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Feedback Loops Between National Climate Policies and Urban GHG Mitigation: A System Dynamics and Machine Learning Analysis
Presenter: Rebecca Su An Chew
Keywords: Environment and Resources
The policy-emissions relationship is often analysed at the same spatial scale, for example, country-level policies and country-level emissions. Less attention is paid to assessing the link between national climate policies (NCPs) and city-level greenhouse gas (GHG) emissions. This study addresses that gap by using a hybrid system dynamics and machine learning approach. Following a literature review, a conceptual model was developed in VenSim to map feedback loops, model boundaries, and delays. Supervised machine learning was then used to rank hypothesised variables and examine non-linear relationships empirically with a dataset of nearly 7,000 cities across 66 countries. Preliminary results support the strongest model for CO2 (N=6,967, R²=0.578, RMSE=3,075,615) and total GHG emissions (N=6,932, R²=0.516, RMSE=3,560,281). Built-up volume, NCPs, HDI, green and cropland areas are most strongly associated with emissions outcomes, while NCPs’ effects vary by emission type, time since implementation, and levels of industrialisation. The study contributes a hybrid SD–machine learning approach that explores and empirically supports how multi-level climate governance shapes urban GHG mitigation over time.
Modeling Circular Economy Barriers to Textile Waste Valorization using Causal Loop Diagram
Presenters: Jade Sagnard, Natalia Vechiu, Jérémy Legardeur
Keywords: Environment and Resources
Despite growing commitments to circular economy principles, fiber-to-fiber recycling in the textile industry remains limited to around 1% globally. This gap suggests the presence of systemic barriers that hinder the valorization of textile waste. This study focuses on post-industrial and pre-consumer textile waste in Europe, which, despite their high recycling potential, remain largely underutilized due to fragmented and low-volume material flows. Adopting a System Dynamics approach, this research uses causal loop diagrams (CLDs) to analyze the interdependencies between economic, technical, logistical, organizational, and institutional barriers. Based on a literature review and semi-structured interviews with French textile value chain actors. Preliminary feedback loops are identified, highlighting the role of economies of scale, relational capital, and investment dynamics. The study hypothesizes that the lack of volume consolidation constitutes a structural lock-in that prevents system-wide change. The resulting CLD aims to provide a qualitative understanding of the system and support the identification of leverage points for improving material valorization.
Understanding the drivers and barriers to effective Post Occupancy Evaluation through system thinking.
Presenter: Jaime Bainbridge
Keywords: Environment and Resources
THIS IS FOR A POSTER: Improving operational building performance is essential for meeting the ambitious UK Net Zero targets in the context of the climate emergency. A holistic understanding of the drivers and barriers to evaluating the performance of operational buildings is therefore required to understand the causes of the performance gap and foster a culture of continuous improvement in the built environment. Post-occupancy evaluation (POE) remains an underutilised tool for closing this gap. Although existing research has identified a range of drivers and barriers affecting POE adoption, there remains a lack of systems-level analysis examining the interactions between these factors and their underlying causal relationships. Consequently, leverage points that could encourage the adoption of POE across the built environment supply change remain insufficiently understood. Within this context, a systems think approach is proposed to capture and analyse the complexity of the factors influencing POE adoption focused on non- domestic buildings. The goal of this study is to map the current interactions of drivers and barriers to POE from multiple perspectives in the building supply chain to provide a holistic understanding of the complex dynamics and interdependencies of this system and identify leverage points capable of increasing the uptake and effectiveness of POE.
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Endogenous Drivers of Cascading Rebound: Mapping Feedback Loops in Digitally-enabled Sharing Platforms
Presenters: Fenna Kortstee, Bob Walrave, Zahra Shams Esfandabadi
Keywords: Environment and Resources
Digitally-enabled sharing platforms (DSPs) are increasingly promoted as potential enablers of circular economy transitions. Yet, growing evidence shows that DSPs can trigger rebound effects—systemic responses that offset or reverse anticipated sustainability gains. Existing research typically conceptualizes rebound mechanisms in isolated, static, and linear terms, overlooking how they emerge from endogenous, feedback-driven interactions across micro, meso, and macro levels. In response, this study adopts a system dynamics perspective to investigate how rebound mechanisms arise from the underlying, inherently complex system structure of DSPs. Building on a systematic literature review followed by a Gioia-informed coding process, we identified key variables, causal relationships, and partially described mechanisms. These were translated into three integrated causal loop diagrams (CLDs), which articulate the dominant reinforcing loops driving consumption dynamics, ownership-related dynamics, and socially mediated dynamics. This study shows that rebound effects in DSPs result from the system's structure—including their multi-level nature. More specifically, our CLDs reveal how feedback loops interact across micro, meso, and macro levels, showing how these rebound effects cascade across the complex system. It uncovers interdependencies, nonlinearities, and feedback structures, explaining why rebound effects persist. The resulting CLDs provide a foundation for future quantitative system dynamics modeling, enabling exploration of leverage points, counteracting balancing loops, and policy interventions that can alter system behavior. This work contributes to research on rebound effects by clarifying how DSP-induced rebound effects unfold endogenously through complex, multi-level feedback processes and how systems dynamics can inform this understanding.
Modeling energy demand in informal settlements
Presenter: Emma Borjigin-Wang
Keywords: Environment and Resources
Informal settlements house a growing number of the global urban population, particularly in sub‑Saharan Africa. Energy use in informal settlements is marked by limited or unaffordable grid access, reliance on informal electricity arrangements, and continued use of traditional fuels. Informal settlements are largely excluded from energy models and planning, motivating this study’s intent to characterize energy service demands and develop a conceptual model of energy use in these settings. This project will characterize the drivers and barriers to energy service and energy carrier use. It is the first known attempt at modeling overall energy use dynamics in informal settlements. The outcomes of this work will hopefully facilitate participation of these communities in energy planning processes and form the basis of future models.
Understanding Catchment-Based Initiatives That Support Habitat Recovery and Improved Water Quality in Tamar Estuary, England
Presenters: Folasade Adeboyejo, Joanne Preston, Toby Marthews, Angus Garbutt, Phillip Turner, Melanie Austen
Keywords: Environment and Resources
Conservation strategies and efforts to restore estuarine habitats that provide ecosystem services, such as seagrass, saltmarsh, and oyster reefs, are having limited or variable success in the UK. Upstream water quality driven by human perturbation has been linked to these successes and failures with excess nutrients (nitrogen and phosphorus) causing damaging eutrophication. Empirical modelling involving the use of weighted regression on time, discharge and season (WRTDS) was deployed for long-term river water quality analysis across the Tamar catchment. The result of the empirical analysis indicates that’s there have been periods of short term improvement in nitrogen and phosphorus fluxes in the past which coincide with the emergence of intertidal seagrass in the estuary. However, this outcome is quite inconsistent with prevailing narratives of environmental decline driven by combine sewage overflows (CSO) discharges. The next phase of my research is to develop a dynamic explanation of these observed changes. Specifically, I seek to identify the interventions introduced during the study period and to assess whether their cumulative and interacting effects contributed to downstream water quality improvement and coastal habitat recovery. These questions are inherently concerned with feedback structure, time delays, non linearity, and threshold behaviour, making system dynamics an appropriate and necessary framework.
Solving the Missing Link Between Cyber Risk Management and Resilience
Presenter: Nadia Lorraine Lawal
Keywords: Security Stability and Resilience
Organizations face growing cyber threats that expose the limitations of traditional risk management approaches focused on prevention. While cyber risk management and cyber resilience are complementary, they are often developed in isolation, leading to overemphasis on short-term mitigation at the expense of long-term adaptive capabilities. This study proposes a conceptual system dynamics model that integrates both domains through the mechanisms of resilience-informed risk management (RIRM) and risk-informed resilience (RIR). Drawing on the capability trap perspective, the model explains how resource allocation between operational activities and capability development shapes organizational cybersecurity performance over time. By capturing the dynamic interaction between preventive and adaptive capabilities across disruption phases, the framework highlights how organizations can escape reactive cycles and achieve more balanced and resilient cybersecurity governance.
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